Emotions are at the core of our sense of wellbeing. Their origins likely stem from an ability to motivate and inform behaviors that enable us to adapt to an often uncertain environment. The dysregulation of emotions, a common phenotype of patients with mood disorders, can disrupt healthy cognitive function in day-to-day life. Because of the importance of emotions to human functioning, scientists have been invested in using neuroimaging tools and techniques to better understand their neurophysiological bases. The past several decades of neuroimaging research has resulted in converging evidence that a diverse network of brain regions, particularly regions in the frontoparietal, midline, and mesolimbic areas of the brain, interact during a variety of emotional experiences. However, the more traditional affective neuroimaging studies typically use stimuli that are static and highly-constrained as well as analytical methods that average brain activation over time. These so-called univariate designs are therefore not conducive for studying richer, dynamic experiences that more closely resemble the real world. It is partially because of these shortcomings that the current state of the field of affective neuroscience is still very much in flux and has yet to arrive at a consensus in terms of the biological theory of emotions.
Recently, in an effort to enhance the ecological validity of neuroscientific findings, there has been a push to incorporate more dynamic and complex stimuli in experimental designs, as well as multivariate methods that can assess changes in brain activation patterns both across space and time. Previous research has shown that such paradigms with movies and music have allowed researchers to uncover time-varying patterns of brain activation related to language processing, memory, and executive functioning. Such stimuli are ideal studying emotions as well because they reliably convey and induce a range of feeling states that change over time. The aim of this Research Topic is to compile recent explorations and endeavors that leverage naturalistic paradigms in order to provide a novel understanding of the dynamic functioning of the brain and affective processing. We hope to compile perspectives that utilize a variety of neuroimaging tools (fMRI, EEG, ECoG, MEG) as well as a variety of evocative stimuli (movies, films, stories, etc.). While some researchers have recently examined brain activation associated with realistic stimuli, avenues are needed to facilitate a profitable dialogue both with computational neuroscientists improving methods for analyzing neural signals over time and affective cognitive scientists trying to define, delineate, and map emotional constructs.
Potential topics include, but are not limited to:
• Functional connectivity assessment across different emotion states in response to naturalistic stimuli using one or more neuroimaging techniques;
• Novel analytical methods and models for quantifying and interpreting time-varying patterns of emotional signal, whether it be continuous ratings, psychophysiological measures, or brain activation;
• Relating individual variation in dynamics of the brain activation in response to naturalistic stimuli to development, individual differences in emotion processing, and/or clinically-relevant symptoms and behaviors;
• Identifying, clarifying, and disentangling the temporal patterns associated with different components of affective experience (perception vs. subjective feeling vs aesthetic appreciation);
• General discussion of the advantages and disadvantages of different types of models (univariate vs. multivariate, dynamic vs. static), imaging tools, and stimuli (music vs. film vs. story) for uncovering changes in complex, affective processing.
Emotions are at the core of our sense of wellbeing. Their origins likely stem from an ability to motivate and inform behaviors that enable us to adapt to an often uncertain environment. The dysregulation of emotions, a common phenotype of patients with mood disorders, can disrupt healthy cognitive function in day-to-day life. Because of the importance of emotions to human functioning, scientists have been invested in using neuroimaging tools and techniques to better understand their neurophysiological bases. The past several decades of neuroimaging research has resulted in converging evidence that a diverse network of brain regions, particularly regions in the frontoparietal, midline, and mesolimbic areas of the brain, interact during a variety of emotional experiences. However, the more traditional affective neuroimaging studies typically use stimuli that are static and highly-constrained as well as analytical methods that average brain activation over time. These so-called univariate designs are therefore not conducive for studying richer, dynamic experiences that more closely resemble the real world. It is partially because of these shortcomings that the current state of the field of affective neuroscience is still very much in flux and has yet to arrive at a consensus in terms of the biological theory of emotions.
Recently, in an effort to enhance the ecological validity of neuroscientific findings, there has been a push to incorporate more dynamic and complex stimuli in experimental designs, as well as multivariate methods that can assess changes in brain activation patterns both across space and time. Previous research has shown that such paradigms with movies and music have allowed researchers to uncover time-varying patterns of brain activation related to language processing, memory, and executive functioning. Such stimuli are ideal studying emotions as well because they reliably convey and induce a range of feeling states that change over time. The aim of this Research Topic is to compile recent explorations and endeavors that leverage naturalistic paradigms in order to provide a novel understanding of the dynamic functioning of the brain and affective processing. We hope to compile perspectives that utilize a variety of neuroimaging tools (fMRI, EEG, ECoG, MEG) as well as a variety of evocative stimuli (movies, films, stories, etc.). While some researchers have recently examined brain activation associated with realistic stimuli, avenues are needed to facilitate a profitable dialogue both with computational neuroscientists improving methods for analyzing neural signals over time and affective cognitive scientists trying to define, delineate, and map emotional constructs.
Potential topics include, but are not limited to:
• Functional connectivity assessment across different emotion states in response to naturalistic stimuli using one or more neuroimaging techniques;
• Novel analytical methods and models for quantifying and interpreting time-varying patterns of emotional signal, whether it be continuous ratings, psychophysiological measures, or brain activation;
• Relating individual variation in dynamics of the brain activation in response to naturalistic stimuli to development, individual differences in emotion processing, and/or clinically-relevant symptoms and behaviors;
• Identifying, clarifying, and disentangling the temporal patterns associated with different components of affective experience (perception vs. subjective feeling vs aesthetic appreciation);
• General discussion of the advantages and disadvantages of different types of models (univariate vs. multivariate, dynamic vs. static), imaging tools, and stimuli (music vs. film vs. story) for uncovering changes in complex, affective processing.