Advancing emotion theory with multivariate pattern classification

Relationships between subjective experience, electroencephalogram, and heart rate variability during a series of cosmetic behavior

Introduction

Cosmetic behavior is an important daily activity, especially for women, because it increases visual attractiveness, self-confidence, and positive emotions. However, it is unknown whether a relationship exists between physiological measures and subjective experiences during the series of cosmetic behaviors.

Methods

Electroencephalograms (EEG) and electrocardiograms (ECG) from thirty female participants who were asked to look in a mirror after applying skincare, as well as base, eye, cheek, and lip makeup were recorded. The price range of cosmetic products was also considered. Subjective evaluations of the skin surface, emotions, and self-confidence were equally measured after looking in the mirror at each step of the cosmetic behavior. Linear mixed models were fitted to examine whether the subjective experience could be explained by the variety of cosmetic products and/or physiological responses.

Results

The subjective evaluation was summarized into the following three factors using a factor analysis: self-confidence, hedonic perception, and negative emotion. Each theta-band (4-6 Hz) power, alpha-band (8-13 Hz) power of the EEG, and heart rate variability measures were subjected to a principal component analysis separately. The linear mixed models indicated that the variation in the self-confidence score and the negative emotion score was explained only by the steps of cosmetic behaviors, that is, self-confidence increased while negative emotions decreased as the steps of cosmetic behaviors proceeded. On the other hand, the hedonic perception score was explained by the interaction of the steps of cosmetic behaviors and price, indicating that positive tactile perception and positive emotion were higher when luxury cosmetic products were applied than when affordable products were applied. Furthermore, the model indicated that the hedonic perception score was positively associated with the alpha-band power over occipital sites whereas sympathetic nervous system activity was negatively associated with the alpha-band power over lateral central sites.

Discussion

These results suggest that positive perceptual and emotional experiences are associated with greater attention to somatosensory information than to visual information and sympathetic autonomic nervous system activities. The current results also emphasize the possibility of using physiological measurements as objective measures of cosmetic behavior.

Dynamic autonomic nervous system states arise during emotions and manifest in basal physiology

The outflow of the autonomic nervous system (ANS) is continuous and dynamic, but its functional organization is not well understood. Whether ANS patterns accompany emotions, or arise in basal physiology, remain unsettled questions in the field. Here, we searched for brief ANS patterns amidst continuous, multichannel physiological recordings in 45 healthy older adults. Participants completed an emotional reactivity task in which they viewed video clips that elicited a target emotion (awe, sadness, amusement, disgust, or nurturant love); each video clip was preceded by a pre-trial baseline period and followed by a post-trial recovery period. Participants also sat quietly for a separate 2-min resting period to assess basal physiology. Using principal components analysis and unsupervised clustering algorithms to reduce the second-by-second physiological data during the emotional reactivity task, we uncovered five ANS states. Each ANS state was characterized by a unique constellation of patterned physiological changes that differentiated among the trials of the emotional reactivity task. These ANS states emerged and dissipated over time, with each instance lasting several seconds on average. ANS states with similar structures were also detectable in the resting period but were intermittent and of smaller magnitude. Our results offer new insights into the functional organization of the ANS. By assembling short-lived, patterned changes, the ANS is equipped to generate a wide range of physiological states that accompany emotions and that contribute to the architecture of basal physiology.

Somatovisceral influences on emotional development

Frameworks of emotional development have tended to focus on how environmental factors shape children's emotion understanding. However, individual experiences of emotion represent a complex interplay between both external environmental inputs and internal somatovisceral signaling. Here, we discuss the importance of afferent signals and coordination between central and peripheral mechanisms in affective response processing. We propose that incorporating somatovisceral theories of emotions into frameworks of emotional development can inform how children understand emotions in themselves and others. We highlight promising directions for future research on emotional development incorporating this perspective, namely afferent cardiac processing and interoception, immune activation, physiological synchrony, and social touch.

Functional connectivity profiles of the default mode and visual networks reflect temporal accumulative effects of sustained naturalistic emotional experience

Determining and decoding emotional brain processes under ecologically valid conditions remains a key challenge in affective neuroscience. The current functional Magnetic Resonance Imaging (fMRI) based emotion decoding studies are mainly based on brief and isolated episodes of emotion induction, while sustained emotional experience in naturalistic environments that mirror daily life experiences are scarce. Here we used 12 different 10-minute movie clips as ecologically valid emotion-evoking procedures in n = 52 individuals to explore emotion-specific fMRI functional connectivity (FC) profiles on the whole-brain level at high spatial resolution (432 parcellations including cortical and subcortical structures). Employing machine-learning based decoding and cross validation procedures allowed to investigate FC profiles contributing to classification that can accurately distinguish sustained happiness and sadness and that generalize across subjects, movie clips, and parcellations. Both functional brain network-based and subnetwork-based emotion classification results suggested that emotion manifests as distributed representation of multiple networks, rather than a single functional network or subnetwork. Further, the results showed that the Visual Network (VN) and Default Mode Network (DMN) associated functional networks, especially VN-DMN, exhibited a strong contribution to emotion classification. To further estimate the temporal accumulative effect of naturalistic long-term movie-based video-evoking emotions, we divided the 10-min episode into three stages: early stimulation (1∼200 s), middle stimulation (201∼400 s), and late stimulation (401∼600 s) and examined the emotion classification performance at different stimulation stages. We found that the late stimulation contributes most to the classification (accuracy=85.32%, F1-score=85.62%) compared to early and middle stimulation stages, implying that continuous exposure to emotional stimulation can lead to more intense emotions and further enhance emotion-specific distinguishable representations. The present work demonstrated that sustained happiness and sadness under naturalistic conditions are presented in emotion-specific network profiles and these expressions may play different roles in the generation and modulation of emotions. These findings elucidated the importance of network level adaptations for sustained emotional experiences during naturalistic contexts and open new venues for imaging network level contributions under naturalistic conditions.

Cross-paradigm integration shows a common neural basis for aversive and appetitive conditioning

Sharing imaging data and comparing them across different psychological tasks is becoming increasingly possible as the open science movement advances. Such cross-paradigm integration has the potential to identify commonalities in findings that neighboring areas of study thought to be paradigm-specific. However, even the integration of research from closely related paradigms, such as aversive and appetitive classical conditioning is rare - even though qualitative comparisons already hint at how similar the 'fear network' and 'reward network' may be. We aimed to validate these theories by taking a multivariate approach to assess commonalities across paradigms empirically. Specifically, we quantified the similarity of an aversive conditioning pattern derived from meta-analysis to appetitive conditioning fMRI data. We tested pattern expression in three independent appetitive conditioning studies with 29, 76 and 38 participants each. During fMRI scanning, participants in each cohorts performed an appetitive conditioning task in which a CS+ was repeatedly rewarded with money and a CS- was never rewarded. The aversive pattern was highly similar to appetitive CS+ > CS- contrast maps across samples and variations of the appetitive conditioning paradigms. Moreover, the pattern distinguished the CS+ from the CS- with above-chance accuracy in every sample. These findings provide robust empirical evidence for an underlying neural system common to appetitive and aversive learning. We believe that this approach provides a way to empirically integrate the steadily growing body of fMRI findings across paradigms.

Distinct medial-tempora lobe mechanisms of encoding and amygdala-mediated memory reinstatement for disgust and fear

Current models of episodic memory posit that retrieval involves the reenactment of encoding processes. Recent evidence has shown that this reinstatement process - indexed by subsequent encoding-retrieval similarity of brain activity patterns - is related to the activity in the hippocampus during encoding. However, we tend to re-experience emotional events in memory more richly than dull events. The role of amygdala - a critical hub of emotion processing - in reinstatement of emotional events was poorly understood. To investigate it, we leveraged a previously overlooked divergence in the role of amygdala in memory modulation by distinct emotions - disgust and fear. Here we used a novel paradigm in which participants encoded complex events (word pairs) and their memory was tested after 3 weeks, both phases during fMRI scanning. Using representational similarity analysis and univariate analyses, we show that the strength of amygdala activation during encoding was correlated with memory reinstatement of individual event representations in emotion-specific regions. Critically, amygdala modulated reinstatement more for disgust than fear. This was in line with other differences observed at the level of memory performance and neural mechanisms of encoding. Specifically, amygdala and perirhinal cortex were more involved during encoding of disgust-related events, whereas hippocampus and parahippocampal gyrus during encoding of fear-related events. Together, these findings shed a new light on the role of the amygdala and medial temporal lobe regions in encoding and reinstatement of specific emotional memories.

Interoception and Emotion: A Potential Mechanism for Intervention With Manual Treatment

Interoception is considered a perception pathway as important as the exteroceptive pathways for determining responses to maintain homeostasis. There is evidence about the influence of the interoception on emotional responses as these expressions are considered to be a combination of physical, environmental and individual beliefs. A large percentage of afferent fibers in the body are related to free nerve endings which, when stimulated, reach the insular cortex that participates in the process of emotions. The viscera afferent fibers represent 5% to 15% of all these inputs. Evidence emerges that demonstrates the importance of visceral health as part of the treatment of patients with emotional imbalances. It can be postulated that manual treatment applied to visceral fasciae can assist in interoceptive balance and have a positive impact on emotions. Therefore, the objective of the present study is to discuss the concepts of interoception, central sensitization, emotional health and visceral manual treatment.

Contactless differentiation of pleasant and unpleasant valence: Assessment of the acoustic startle eyeblink response with infrared reflectance oculography

The ability to distinguish between discrete emotions by monitoring autonomic or facial features has been an elusive "holy grail" for fields such as psychophysiology, affective computing, and human-computer interface design. However, cross-validated models are lacking, and contemporary theory suggests that emotions may lack distinct physiological or facial "signatures." Therefore, in this study, we propose a reorientation toward distinguishing between pleasant and unpleasant affective valence. We focus on the acoustic eyeblink response, which exhibits affective modulation but remains underutilized. The movement of the eyelid was monitored in a contactless manner via infrared reflectance oculography at 1 kHz while 36 participants viewed normatively pleasant, neutral, and unpleasant images, and 50-ms bursts of white noise were presented binaurally via headphones. Startle responses while viewing pleasant images exhibited significantly smaller amplitudes than those while viewing unpleasant images, with a large effect size (d = 1.56). The affective modulation of the eyeblink startle response is a robust phenomenon that can be assessed in a contactless manner. As research continues on whether systems based on psychophysiological or facial features can distinguish between discrete emotions, the eyeblink startle response offers a relatively simple way to distinguish between pleasant and unpleasant affective valence.

A Voxel-based lesion study on facial emotion recognition after circumscribed prefrontal cortex damage

Previous studies have shown inconsistent findings regarding the contribution of the different prefrontal regions in emotion recognition. Moreover, the hemispheric lateralization hypothesis posits that the right hemisphere is dominant for processing all emotions regardless of affective valence, whereas the valence specificity hypothesis posits that the left hemisphere is specialized for processing positive emotions while the right hemisphere is specialized for negative emotions. However, recent findings suggest that the evidence for such lateralization has been less consistent. In this study, we investigated emotion recognition of fear, surprise, happiness, sadness, disgust, and anger in 30 patients with focal prefrontal cortex lesions and 30 control subjects. We also examined the impact of lesion laterality on recognition of the six basic emotions. The results showed that compared to control subjects, the frontal subgroups were impaired in recognition of three negative basic emotions of fear, sadness, and anger - regardless of the lesion laterality. Therefore, our findings did not establish that each hemisphere is specialized for processing specific emotions. Moreover, the voxel-based lesion symptom mapping analysis showed that recognition of fear, sadness, and anger draws on a partially common bilaterally distributed prefrontal network.

Decoding Neural Representations of Affective Scenes in Retinotopic Visual Cortex

The perception of opportunities and threats in complex visual scenes represents one of the main functions of the human visual system. The underlying neurophysiology is often studied by having observers view pictures varying in affective content. It has been shown that viewing emotionally engaging, compared with neutral, pictures (1) heightens blood flow in limbic, frontoparietal, and anterior visual structures and (2) enhances the late positive event-related potential (LPP). The role of retinotopic visual cortex in this process has, however, been contentious, with competing theories predicting the presence versus absence of emotion-specific signals in retinotopic visual areas. Recording simultaneous electroencephalography-functional magnetic resonance imaging while observers viewed pleasant, unpleasant, and neutral affective pictures, and applying multivariate pattern analysis, we found that (1) unpleasant versus neutral and pleasant versus neutral decoding accuracy were well above chance level in retinotopic visual areas, (2) decoding accuracy in ventral visual cortex (VVC), but not in early or dorsal visual cortex, was correlated with LPP, and (3) effective connectivity from amygdala to VVC predicted unpleasant versus neutral decoding accuracy, whereas effective connectivity from ventral frontal cortex to VVC predicted pleasant versus neutral decoding accuracy. These results suggest that affective scenes evoke valence-specific neural representations in retinotopic visual cortex and that these representations are influenced by reentry signals from anterior brain regions.

Predicting Individuals' Experienced Fear From Multimodal Physiological Responses to a Fear-Inducing Stimulus

Emotions are experienced differently by individuals, and thus, it is important to account for individuals' experienced emotions to understand their physiological responses to emotional stimuli. The present study investigated the physiological responses to a fear-inducing stimulus and examined whether these responses can predict experienced fear. A total of 230 participants were presented with neutral and fear-inducing film clips, after which they self-rated their experienced emotions. Physiological measures (skin conductance level and response: SCL, SCR, heart rate: HR, pulse transit time: PTT, fingertip temperature: FT, and respiratory rate: RR) were recorded during the stimuli presentation. We examined the correlations between the physiological measures and the participants' experienced emotional intensity, and performed a multiple linear regression to predict fear intensity based on the physiological responses. Of the participants, 92.5% experienced the fear emotion, and the average intensity was 5.95 on a 7-point Likert scale. Compared to the neutral condition, the SCL, SCR, HR, and RR increased significantly during the fear-inducing stimulus presentation whereas FT and PTT decreased significantly. Fear intensity correlated positively with SCR and HR and negatively with SCL, FT, PTT, and RR. The multiple linear regression demonstrated that fear intensity was predicted by a combination of SCL, SCR, HR, FT, and RR. Our findings indicate that the physiological responses to experiencing fear are associated with cholinergic, sympathetic, and α-adrenergic vascular activation as well as myocardial β-sympathetic excitation, and support the use of multimodal physiological signals for quantifying emotions.

Distinct dimensions of emotion in the human brain and their representation on the cortical surface

We experience a rich variety of emotions in daily life, and a fundamental goal of affective neuroscience is to determine how these emotions are represented in the brain. Recent psychological studies have used naturalistic stimuli (e.g., movies) to reveal high dimensional representational structures of diverse daily-life emotions. However, relatively little is known about how such diverse emotions are represented in the brain because most of the affective neuroscience studies have used only a small number of controlled stimuli. To reveal that, we measured functional MRI to obtain blood-oxygen-level-dependent (BOLD) responses from human subjects while they watched emotion-inducing audiovisual movies over a period of 3 hours. For each of the one-second movie scenes, we annotated the movies with respect to 80 emotions selected based on a wide range of previous emotion literature. By quantifying canonical correlations between the emotion ratings and the BOLD responses, the results suggest that around 25 distinct dimensions (ranging from 18 to 36 and being subject-dependent) of the emotion ratings contribute to emotion representations in the brain. For demonstrating how the 80 emotion categories were represented in the cortical surface, we visualized a continuous semantic space of the emotion representation and mapped it on the cortical surface. We found that the emotion categories were changed from unimodal to transmodal regions on the cortical surface. This study presents a cortical representation of a rich variety of emotion categories, which covers many of the emotional experiences of daily living.

EmotionMeter: A Multimodal Framework for Recognizing Human Emotions

In this paper, we present a multimodal emotion recognition framework called EmotionMeter that combines brain waves and eye movements. To increase the feasibility and wearability of EmotionMeter in real-world applications, we design a six-electrode placement above the ears to collect electroencephalography (EEG) signals. We combine EEG and eye movements for integrating the internal cognitive states and external subconscious behaviors of users to improve the recognition accuracy of EmotionMeter. The experimental results demonstrate that modality fusion with multimodal deep neural networks can significantly enhance the performance compared with a single modality, and the best mean accuracy of 85.11% is achieved for four emotions (happy, sad, fear, and neutral). We explore the complementary characteristics of EEG and eye movements for their representational capacities and identify that EEG has the advantage of classifying happy emotion, whereas eye movements outperform EEG in recognizing fear emotion. To investigate the stability of EmotionMeter over time, each subject performs the experiments three times on different days. EmotionMeter obtains a mean recognition accuracy of 72.39% across sessions with the six-electrode EEG and eye movement features. These experimental results demonstrate the effectiveness of EmotionMeter within and between sessions.

Distributed affective space represents multiple emotion categories across the human brain

The functional organization of human emotion systems as well as their neuroanatomical basis and segregation in the brain remains unresolved. Here, we used pattern classification and hierarchical clustering to characterize the organization of a wide array of emotion categories in the human brain. We induced 14 emotions (6 ‘basic’, e.g. fear and anger; and 8 ‘non-basic’, e.g. shame and gratitude) and a neutral state using guided mental imagery while participants' brain activity was measured with functional magnetic resonance imaging (fMRI). Twelve out of 14 emotions could be reliably classified from the haemodynamic signals. All emotions engaged a multitude of brain areas, primarily in midline cortices including anterior and posterior cingulate gyri and precuneus, in subcortical regions, and in motor regions including cerebellum and premotor cortex. Similarity of subjective emotional experiences was associated with similarity of the corresponding neural activation patterns. We conclude that different basic and non-basic emotions have distinguishable neural bases characterized by specific, distributed activation patterns in widespread cortical and subcortical circuits. Regionally differentiated engagement of these circuits defines the unique neural activity pattern and the corresponding subjective feeling associated with each emotion.

Regulating emotion through distancing: A taxonomy, neurocognitive model, and supporting meta-analysis

Distancing is a type of emotion regulation that involves simulating a new perspective to alter the psychological distance and emotional impact of a stimulus. The effectiveness and versatility of distancing relative to other types of emotion regulation make it a promising tool for clinical applications. However, the neurocognitive mechanisms of this tactic are unclear, and inconsistencies in terminology and methods across studies make it difficult to synthesize the literature. To promote more effective research, we propose a taxonomy of distancing within the broader context of emotion regulation strategies; review the effects of this tactic; and offer a preliminary neurocognitive model describing key cognitive processes and their neural bases. Our model emphasizes three components-self-projection, affective self-reflection, and cognitive control. Additionally, we present results from a supporting meta-analysis of neuroimaging studies of distancing. These efforts are presented within the overarching goals of supporting effective applications of distancing in laboratory, clinical, and other real-world contexts, and advancing understanding of the relevant high-level cognitive functions in the brain.

Coverage of Emotion Recognition for Common Wearable Biosensors

The present research proposes a novel emotion recognition framework for the computer prediction of human emotions using common wearable biosensors. Emotional perception promotes specific patterns of biological responses in the human body, and this can be sensed and used to predict emotions using only biomedical measurements. Based on theoretical and empirical psychophysiological research, the foundation of autonomic specificity facilitates the establishment of a strong background for recognising human emotions using machine learning on physiological patterning. However, a systematic way of choosing the physiological data covering the elicited emotional responses for recognising the target emotions is not obvious. The current study demonstrates through experimental measurements the coverage of emotion recognition using common off-the-shelf wearable biosensors based on the synchronisation between audiovisual stimuli and the corresponding physiological responses. The work forms the basis of validating the hypothesis for emotional state recognition in the literature and presents coverage of the use of common wearable biosensors coupled with a novel preprocessing algorithm to demonstrate the practical prediction of the emotional states of wearers.

Putting Feelings Into Words: Affect Labeling as Implicit Emotion Regulation

Putting feelings into words, or “affect labeling,” can attenuate our emotional experiences. However, unlike explicit emotion regulation techniques, affect labeling may not even feel like a regulatory process as it occurs. Nevertheless, research investigating affect labeling has found it produces a pattern of effects like those seen during explicit emotion regulation, suggesting affect labeling is a form of implicit emotion regulation. In this review, we will outline research on affect labeling, comparing it to reappraisal, a form of explicit emotion regulation, along four major domains of effects—experiential, autonomic, neural, and behavioral—that establish it as a form of implicit emotion regulation. This review will then speculate on possible mechanisms driving affect labeling effects and other remaining unanswered questions.

Mind the Hype: A Critical Evaluation and Prescriptive Agenda for Research on Mindfulness and Meditation

During the past two decades, mindfulness meditation has gone from being a fringe topic of scientific investigation to being an occasional replacement for psychotherapy, tool of corporate well-being, widely implemented educational practice, and "key to building more resilient soldiers." Yet the mindfulness movement and empirical evidence supporting it have not gone without criticism. Misinformation and poor methodology associated with past studies of mindfulness may lead public consumers to be harmed, misled, and disappointed. Addressing such concerns, the present article discusses the difficulties of defining mindfulness, delineates the proper scope of research into mindfulness practices, and explicates crucial methodological issues for interpreting results from investigations of mindfulness. For doing so, the authors draw on their diverse areas of expertise to review the present state of mindfulness research, comprehensively summarizing what we do and do not know, while providing a prescriptive agenda for contemplative science, with a particular focus on assessment, mindfulness training, possible adverse effects, and intersection with brain imaging. Our goals are to inform interested scientists, the news media, and the public, to minimize harm, curb poor research practices, and staunch the flow of misinformation about the benefits, costs, and future prospects of mindfulness meditation.

What Is the Effect of Basic Emotions on Directed Forgetting? Investigating the Role of Basic Emotions in Memory

Studies presenting memory-facilitating effect of emotions typically focused on affective dimensions of arousal and valence. Little is known, however, about the extent to which stimulus-driven basic emotions could have distinct effects on memory. In the present paper we sought to examine the modulatory effect of disgust, fear, and sadness on intentional remembering and forgetting using widely used item-method directed forgetting (DF) paradigm. Eighteen women underwent fMRI scanning during encoding phase in which they were asked either to remember (R) or to forget (F) pictures. In the test phase all previously used stimuli were re-presented together with the same number of new pictures and participants had to categorize them as old or new, irrespective of the F/R instruction. On the behavioral level we found a typical DF effect, i.e., higher recognition rates for to-be-remembered (TBR) items than to-be-forgotten (TBF) ones for both neutral and emotional categories. Emotional stimuli had higher recognition rate than neutral ones, while among emotional those eliciting disgust produced highest recognition, but at the same time induced more false alarms. Therefore, when false alarm corrected recognition was examined the DF effect was equally strong irrespective of emotion. Additionally, even though subjects rated disgusting pictures as more arousing and negative than other picture categories, logistic regression on the item level showed that the effect of disgust on recognition memory was stronger than the effect of arousal or valence. On the neural level, ROI analyses (with valence and arousal covariates) revealed that correctly recognized disgusting stimuli evoked the highest activity in the left amygdala compared to all other categories. This structure was also more activated for remembered vs. forgotten stimuli, but only in case of disgust or fear eliciting pictures. Our findings, despite several limitations, suggest that disgust have a special salience in memory relative to other negative emotions, which cannot be put down to differences in arousal or valence. The current results thereby support the suggestion that a purely dimensional model of emotional influences on cognition might not be adequate to account for observed effects.

Decoding the Nature of Emotion in the Brain

A central, unresolved problem in affective neuroscience is understanding how emotions are represented in nervous system activity. After prior localization approaches largely failed, researchers began applying multivariate statistical tools to reconceptualize how emotion constructs might be embedded in large-scale brain networks. Findings from pattern analyses of neuroimaging data show that affective dimensions and emotion categories are uniquely represented in the activity of distributed neural systems that span cortical and subcortical regions. Results from multiple-category decoding studies are incompatible with theories postulating that specific emotions emerge from the neural coding of valence and arousal. This 'new look' into emotion representation promises to improve and reformulate neurobiological models of affect.

Perceptual and affective mechanisms in facial expression recognition: An integrative review

Facial expressions of emotion involve a physical component of morphological changes in a face and an affective component conveying information about the expresser's internal feelings. It remains unresolved how much recognition and discrimination of expressions rely on the perception of morphological patterns or the processing of affective content. This review of research on the role of visual and emotional factors in expression recognition reached three major conclusions. First, behavioral, neurophysiological, and computational measures indicate that basic expressions are reliably recognized and discriminated from one another, albeit the effect may be inflated by the use of prototypical expression stimuli and forced-choice responses. Second, affective content along the dimensions of valence and arousal is extracted early from facial expressions, although this coarse affective representation contributes minimally to categorical recognition of specific expressions. Third, the physical configuration and visual saliency of facial features contribute significantly to expression recognition, with "emotionless" computational models being able to reproduce some of the basic phenomena demonstrated in human observers. We conclude that facial expression recognition, as it has been investigated in conventional laboratory tasks, depends to a greater extent on perceptual than affective information and mechanisms.

Discrete Neural Signatures of Basic Emotions

Categorical models of emotions posit neurally and physiologically distinct human basic emotions. We tested this assumption by using multivariate pattern analysis (MVPA) to classify brain activity patterns of 6 basic emotions (disgust, fear, happiness, sadness, anger, and surprise) in 3 experiments. Emotions were induced with short movies or mental imagery during functional magnetic resonance imaging. MVPA accurately classified emotions induced by both methods, and the classification generalized from one induction condition to another and across individuals. Brain regions contributing most to the classification accuracy included medial and inferior lateral prefrontal cortices, frontal pole, precentral and postcentral gyri, precuneus, and posterior cingulate cortex. Thus, specific neural signatures across these regions hold representations of different emotional states in multimodal fashion, independently of how the emotions are induced. Similarity of subjective experiences between emotions was associated with similarity of neural patterns for the same emotions, suggesting a direct link between activity in these brain regions and the subjective emotional experience.

Multivariate neural biomarkers of emotional states are categorically distinct

Understanding how emotions are represented neurally is a central aim of affective neuroscience. Despite decades of neuroimaging efforts addressing this question, it remains unclear whether emotions are represented as distinct entities, as predicted by categorical theories, or are constructed from a smaller set of underlying factors, as predicted by dimensional accounts. Here, we capitalize on multivariate statistical approaches and computational modeling to directly evaluate these theoretical perspectives. We elicited discrete emotional states using music and films during functional magnetic resonance imaging scanning. Distinct patterns of neural activation predicted the emotion category of stimuli and tracked subjective experience. Bayesian model comparison revealed that combining dimensional and categorical models of emotion best characterized the information content of activation patterns. Surprisingly, categorical and dimensional aspects of emotion experience captured unique and opposing sources of neural information. These results indicate that diverse emotional states are poorly differentiated by simple models of valence and arousal, and that activity within separable neural systems can be mapped to unique emotion categories.

An asymmetric inhibition model of hemispheric differences in emotional processing

Two relatively independent lines of research have addressed the role of the prefrontal cortex in emotional processing. The first examines hemispheric asymmetries in frontal function; the second focuses on prefrontal interactions between cognition and emotion. We briefly review each perspective and highlight inconsistencies between them. We go on to describe an alternative model that integrates approaches by focusing on hemispheric asymmetry in inhibitory executive control processes. The asymmetric inhibition model proposes that right-lateralized executive control inhibits processing of positive or approach-related distractors, and left-lateralized control inhibits negative or withdrawal-related distractors. These complementary processes allow us to maintain and achieve current goals in the face of emotional distraction. We conclude with a research agenda that uses the model to generate novel experiments that will advance our understanding of both hemispheric asymmetries and cognition-emotion interactions.