The Effects of Social Distancing on Body and Brain

Post by Anastasia Sares

What’s the science?

Humans evolved to be social with one another, and we function best when we have strong relationships and regular social contact. However, in many cities, half or more of the inhabitants live alone, and in the current COVID-19 pandemic, people are additionally deprived of in-person interactions at work and social gatherings. It is a good time to remind ourselves of the far-reaching impacts of loneliness and find ways to mitigate it. This week in Trends in Cognitive Sciences, Bzdok and Dunbar reviewed the consequences of social isolation and what we know about its neurobiology.

What do we already know?

Social connectivity is a huge factor in life expectancy. Social isolation increases the risk of dying within the next decade by 25%. The death of someone close, like a spouse, increases the likelihood of death in the immediate future by more than 15%. Severe social deprivation also shortens our telomeres, which are like caps on the DNA of every cell. Shortening telomeres are linked to aging.

Social connectivity is also related to immune function and physical health. In both humans and other primates, social belonging is related to stronger immune responses, faster wound healing, better regulation of stress hormones, lower systolic blood pressure, lower body mass index, and less inflammation. Finally, social connectivity protects against depression. People with a history of depression are 25% less likely to become depressed again if they belong to one social group (like a sports club, church, hobby group, or charity). If they belong to three social groups, their risk is decreased by around 67%.

One caveat for many of these large-scale human studies is that they involve correlation instead of causation. For example, if social isolation and body-mass index (weighing more for your height) are correlated, does it mean that social isolation leads to a higher body-mass index, or that having a higher body-mass index leads to social isolation? However, accumulating evidence from many different fields seems to indicate that loneliness is detrimental to our well-being.

What’s new?

We now understand a little better what’s going on in the brain. Advances in neuroscience have shown that social cognition recruits areas such as the default mode network (related to identity, reflection, etc.) and the limbic system (involved in emotion, motivation, and threat processing). Social isolation affects the brain just as much as the body—the shape and size of the limbic system change with our level of social isolation, and it also affects communication within the default mode network, and between the default mode network and the limbic system. 

Meanwhile, our social lives have gone digital. Research shows that people’s social tendencies are similar online. We seek out social interaction with the same frequency and have a similar social network as in real life. The problem with online interaction is that it is lower quality: until the rise of video chats, we couldn’t even pick up on facial expression and body language, which are important nonverbal cues. Synchronous behavior is still a challenge because of short delays in communication—as anyone who has tried to sing “Happy Birthday” in a conference call will know. Synchronous activities like team rowing or singing in a choir promote bonding in ways similar to physical touch and grooming and can help to prevent or reduce feelings of isolation. In short, nothing can fully replace face-to-face interaction, but digital communication does help to alleviate loneliness to some degree.

What's the bottom line?

We must take our social connections seriously, individually, and as a society. During times of social isolation like the current pandemic, this is especially important, but trends of urban living and aging populations mean that it is an issue we will be dealing with for years to come. Community organizations and hobby groups are crucial to preserving social interaction and community in this regard, as they can help to protect against social isolation.

Bzdok and Dunbar. The Neurobiology of Social Distance. Trends in Cognitive Sciences (2020). Access the original scientific publication here.

Loneliness Distorts Neural Representations of Social Connection

Post by Cody Walters

What’s the science?

Social connection is a key component of well-being. Social isolation and loneliness, on the other hand, are known to pose significant health risks. Despite the important role that social relationships play in one’s overall wellness, it remains unclear how the brain represents relationships between oneself and others and whether those representations are modified by loneliness. This week in The Journal of Neuroscience, Courtney and Meyer show that there are distinct neural representations stratified along social-closeness categories, with lonelier individuals having representational distortions between themselves and others.

How did they do it?

The authors used both univariate (i.e., average activity across voxels) and multivariate (i.e., multi-voxel patterns of activity; a voxel is like a 3D pixel in an image of the brain) functional magnetic resonance imaging (fMRI) analyses. Multivariate analyses typically involve training a classifier (machine learning model) to distinguish between multi-voxel activation patterns that correspond to specific stimuli. The authors used two multivariate methods: representational similarity analysis (RSA) and whole-brain searchlight analysis: RSA is a method for comparing patterns of blood-oxygen-level-dependent (BOLD) brain activity between distinct stimuli to quantify how similar (or dissimilar) they are, whereas whole-brain searchlight analysis is an approach for identifying voxelated neighborhoods that exhibit specific patterns of brain activity.

Prior to placing the participants inside the MRI scanner, the authors had participants list out and rank the names of five close others as well as five acquaintances. While in the scanner, participants fixated on a screen that displayed these target names (either their own name, one they supplied or one of five well-known celebrities) along with traits (e.g., polite, amusing, etc.). Participants then had to indicate how well the trait described that person on a scale from 1 (‘not at all’) to 4 (‘very much’).

What did they find?

The medial prefrontal cortex (MPFC) is known to represent information about the self as well as close others, thus the authors examined the activity of a predefined MPFC region of interest. Specifically, they constructed a representational dissimilarity matrix in order to test whether there was any meaningful structure in how self-other relationships are categorized in the MPFC. The authors identified that there were three representational clusters corresponding to self, social network members (i.e., close others and acquaintances combined), and celebrities. The authors then employed a whole-brain searchlight analysis to look for other brain regions that shared a similar clustering profile as the MPFC. They found that regions commonly implicated in social cognition — the posterior cingulate cortex (PCC), precuneus, middle temporal gyrus, and temporal poles — also exhibited a three-cluster structuring of self-other representations. Next, the authors investigated whether ranked closeness to the targets influenced neural responses. Restricting their analysis to the predefined MPFC region of interest, they found that mean MPFC activation linearly increased with perceived closeness to the target. The authors examined the extent to which representations of the self overlapped with representations of others. While self-other overlap did not linearly increase by target category (close others, acquaintances, and celebrities), they did find greater overlap between representations of the self and close others relative to acquaintances and celebrities. They identified the PCC/precuneus, as well as the MPFC as regions where the representations of others, were more similar to the representation corresponding to the self.

To examine whether loneliness modulated self-other representations, the authors used an established loneliness questionnaire. Between target categories, they found that the MPFC of individuals who reported higher loneliness represented adjacent (e.g., close others and acquaintances) and distal (e.g., close others and celebrities) targets as being more similar to one another. Furthermore, they found that within categories, acquaintances were represented more similarly to one another in both the MPFC and PCC of lonelier individuals. These data suggest that there is a blurring of representational similarity within and between social groups in lonely individuals. The authors also found that loneliness was negatively correlated with self-other similarity across all categories (close others, acquaintances, and celebrities) in the MPFC, whereas loneliness was positively correlated with self-other similarity across all categories in the PCC. These findings suggest that lonelier individuals might perceive others as being dissimilar from themselves owing to a lack of self-other representational similarity.

What’s the impact?

The authors provided evidence indicating how the brain might map out subjective social closeness in terms of representational similarity and how these representations are blurred and skewed in lonelier individuals. Developing a better understanding of how the brain processes interpersonal ties and how that processing is disrupted as a result of social isolation has implications for advancing our scientific understanding of happiness and well-being.

Self-other representation in the social brain reflects social connection. The Journal of Neuroscience, (2020). Access the publication here.

Decoding of Natural Sounds in Congenitally Blind Individuals

Post by Stephanie Williams

What's the science?

Previous work has shown that patterns of brain activity measured with functional magnetic resonance imaging (fMRI) data can be used to classify sounds. Typically, these studies are performed with complex sounds (traffic, nature sounds) as the stimuli, and the classifiers (machine learning models) are built to predict groups of sounds. For example, fMRI could be used to predict whether an individual was listening to traffic noise or to a group of people speaking. One region that can be used for this decoding of auditory information is the early “visual” cortex (V1, V2, V3), which suggests that early visual cortex processes non-visual auditory information. Earlier work on auditory decoding in the early visual cortex was performed in sighted individuals only, leaving open the question of whether the same auditory information could be decoded from the visual cortex of blind individuals. This week in Current Biology, Vetter and colleagues show that sound decoding can be performed in both sighted and blind individuals with similar accuracy.

How did they do it?                             

The authors collected fMRI data from 8 congenitally blind individuals while they listened to three different natural scene sounds. The authors compared these data to previously published data (N=10) from sighted individuals, which was collected with similar stimuli and MRI acquisition parameters. The sounds consisted of 1) a bird singing and a stream 2) people talking without any clear semantic information and 3) traffic noise with cars and motorbikes. Participants listened to four rounds (‘runs’) of 18 randomized repetitions of the three sounds. The authors focused their analysis primarily on three visual areas called V1, V2, and V3, and further subdivided these into three eccentricities: foveal, peripheral and far peripheral regions. They also conducted some whole-brain analyses, searching on a voxel-by-voxel basis across the brain, rather than using predefined regions, for voxels that could be used to predict which sounds the subjects were listening to. The authors used multivariate pattern analysis (MVPA) to predict which of the three sounds participants were listening to based on the activity patterns derived from the fMRI data. They trained their classifier on three of the four runs and tested on the left-out fourth run for each subject. They compared their decoding accuracy results from the early visual cortex to the auditory cortex (which acted as a positive control) and motor cortex (negative control). The authors then analyzed how the sounds were represented in the eccentricity pattern across the early visual cortex. 

What did they find?

The authors successfully decoded natural sounds from the early visual cortex of congenitally blind individuals, showing that visual imagery and experience is not a prerequisite for the representation of auditory information in the early visual cortex and that there’s a similar cortical organization for auditory feedback in visual cortex between sighted and congenitally blind individuals. The authors saw both higher decoding accuracy for the early visual cortex and lower decoding accuracy for the auditory cortex in the blind group compared in the sighted group. This result indicates that visual deprivation may cause sound representation to be more distributed across the auditory and visual cortex in congenitally blind individuals. When the authors analyzed how eccentricity affected decoding results, they found that they had higher decoding accuracy for peripheral regions of visual cortex compared to foveal regions. This finding is supported by previous research showing that the peripheral visual cortex is connected to many non-visual brain regions. Interestingly, the authors point out that none of the three sounds induced a statistically significant response in the overall brain activity while listening to sounds compared to at rest in any of the 3 early visual areas. This suggests that their decoding accuracy is driven by small activity differences across voxels in each region of interest. 

What's the impact?

The authors extend previous work on auditory decoding in the early visual cortex to include blind individuals, showing that there may be a similar organization of auditory information in the early visual cortex of both sighted and blind individuals. This study provides further evidence that the early visual cortex is involved in functions other than the feedforward processing of visual information in both sighted and blind individuals.  

Petter et al. Decoding Natural Sounds in Early “Visual” Cortex of Congenitally Blind Individuals. (2020). Access the original scientific publication here.