How Emotion Concepts Develop and Synchronize in the Brain


Emotions are essential for human social interactions. We need to understand how other people feel and why they behave in certain ways. But how do we learn to recognize and interpret emotions? And how does this ability change as we grow up?

In this article, we will review a recent study by Camacho et al. (2023) that investigated how the brain encodes emotion concepts from childhood to adolescence. Emotion concepts are mental representations that help us predict and explain emotional situations. For example, when we see someone crying, we may activate our concept of sadness and infer that they are feeling unhappy or distressed.

The researchers used functional magnetic resonance imaging (fMRI) to measure brain activity in 823 children aged 5 to 15 years old. The children watched videos of actors portraying different emotions, such as happiness, sadness, anger, fear, disgust and surprise. The videos had a narrative context that explained why the actors felt that way.

The researchers found that different emotions elicited distinct patterns of brain activity throughout the cortex, cerebellum and caudate. These patterns were relatively stable across development, meaning that they did not change much from age 5 to 15.

However, the researchers also found that the patterns became more similar between individuals as they got older. This means that older children had more shared neural representations of emotion concepts than younger children.

The researchers also analyzed how the brain responded to scenes that required inferring negative emotional states, such as fear or disgust.

They found that older children showed higher similarity in their default mode network (DMN) activation than younger children. The DMN is a brain network that is involved in self-referential and social cognition. The researchers suggested that older children may use more mental simulation and perspective-taking to understand others’ emotions.

in deep…..

The default mode network (DMN) is a system of connected brain areas that show increased activity when a person is not focused on what is happening around them. The DMN is especially active, research shows, when one engages in introspective activities such as daydreaming, contemplating the past or the future, or thinking about the perspective of another person.

The DMN has been implicated in various cognitive functions and mental disorders, such as memory, creativity, depression, loneliness, Alzheimer’s disease, and schizophrenia. However, the exact role of the DMN in naturalistic cognition remains unclear.

What is the Default Mode Network?

The DMN was first discovered by neurologist Marcus Raichle and his colleagues in the late 1990s, when they observed that some brain regions showed decreased blood flow during tasks that required attention to external stimuli, compared to when participants were resting with their eyes closed. These regions included parts of the medial prefrontal cortex (mPFC), posterior cingulate cortex (PCC), precuneus, lateral parietal cortex (LPC), and medial temporal lobe (MTL).

Raichle and his colleagues proposed that these regions form a network that is active by default when the brain is not engaged in any specific task. They suggested that this network supports internal mental processes that are unrelated to the external environment, such as self-referential thoughts, autobiographical memory retrieval, mental simulation, and social cognition.

Since then, many studies have confirmed and expanded the findings on the DMN using various techniques, such as functional magnetic resonance imaging (fMRI), electroencephalography (EEG), magnetoencephalography (MEG), and positron emission tomography (PET).

The DMN has been shown to exhibit coherent low-frequency oscillations across its regions during resting state, indicating functional connectivity among them. The DMN has also been shown to be modulated by various factors, such as age, gender, personality traits, mood states, and cognitive abilities.

What is the Role of the Default Mode Network in Naturalistic Cognition?

Naturalistic cognition refers to the complex and dynamic mental processes that occur when we interact with real-world stimuli and situations, such as watching a movie, listening to a story, or having a conversation. Naturalistic cognition involves multiple cognitive domains, such as perception, attention, memory, emotion, language, and social understanding.

Recently, several studies have used naturalistic stimuli to investigate the role of the DMN in naturalistic cognition. These studies have found that the DMN is not only active during rest, but also during naturalistic stimulation. Moreover, the DMN activity during naturalistic stimulation reflects aspects of the stimulus content and structure, such as narrative coherence, emotional valence, semantic meaning, and temporal order.

For example, one study by Hasson et al. (2004) showed that participants who watched an episode of “The Good,
the Bad and the Ugly” had synchronized activity in their DMNs across different brain regions and across different viewers. This synchronization was correlated with the degree of narrative comprehension and memory of the movie.

Another study by Simony et al. (2016) showed that participants who listened to an audio story had increased activity in their DMNs during segments of high surprise compared to segments of low surprise. The authors suggested that surprise reflects a prediction error signal that triggers DMN activation to update one’s mental model of the story.

These studies suggest that the DMN plays a role in processing naturalistic events that are relevant for one’s self and social understanding. The DMN may help integrate information from different sources and timescales to form a coherent representation of one’s experience.

What are the Challenges and Future Directions for Studying the Default Mode Network in Naturalistic Settings?

Studying the DMN in naturalistic settings poses several methodological challenges that need to be addressed by future research. Some of these challenges are:

  • How to measure and model the cognitive state of participants during naturalistic stimulation? Unlike controlled tasks that have predefined stimuli and responses, naturalistic stimuli are complex and variable, and participants may have different interpretations and reactions to them. Therefore, researchers need to develop new techniques to capture the cognitive state of participants during naturalistic stimulation, such as using behavioral sampling, eye tracking, or physiological measures.
  • How to isolate the specific contribution of the DMN from other brain networks during naturalistic stimulation? Naturalistic cognition involves the interaction of multiple brain networks, such as the attention, memory, and emotion networks. Therefore, researchers need to develop new techniques to disentangle the specific role of the DMN from other networks during naturalistic stimulation, such as using multivariate pattern analysis, causal modeling, or network analysis.
  • How to generalize the findings from one naturalistic stimulus to other naturalistic stimuli? Naturalistic stimuli are diverse and heterogeneous, and may differ in their content, structure, modality, and genre. Therefore, researchers need to test whether the findings from one naturalistic stimulus can be replicated and generalized to other naturalistic stimuli, such as using cross-validation, meta-analysis, or computational modeling.

These findings suggest that emotion concepts are relatively well-established by mid to late childhood and become more synchronized between individuals during adolescence.

This may reflect a process of socialization and cultural learning that shapes our emotional understanding. The researchers also highlighted the importance of early intervention for children who have difficulties in processing emotional cues, such as those with anxiety or autism spectrum disorder.

In conclusion, this study provides novel insights into how the brain develops and encodes emotion concepts in naturalistic contexts. It also demonstrates the potential of using large-scale neuroimaging data to study complex social phenomena across development.

reference link : Camacho, M.C., Nielsen, A.N., Balser, D. et al. Large-scale encoding of emotion concepts becomes increasingly similar between individuals from childhood to adolescence. Nat Neurosci (2023).


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