impact of emotions on problem solving and decision making

Decision-Making

The power of emotions in decision making, how to use emotions constructively in decision making..

Updated August 7, 2023 | Reviewed by Monica Vilhauer

• Emotions play a significant role in decision-making.
• Without emotions to motivate and push us, we would be passive and do nothing.
• Make sure to balance and integrate emotional insights with logical reasoning.
• Practice emotional intelligence skills to better your decisions.

Many would consider emotions to be a hindrance to decision-making and, therefore, think that they would be better off without them. They may avoid or suppress them, rather than feel, process and understand their meaning. When it comes to the decision-making process, they would prefer to be rational rather than emotional.

However, emotions have value. It appears that without emotions to motivate and push us, we would be passive and do nothing. Decisions are very much informed by our emotional state since this is what emotions are designed to do. Emotions quickly condense an experience, and evaluate it to inform our decision, so we can rapidly respond to the situation.

While emotions serve to direct us, they are driven by our automatic survival nature. As such, most of the time emotions communicate their messages below our level of awareness. It is important to note that because of their speed and survival purpose, emotions are not particularly accurate. Their speed and effectiveness compensate for what they lack in being specific and detailed. This is why the emotional system provides many false alarms, which requires us to reevaluate our response and check if it is appropriate to the particular situation.

The latest research has established that emotion is crucial in a rational decision-making process. Antonio Damasio and his colleagues concluded that in the absence of emotional markers, decision making is virtually unattainable. Our emotions will drive the conclusions we make, and our well-being may depend upon our ability to understand and interpret them while integrating them with a rational mind to make an appropriate decision. While it is important to consider and process emotional signals, we need to evaluate our responses and see if they are proper to the relevant situation.

How to use emotions to make effective decision-making?

Here are some steps to effectively use emotions for successful decision-making:

Welcome your emotions

Don’t repress or ignore your emotions. Start by identifying and understanding your emotions. Take a moment to recognize what you are feeling and why you are feeling. This mindful process of self-examination is critical to healthy decisions, since emotions can influence our views and judgments.

Remember “emotional bias”

Because of their survival nature, emotions can create biases that affect how we perceive information and interpret situations. Remember that the emotional brain cares more about being safe than about being correct. Listen to its alarm signal, and at the same time question its message.

Regulate your emotions

Emotions, especially at a high intensity, impact our ability to make rational decisions. Strong emotions can impair our judgment and make it challenging to think objectively and critically. This is why it is important to temper our emotions to be balanced and proportional to the situation.

Utilize emotions as a guide

Emotions can act as a compass, pointing you toward what matters most to you and/or what aligns with your values. However, it is essential to avoid letting emotions dictate your decision-making. Make sure to balance emotional insights with logical reasoning.

Enlist your rational mind

It is important to enlist the help of the rational mind. By doing so, you move from a system that operates quickly, intuitively, and unconsciously to a system that is slower and more controlled, rational, and conscious. You move beyond an impulsive, reactive emotional system to one that is contemplative, flexible, and strategic.

Consider the context

Evaluate the situation at hand and consider that emotions may be influenced by the context. Emotions that arise from past experiences or personal biases might cloud your judgment. Separate the present situation from the past and focus on the relevant factors.

Assemble relevant information

Emotions can provide valuable insights, but they should be complemented with factual information. Take your time to gather crucial information before making important decisions. Analyze the pros and cons of your options to make the best possible decisions.

Mindfulness is key to harmonizing the mind. The unregulated mind can become deluded, allowing passions, urges, and wild emotions to take over. Mindfulness allows us to notice our emotions and engage the rational mind to interpret their message. The goal is to treat your emotions as a gateway to a greater level of awareness.

Cultivate compassion

Cultivating compassion in decision making is a powerful way to make more empathetic , ethical, and balanced choices that consider the well-being of all. Compassion helps us soothe the emotional mind and choose actions that will benefit ourselves and others.

Practice emotional intelligence

Emotional intelligence is the ability to recognize and manage your emotions effectively. Key elements of emotional intelligence are self-awareness, self-regulation , motivation , empathy, and social skills. By developing emotional intelligence skills, you can use your emotions to inform your decisions without being controlled by them.

Reframe the situation

Reframing means consciously changing your way of thinking about the meaning of an emotionally charged situation in order to reduce negative feelings. You shift your interpretation of an event by specifically having loving thoughts and extending compassion to yourself and to other people.

Expand your perspective

When you see the big picture and are focused on your highest purpose, you are not distracted by smaller issues and impulses. Figuring out your deepest long-term goals and pursuing them will channel your emotions toward peace and harmony. It will allow you to recognize that if the decision is driven by your values, it’s the best decision regardless of the outcome.

To sum up, emotions play a significant role in decision-making and, when used properly, they can enhance the effectiveness of the decision-making process. Remember, emotions are a natural part of being human, and they can be a valuable asset in decision-making. By combining emotional insights with rational thinking, you can make more effective and well-rounded decisions.

Keltner D, Lerner JS.( 2010). Emotion. In The Handbook of social psychology, ed. DT Gilbert, ST Fiske, G Lindzey, pp. 317-52. New York, NY: Wiley

Damasio, A.R. (1990). Individuals with sociopathic behavior caused by frontal damage fail to respond autonomically to social stimuli". Behavioural brain research, 41 , 81-94

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Emotions Aren’t the Enemy of Good Decision-Making

• Cheryl Strauss Einhorn

Identify how you feel about the decision — and how you want to feel when it’s made.

Too often, when we need to make a difficult decision, we rush through it to avoid sitting with uncomfortable emotions. But channelling those emotions — a process the author calls “emotional bookending” — can help us ensure that we’ve correctly identified the decision we have to make and set us up to move forward with clarity and confidence. The process is as simple as taking the time to identify 1) the emotions you feel as you face your decision, and 2) the emotions you want to feel as you’re looking at your decision in the rearview mirror. What do you see? How is your life better for a satisfying decision outcome?

I recently gave a keynote address at Cornell University about how to better ensure the success of the decisions we make. I began by polling the audience of about 2,000 people to gauge whether they worry about making mistakes when they face a big decision. A whopping 92% of attendees responded yes.

• Cheryl Strauss Einhorn is the founder and CEO of Decisive, a decision sciences company using her AREA Method decision-making system for individuals, companies, and nonprofits looking to solve complex problems. Decisive offers digital tools and in-person training, workshops, coaching and consulting. Cheryl is a long-time educator teaching at Columbia Business School and Cornell and has won several journalism awards for her investigative news stories. She’s authored two books on complex problem solving, Problem Solved for personal and professional decisions, and Investing In Financial Research about business, financial, and investment decisions. Her new book, Problem Solver, is about the psychology of personal decision-making and Problem Solver Profiles. For more information please watch Cheryl’s TED talk and visit areamethod.com .

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The Power Of Emotions: Unveiling Their Impact On Critical Thinking

Table of Contents

Importance of Critical Thinking

Critical thinking is a crucial skill that allows individuals to analyze, evaluate, and interpret information in a logical and rational manner. It enables us to make informed decisions, solve problems effectively, and think independently. In today’s complex and fast-paced world, critical thinking has become increasingly important in various aspects of our lives, including education, work, and personal relationships.

Influence of Emotions on Critical Thinking

While critical thinking is often associated with rationality and logic, it is important to recognize the significant role that emotions play in our thought processes. Emotions are an integral part of being human, and they can greatly influence our thinking and decision-making abilities. Understanding the relationship between emotions and critical thinking is essential for developing a well-rounded approach to problem-solving and decision-making.

Emotions can impact critical thinking in several ways. They can shape our perception and interpretation of information, influence our biases and judgments, and even affect our creativity and problem-solving skills. Emotions can either enhance or hinder our ability to think critically, depending on how we manage and regulate them.

In this article, we will explore the concept of emotions and their influence on critical thinking. We will delve into the different types of emotions, how they are triggered and experienced, and their impact on decision-making, perception, and problem-solving. We will also discuss the importance of emotion regulation and how it can enhance critical thinking skills. Additionally, we will explore the connection between emotional intelligence and critical thinking abilities and provide tips for developing emotional intelligence to improve critical thinking skills.

By understanding the relationship between emotions and critical thinking, we can learn to harness the power of emotions to enhance our decision-making and problem-solving abilities. We can also develop strategies to regulate our emotions effectively, ensuring that they do not hinder our critical thinking processes. Ultimately, by cultivating emotional intelligence and balancing emotions with rationality, we can become more effective critical thinkers in all aspects of our lives.

In the following sections, we will delve deeper into the understanding of emotions, explore their relationship with critical thinking, discuss strategies for emotion regulation, and provide tips for developing emotional intelligence. We will also analyze real-life case studies and examples to illustrate the impact of emotions on critical thinking. Finally, we will provide practical techniques for balancing emotions and critical thinking and conclude with a summary of the importance of understanding and managing emotions in the pursuit of effective critical thinking.

So, let’s dive in and explore the fascinating world of emotions and their influence on critical thinking!

Understanding Emotions

Emotions play a significant role in our lives, influencing our thoughts, actions, and decision-making processes. Understanding emotions is essential for developing effective critical thinking skills. In this section, we will explore the definition and characteristics of emotions, how they are triggered and experienced, and the different types of emotions that exist.

Definition and Explanation of Emotions

Emotions can be defined as intense feelings that arise in response to specific situations or stimuli. They are complex psychological and physiological responses that involve subjective experiences, physiological changes, and behavioral expressions. Emotions are an integral part of the human experience and are closely tied to our thoughts and perceptions.

Different Types of Emotions and Their Characteristics

Emotions can be categorized into various types, each with its own unique characteristics. Some common types of emotions include happiness, sadness, anger, fear, surprise, and disgust. Each emotion has its own distinct set of physiological responses, such as changes in heart rate, facial expressions, and body language.

For example, happiness is often associated with positive experiences and is characterized by feelings of joy, contentment, and satisfaction. It is typically accompanied by a smile, relaxed facial muscles, and an overall sense of well-being. On the other hand, anger is an emotion that arises in response to perceived threats or injustices and is characterized by feelings of frustration, hostility, and the desire to retaliate. It is often accompanied by increased heart rate, clenched fists, and a tense facial expression.

How Emotions are Triggered and Experienced

Emotions can be triggered by various factors, including external events, internal thoughts, and physiological changes. External events, such as receiving good news or experiencing a traumatic event, can elicit emotional responses. Internal thoughts and interpretations of situations also play a significant role in triggering emotions. For example, perceiving a situation as threatening can lead to feelings of fear or anxiety.

Once emotions are triggered, they are experienced subjectively. Individuals may have different emotional responses to the same situation based on their personal experiences, beliefs, and values. The experience of emotions involves a combination of cognitive processes, physiological changes, and behavioral expressions. These experiences can vary in intensity, duration, and the way they are expressed.

Understanding emotions and their characteristics is crucial for developing effective critical thinking skills. Emotions can significantly influence our decision-making processes, perceptions, and problem-solving abilities. By gaining a deeper understanding of emotions, we can better navigate their impact on our critical thinking and make more informed and rational decisions.

In the next section, we will explore the relationship between emotions and critical thinking, examining how emotions can influence our decision-making, perception of information, and problem-solving abilities.

The Relationship Between Emotions and Critical Thinking

Emotions play a significant role in our daily lives, influencing our thoughts, actions, and decision-making processes. When it comes to critical thinking, emotions can have a profound impact on how we perceive and interpret information, make decisions, and solve problems. Understanding the relationship between emotions and critical thinking is crucial for developing effective thinking skills and making rational choices.

Exploring the Impact of Emotions on Decision-Making

Emotions can greatly influence our decision-making processes. When we are experiencing strong emotions such as fear, anger, or excitement, our ability to think critically may be compromised. These emotions can cloud our judgment and lead us to make impulsive or irrational decisions. On the other hand, positive emotions like happiness or enthusiasm can enhance our creativity and open our minds to new possibilities.

How Emotions Influence Perception and Interpretation of Information

Emotions can also shape how we perceive and interpret information. Our emotional state can affect our attention, memory, and reasoning abilities, leading us to focus on certain aspects of a situation while ignoring others. For example, if we are feeling anxious or fearful, we may be more likely to interpret ambiguous information in a negative or threatening way. This can hinder our ability to think critically and objectively analyze the facts.

The Role of Emotions in Problem-Solving and Creativity

Emotions can have a significant impact on problem-solving and creative thinking. While negative emotions can sometimes hinder our problem-solving abilities by narrowing our focus and limiting our options, positive emotions can enhance our creativity and innovative thinking. When we are in a positive emotional state, we are more likely to think outside the box, consider alternative solutions, and approach problems from different perspectives.

The Connection Between Emotions and Biases in Critical Thinking

Emotions can also contribute to biases in critical thinking. Our emotions can influence our beliefs, attitudes, and opinions, leading us to be more receptive to information that aligns with our emotional state and dismissive of contradictory evidence. This confirmation bias can hinder our ability to think critically and objectively evaluate information. Recognizing and managing our emotions is essential for overcoming biases and engaging in unbiased critical thinking.

Understanding the relationship between emotions and critical thinking is crucial for developing effective thinking skills and making rational choices. Emotion regulation, the ability to manage and control our emotions, is essential for enhancing critical thinking abilities. By learning strategies for managing emotions, such as deep breathing, mindfulness, and reframing techniques, we can improve our decision-making and problem-solving skills.

Cultivating Emotional Intelligence for Improved Critical Thinking

Emotional intelligence, the ability to understand and manage our own emotions and empathize with others, is closely linked to critical thinking abilities. Developing emotional intelligence can enhance our self-awareness, self-regulation, and empathy, all of which are essential for effective critical thinking. By practicing self-reflection, active listening, and empathy, we can cultivate emotional intelligence and improve our critical thinking skills.

Case Studies and Examples

Real-life examples can provide valuable insights into how emotions can impact critical thinking. By analyzing specific situations where emotions played a significant role in decision-making or problem-solving, we can gain a deeper understanding of the relationship between emotions and critical thinking. These case studies can serve as learning opportunities and help us develop strategies for managing emotions in similar situations.

Strategies for Balancing Emotions and Critical Thinking

Maintaining a balance between emotions and rationality is essential for effective critical thinking. Techniques such as recognizing and acknowledging our emotions, taking a step back to evaluate the situation objectively, and seeking different perspectives can help us balance our emotions and engage in logical and rational thinking. Incorporating emotional awareness into our critical thinking practices can lead to more informed and thoughtful decision-making.

In conclusion, emotions and critical thinking are closely intertwined. Emotions can greatly influence our decision-making, perception, and problem-solving abilities. By understanding the relationship between emotions and critical thinking and developing emotional intelligence, we can enhance our critical thinking skills and make more rational and informed choices. Managing and balancing our emotions is key to effective critical thinking and achieving success in various aspects of our lives.

Emotion Regulation and its Effect on Critical Thinking

Emotion regulation plays a crucial role in enhancing critical thinking skills. When emotions are not effectively managed, they can cloud judgment and hinder rational decision-making. On the other hand, when emotions are regulated and controlled, they can contribute to more accurate and effective critical thinking. In this section, we will explore the importance of emotion regulation and its effect on critical thinking.

The Importance of Regulating Emotions for Effective Critical Thinking

Emotions can have a significant impact on critical thinking. When we are overwhelmed by strong emotions such as anger, fear, or sadness, our ability to think critically may be compromised. These intense emotions can distort our perception of reality and lead to biased thinking. Emotion regulation is essential because it allows us to maintain a balanced and rational mindset, enabling us to make better decisions and solve problems more effectively.

Strategies for Managing and Controlling Emotions

To regulate emotions effectively, it is essential to develop strategies that help us manage and control our emotional responses. Here are a few techniques that can be helpful:

Self-awareness : Recognizing and acknowledging our emotions is the first step towards regulating them. Taking the time to understand what we are feeling and why can help us gain control over our emotional state.

Deep breathing and relaxation techniques : When we are experiencing intense emotions, taking deep breaths and engaging in relaxation techniques can help calm our minds and bodies. This can create space for clearer thinking and better decision-making.

Cognitive reappraisal : This technique involves reframing our thoughts and changing our perspective on a situation. By challenging negative or irrational thoughts, we can reduce the intensity of our emotional response and think more objectively.

Seeking support : Talking to a trusted friend, family member, or therapist can provide valuable support and perspective. Sharing our emotions and concerns with others can help us gain insight and find healthier ways to cope with challenging situations.

How Emotion Regulation Enhances Decision-Making and Problem-Solving Skills

Emotion regulation directly impacts our decision-making and problem-solving abilities. When we can effectively regulate our emotions, we are better able to:

Consider multiple perspectives : Emotion regulation allows us to step back from our initial emotional reactions and consider alternative viewpoints. This broader perspective enables us to make more informed decisions and find creative solutions to problems.

Evaluate evidence objectively : Emotions can bias our interpretation of information. By regulating our emotions, we can approach evidence more objectively, weighing its credibility and relevance without being swayed by our emotional biases.

Manage conflicts : Emotion regulation helps us navigate conflicts more effectively. By staying calm and composed, we can engage in constructive dialogue, listen to others’ perspectives, and find mutually beneficial solutions.

Maintain focus and attention : Emotion regulation helps us stay focused on the task at hand. By managing distractions and reducing emotional interference, we can concentrate better and think more critically.

In conclusion, emotion regulation is a vital skill for enhancing critical thinking. By managing and controlling our emotions, we can improve our decision-making, problem-solving, and overall critical thinking abilities. Developing strategies for emotion regulation, such as self-awareness, relaxation techniques, cognitive reappraisal, and seeking support, can significantly contribute to our success in critical thinking endeavors. So, let us strive to cultivate emotional intelligence and regulate our emotions to become more effective critical thinkers.

Emotional intelligence plays a crucial role in our ability to think critically. It involves understanding and managing our emotions effectively, which in turn enhances our decision-making, problem-solving, and creativity skills. By cultivating emotional intelligence, we can significantly improve our critical thinking abilities. In this section, we will explore the concept of emotional intelligence, its link to critical thinking, and provide tips for developing emotional intelligence to enhance our critical thinking skills.

Definition and Explanation of Emotional Intelligence

Emotional intelligence refers to the ability to recognize, understand, and manage our own emotions, as well as the emotions of others. It involves being aware of our emotions and using that awareness to guide our thoughts and actions. Emotional intelligence comprises several components, including self-awareness, self-regulation, empathy, and social skills.

The Link Between Emotional Intelligence and Critical Thinking Abilities

Emotional intelligence and critical thinking are closely intertwined. When we have a high level of emotional intelligence, we are better equipped to think critically and make informed decisions. Here’s how emotional intelligence enhances our critical thinking abilities:

Self-Awareness: Emotional intelligence helps us become more aware of our own emotions, biases, and thought patterns. This self-awareness allows us to recognize when our emotions may be influencing our thinking and helps us approach problems and decisions with a more rational mindset.

Empathy: Emotional intelligence enables us to understand and empathize with the perspectives and emotions of others. This ability to see things from different viewpoints enhances our critical thinking by allowing us to consider alternative solutions and evaluate information from a broader perspective.

Self-Regulation: Emotional intelligence helps us regulate our emotions, preventing them from clouding our judgment. By managing our emotions effectively, we can approach critical thinking tasks with a clear and objective mindset, leading to more accurate analysis and decision-making.

Social Skills: Emotional intelligence also encompasses social skills, such as effective communication, collaboration, and conflict resolution. These skills are essential for critical thinking, as they enable us to engage in constructive discussions, consider diverse opinions, and work effectively with others to solve complex problems.

Tips for Developing Emotional Intelligence to Enhance Critical Thinking Skills

Developing emotional intelligence is an ongoing process that requires self-reflection and practice. Here are some tips to cultivate emotional intelligence and improve critical thinking skills:

Self-Reflection: Take time to reflect on your emotions, thoughts, and reactions in different situations. Identify any patterns or biases that may be influencing your critical thinking. Regular self-reflection helps you become more self-aware and better understand the impact of emotions on your thinking process.

Emotion Regulation Techniques: Learn and practice techniques for managing and regulating your emotions. Deep breathing exercises, mindfulness meditation, and journaling are effective methods for calming your mind and gaining control over your emotions. These techniques can help you approach critical thinking tasks with a clear and focused mindset.

Active Listening and Empathy: Practice active listening and empathy in your interactions with others. Pay attention to their emotions, perspectives, and concerns. This will enhance your ability to understand different viewpoints and think critically about complex issues.

Seek Diverse Perspectives: Actively seek out diverse perspectives and opinions. Engage in discussions with people who have different backgrounds, experiences, and beliefs. This exposure to diverse viewpoints will broaden your thinking and challenge your assumptions, leading to more robust critical thinking.

Continuous Learning: Engage in lifelong learning to expand your knowledge and skills. Read books, attend workshops, and take courses that focus on emotional intelligence, critical thinking, and related topics. Continuous learning helps you develop a growth mindset and stay updated with the latest research and practices in emotional intelligence and critical thinking.

By cultivating emotional intelligence, we can enhance our critical thinking skills and make more informed decisions. Developing self-awareness, empathy, self-regulation, and social skills enables us to approach critical thinking tasks with clarity and objectivity. Remember, emotional intelligence is a journey, and with consistent practice and effort, we can continuously improve our ability to think critically and make sound judgments.

In this section, we will explore real-life case studies and examples that demonstrate the impact of emotions on critical thinking. By analyzing these situations, we can gain a deeper understanding of how emotions can influence our decision-making and problem-solving abilities.

Real-life examples demonstrating the impact of emotions on critical thinking

Example 1: the impulsive purchase.

Imagine a scenario where you are shopping for a new smartphone. You have done thorough research, comparing different models and reading reviews. However, when you visit the store, you come across a flashy advertisement for a brand-new phone that promises to be the “best in the market.” Despite your initial research, you are swayed by the excitement and emotions triggered by the advertisement. As a result, you make an impulsive purchase without considering all the factors you had previously analyzed.

This example highlights how emotions can override critical thinking and lead to irrational decision-making. The excitement and desire for the latest technology can cloud our judgment and prevent us from making a well-informed choice.

Example 2: The Confirmation Bias

Confirmation bias is a cognitive bias that occurs when we seek out information that confirms our existing beliefs and ignore or dismiss evidence that contradicts them. Emotions play a significant role in this bias, as our emotional attachment to certain beliefs can prevent us from critically evaluating alternative perspectives.

For instance, imagine a political debate where two individuals hold opposing views. Despite being presented with well-reasoned arguments and evidence from the other side, both individuals remain steadfast in their beliefs. Their emotional attachment to their respective ideologies prevents them from critically analyzing the opposing viewpoints and considering alternative perspectives.

Analysis of how emotions affected critical thinking in specific situations

Situation 1: the job interview.

During a job interview, emotions can significantly impact our critical thinking abilities. For example, if a candidate is feeling nervous or anxious, they may struggle to articulate their thoughts clearly or think critically under pressure. On the other hand, if a candidate is overconfident, they may overlook important details or fail to consider alternative solutions.

In this situation, it is crucial to recognize and regulate emotions to ensure that they do not hinder our ability to think critically. By practicing emotional intelligence and maintaining a calm and composed mindset, candidates can enhance their critical thinking skills and make more informed decisions during the interview process.

Situation 2: The Negotiation

Emotions can also play a significant role in negotiations. For instance, if a negotiator becomes angry or frustrated during a negotiation, they may lose focus and make impulsive decisions that are not in their best interest. On the other hand, if a negotiator is too empathetic, they may give in to the demands of the other party without critically evaluating the situation.

To overcome these challenges, it is important to develop emotional intelligence and practice emotion regulation techniques. By staying calm, managing emotions, and maintaining a rational mindset, negotiators can make more strategic decisions and achieve better outcomes.

In conclusion, these case studies and examples illustrate the impact of emotions on critical thinking. Emotions can either enhance or hinder our ability to think critically, depending on how we manage and regulate them. By understanding the influence of emotions on our decision-making processes, we can develop strategies to cultivate emotional intelligence and improve our critical thinking skills. It is essential to recognize the role of emotions in critical thinking and strive for a balance between emotions and rationality in order to make well-informed and effective decisions.

In the pursuit of effective critical thinking, it is crucial to find a balance between emotions and rationality. While emotions play a significant role in decision-making and problem-solving, they can also cloud judgment and lead to biased thinking. To ensure that emotions do not hinder the critical thinking process, it is essential to employ strategies for recognizing, managing, and balancing emotions. Here are some techniques to help achieve this balance:

Recognize and Acknowledge Emotions

The first step in balancing emotions and critical thinking is to recognize and acknowledge the emotions you are experiencing. Emotions can be powerful and can influence our thoughts and actions. By being aware of our emotions, we can better understand how they might be impacting our critical thinking processes. Take a moment to reflect on your emotions and identify any biases or preconceived notions they may be causing.

Practice Emotional Regulation

Emotional regulation is the ability to manage and control our emotions effectively. By practicing emotional regulation techniques, we can prevent our emotions from overwhelming our critical thinking abilities. Deep breathing exercises, mindfulness meditation, and journaling are just a few examples of strategies that can help regulate emotions. These techniques can help calm the mind and create a space for rational thinking.

Seek Different Perspectives

When faced with a challenging problem or decision, it is essential to seek different perspectives. Engaging with diverse viewpoints can help counteract the influence of emotions on critical thinking. By considering alternative viewpoints, we can gain a more comprehensive understanding of the situation and make more informed decisions. Engaging in discussions with others who may have different opinions can help challenge our own biases and emotional attachments.

Use Logic and Reasoning

To balance emotions and critical thinking, it is crucial to rely on logic and reasoning. Emotions can sometimes lead to impulsive or irrational decisions. By employing logical thinking and reasoning, we can evaluate information objectively and make sound judgments. When faced with a challenging situation, take a step back and analyze the facts and evidence at hand. This will help reduce the influence of emotions and ensure a more balanced approach to critical thinking.

Take Breaks and Self-Care

Taking breaks and practicing self-care is essential for maintaining a healthy balance between emotions and critical thinking. When we are stressed or overwhelmed, our emotions can become heightened, leading to biased thinking. By prioritizing self-care activities such as exercise, spending time with loved ones, or engaging in hobbies, we can reduce stress levels and promote emotional well-being. Taking breaks from intense critical thinking tasks allows us to recharge and approach problems with a fresh perspective.

Reflect and Learn from Mistakes

Balancing emotions and critical thinking is an ongoing process that requires self-reflection and learning from mistakes. It is essential to reflect on past experiences and identify how emotions may have influenced our critical thinking. By learning from these experiences, we can develop strategies to better manage emotions in the future. Embrace failures and mistakes as opportunities for growth and improvement.

In conclusion, balancing emotions and critical thinking is crucial for effective decision-making and problem-solving. By recognizing and acknowledging emotions, practicing emotional regulation, seeking different perspectives, using logic and reasoning, taking breaks and practicing self-care, and reflecting on past experiences, we can achieve a healthy balance between emotions and critical thinking. Developing these strategies will enhance our ability to think critically and make informed decisions, leading to personal and professional success.

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Emotion and Information Processing pp 1–14 Cite as

Effect of Emotion in Information Processing for Decision-Making

• Smriti Pathak 2 &
• Kailash B. L. Srivastava 2  
• First Online: 22 October 2020

852 Accesses

Decision-making is a process of selection among other options and a problem-solving activity. This is a cognitive process which is influenced by cognitive skills, the psychological makeup of the decision-maker and the situation itself. The deliberation and selection of the final decision go through certain information processing. This chapter discusses the effect of emotion in information processing for decision-making. The influence of emotion has been recognized as the motivational process and input information in decision-making. The types of emotions and influence, the categorical dimensional model of emotion and dual processing in the emotional state are discussed in detail with an understanding of an advantageous or disadvantageous role played by emotion in decision-making. The effect of emotional state on risk perception and judgement and the possibility of gender difference in information processing are integrated into different sections. This chapter also attempts to address relevant neuroscientific research finding related to information processing in decision-making.

• Decision-making
• Information processing
• Dual processing
• Risk perception

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Pathak, S., Srivastava, K.B.L. (2020). Effect of Emotion in Information Processing for Decision-Making. In: Mohanty, S.N. (eds) Emotion and Information Processing. Springer, Cham. https://doi.org/10.1007/978-3-030-48849-9_1

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The Influences of Emotion on Learning and Memory

Emotion has a substantial influence on the cognitive processes in humans, including perception, attention, learning, memory, reasoning, and problem solving. Emotion has a particularly strong influence on attention, especially modulating the selectivity of attention as well as motivating action and behavior. This attentional and executive control is intimately linked to learning processes, as intrinsically limited attentional capacities are better focused on relevant information. Emotion also facilitates encoding and helps retrieval of information efficiently. However, the effects of emotion on learning and memory are not always univalent, as studies have reported that emotion either enhances or impairs learning and long-term memory (LTM) retention, depending on a range of factors. Recent neuroimaging findings have indicated that the amygdala and prefrontal cortex cooperate with the medial temporal lobe in an integrated manner that affords (i) the amygdala modulating memory consolidation; (ii) the prefrontal cortex mediating memory encoding and formation; and (iii) the hippocampus for successful learning and LTM retention. We also review the nested hierarchies of circular emotional control and cognitive regulation (bottom-up and top-down influences) within the brain to achieve optimal integration of emotional and cognitive processing. This review highlights a basic evolutionary approach to emotion to understand the effects of emotion on learning and memory and the functional roles played by various brain regions and their mutual interactions in relation to emotional processing. We also summarize the current state of knowledge on the impact of emotion on memory and map implications for educational settings. In addition to elucidating the memory-enhancing effects of emotion, neuroimaging findings extend our understanding of emotional influences on learning and memory processes; this knowledge may be useful for the design of effective educational curricula to provide a conducive learning environment for both traditional “live” learning in classrooms and “virtual” learning through online-based educational technologies.

Introduction

Emotional experiences are ubiquitous in nature and important and perhaps even critical in academic settings, as emotion modulates virtually every aspect of cognition. Tests, examinations, homework, and deadlines are associated with different emotional states that encompass frustration, anxiety, and boredom. Even subject matter influences emotions that affect one’s ability to learn and remember. The usage of computer-based multimedia educational technologies, such as intelligent tutoring systems (ITSs) and massive open online courses (MOOCs), which are gradually replacing traditional face-to-face learning environments, is increasing. This may induce various emotional experiences in learners. Hence, emotional influences should be carefully considered in educational courses design to maximize learner engagement as well as improve learning and long-term retention of the material ( Shen et al., 2009 ). Numerous studies have reported that human cognitive processes are affected by emotions, including attention ( Vuilleumier, 2005 ), learning and memory ( Phelps, 2004 ; Um et al., 2012 ), reasoning ( Jung et al., 2014 ), and problem-solving ( Isen et al., 1987 ). These factors are critical in educational domains because when students face such difficulties, it defeats the purpose of schooling and can potentially render it meaningless. Most importantly, emotional stimuli appear to consume more attentional resources than non-emotional stimuli ( Schupp et al., 2007 ). Moreover, attentional and motivational components of emotion have been linked to heightened learning and memory ( Pekrun, 1992 ; Seli et al., 2016 ). Hence, emotional experiences/stimuli appear to be remembered vividly and accurately, with great resilience over time.

Recent studies using functional neuroimaging techniques detect and recognize human emotional states and have become a topic of increasing research in cognitive neuroscience, affective neuroscience, and educational psychology to optimize learning and memory outcomes ( Carew and Magsamen, 2010 ; Um et al., 2012 ). Human emotions comprise complex interactions of subjective feelings as well as physiological and behavioral responses that are especially triggered by external stimuli, which are subjectively perceived as “personally significant.” Three different approaches are used to monitor the changes in emotional states: (1) subjective approaches that assess subjective feelings and experiences; (2) behavioral investigations of facial expressions ( Jack and Schyns, 2015 ), vocal expressions ( Russell et al., 2003 ), and gestural changes ( Dael et al., 2012 ); and (3) objective approaches via physiological responses that include electrical and hemodynamic of the central nervous system (CNS) activities ( Vytal and Hamann, 2010 ) in addition to autonomic nervous system (ANS) responses such as heart rate, respiratory volume/rate, skin temperature, skin conductance and blood volume pulses ( Li and Chen, 2006 ). The CNS and ANS physiological responses (brain vs. body organs) can be objectively measured via neuroimaging and biosensors and are more difficult to consciously conceal or manipulate compared to subjective and behavioral responses. Although functional neuroimaging enables us to identify brain regions of interest for cognitive and emotional processing, it is difficult to comprehend emotional influences on learning and memory retrieval without a fundamental understanding of the brain’s inherent emotional operating systems.

The aim of this current article was to highlight an evolutionary approach to emotion, which may facilitate understanding of the effects of emotion on learning and memory. We initially present the terminology used in affective neuroscience studies, describe the roles of emotion and motivation in learning and memory, and outline the evolutionary framework and the seven primary emotional system. This is followed by the emotional-cognitive interactions in the various brain regions that are intimately involved in emotion and memory systems. This is performed to define the congruent interactions in these regions are associated with long-term memory (LTM) retention. We then discuss the emerging studies that further our understanding of emotional effects deriving from different modalities of emotional content. This is followed by a discussion of four major functional neuroimaging techniques, including functional magnetic resonance imaging (fMRI), positron emission tomography (PET), electroencephalography (EEG), and functional near-infrared spectroscopy (fNIRS). We then present the important factors for consideration in experimental design, followed by a description of psychiatric disorders, such as depression and anxiety, which are emotionally charged dysfunctions that are strongly detrimental to cognitive performance. Our review ends with concluding remarks on the current issues and future research possibilities with respect to the efficient enhancement of educational practices and technologies.

Emotions, Moods, Feelings, Affects and Drives

Subjective terms used in affective neuroscience include emotions, moods, feelings, affects and drives. Although emotion has long been studied, it bears no single definition. A review of 92 putative definitions and nine skeptical statements ( Kleinginna and Kleinginna, 1981 ) suggests a definition with a rather broad consensus:

• simple  Emotions describe a complex set of interactions between subjective and objective variables that are mediated by neural and hormonal systems, which can (a) give rise to affective experiences of emotional valence (pleasure-displeasure) and emotional arousal (high-low activation/calming-arousing); (b) generate cognitive processes such as emotionally relevant perceptual affect, appraisals, labeling processes; (c) activate widespread psychological and physiological changes to the arousing conditions; and (d) motivate behavior that is often but not always expressive, goal-directed and adaptive.

Although this definition may be adequate for everyday purposes, it does not encompass some important aspects of emotional systems such as how emotions operate to create subjectively experienced feelings and how they control personality dimensions. Accordingly, Panksepp (1998) suggested the following:

• simple  Emotions are the psychoneural processes that are influential in controlling the vigor and patterning of actions in the dynamic flow of intense behavioral interchanges between animals as well as with certain objects that are important for survival. Hence, each emotion has a characteristic “feeling tone” that is especially important in encoding the intrinsic values of these interactions, depending on their likelihood of either promoting or hindering survival (both in the immediate “personal” and long-term “reproductive” sense). Subjective experiential-feelings arise from the interactions of various emotional systems with the fundamental brain substrates of “the self,” that is important in encoding new information as well as retrieving information on subsequent events and allowing individuals efficiently to generalize new events and make decisions.

He went further to propose seven primary emotional systems/prototype emotional states, namely SEEKING, RAGE, FEAR, LUST, CARE, PANIC/GRIEF, and PLAY that represent basic foundations for living and learning.

Moods last longer than emotions, which are also characterized by positive and negative moods. In contrast, feelings refer to mental experiences that are necessarily valence, either good or bad as well as accompanied by internal physiological changes in the body, specifically the viscera, including the heart, lungs, and gut, for maintaining or restoring homeostatic balances. Feelings are not commonly caused emotions. Because the generation of emotional feelings requires a neural re-mapping of different features of the body state in the CNS, resulting from cognitive “appraisal” where the anterior insular cortex plays a key integrative role ( Craig and Craig, 2009 ; Damasio and Carvalho, 2013 ). Nonetheless, Panksepp (2005) has defended the view that emotional operating systems (caudal and medial subcortical brain regions) appeared to generate emotional experiences via localized electrical stimulation of the brain stimulation (ESB) rather dependent on changes of the external environment or bodily states. Affects are subjective experienced emotional feelings that are difficult to describe, but have been linked to bodily states such as homeostatic drives (hunger and thirst) and external stimuli (visual, auditory, taste, touch, smell) ( Panksepp, 2005 ). The latter are sometimes called “core affect,” which refers to consciously accessible elemental processes involving pleasure and arousal that span bipolar dimensions ( Russell and Barrett, 1999 ). In addition, a “drive” is an inherent action program that is responsible for the satisfaction of basic and instinctual (biologically pre-set) physiological needs, e.g., hunger, thirst, libido, exploration, play, and attachment to mates ( Panksepp, 1998 ); this is sometimes called “homeostatic drive.” In brief, a crucial characteristic shared by emotion, mood, feeling, affect and drive is their intrinsic valence, which lies on the spectrum of positive and negative valence (pleasure-displeasure/goodness-badness). The term emotion exemplifies the “umbrella” concept that includes affective, cognitive, behavioral, expressive and physiological changes; emotion is triggered by external stimuli and associated with the combination of feeling and motivation.

Recent Evidence Regarding the Role of Emotion in Learning and Memory

The impact of emotion on learning processes is the focus of many current studies. Although it is well established that emotions influence memory retention and recall, in terms of learning, the question of emotional impacts remains questionable. Some studies report that positive emotions facilitate learning and contribute to academic achievement, being mediated by the levels of self-motivation and satisfaction with learning materials ( Um et al., 2012 ). Conversely, a recent study reported that negative learning-centered state (confusion) improve learning because of an increased focus of attention on learning material that leads to higher performances on post tests and transfer tests ( D’Mello et al., 2014 ). Confusion is not an emotion but a cognitive disequilibrium state induced by contradictory data. A confused student might be frustrated with their poor understanding of subject matter, and this is related to both the SEEKING and RAGE systems, with a low-level of activation of rage or irritation, and amplification of SEEKING. Hence, motivated students who respond to their confusion seek new understanding by doing additional cognitive work. Further clarification of this enhances learning. Moreover, stress, a negative emotional state, has also been reported to facilitate and/or impair both learning and memory, depending on intensity and duration ( Vogel and Schwabe, 2016 ). More specifically, mild and acute stress facilitates learning and cognitive performance, while excess and chronic stress impairs learning and is detrimental to memory performance. Many other negative consequences attend owing to overactivity of the hypothalamic-pituitary-adrenal (HPA) axis, which results in both impaired synaptic plasticity and learning ability ( Joëls et al., 2004 ). Nonetheless, confounding influences of emotions on learning and memory can be explained in terms of attentional and motivational components. Attentional components enhance perceptual processing, which then helps to select and organize salient information via a “bottom-up” approach to higher brain functions and awareness ( Vuilleumier, 2005 ). Motivational components induce curiosity, which is a state associated with psychological interest in novel and/or surprising activities (stimuli). A curiosity state encourages further exploration and apparently prepares the brain to learn and remember in both children and adults ( Oudeyer et al., 2016 ). The term “surprising” might be conceptualized as an incongruous situation (expectancy violation) refers to a discrepancy between prior expectations and the new information; it may drive a cognitive reset for “learned content” that draws one’s attention.

Similarly, emotionally enhanced memory functions have been reported in relation to selective attention elicited by emotionally salient stimuli ( Vuilleumier, 2005 ; Schupp et al., 2007 ). During the initial perceptual stage, attention is biased toward emotionally salient information that supports detection by the salient input. Thus, stimulating selective attention increases the likelihood for emotional information to become encoded in LTM storage associated with a top-down control in sensory pathways that are modulated by the frontal and parietal cortices. This is an example of an indirect influence on perception and attention that regulates selective sensory processing and behavioral determination ( Vuilleumier, 2005 ). Because the human sensory systems have no capacity to simultaneously process everything at once, which necessitates attentional mechanisms. Top-down attentional processing obtains adequate attentional resource allocation to process emotional valence information for encoding and retrieval via cooperation with the brain regions such as the ventromedial prefrontal cortex and superior temporal sulcus, along with the primary visual cortex (helps to realize both emotion and conceptualization). Similarly, experimental studies have examined the phenomenon by using various attentional tasks, including filtering (dichotic listening and Stroop task), search (visual search), cuing (attentional probe, spatial cuing) and attentional blink [rapid serial visual presentation (RSVP)] paradigms ( Yiend, 2010 ). These investigations demonstrated biased attentional processing toward emotionally stimulating material content attended by increased sensory responses. One study reported that emotional stimuli induce a “pop-out” effect that leads to the attentional capture and privileged processing ( Öhman et al., 2001 ). Moreover, a study using the RSVP paradigm compared healthy subjects with a group of patients with bilateral amygdala damage. The results revealed that healthy subjects exhibited increased perception and attention toward emotional words compared to patients, indicating that the amygdala plays a crucial role in emotional processing ( Anderson and Phelps, 2001 ). In addition, functional neuroimaging showed that the insular cortex, the secondary somatosensory cortex, the cingulate cortex and nuclei in the tegmentum and hypothalamus are the brain regions that regulate attentional focus by integrating external and internal inputs to create emotional feeling states, thus modulating a motivational state that obtains homeostasis ( Damasio et al., 2000 ). All emotional systems associated with strong motivational components such as psychological salient bodily need states operate through the SEEKING system that motivates appetitive/exploratory behavior to acquire resources needed for survival ( Montag and Panksepp, 2017 ).

The distinction between emotion and homeostasis, is the process of regulation for continuously changing internal states via appropriate corrective responses that respond to both internal and external environmental conditions to maintain an optimal physiological state in the body. Homeostatic affects , such as hunger and thirst, are not considered prototype emotional states. Because homeostatic affects have never been mapped using ESB that arouse basic emotional responses ( Panksepp, 2005 , 2007 ). However, emotional prototypes can be thought of as evolutionary extensions/predictions of impending homeostatic threats; for example, SEEKING might be an evolutionary extension of intense hunger and thirst (the major sources of suffering that signal energy depletion to search for food and water intake) ( Watt, 2012 ). Homeostatic imbalances engage the mesolimbic motivational system via hypothalamic interactions with the extended trajectory of the SEEKING system [centrally including the lateral hypothalamus, ventral basal ganglia, and ventral tegmental area (VTA)]. It is the distributed functional network that serves the general function of finding resources for survival that gets hungry animals to food, thirsty animals to water, cold animals to warmer environments, etc. ( Panksepp, 1998 ). To summarize, both emotion and motivation are crucial for the maintenance of psychological and physiological homeostasis, while emotional roles are particularly important in the process of encoding new information containing emotional components. The latter increases attention toward salient new information by selectively enhancing detection, evaluation, and extraction of data for memorization. In addition, motivational components promote learning and enhance subsequent memory retrieval while generalizing new events consequent to adaptive physiological changes.

The Evolutionary Framework of Emotion and The Seven Primary Emotional Systems

Evolution built our higher minds (the faculty of consciousness and thoughts) on a foundation of primary-process of emotional mechanism that preprogrammed executive action systems (the prototype emotions) rely on cognitive processing (interpretation) and appraisal in the organisms attempt to decipher the type of situation they might be in; in other words, how to deal with emotionally challenging situations, whether it is a play situation or a threat situation (where RAGE and FEAR might be the appropriate system to recruit). Emotion offers preprogrammed but partially modifiable (under the secondary process of learning and memory) behavioral routines in the service of the solution of prototypical adaptive challenges, particularly in dealing with friend vs. foe; these routines are evolutionary extensions of homeostasis and embed a prediction beyond the current situation to a potentially future homeostatic benefit or threat. Thus, evolution uses whatever sources for survival and procreative success. According to Panksepp and Solms (2012) , key CNS emotional-affective processes are (1) Primary-process emotions; (2) Secondary-process learning and memory; and (3) Tertiary-process higher cognitive functions. Fundamentally, primary emotional processes regulate unconditioned emotional actions that anticipate survival needs and consequently guide secondary process via associative learning mechanisms (classical/Pavlovian and instrumental/operant conditioning). Subsequently, learning process sends relevant information to higher brain regions such as the prefrontal cortex to perform tertiary cognition process that allows planning for future based on past experiences, stored in LTM. In other words, the brain’s neurodevelopment trajectory and “wiring up” activations show that there is a genetically coded aversion to situations that generate RAGE, FEAR and other negative states for minimizing painful things and maximizing pleasurable kinds of stimulation. These are not learned- all learning (secondary-process) is piggybacked on top of the “primary-process emotions” that are governed by “Law of Affect” (see Figure ​ Figure1 1 ). What now follows is an explanation of these CNS emotional-affective processing sub-levels and their inter-relationships.

Shows the nested hierarchies of circular emotional control and cognitive regulation for “bottom-up” influences and “top-down” regulations. The schematic shows conceptual relationships between primary processes of emotional system (lower brain function), as well as secondary processes of cognitive system and tertiary processing (higher brain function). Primary emotional processing for homeostatic, sensory and emotional affects facilitate secondary learning and memory processing via the “SEEKING” system that promotes survival and reproductive success (bottom-up instinctual influences). As secondary processes are continually integrated with primary emotional processing, they mature to higher brain cognitive faculties to generate effective solutions for living and subsequently exert top-down regulatory control over behavior. The primary emotional processing is mediated by complex unconditioned emotional responses (evolutionary “memories”) through “Law of Affect”; sometimes called “reinforcement principle” that explains how the brain emotional networks control learning. This bi-circular causation for higher brain functionality is coordinated by lower brain functions [adapted from ( Panksepp and Solms, 2012 )].

Primary-Process Emotions (Prototype Emotional States)

The emotional operating system is an inherited and genetically encoded circuitry that anticipates key survival and homeostatic needs. Thus, animals and humans share primary emotional network at the subcortical level, which includes the midbrain’s periaqueductal grey (PAG) and VTA, basal ganglia (amygdala and nucleus accumbens), and insula, as well as diencephalon (the cingulate and medial frontal cortices through the lateral and medial hypothalamus and medial thalamus). Subcortical brain regions are involved in three sub-components of affects: (1) core emotional feelings (fear, anger, joy and various forms of distress); (2) homeostatic drives/motivational experiences (hunger and thirst); and (3) sensory affects (pain, taste, temperature and disgust). Primary-process emotions are not unconscious. Strong emotion is intrinsically conscious at least in the sense that it is experienced even if we might mislabel it, or animal clearly is not able to attach a semantic label-these are simply not realistic standards for determining whether something is conscious or not conscious. Nonetheless, the emotional experiences guide behavior to promote survival and procreative success as well as mediate learning (‘ rewarding ’ and ‘ punishing ’ learning effects) and thinking at secondary and tertiary levels.

Secondary-Process Emotions (Learning and Memory)

Primary emotional systems guide associative learning and memory (classical/operant conditioning and emotional habit) processes via the mediation of emotional networks. This includes the basal ganglia (basolateral and central amygdala, nucleus accumbens, thalamus and dorsal striatum), and the medial temporal lobe (MTL) including hippocampus as well as the entorhinal cortex, perirhinal cortex, and parahippocampal cortices that responsible for declarative memories. Thus, secondary processes of learning and memory scrutinize and regulate emotional feelings in relation to environmental events that subsequently refine effective solutions to living.

Tertiary-Process Emotions (Higher Cognitive Functions)

Higher cognitive functions operate within the cortical regions, including the frontal cortex for awareness and consciousness functions such as thinking, planning, emotional regulation and free-will (intention-to-act), which mediate emotional feelings. Hence, cognition is an extension of emotion (just as emotion is an extension of homeostasis aforementioned). Tertiary processes are continually integrated with the secondary processes and reach a mature level (higher brain functions) to better anticipating key survival issues, thus yielding cognitive control of emotion via “top-down” regulation. In other words, brain-mind evolution enables human to reason but also regulate our emotions.

Psychologist Neisser (1963) suggested that cognition serves emotion and homeostatic needs where environmental information is evaluated in terms of its ability to satisfy or frustrate needs. In other words, cognition is in the service of satisfying emotional and homeostatic needs. This infers that cognition modulates, activates and inhibits emotion. Hence, emotion is not a simple linear event but rather a feedback process that autonomously restores an individual’s state of equilibrium. More specifically stated, emotion regulates the allocation of processing resources and determines our behavior by tuning us to the world in certain biased ways, thus steering us toward things that “feel good” while avoiding things that “feel bad.” This indicates that emotion guides and motivates cognition that promotes survival by guiding behavior and desires according to unique goal orientation ( Northoff et al., 2006 ). Therefore, the CNS maintains complex processes by continually monitoring internal and external environments. For example, changes in internal environments (contraction of visceral muscles, heart rate, etc.) are sensed by an interoceptive system (afferent peripheral nerves) that signals the sensory cortex (primary, secondary and somatosensory) for integration and processing. Thus, from an evolutionary perspective, human mental activity is driven by the ancient emotional and motivational brain systems shared by cross-mammalians that encode life-sustaining and life-detracting features to promote adaptive instinctual responses. Moreover, emotional and homeostasis mechanisms are characterized by intrinsic valence processing that is either a positive/pleasure or negative/displeasure bias. Homeostasis imbalance is universally experienced as negative emotional feelings and only becomes positively valenced when rectified. Hence, individuals sustain bodily changes that underlie psychological (emotional) and biological (homeostatic) influences on two sides, i.e., one side is oriented toward the survival and reproductive success that is associated with positively valenced emotional and physiologic homeostasis (anticipatory response) and the other responds to survival and reproductive failure associated with negatively valenced emotional and physiologic homeostasis (reactive response). Consequently, cognition modulates both emotional and homeostatic states by enhancing survival and maximizing rewards while minimizing risk and punishments. Thus, this evolutionary consideration suggests the brain as a ‘predictive engine’ to make it adaptive in a particular environment. Figure ​ Figure2 2 demonstrates this cyclic homeostatic regulation.

Conceptually maps the homeostatic regulation of internal and external inputs that affect cognition, emotion, feeling, and drive: Inputs → Homeostasis ↔ Emotion ∗ ↔ Cognition. This lead to the experience of one’s self via overt behavior that is biased by a specific emotion stimulated by bodily changes that underlie psychological/physiological states. ∗ Represents emotion associated with a combination of feeling and motivation/drive; ↔ indicates a bi-directional interaction; and → indicates a one-directional relationship. Adapted from Damasio and Carvalho (2013) .

Panksepp (1998) identified seven primary emotional systems that govern mammalian brains as follows: SEEKING, RAGE, FEAR, LUST, CARE, PANIC/GRIEF, and PLAY. Here, we use UPPERCASE letters to denote unconditional emotional responses (emotional primes). These primary emotional neural networks are situated in the subcortical regions; moreover, the evidence demonstrates that decortication leaves primary emotional systems intact ( Panksepp et al., 1994 ). Hence, cortical regions are non-essential for the generation of prototype emotional states but are responsible for their modulation and regulation. The present article emphasizes SEEKING because it is the most fundamental of the primary emotional systems and is crucial for learning and memory. The SEEKING system facilitates learning because when fully aroused, it fills the mind with interest that then motivates the individual to search out and learn things that they need, crave and desire. Accordingly, SEEKING generates and sustains curiosity’s engagement for a particular purpose while also promoting learning via its mediation of anticipatory eagerness ( Oudeyer et al., 2016 ). In other words, the SEEKING system has been designed to automatically learn by exploring anything that results in acquired behavioral manifestations for survival operations, all the way from the mesolimbic-mesocortical dopamine system through to the prefrontal cortex (PFC); thus, it is intimately linked with LTM formation ( Blumenfeld and Ranganath, 2007 ). Consequently, it is the foundation of secondary learning and higher cognitive processes when compared with the remaining six emotional systems. However, this system is less activated during chronic stress, sickness, and depression, all of which are likely to impair learning and various higher cognitions. On the other hand, overactivity of this system promotes excessively impulsive behaviors attended by manic thoughts and psychotic delusions. Moreover, massive lesion of SEEKING’s neural network (midline subcortical regions-the PAG, VTA, nucleus accumbens (NAc), medial forebrain and anterior cingulate) lead to consciousness disorder, specifically akinetic mutism (AKM) syndrome that the patient appears wakeful, attentive but motionless ( Schiff and Plum, 2000 ; Watt and Pincus, 2004 ). In brief, the SEEKING system holds a critical position that optimizes the performance of emotion, motivation, and cognition processes by generating positive subjective emotional states-positive expectancy, enthusiastic exploration, and hopefulness. Because the seven primary emotional systems and their associated key neuroanatomical and key neurochemical features have been reviewed elsewhere ( Panksepp, 2011a , b ), they are not covered in this review.

Emotion–Cognition Interactions and its Impacts on Learning and Memory

Studies in psychology ( Metcalfe and Mischel, 1999 ) and neuroscience ( Dolcos et al., 2011 ) proposed that cognition and emotion processes are operated at two separate but interacting systems: (i) the “cool cognitive system” is hippocampus-based that is associated with emotionally neutral cognitive functions as well as cognitive controls; and (ii) the “hot emotional system” is amygdala-based that responsible for emotional processing and responses toward unconditioned emotional stimuli such as appetitive and fear-evoking conditions. In addition, an early view of a dorsal/ventral stream distinction was commonly reported between both systems. The dorsal stream encompasses the dorsolateral prefrontal cortex (DLPFC) and lateral parietal cortex, which are involved in the cool system for active maintenance of controlled processes such as cognitive performance and the pursuit of goal-relevant information in working memory (WM) amidst interference. In contrast, the hot system involves the ventral neural system, including the amygdala, ventrolateral prefrontal cortex (VLPFC) and medial prefrontal cortex (mPFC) as well as orbitofrontal (OFC) and occipito-temporal cortex (OTC), all of which encompass emotional processing systems ( Dolcos et al., 2011 ). Nonetheless, recent investigations claim that distinct cognitive and emotional neural systems are not separated but are deeply integrated and contain evidence of mediation and modulation ( Dolcos et al., 2011 ; Okon-Singer et al., 2015 ). Consequently, emotions are now thought to influence the formation of a hippocampal-dependent memory system ( Pessoa, 2008 ), exerting a long-term impact on learning and memory. In other words, although cognitive and affective processes can be independently conceptualized, it is not surprising that emotions powerfully modify cognitive appraisals and memory processes and vice versa. The innate emotional systems interact with higher brain systems and probably no an emotional state that is free of cognitive ramifications. If cortical functions were evolutionarily built upon the pre-existing subcortical foundations, it provides behavioral flexibility ( Panksepp, 1998 ).

The hippocampus is located in the MTL and is thought to be responsible for the potentiation and consolidation of declarative memory before newly formed memories are distributed and stored in cortical regions ( Squire, 1992 ). Moreover, evidence indicates that the hippocampus functions as a hub for brain network communications-a type of continuous exchange of information center that establishes LTM dominated by theta wave oscillations ( Battaglia et al., 2011 ) that are correlated with learning and memory ( Rutishauser et al., 2010 ). In other words, hippocampus plays a crucial role in hippocampal-dependent learning and declarative memories. Numerous studies have reported that the amygdala and hippocampus are synergistically activated during memory encoding to form a LTM of emotional information, that is associated with better retention ( McGaugh et al., 1996 ; Richter-Levin and Akirav, 2000 ; Richardson et al., 2004 ). More importantly, these studies (fear-related learning) strongly suggest that the amygdala’s involvement in emotional processing strengthens the memory network by modulating memory consolidation; thus, emotional content is remembered better than neutral content.

In addition to amygdala-hippocampus interactions, one study reported that the PFC participates in emotional valence (pleasant vs. unpleasant) processing during WM ( Perlstein et al., 2002 ). Simons and Spiers (2003) also reviewed studies of interactions between the PFC and MTL during the memory encoding and retrieval processes underlying successful LTM. They demonstrated that the PFC is crucial for LTM because it engages with the active maintenance of information linked to the cognitive control of selection, engagement, monitoring, and inhibition. Hence, it detects relevant data that appears worthwhile, which is then referred for encoding, thus leading to successful LTM ( Simons and Spiers, 2003 ). Consistent findings were reported for recognition tasks investigated by fMRI where the left PFC-hippocampal network appeared to support successful memory encoding for neutral and negative non-arousing words. Simultaneously, amygdala-hippocampus activation was observed during the memory encoding of negative arousing words ( Kensinger and Corkin, 2004 ). Moreover, Mega et al. (1996) proposed two divisions for the limbic system: (i) the paleocortex division (the amygdala, orbitofrontal cortex, temporal polar and anterior insula), and (ii) the archicortical division (the hippocampus and anterior cingulate cortex). The first component is responsible for the implicit integration of affects, drives and object associations; the second deals with explicit sensory processing, encoding, and attentional control. Although divided into two sub-divisions, the paleocortex and archicortical cortex remain integrated during learning. Here, the paleocortex appears to manage the internal environment for implicit learning while integrating affects, drives, and emotions. Simultaneously, the archicortical division appears to manage external environment input for explicit learning by facilitating attention selection with attendant implicit encoding. To some extent, the paleocortex system might come to exercise a supervisory role and link the ancient affective systems to the newer cognitive systems.

Amygdala–Hippocampus Interactions

The findings of previous studies suggest that the amygdala is involved in emotional arousal processing and modulation of the memory processes (encoding and storage) that contribute to the emotional enhancement of memory ( McGaugh et al., 1996 ; Richter-Levin and Akirav, 2000 ). Activation of the amygdala during the encoding of emotionally arousing information (both pleasant/unpleasant) has been reported that correlates with subsequent recall. Because of the interaction between basolateral complex of the amygdala (BLA) with other brain regions that are involved in consolidating memories, including the hippocampus, caudate nucleus, NAc, and other cortical regions. Thus, BLA activation results from emotionally arousing events, which appear to modulate memory storage-related regions that influence long-term memories ( McGaugh, 2004 ). Memory consolidation is a part of the encoding and retention processes where labile memories of newly learned information become stabilized and are strengthened to form long-lasting memories ( McGaugh, 2000 ). Moreover, the amygdala transmits direct feedback/projection along the entire rostral-caudal cortices to the visual cortex of the ventral stream system, including primary visual (V1) and temporal cortices ( Amaral et al., 2003 ); furthermore, the amygdala activates the frontal and parietal regions during negative emotion processing that are involved in attention control. Consequently, during emotional processing, direct projections from the amygdala to sensory cortices enhance attentional mechanism might also allow the parallel processing of the attentional (fronto-parietal) system ( Vuilleumier, 2005 ). This suggests that amygdala activation is associated with enhanced attention and is a part of how salience enhances information retention.

In addition to attentional biases toward emotional content during memory encoding, emotionally arousing experiences have been found to induce the release of adrenal stress hormones, followed by the activation of β-noradrenergic receptors in the BLA, which then release epinephrine and glucocorticoids in the BLA, while enhancing memory consolidation of emotional experiences ( McGaugh and Roozendaal, 2002 ). Thus, there is evidence that the consolidation of new memory that is stimulated by emotionally arousing experiences can be enhanced through the modulating effects of the release of stress hormones and stress-activated neurotransmitters associated with amygdala activation. The BLA comprises the basal amygdala (BA) and lateral amygdala (LA), which project to numerous brain regions involved in learning and memory, including the hippocampus and PFC ( Cahill and McGaugh, 1998 ; Sharot and Phelps, 2004 ; McGaugh, 2006 ). However, stress and emotion do not always induce strong memories of new information. Indeed, they have also been reported to inhibit WM and LTM under certain conditions related to mood and chronic stress ( Schwabe and Wolf, 2010 ). Consequently, understanding, managing, and regulating emotion is critical to the development of enhanced learning programs informed by the significant impacts of learning and memory under different types of stress ( Vogel and Schwabe, 2016 ).

Prefrontal Cortex–Hippocampus Interaction

The PFC is located in the foremost anterior region of the frontal lobe and is associated with higher-order cognitive functions such as prediction and planning of/for the future ( Barbey et al., 2009 ). Moreover, it is thought to act as a control center for selective attention ( Squire et al., 2013 ), and also plays a critical role in WM as well as semantic processing, cognitive control, problem-solving, reasoning and emotional processing ( Miller and Cohen, 2001 ; Yamasaki et al., 2002 ). The PFC is connected to sub-cortical regions in the limbic system, including the amygdala and various parts of the MTL ( Simons and Spiers, 2003 ). Its involvement in WM and emotional processing are intimately connected with the MTL structures that decisively affect LTM encoding and retrieval ( Blumenfeld and Ranganath, 2007 ) in addition to self-referential processing ( Northoff et al., 2006 ). Structurally, the PFC is divided into five sub-regions: anterior (BA 10), dorsolateral (BA 9 and 46), ventrolateral (BA 44, 45, and 47), medial (BA 25 and 32) and orbitofrontal (BA 11, 12, and 14) ( Simons and Spiers, 2003 ).

The mPFC has been associated with anticipatory responses that reflect cognitive expectations for pleasant/unpleasant experiences (appraising rewarding/aversive stimuli to generate emotional responses) ( Ochsner et al., 2002 ; Ochsner and Gross, 2005 ). Specifically, increased mPFC activation has been noted during reappraisal and is associated with the suppressed subjective experience of negative emotions. Furthermore, an fMRI study revealed concurrent activation levels of the dorsomedial prefrontal cortex (dmPFC) with emotional valence when processing emotional stimuli: (i) activation was associated with positive valence, and (ii) deactivation was associated with negative valence ( Heinzel et al., 2005 ). Similarly, emotional and non-emotional judgment task using the International Affective Pictures System (IAPS) demonstrated increased activation of the mPFC, specifically both ventromedial prefrontal cortex (vmPFC) and dmPFC during emotional judgment when compared with non-emotional judgment. However, an inverse relationship was observed in the lateral prefrontal cortex (VLPFC and DLPFC) during non-emotional judgment ( Northoff et al., 2004 ). These findings suggested reciprocal interactions between cognitive and emotional processing between dorsal and lateral neural systems when processing emotional and cognitive tasking demands ( Bartolic et al., 1999 ).

Other studies reported strong cognition-emotion interactions in the lateral prefrontal cortex with increased activity in the DLPFC, which plays a key role in top-down modulation of emotional processing ( Northoff et al., 2004 ; Comte et al., 2014 ). This indicates increased attentional control of regulatory mechanisms that process emotional content. For instance, one study reported that cognitive task appeared to require active retention in WM, noting that the process was influenced by emotional stimuli when subjects were instructed to remember emotional valence information over a delay period ( Perlstein et al., 2002 ). Their findings revealed increased activation in the right DLPFC in response to pleasant IAPS pictures, but with an opposite effect in response to unpleasant pictures (decreased activity in the right DLPFC). This could be interpreted as increased WM-related activity when processing positive emotional stimuli, thus leading to positive emotion maintenance of stimulus representation in WM. Furthermore, they observed that the DLPFC contributed to increased LTM performance linked to stronger item associations and greater organization of information in WM during pleasant compared to unpleasant emotion ( Blumenfeld and Ranganath, 2006 ).

Another study investigated the PFC’s role in emotional mediation, reporting that the right VLPFC provided cognitive resources for both emotional reappraisal and learning processes via two separate subcortical pathways: (i) a path through NAc appeared to greater reappraisal success (suppress negative emotion) and (ii) another path through the ventral amygdala appeared to reduced reappraisal success (boost negative experience). This result indicates the VLPFC’s role in the regulation of emotional responses (reducing negative appraisal and generating positive appraisal) by retrieving appropriate information from memory ( Wager et al., 2008 ). Certain characteristics of emotional content were found to mediate the encoding and retrieval of selective information by leading high levels of attention, distinctiveness, and information organization that enhanced recall for emotional aspects of complex events ( Talmi, 2013 ). Hence, this direction of additional attention to emotional information appears to enhance LTM with the pronounced effects deriving from positive emotions compared with negative emotions. Effects of emotion on memory was also investigated using immediate (after 20 s) and delayed (after 50 min) testing paradigm, has shown that better recall for emotionally negative stimuli during immediate test compared to delayed test because of attentional allocation for encoding while the delayed test demonstrated that the role of amygdala in modulating memory consolidation of emotional stimuli. Because selective attention drives priority assignment for emotional material ( Talmi et al., 2007 ). Meanwhile, the distinctiveness and organization of information can improve memory because unique attributes and inter-item elaboration during encoding serve as retrieval cues, which then lead to high possibilities for correct recall ( Erk et al., 2003 ). Consistent findings were also reported by ( Dolcos et al., 2004 ), who suggested an emotional mediation effect deriving from PFC activity in relation to cognitive functions such as strategic memory, semantic memory, and WM, which subsequently enhanced memory formation. Table ​ Table1 1 summarizes cognitive-emotional functions associated with each sub-region of the PFC and corresponding Brodmann areas. Taken together, these findings indicate that the PFC is a key component in both cognitive and emotional processing for successful LTM formation and retrieval.

The prefrontal cortex (PFC) sub-regions, corresponding Brodmann areas, and associated cognitive-emotional functions.

Effects Deriving From Different Modalities of Emotional Stimuli on Learning and Memory

As discussed above, evidence indicates the neural mechanisms underlying the emotional processing of valence and arousal involve the amygdala and PFC, where the amygdala responds to emotionally arousing stimuli and the PFC responds to the emotional valence of non-arousing stimuli. We have thus far primarily discussed studies examining neural mechanisms underlying the processing of emotional images. However, recent neuroimaging studies have investigated a wider range of visual emotional stimuli. These include words ( Sharot et al., 2004 ), pictures ( Dolcos et al., 2005 ; Weymar et al., 2011 ), film clips ( Cahill et al., 1996 ), and faces ( González-Roldan et al., 2011 ), to investigate neural correlates of emotional processing and the impact of emotion on subsequent memory. These studies provided useful supplemental information for future research on emotional effects of educational multimedia content (combination of words and pictures), an increasingly widespread channel for teaching and learning.

An event-related fMRI study examined the neural correlates of responses to emotional pictures and words in which both were manipulated in terms of positive and negative valence, and where neutral emotional content served as a baseline (“conditioned stimuli”/no activating emotion with valence rating of 5 that spans between 1/negative valence-9/positive valence), even though all stimuli were consistent in terms of arousal levels ( Kensinger and Schacter, 2006 ). Subjects were instructed to rate each stimulus as animate or inanimate and common or uncommon . The results revealed the activation of the amygdala in response to positive and negative valence (valence-independent) for pictures and words. A lateralization effect was observed in the amygdala when processing different emotional stimuli types. The left amygdala responded to words while either the right and/or bilateral amygdala activation regions responded to pictures. In addition, participants were more sensitive to emotional pictures than to emotional words. The mPFC responded more rigorously during the processing of positive than to that of negative stimuli, while the VLPFC responded more to negative stimuli. The researchers concluded that arousal-related responses occur in the amygdala, dmPFC, vmPFC, anterior temporal lobe and temporo-occipital junction, whereas valence-dependent responses were associated with the lateral PFC for negative stimuli and the mPFC for positive stimuli. The lateralization of the amygdala’s activation was consistent with that in other studies that also showed left-lateralized amygdala responses for words ( Hamann and Mao, 2002 ) vs. right-lateralized amygdala responses for images ( Pegna et al., 2005 ). However, a wide range of studies suggest that lateralization likely differs with sex ( Hamann, 2005 ), individual personality ( Hamann and Canli, 2004 ), mood ( Rusting, 1998 ), age ( Allard and Kensinger, 2014 ), sleep ( Walker, 2009 ), subject’s awareness of stimuli ( Morris et al., 1998 ), stress ( Payne et al., 2007 ) and other variables. Hence, these factors should be considered in future studies.

Event-related potentials (ERPs) were used to investigate the modality effects deriving from emotional words and facial expressions as stimuli in healthy, native German speakers ( Schacht and Sommer, 2009a ). German verbs or pseudo-words associated with positive, negative or neutral emotions were used, in addition to happy vs. angry faces, as well as neutral and slightly distorted faces. The results revealed that negative posterior ERPs were evoked in the temporo-parieto-occipital regions, while enhanced positive ERPs were evoked in the fronto-central regions (positive verbs and happy faces) when compared with neutral and negative stimuli. These findings were in agreement with the previous findings ( Schupp et al., 2003 ; Schacht and Sommer, 2009b ). While the same neuronal mechanisms appear to be involved in response to both emotional stimuli types, latency differences were also reported with faster responses to facial stimuli than to words, likely owing to more direct access to neural circuits-approximately 130 ms for happy faces compared to 380 ms for positive verbs ( Schacht and Sommer, 2009a ). Moreover, augmented responses observed in the later positive complex (LPP), i.e., larger late positive waves in response to emotional verbs (both positive and negative) and angry faces, all associated with the increased motivational significance of emotional stimuli ( Schupp et al., 2000 ) and increased selective attention to pictures ( Kok, 2000 ).

Khairudin et al. (2011) investigated effects of emotional content on explicit memory with two standardized stimuli: emotional words from the Affective Norms for English Words (ANEW) and emotional pictures from the IAPS. All stimuli were categorized as positive, negative or neutral, and displayed in two different trials. Results revealed that better memory for emotional images than for emotional words. Moreover, a recognition test demonstrated that positive emotional content was remembered better than negative emotional content. Researchers concluded that emotional valence significantly impacts memory and that negative valence suppressed the explicit memory. Another study by Khairudin et al. (2012) investigated the effects of emotional content on explicit verbal memory by assessing recall and recognition for emotionally positive, negative and neutral words. The results revealed that emotion substantially influences memory performance and that both positive and negative words were remembered more effectively than neutral words. Moreover, emotional words were remembered better in recognition vs. recall test.

Another group studied the impacts of emotion on memory using emotional film clips that varied in emotion with neutral, positive, negative and arousing contents ( Anderson and Shimamura, 2005 ). A subjective experiment for word recall and context recognition revealed that memory, for words associated with emotionally negative film clips, was lower than emotionally neutral, positive and arousing films. Moreover, emotionally arousing film clips were associated with enhanced context recognition memory but not during a free word recall test. Therefore, clarifying whether emotional stimuli enhance recognition memory or recall memory requires further investigation, as it appears that emotional information was better remembered for recognition compared to recall. In brief, greater attentional resource toward emotional pictures with large late positive waves of LPP in the posterior region, the amygdala responds to emotional stimuli (both words and pictures) independent on its valence, leading to enhanced memory. Table ​ Table2 2 summarizes studies on the brain regions that respond to standardized stimuli as cited above, and also for pictures of emotional facial expression or Pictures of Facial Affect (POFA), Affective Norms for English Words (ANEW) for emotional words, as well as for the International Affective Digitized Sound System (IDAS) for emotional sounds.

Comparison of different emotional stimulus categories.

Neuroimaging Techniques for the Investigation of Emotional-Cognitive Interactions

The brain regions associated with cognitive-emotional interactions can be studied with different functional neuroimaging techniques (fMRI, PET, and fNIRS) to examine hemodynamic responses (indirect measurement). EEG is used to measure brain electrical dynamics (direct measurement) associated with responses to cognitive and emotional tasks. Each technique has particular strengths and weaknesses, as described below.

Functional Magnetic Resonance Imaging (fMRI)

Functional magnetic resonance imaging is a widely used functional neuroimaging tool for mapping of brain activation as it provides a high spatial resolution (a few millimeters). fMRI is an indirect measure of hemodynamic response by measuring changes in local ratios of oxy-hemoglobin vs. deoxy-hemoglobin, typically known as a blood oxygenation level dependent (BOLD) signal ( Cabeza and Nyberg, 2000 ). Dolcos et al. (2005) examined the effects of emotional content on memory enhancement during retrieval process using event-related fMRI to measure retrieval-related activity after a retention interval of 1 year. The researchers concluded that successful retrieval of emotional pictures involved greater activation of the amygdala as well as the entorhinal cortex and hippocampus than that of neutral pictures. Both the amygdala and hippocampus were rigorously activated during recollection compared to familiarity recognition, whereas no differences were found in the entorhinal cortex for either recollection or familiarity recognition. Moreover, a study investigates motivation effect (low vs. high monetary reward) on episodic retrieval by manipulating task difficulty, fMRI data reports that increased activation in the substantia nigra/VTA, MTL, dmPFC, and DLPFC when successful memory retrieval with high difficulty than with low difficulty. Moreover, reward-related of functional connectivities between the (i) SN/VTA–MTL and (ii) SN/VTA–dmPFC appear to increases significantly with increases retrieval accuracy and subjective motivation. Thus, Shigemune et al. (2017) suggest that reward/motivation-related memory enhancement modulated by networking between the SN/VTA (reward-related), dmPFC (motivation-related) and MTL (memory-related) network as well as DLPFC (cognitive controls) with high task difficulty.

Taken together, these findings indicate that the amygdala and MTL have important roles in the recollection of emotional and motivational memory. Another fMRI study reported that greater success for emotional retrieval (emotional hits > misses ) was associated with neural activation of the bilateral amygdala, hippocampus, and parahippocampus, whereas a higher success rate for neutral retrieval is associated with a greater activity in right posterior parahippocampus regions ( Shafer and Dolcos, 2014 ). Hence, fMRI has clearly revealed interactions between cognitive and emotional neural networks during information processing, particularly in response to emotion-related content. Such interactions appear to modulate memory consolidation while also mediating encoding and retrieval processes that underlie successful LTM formation and memory recall. More specifically, it appears that amygdala activation modulates both the hippocampus and visual cortex during visual perception and enhances the selection and organization of salient information via the “bottom-up” approach to higher cognitive functions directed at awareness. Although fMRI is widely used, it poses several limitations such as poor temporal resolution, expensive setup costs, plus the difficulty of having a subject hold still during the procedure in an electromagnetically shielded room (immobility). Furthermore, fMRI is slightly more metabolically sluggish, as BOLD signal exhibits an initial dip, where the increase of subsequent signal is delayed by 2–3 s and it takes approximately 6–12 s to reach to a peak value that reflects the neural responses elicited by a stimulus ( Logothetis et al., 2001 ). This means that fMRI having a coarse temporal resolution (several seconds) when compared with electrophysiological techniques (a few milliseconds) and also not a great technique for visualizing subcortical regions (mesencephalon and brainstem) due to metabolically sluggish compared to PET.

Positron Emission Tomography (PET)

Positron emission tomography is another functional neuroimaging tool that maps CNS physiology and neural activation by measuring glucose metabolism or regional cerebral blood flow (rCBF). PET uses positron-emitting radionuclides such as 18 F-fluorodeoxyglucose (FDG) and positron-emitting-oxygen isotope tagged with water ([ 15 O] H 2 O), etc. This technique identifies different neural networks involving pleasant, unpleasant and neutral emotions ( Lane et al., 1997 ). It thus far appears that increased rCBF in the mPFC, thalamus, hypothalamus, and midbrain associated with pleasant and unpleasant emotional processing, while unpleasant emotions are more specifically associated with the bilateral OTC, cerebellum, left parahippocampal gyrus, hippocampus, and amygdala; moreover, the caudate nucleus is associated with pleasant emotions.

Using PET scanning demonstrated that emotional information enhances visual memory recognition via interactions between perception and memory systems, specifically with greater activation of the lingual gyrus for visual stimuli ( Taylor et al., 1998 ). The results also showed that strong negative emotional valence appeared to enhance the processing of early sensory input. Moreover, differences in neural activation appeared in the left amygdaloid complex (AC) during encoding, while the right PFC and mPFC responded during recognition memory. Similarly, Tataranni et al. (1999) identified CNS regions associated with appetitive states (hunger and satiation) ( Tataranni et al., 1999 ). Hunger stimulated increased rCBF uptake in multiple regions including the hypothalamus, insular cortex, limbic and paralimbic regions (anterior cingulate cortex, parahippocampal and hippocampal formation, the anterior temporal and posterior orbitofrontal cortex), as well as the thalamus, caudate, precuneus, putamen, and cerebellum. Satiation was associated with increased rCBF uptake in the bilateral vmPFC, the DLPFC, and the inferior parietal lobule. These results imply that (i) subcortical regions associated with emotion/motivation involved in hunger that signals distressing feeling (discomfort, pain and anxiety) for the regulation of food intake; and (ii) the PFC associated with inhibition of inappropriate behavioral response involved in satiation that signals excessive food consumption for a termination of meal.

In a study of emotional self-generation using PET noted that the insular cortex, secondary somatosensory cortex, and hypothalamus, as well as the cingulate cortex and nuclei in the brainstem’s tegmentum, including PAG, parabrachial nucleus, and substantia nigra maintained current homeostasis by generating regulatory signals ( Damasio et al., 2000 ). PET scanning has also been used for neuroanatomical mapping of emotions ( Davidson and Irwin, 1999 ), emotional processing ( Choudhary et al., 2015 ), and cognitive functions ( Cabeza and Nyberg, 2000 ). Although PET scanning has a relatively good spatial resolution for both the brain and bodily functions, it is costly and yields lower temporal resolution than does EEG and is invasive as opposed to fMRI. Moreover, PET tends to show better activation of more ancient brain regions in the mesencephalon and brainstem when compared to fMRI. Hence, it is generally reserved for the clinical diagnoses of cancers, neurological diseases processes (e.g., epilepsy and Alzheimer’s disease), and heart diseases.

Electroencephalography (EEG)

Electroencephalography obtains high temporal resolution in milliseconds, portable, less expensive, and non-invasive techniques by attaching scalp electrodes to record brain electrical activity. Moreover, numerous studies reported that EEG is useful in mapping CNS cognitive and emotional processing. The technique offers a comprehensive range of feature extraction and analysis methods, including power spectral analysis, EEG coherence, phase delay, and cross-power analysis. One study examined changes in EEG oscillations in the amygdala during the consolidation of emotionally aroused memory processing that exhibited theta (4–8 Hz) activity ( Paré et al., 2002 ), indicating the facilitation of memory consolidation, improved retention of emotional content, and enhanced memory recall. This finding was later supported by the revelation of increased theta activity in the right frontal ( Friese et al., 2013 ) and right temporal cortices ( Sederberg et al., 2003 ) and consequently associated with the successful encoding of new information. Another study ( Buzsáki, 2002 ) revealed that theta oscillations were positively related to the activation of the hippocampus represent the active brain state during sensory, motor and memory-related processing. The theta waves are generated through an interaction between the entorhinal cortex, the Schaffer collateral (CA3 region) and the pyramidal cell dendrites (both CA3 and CA1 regions) that result in a synaptic modification underlie learning and memory. Thus, theta oscillation is thought to be associated with the encoding of new memories.

Increased gamma oscillation in the neocortex and right amygdala have been reported in response to emotionally arousing pictures during learning and memory tasks undertaken by 148 right-handed female participants ( Headley and Paré, 2013 ). A more detailed study by Müller et al. (1999) reported increased gamma potentials in the left frontal and temporal regions in response to images having a negative valence, whereas increased gamma-bands in the right frontal regions were observed in responses to images with positive valence for 11 right-handed male participants. During an emotionally positive experience, another study reported significantly increased EEG theta-alpha coherence between prefrontal and posterior parietal regions ( Aftanas and Golocheikine, 2001 ). They concluded the change was associated with heightened attention in association with improved performance in memory and emotional processing. Thus, we have a number of EEG investigations of left and right hemispheric activity while processing positive (pleasant) and negative (unpleasant) stimuli that revealed differences in regional electrophysiological activation. Nonetheless, EEG exhibits a relatively poor spatial resolution approximately 5 to 9 cm compared with fMRI and PET ( Babiloni et al., 2001 ). Thus, scalp EEG unable to measure activation much below cortex owing to the distortion of scalp potentials where different volume conduction effects of the cortex, dura mater, skull, and scalp resulting in imprecise localization of the electromagnetic field patterns associated with neural current flow. Subsequent studies have demonstrated that the EEG spatial resolution can be improved using high-resolution EEG (high-density electrode arrays to increase spatial sampling) with surface Laplacian estimation and cortical imaging (details discussion of this area is beyond the scope of this review, see ( Nunez et al., 1994 ) for theoretical and experimental study) or integrating multiple imaging modalities that provide complement information, for instance EEG-fMRI and EEG-fNIRS ( Dale and Halgren, 2001 ).

Functional Near-Infrared Spectroscopy (fNIRS)

Functional near-infrared spectroscopy is an emerging and relatively low-cost imaging technique that is also portable and non-invasive. It can be used to map the hemodynamic responses associated with brain activation. This technology measures cerebral changes in the concentration of oxygenated hemoglobin (oxy-Hb) vs. deoxygenated hemoglobin (deoxy-Hb) using optodes (light emitters and detectors) placed on the scalp ( Villringer et al., 1993 ). It is limited to visualizations of cortical activity compared to the subcortical regions, and findings only imply increased brain activity associated with increased glucose and oxygen consumption. Elevations in cerebral blood flow and oxygen delivery exceed quo oxygen consumption, thereby enabling changes in local cerebral blood oxygenation to be measured by optic penetration.

The number of studies that have implemented this investigative technique are associated with task performance ( Villringer et al., 1993 ), including exercise ( Perrey, 2008 ), cognitive workload ( Durantin et al., 2014 ), psychiatric disorders ( Ehlis et al., 2014 ), emotional processing ( Bendall et al., 2016 ), and aging ( Hock et al., 1995 ). One study used fNIRS to examine the relationship between subjective happiness and emotional changes ( Oonishi et al., 2014 ). The results revealed that the level of subjective happiness influenced the pattern of left-right PFC activation during the emotion-related task, showing increased oxy-Hb in the left PFC when viewing pleasant pictures, and increased oxy-Hb in the right PFC when viewing unpleasant pictures. Viewing unpleasant emotional stimuli accompanied increased in oxy-Hb levels in the bilateral VLPFC while also activating several regions in both the right VLPFC (BA45/47) and left VLPFC (BA10/45/46/47). However, another fNIRS study reported that viewing pleasant emotional stimuli was associated with decreased oxy-Hb in the left DLPFC (BA46/10) when affective images were presented for 6 s ( Hoshi et al., 2011 ). Thus, this study found an opposite pattern indicating left hemisphere involvement in positive/approach processing and right hemisphere involvement in negative/withdrawal processing ( Davidson, 1992 ; Davidson and Irwin, 1999 ). This inconsistent finding of frontal hemispheric asymmetric might result from the comparison of state-related changes rather than baseline levels of asymmetric. Thus, several issues should take into consideration: (i) methodological issues to assess hemispheric asymmetry, including requires repeat measures of anterior asymmetry for at least two sessions, stimulus content should comprise both positive valence and negative valence while maintaining at a similar level of arousal and with a baseline resting condition, appropriate selection of reference electrode and individual differences, etc; and (ii) conceptual issues is related to the fact that prefrontal cortex is an anatomically and functionally heterogeneous and complex region interacts with other cortical and subcortical structures during emotional processing ( Davidson, 2004 ). Another fNIRS study examined the relationship between PFC function and cognitive control of emotion ( Ozawa et al., 2014 ). This was done by presenting emotional IAPS pictures for 5.2 s, followed by the n -back task. The results revealed a significantly greater increase in oxy-HB in the mPFC and left superior frontal gyrus in response to negative pictures compared with neutral pictures. Meanwhile, no significant hemodynamic changes were observed during image presentation and the n -back task, indicating the need for further investigation.

Factors Affecting the Effect of Emotion on Learning and Memory

The preceding section described neuroimaging techniques used to examine brain responses to emotional stimuli during WM processing leading to LTM. This section presents six key factors that are recommended for consideration in the experimental design and appropriate protocol.

Individual Differences

A number of studies have reported numerous influences in addition to a range of individual differences in emotional processing. These include personality traits ( Montag and Panksepp, 2017 ), intellectual ability ( Brackett et al., 2004 ), and sex ( Cahill, 2003 ). Moreover, sex hormones and personality traits (e.g., extraversion and neuroticism) appear to influence individual responses to emotional stimuli as well as modulate emotional processing. Appropriate screening with psychological testing as well as balancing experimental cohorts in terms of sex can help reduce spurious results owing to individual differences.

Age-Related Differences

Studies have also shown that older adults are associated with the greater familiarity with psychological stress and emotional experiences, thus causing positivity biases in emotional processing and better emotional control than in younger adults ( Urry and Gross, 2010 ; Allard and Kensinger, 2014 ). Consequently, the age of participants in a sample population should be considered for both cognitive and emotional studies.

Emotional Stimulus Selection

The selection of emotional stimuli for experimental studies is generally divided into two streams: (1) discrete emotional, and (2) dimensional emotions of valence, arousal, dominance and familiarity ( Russell, 1980 ; Barrett, 1998 ). The latter include pictures from the IAPS database and words from the ANEW database, which are both available for non-commercial research. Appropriate selection of emotional stimuli is another important consideration that ensures experimental tasks are suitable for the investigation of emotional processing in learning and memory. Furthermore, the type of stimulus determines stimulus presentation duration, especially for experimental tasks involving the induction of emotions.

Self-assessment Techniques

There are numerous self-assessment techniques used to measure individual emotional states ( Bradley and Lang, 1994 ). The most widely used techniques are the Self-Assessment Manikin (SAM), the Semantic Differential (SD) scale, and the Likert scale. The SAM is a non-verbal pictorial assessment technique directly measures emotional responses to emotional stimuli for valence, arousal, and dominance. The SD scale consists of a set of bipolar adjective pairs for the subjective rating of image stimuli. The Likert’s “ x -point” scale allows participants to rate their own emotional responses. If a study does not seek to assess distinct emotional states but rather involves the assessment of two primary dimensions of emotion (positive and negative valence), then the Positive and Negative Affect Schedule (PANAS) is a recommended method ( Watson et al., 1988 ). Thus, selection of the most appropriate self-assessment technique is an important part of the experimental design but can also become an overwhelming task.

Selection of Brain Imaging Techniques

As mentioned above, the two major types of brain imaging techniques EEG (direct) and fMRI/PET/fNIRS (indirect) have respective advantages and disadvantages. To overcome these limitations, simultaneous or combined dual-modality imaging (EEG-fMRI or EEG-fNIRS) can now be implemented for complementary data collection. Although functional neuroimaging works to identify the neural correlates of emotional states, technologies such as deep brain stimulation (DBS) and connectivity maps might provide new opportunities to seek understanding of emotions and its corresponding psychological responses.

Neurocognitive Research Design

The neuroscience of cognition and emotion requires appropriate task designs to accomplish specific study objectives ( Amin and Malik, 2013 ). Environmental factors, ethical issues, memory paradigms, cognitive task difficulty, and emotional induction task intensity must be considered for this.

Numerous neuroimaging studies cited thus far have indicated that emotions influence memory processes, to include memory encoding, memory consolidation, and memory retrieval. Emotional attentional and motivational components might explain why emotional content exhibits privileged information processing. Emotion has a “pop-out” effect that increases attention and promotes bottom-up instinctual impact that enhances awareness. Significant emotional modulation affects memory consolidation in the amygdala, and emotional content also appears to mediate memory encoding and retrieval in the PFC, leading to slow rates of memory lapse accompanied by the accurate recall. Moreover, cognitive and emotional interactions also appear to modulate additional memory-related CNS regions, such as the frontal, posterior parietal and visual cortices. The latter are involved in attentional control, association information, and the processing of visual information, respectively. Therefore, higher-level cognitive functions such as learning and memory, appear to be generally guided by emotion, as outlined in the Panksepp’s framework of brain processing ( Panksepp, 1998 ).

Neuroimaging findings also indicate the involvement of the PFC in emotional processing by indirectly influencing WM and semantic memory ( Kensinger and Corkin, 2003 ). This is reflected by the involvement of the DLPFC in WM and the role played by VLPFC in semantic processing, both of which have been found to enhance or impair semantic encoding task performance when emotion is involved. Various parts of the lateral PFC (ventrolateral, dorsolateral and medial prefrontal cortical regions) are suspected of having key roles that support memory retrieval ( Simons and Spiers, 2003 ). All of these findings suggest that PFC-MTL interactions underlie effective semantic memory encoding and thus strategically mediate information processing with increased transfer to the hippocampus, consequently enhancing memory retrieval. Accordingly, learning strategies that emphasize emotional factors are more likely to result in long-term knowledge retention. This consideration is potentially useful in the design of educational materials for academic settings and informed intelligent tutoring systems.

Based on numerous previous findings, future research might take emotional factors more seriously and more explicitly in terms of their potential impact on learning. By monitoring the emotional state of students, the utilization of scientifically derived knowledge of stimulus selection can be particularly useful in the identification of emotional states that advance learning performance and outcomes in educational settings. Moreover, functional neuroimaging investigations now include single and/or combined modalities that obtain complementary datasets that inform a more comprehensive overview of neuronal activity in its entirety. For example, curiosity and motivation promote learning, as it appears cognitive network become energized by the mesolimbic-mesocortical dopamine system (generalized motivational arousal/SEEKING system). In addition, the identification of emotional impact on learning and memory potentially has direct implications for healthy individuals as well as patients with psychiatric disorders such as depression, anxiety, schizophrenia, autism, mania, obsessive-compulsive disorder and post-traumatic stress disorder (PTSD) ( Panksepp, 2011a ). To emphasize, depression and anxiety are the two most commonly diagnosed psychiatric disorders associated with learning/memory impairment and pose negative consequences that (i) limit the total amount of information that can otherwise be learned, and (ii) inhibit immediate recall as well as memory retention and retrieval of newly learned information. Depression and anxiety are also associated with negative emotions such as hopelessness, anxiety, apathy, attention deficit, lack of motivation, and motor and mental insufficiencies. Likewise, neuroscience studies report that decreased activation of the dorsal limbic (the anterior and posterior cingulate) as well as in the prefrontal, premotor and parietal cortices causes attentional disturbance, while increased neural activation in the ventral paralimbic region (the subgenual cingulate, anterior insula, hypothalamus and caudate) is associated with emotional and motivational disorders ( Mayberg, 1997 ).

Concluding Remarks, Open Questions, and Future Directions

Substantial evidence has established that emotional events are remembered more clearly, accurately and for longer periods of time than are neutral events. Emotional memory enhancement appears to involve the integration of cognitive and emotional neural networks, in which activation of the amygdala enhances the processing of emotionally arousing stimuli while also modulating enhanced memory consolidation along with other memory-related brain regions, particularly the amygdala, hippocampus, MTL, as well as the visual, frontal and parietal cortices. Similarly, activation of the PFC enhances cognitive functions, such as strategic and semantic processing that affect WM and also promote the establishment of LTM. Previous studies have primarily used standardized emotional visual, or auditory stimuli such as pictures, words, facial expression, and film clips, often based on the IAPS, ANEW, and POFA databases for emotional pictures, words and facial expressions, respectively. Further studies have typically focused on the way individuals memorize (intentional or incidental episodic memory paradigm) emotional stimuli in controlled laboratory settings. To our knowledge, there are few objective studies that employed brain-mapping techniques to examine semantic memory of learning materials (using subject matter) in the education context. Furthermore, influences derived from emotional factors in human learning and memory remains unclear as to whether positive emotions facilitate learning or negative emotions impair learning and vice versa. Thus, several remaining questions should be addressed in future studies, including (i) the impact of emotion on semantic knowledge encoding and retrieval, (ii) psychological and physiological changes associated with semantic learning and memory, and (iii) the development of methods that incorporate emotional and motivational aspects that improve educational praxes, outcomes, and instruments. The results of studies on emotion using educational learning materials can indeed provide beneficial information for informed designs of new educational courses that obtain more effective teaching and help establish better informed learning environments. Hence, to understand how emotion influence learning and memory requires understanding of an evolutionary consideration of the nested hierarchies of CNS emotional-affective processes as well as a large-scale network, including the midbrain’s PAG and VTA, basal ganglia (amygdala and NAc), and insula, as well as diencephalon (the cingulate and medial frontal cortices through the lateral and medial hypothalamus and medial thalamus) together with the MTL, including the hippocampus as well as the entorhinal cortex, perirhinal cortex, and parahippocampal cortices that responsible for declarative memories. Moreover, the SEEKING system generates positive subjective emotional states-positive expectancy, enthusiastic exploration, and hopefulness, apparently, initiates learning and memory in the brain. All cognitive activity is motivated from ‘underneath’ by basic emotional and homeostatic needs (motivational drives) that explore environmental events for survival while facilitating secondary processes of learning and memory.

Author Contributions

CMT drafted this manuscript. CMT, HUA, MNMS, and ASM revised this draft. All authors reviewed and approved this manuscript.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We would like to thank Ministry of Education (MOE), Malaysia for the financial support. We gratefully thank Frontiers in Psychology, Specialty Section Emotion Sciences reviewers and the journal Associate Editor, for their helpful input and feedback on the content of this manuscript.

Funding. This research work was supported by the HiCoE grant for CISIR (Ref No. 0153CA-002), Ministry of Education (MOE), Malaysia.

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BRIEF RESEARCH REPORT article

The asymmetric impact of decision-making confidence on regret and relief.

• School of Education and Music, Sanming University, Sanming, China

When individuals make uncertain decisions, they often evaluate the correctness of their choices in what is referred to as decision-making confidence. The outcomes of such decision-making can lead to counterfactual thinking wherein alternative possible outcomes are contemplated. This, in turn, can elicit counterfactual emotions including upward and downward counterfactual thinking, which, respectively, refer to regret and relief. Decision-making confidence and counterfactual emotions have key effects on how individuals learn from the past and prepare for the future. However, there has been little understanding of how these experiences are related. For this study, 98 total adults were recruited with the goal of assessing the connections between decision-making confidence and sensations of regret and relief when completing a card-based gambling task. The results of this study suggest that decision-making confidence may reduce the intensity of relief while increasing the degree of regret experienced. These findings thus emphasize the important effect that decision confidence has on emotional processing.

1 Introduction

Individuals must inevitably make a large number of decisions each day, and uncertainty in the decision-making process complicates the decision-making process in many cases. After a decision has been made, people often consider the potential outcomes that would have arisen had an alternate decision been made ( FitzGibbon et al., 2021 ). Indeed, such reflection and reconsideration of past decisions is a common facet of human reasoning, and this process of retroactively altering the imagined outcomes of particular events has been termed counterfactual thinking or counterfactual reasoning ( Epstude and Roese, 2008 ; Van Hoeck et al., 2015 ; Byrne, 2016 ; Briazu et al., 2017 ; Huang et al., 2021 ). Such counterfactual thinking can provide adaptive benefits, enabling individuals to learn from these prior experiences such that they can better prepare for the future ( Byrne, 2016 ; Roese and Epstude, 2017 ), thus bridging the past and future ( Pieters and Zeelenberg, 2007 ). A range of emotional responses can be evoked by counterfactual thinking, including both regret and relief. Regret is experienced by individuals who engage in upward counterfactual thinking, which entails the imaging of how an alternative decision should have been made and how better outcomes may have been achieved for a given event ( Bell, 1982 ; Landman, 1993 ; Gilovich et al., 1995 ; Pieters and Zeelenberg, 2007 ). Conversely, relief is experienced when the imagined state is worse than the actual situation associated with a given decision or event ( Connolly and Zeelenberg, 2002 ; Liu et al., 2016 ; De Brigard et al., 2019 ).

Decision-making confidence refers to an individual’s estimation of the correctness of their choices in an uncertain situation, and such confidence can strongly affect emotional responses to a given situational outcome ( Kirkebøen et al., 2013 ; Kirkebøen and Nordbye, 2017 ). Confidence is a subjective feeling that refers to one’s belief in the validity of their knowledge, choices, or actions, serving as a measure of the extent to which a given person believes a particular thought or action to be accurate ( Yeung and Summerfield, 2012 ; Grimaldi et al., 2015 ; Navajas et al., 2016 ; Dotan et al., 2018 ). Given that they can evaluate their own decisions in great detail, individuals are often able to recognize mistakes that they have made even when they do not receive any direct feedback. The degree of certainty that individuals express in response to particular choices also varies ( Yeung and Summerfield, 2012 ). In research settings, retrospective judgments are often used to quantify levels of decision-making confidence, with confidence ratings being the most commonly employed approach ( Grimaldi et al., 2015 ). This strategy entails asking participants to rate their degree of confidence from 0% (total uncertainty) to 100% (total certainty). Decision-making confidence and counterfactual thinking are key facets of the decision-making process, and both have important implications for the ability of individuals to learn from particular experiences and for their overall well-being ( De Martino et al., 2013 ; Brus et al., 2021 ; Liu et al., 2022 ). The precise link between decision-making confidence and counterfactual thinking, however, remains to be fully characterized.

Several emotion-related theories that have been advanced to date have potential implications for the association between decision-making confidence and counterfactual thinking. The first of these is the subjective expected pleasure theory (SEP; Mellers et al., 1999 ), which posits that unexpected outcomes tend to evoke emotions stronger than those resulting from expected outcomes. This theory suggests that the magnitude of regret following a poor decision is likely to be reduced if the individual who made that decision had lower decision-making confidence before being aware of the outcome. Conversely, the relief experienced after making an appropriate decision will be reduced if the individual was already highly confident in the decision that they made. An alternative model of the link between confidence and regret can be inferred based on decision justification theory (DJT; Connolly and Zeelenberg, 2002 ), which suggests that justifications and feelings of self-blame influence the degree of regret. The degree of regret that individuals experience has been shown to be impacted by whether or not they perceive themselves as being responsible for a given mistake. Seemingly unreasonable choices made with lower levels of confidence may thus result in individuals feeling responsible for having made an “incorrect” decision. van de Calseyde et al. (2018) performed six studies based on experimental manipulation and autobiographical recall, and ultimately found that lower levels of confidence in the form of doubts arising following a decision can exacerbate regret through the enhancement of feelings of self-blame after making a poor judgment, in line with the DJT. However, they observed mixed results with respect to how post-decisional doubt relates to the experience of relief. In an incentivized trivia game, similar to the effect on regret, doubting one’s decision before knowing the outcome produced more relief after learning that one’s decision was correct. However, in another incentivized trust game, they did not find any significant relationship between doubt and relief.

The present study was conceptualized with the goal of exploring the association between decision-making confidence and experiences of regret and relief using a card game-based task. In each round of this task, participants were presented with two options: to secure their current gains or to opt for the potential for further gains at the risk of losing their accumulated earnings. Relief and regret were, respectively, experienced when the actual outcome was superior and inferior to the counterfactual outcome. For these analyses, an action effect was hypothesized ( Kahneman and Tversky, 1982 ; Feldman, 2020 ; Feldman et al., 2020 ), in which individuals were posited to experience greater regret following negative outcomes arising as a result of action relative to inaction. Many studies have confirmed that acting is associated with greater odds of experiencing regret as compared to a failure to act. Although this action effect has been studied in the context of regret in several prior studies, far less is understood regarding the interplay between this action effect and relief. Accordingly, this study sought to replicate this traditional “regret action effect” while also determining whether it can also be observed in situations characterized by feelings of relief.

2.1 Participants

This study enrolled 98 undergraduate students ( M age  = 20.88, SD age  = 1.15; range: 18–28 years; 49 females). All procedures performed in studies involving human participants were following the ethical standards of the institutional and/or national research committee and in accordance with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The University’s Ethics Committee approved this study, and all participants provided informed consent.

2.2 Procedure

To elicit feelings of regret and relief in a counterfactual framework, playing cards were used to establish a gambling task. In each round of testing, two cards were presented on the computer screen. The leftmost card presented the first number, which was a random integer from 0 to 9. Participants were then directed to select whether or not to reveal the second number, which was another random integer from 0 to 9 that was initially hidden on the right card. If participants elected not to reveal the second number (inaction trial), then the first number was their score for that round. If they instead elected to reveal the second number (action trial), their score was equal to the sum of the two numbers provided the total was ≤9, while their score was otherwise 0. The total possible points that a participant could thus earn each round was 9, with a minimum of 0. Participants were directed to try to achieve as high a score as possible in order to obtain a greater reward. The task consisted of 100 total trials, with each combination of numbers appearing only a single time in a randomized order. After making a decision (action vs. inaction), participants were asked to report their level of confidence in the decision that they made on a scale from −50 (low confidence) to +50 (high confidence). The second number was then revealed, and participants were asked to report their feelings of regret or relief on a scale from −50 (extremely regretful) to +50 (extremely relieved). For example, in a trial where the first number was 6 and a participant elected not to reveal the second number, which was subsequently revealed to be a 3, feelings of regret would be expected. In contrast, the participant would instead be expected to experience relief if they elected to reveal the second number and it was subsequently revealed to be a 3. Trials in which the actual and counterfactual outcomes were identical because the second number was 0 were classified as the neutral condition. For further information on the experimental paradigm and the scoring rules, see Figure 1 .

Figure 1 . Experimental approach and scoring rules.

The expected values (EVs) for scores when electing to reveal the second card in an action trial are calculated with the following formula:

where i represents the number on the first card. The EVs for action and inaction trials are (4.5, 0), (4.5, 1), (4.4, 2), (4.2, 3), (3.9, 4), (3.5, 5), (3, 6), (2.4, 7), (1.7, 8), and (0.9, 9). The optimal strategy in this gambling task is thus to only reveal the second number when the first number is 3 or less (see Supplementary Figure 1A ). JASP ( https://jasp-stats.org/ ; JASP Team, 2021 ) was used to conduct all analyses, and the Bonferroni method was used to correct p values from follow-up tests.

3.1 Task performance

Average decision-making confidence, decision time, and the ratio of choosing to reveal the second number given each candidate number on the first card were calculated for all study participants (see Supplementary Table 1 ; Supplementary Figures 1B–D ). Using the first number as the independent variable f ( x ), a logistic function was fitted ( R 2  = 0.99) based on the proportion of participants who elected to reveal the second card.

When f (x) equals 0.5, this indicates that the odds of an action and an inaction trial were equal to one another. The value of x was 4.57. These analyses revealed that when the first number was 4 or 5, participants exhibited lower levels of decision-making confidence relative to all other experimental conditions, with a corresponding increase in the amount of time required to decide whether to reveal the second number.

Differences between the actual and counterfactual outcomes were defined as the counterfactual difference (CFD). All trials were classified into three conditions: negative (CFD < 0), neutral (CFD = 0), and positive (CFD > 0), and the emotional responses of participants were arranged in a heat-map (see Supplementary Figure 2 ). In this heat-map, the negative condition accounted for 22% of trials, while the positive condition accounted for 68%, and the neutral condition accounted for 10%.

3.2 The relationship between decision-making confidence and feelings of regret and relief

Two Linear Mixed Model (LMM) analyses were conducted to explore the effects of decision-making confidence on regret and relief. In the established LMM, emotions reported by study participants served as the dependent variable, while fixed effects included decision-making confidence and counterfactual difference, both of which were treated as continuous variables. The subject was entered as random intercept ( Table 1 ).

Table 1 . The impact of decision-making confidence on regret and relief.

In instances of negative condition, counterfactual difference had a significant influence on the experienced emotion ( B  = 5.43, SE  = 0.29, df  = 96.77, t  = 18.72, p  < 0.001), indicating that participants experienced higher levels of regret with as the degree to which the counterfactual outcome was better than reality rose. Moreover, decision-making confidence had a significant effect ( B  = − 0.07, SE  = 0.03, df  = 87.09, t  = −2.83, p  < 0.001). This suggests that, in cases of unfavorable outcomes as a result of a participant’s decision, higher levels of confidence in this decision will result in a higher degree of regret, consistent with the predictions of the SEP. Specifically, the negative outcome of a decision made with greater confidence evoked a stronger emotional response when an unexpected result occurred.

In instances of positive condition, counterfactual difference also had a significant impact on the experienced emotion ( B  = 0.86, SE  = 0.11, df  = 96.76, t  = 7.98, p  < 0.001). This indicates that as the real outcome improved as compared to the counterfactual outcome, participants experienced a higher degree of relief. The effect of decision-making confidence was also significant ( B  = −0.34, SE  = 0.03, df  = 87.09, t  = −11.32, and p  < 0.001). When a decision made by a participant resulted in a positive outcome, greater decision-making confidence was thus associated with a reduction in the level of relief experienced.

3.3 Emotional differences among the three conditions

Differences in emotions among the three different conditions were next tested using a Linear Mixed Model (LMM) analysis. In this analysis, the dependent variable was the emotion that participants reported experiencing, while fixed effects included the choice made (action vs. inaction) and the outcome condition (positive, neutral, and negative), which were both categorical variables. The subject was entered as random intercept.

These analyses revealed that the main effects of condition and choice were both significant [ F (96.68, 2) = 248.73, p  < 0.001; F (94.12, 1) = 39.97, p  < 0.001], as was the interaction effect [ F (97.21, 2) = 51.04, p  < 0.001]. A simple effect analysis indicated that action was associated with higher levels of regret in the negative condition ( t  = −8.76, p bonferroni  < 0.001), while also being associated with stronger feelings of relief in the positive condition ( t  = 3.24, p bonferroni  = 0.004). In the neutral condition, there was no significant difference between action and inaction ( t  = 2.80, p bonferroni  = 0.076) ( Figure 2 ).

Figure 2 . Emotional differences among different conditions. Two-way ANOVA results: 2 (choice: action & inaction) × 3 (outcome condition: negative, neutral, and positive) (The Raincloud plots are made up of three parts, namely density estimate plot, box plot, and dithering scatter plot).

4 Discussion

Confidence and counterfactual thinking are key facets of the decision-making process. The results of the present study revealed that higher levels of confidence were sufficient to reduce experiences of relief while increasing experiences of regret among participants completing a gambling task. Per the SEP theory, unexpected results can provoke more intense emotions than expected outcomes. When an individual has total confidence in a given decision and the outcome aligns with these expectations, they will experience lower levels of relief. Conversely, if they have high levels of confidence but then experience an unexpected adverse outcome, they are likely to experience a greater sense of regret. These analyses also replicated the well-characterized action effect of regret, while also demonstrating that this action effect also extends to experiences of relief. Specifically, in the negative condition, action was associated with the worsening of participant emotions (regret), whereas in the positive condition, it was associated with the enhancement of these emotions (relief).

Counterfactual thinking necessitates that an individual process both the true and counterfactual realities ( Redshaw and Suddendorf, 2020 ; Allaert et al., 2021 ; Tagini et al., 2021 ). The difference between these two realities influences the intensity of regret or relief experienced by an individual, with this comparison providing a premise to experience counterfactual emotions. Individuals who exhibit a high degree of confidence regarding their choice believe that their expected outcome will ultimately match the true outcome. In an eye-tracking study using the Wheel of Fortune task, researchers confirmed that participants compared their outcomes and the unselected lottery outcomes during the feedback phase in the full feedback condition, particularly following losses ( Bault et al., 2016 ). This highlights an asymmetry with respect to experiences of upward counterfactual thinking (regret) and downward counterfactual thinking (relief), with negative outcomes being more likely to give rise to counterfactual thinking. Individual expectations may underlie this phenomenon. Under the relief condition, true outcomes were consistent with expectations. In contrast, under the regret condition, expectations and the aversive true outcome differed, prompting a comparison of reality and counterfactual realities that would result in experiences of counterfactual emotions in the form of regret. Decision-making confidence may amplify such asymmetry, given that confidence reflects a given individual’s belief that their decision is accurate ( Pouget et al., 2016 ; Brus et al., 2021 ). Here, decision-making confidence was found to reduce relief (downward counterfactual thinking) while enhancing regret (upward counterfactual thinking).

In the first report demonstrating the action effect ( Kahneman and Tversky, 1982 ), participants were asked to compare two investors who had initially agreed to invest in company A, one of whom ultimately elected to take action by switching their investments to company B, whereas the other took no action. Both investors ultimately lost an equal amount of money. Study participants attributed greater regret to the investor who took action and switched their investments. Since this initial description, the action effect has been replicated in many studies with a focus on the experience of regret ( Towers et al., 2016 ; van de Calseyde et al., 2018 ; Feldman, 2020 ; Jamison et al., 2020 ). In the present study, this action effect was found to be intact under conditions of both relief and regret. Action has been attributed to stronger links between behaviors and outcomes and a greater sense of responsibility for negative outcomes relative to inaction ( Jamison et al., 2020 ). This link between action and responsibility can reinforce feelings of self-blame and contribute to greater levels of regret. A similar process was herein observed under the relief condition, with action contributing to greater relief, possibly as a result of stronger self-attribution, thus serving a self-promoting function.

Together, these data suggest that confidence can abrogate relief while increasing levels of regret, while also demonstrating that the traditional action effect is present in scenarios characterized by both regret and relief. This underscores the importance of meta-cognitive decision-making-related processing for a given individual’s perceptions of outcomes following a given decision, while also offering further insight into the processes that shape risk-taking behaviors in uncertain situations.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving humans were approved by Ethics Committee of Sanming University. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

ZL: Writing – review & editing, Writing – original draft.

The author declares that financial support was received for the research, authorship, and/or publication of this article. This research was supported by a grant from the Fujian Province Social Science Foundation Project (FJ2024BF054), the Sanming University National Social Science Fund Cultivation Project (KD22032SP) and the Sanming University High-level Talent Research Start-up Project (KD22025SP).

Conflict of interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2024.1365743/full#supplementary-material

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Keywords: decision-making confidence, counterfactual thinking, regret, relief, action effect

Citation: Liu Z (2024) The asymmetric impact of decision-making confidence on regret and relief. Front. Psychol . 15:1365743. doi: 10.3389/fpsyg.2024.1365743

Received: 15 January 2024; Accepted: 26 March 2024; Published: 08 April 2024.

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*Correspondence: Zan Liu, [email protected]

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