In episode 28 of Neuroverse, “Subjectivity and Emotional Valence”, Clara and Carolina delve into the mysteries of how the human brain understands experiences and expresses emotions. They touch on the influence of innate vs learned emotions, the importance of expectation, and how subjective experiences inform choice.
Emotions possess a beautiful trait: they are simultaneously personal yet universal
Each emotional experience means something different to each individual, yet emotions are integral to our collective experience as human beings, making up a way in which we can relate to one another through our shared experience of them. Neuroscientists have spent decades navigating this duality, by blending the subjective experiences of people with visualizing their objective representations as activity in the brain using neuroimaging methods. Research at this intersection has revealed how advances in technology and methodology has the potential to bridge the gap between perception, feeling, and scientific exploration.
THE EMOTIONAL EQUATION
The podcast begins by exploring theories of emotions, and how the evolution of such theories has influenced our current framework of understanding. Emotions are not purely
psychological experiences, but share an intricate association with one’s physiological and
genetic makeup, while also exerting bidirectional influences on social structures. In many
ways, neuroscience has attempted to explore each of these pathways in isolation and in
relation with each other. This inevitably brings up the question:
are emotional experiences a product of learned behavior, or fundamental innate processes?
Charles Darwin, the pioneer of evolutionary studies, proposed the biological underpinnings
of emotional expression in his book “The Expression of Emotions in Man and Animals” in
1872. Just like human physiology, emotions evolved over a period of time, to help organisms adapt and respond to their environment to promote survival. In positing the idea that basic emotions such as joy, fear, and anger had evolutionary roots, Darwin’s theory was amongst the first to put forth the idea of a biological basis of emotions.
Illustration from "The Expression of Emotions in Man and Animals" by Charles Darwin (1872)
Building on this evolutionary perspective, contemporary studies began to investigate the
influence of physiological arousal and social factors on emotions. The Two-Factor Theory by
Schacter & Singer remains to this day a crucial theory, being one of the first to accommodate more than one explanation for emotional expression. Their research consisted of a blinded experiment where participants were injected with saline or epinephrine to induce arousal, and then asked to interpret different emotional contexts. Informed participants attributed their feelings to the injection, whereas those unaware of what they were injected with explained their reactions based on the mood of confederates they interacted with. The experiments demonstrated the dual influence of physiological arousal and cognitive appraisal in emotional responses and experiences, and introduced the idea of context-dependent emotional labelling as a critical process in emotional experiences.
Schacter & Singer's Two-Factor Theory involves both physiological and cognitive factors in defining emotions.
Figure taken from: https://www.simplypsychology.org/schachter-singer-theory.html
Another study conducted in San Francisco State University explored the basis of emotional
facial expressions. They noted similarities in the facial expressions of blind and sighted
athletes, suggesting that expression is not learned through sight, but arises from innate
biological abilities. Supported by neurobiological studies into the role of structures such as
the amygdala, and muscles such as the orbicularis oculi, research suggested that evolutionary mechanisms played a role in in communication of information, such as expressing fear or the need for social bonding.
Altogether, although biological temperament likely forms the groundwork for emotional
expression, socialization and learning largely shape how we process emotions. Social
learning theories studying parental interactions demonstrate the dynamic capabilities in
emotional regulation in children; responsive and supportive styles of parenting tend to foster
more positive manifestations, while neglect and anger styles amplify emotional instability.
Cultural norms also influence the way individuals model emotional reactions - through
observation of parents, peers or media.
A child may have a predisposition to certain emotional reactions, but developmental influences certainly shape their tendencies.
THE QUEST FOR OBJECTIVITY: MAPPING EMOTIONAL REPRESENTATIONS
Building on our understanding about where emotions arise and how the brain processes them, technological advancements in neuroimaging provide an unprecedented window into
visualizing brains that are experiencing emotions in real time. For instance, functional MRI
(fMRI) has long been used to visualize the dynamic changes in brain activity while
processing emotions. fMRI has uncovered a key role of a brain region known as the
amygdala as the “emotional hub”, with a wide variety of connections to several brain regions involved in different components of emotional processing.
fMRI has uncovered a key role of a brain region known as the amygdala as the “emotional hub”
Neuroimaging tools are vital in understanding brain activation during emotional experiences. Figure from Wager et al. (2015) https://doi.org/10.1371/journal.pcbi.1004066
Central to this discourse of how the brain represents such emotions, is by first understanding whether emotions exist as discrete categories, or on a continuous spectrum. Evolutionary psychologists hold the view that emotions can be categorized into certain distinct categories – happiness, sadness, fear, and anger – where each have certain unique physiological characteristics and neural signatures. However, fMRI studies have failed to identify discrete neural correlates for different emotions. Instead, the same areas appear to be activated similarly during all basic emotional states. Viewing emotions as continuous importantly acknowledges the unique ability of individuals to interpret and respond to their environment.
Acknowledging the immensity of subjectivity in emotional experiences entails understanding individual differences in expression, perception, and interoception which lie on a spectrum.
Specifically, there is a rising interest in decoding valence processing – how the brain assigns value and significance to any stimuli. This often involves a quantitative assessment of a stimuli as either positive, negative, or neutral, while assigning strength on the spectrum. One region deep in the front of the brain, known as the nucleus accumbens, has been implicated in bidirectional valence processing, signaling either positive (liking/reward) or negative (disliking/aversion) behavior based on the specific subregion that is activated (see Ray et al., 2022). However, much more research is required to distinguish the neural processes underlying valence processing in the brain (see review by Tye, 2018).
Valence processing involves assigning positive or negative value to experiences or emotions
Complementing neuroimaging techniques is machine learning, serving as an emerging tool
for analyzing complex datasets to uncover characteristics unique to certain physiological
processes. With a recognized utility of the brain’s ability to discern between emotions and
their valence, computational tools have been handy in recognizing specific circuits within the brain which are associated with processing different types of emotional valence. By using supervised learning algorithms like Support Vector Machines, scientists have been able to distinguish between positive and negative valence states based on neural activity. This increasing incorporation of machine learning methods in research has enabled scientists to achieve better classification and generalization, thereby advancing both theoretical knowledge and applied interventions for therapeutic strategies for emotional disorders.
CONCLUSION
Exploring emotional valence through neuroscientific methods of investigation certainly raises interesting questions about how experiences are represented within the human brain.
Mapping neural circuits underlying valence has supplemented our understanding of decision making, reward behavior, and dysregulation in mood disorders. In improving technological capabilities, the hope is that such subjective experiences may present certain objective characteristics, which when visualized using neuroimaging and machine learning techniques can enrich our comprehension about the fundamentals of human nature.
Listen to the episode here to find out more!
This article was written by Purnima BR and edited by Clara Lenherr
Purnima is Master's student in Cognitive Neuroscience at the University of Sheffield who is enthusiastic about the neural basis of cognition, and how advances in diagnostic visualization can help inform treatments for neuropsychiatric conditions.
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