Online social network size is reflected in human brain structure

Kanai, Ryota; Bahrami, Bahador; Roylance, R.; Rees, Geraint

doi:10.1098/rspb.2011.1959

Cited by 306 publications

(263 citation statements)

References 56 publications

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“…3) have reported that individuals' social network size and complexity correlated with gray matter in the vmPFC (45,46), amygdala (47,48), and lTPJ (45). Moreover, individual macaques' gray matter in the mPFC and regions approximating human TPJ covary with both social network size (which was experimentally assigned) and social status (49,50).…”

Section: Discussionmentioning

confidence: 98%

Neural mechanisms tracking popularity in real-world social networks

Zerubavel

Bearman

Weber

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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Differences in popularity are a key aspect of status in virtually all human groups and shape social interactions within them. Little is known, however, about how we track and neurally represent others' popularity. We addressed this question in two real-world social networks using sociometric methods to quantify popularity. Each group member (perceiver) viewed faces of every other group member (target) while whole-brain functional MRI data were collected. Independent functional localizer tasks were used to identify brain systems supporting affective valuation (ventromedial prefrontal cortex, ventral striatum, amygdala) and social cognition (dorsomedial prefrontal cortex, precuneus, temporoparietal junction), respectively. During the face-viewing task, activity in both types of neural systems tracked targets' sociometric popularity, even when controlling for potential confounds. The target popularity-social cognition system relationship was mediated by valuation system activity, suggesting that observing popular individuals elicits value signals that facilitate understanding their mental states. The target popularity-valuation system relationship was strongest for popular perceivers, suggesting enhanced sensitivity to differences among other group members' popularity. Popular group members also demonstrated greater interpersonal sensitivity by more accurately predicting how their own personalities were perceived by other individuals in the social network. These data offer insights into the mechanisms by which status guides social behavior.social status | fMRI | social network | popularity | social cognition

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Section: Discussionmentioning

confidence: 98%

Neural mechanisms tracking popularity in real-world social networks

Zerubavel

Bearman

Weber

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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“…For example, childhood SES predicts brain structure (46) and function (45). Likewise, the size of our social networks relates to brain structure (93,94). Given that the social environment is known to affect a wide array of biological responses (5,17,19,95), a next important goal for neuroscience will be to further understand how experience at multiple levels (e.g., culture, family, social networks, SES) affects neural structure and function (46,(96)(97)(98)(99)(100)(101).…”

Section: )mentioning

confidence: 99%

What is a representative brain? Neuroscience meets population science

Falk

Hyde

Mitchell³

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

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The last decades of neuroscience research have produced immense progress in the methods available to understand brain structure and function. Social, cognitive, clinical, affective, economic, communication, and developmental neurosciences have begun to map the relationships between neuro-psychological processes and behavioral outcomes, yielding a new understanding of human behavior and promising interventions. However, a limitation of this fast moving research is that most findings are based on small samples of convenience. Furthermore, our understanding of individual differences may be distorted by unrepresentative samples, undermining findings regarding brain-behavior mechanisms. These limitations are issues that social demographers, epidemiologists, and other population scientists have tackled, with solutions that can be applied to neuroscience. By contrast, nearly all social science disciplines, including social demography, sociology, political science, economics, communication science, and psychology, make assumptions about processes that involve the brain, but have incorporated neural measures to differing, and often limited, degrees; many still treat the brain as a black box. In this article, we describe and promote a perspective-population neuroscience-that leverages interdisciplinary expertise to (i) emphasize the importance of sampling to more clearly define the relevant populations and sampling strategies needed when using neuroscience methods to address such questions; and (ii) deepen understanding of mechanisms within population science by providing insight regarding underlying neural mechanisms. Doing so will increase our confidence in the generalizability of the findings. We provide examples to illustrate the population neuroscience approach for specific types of research questions and discuss the potential for theoretical and applied advances from this approach across areas.neuroimaging | life course | statistics | survey methodology | physics Why Population Neuroscience? How do biology, social situations, and the broader environmental context interact to guide behavior, health, and development? This question is fundamental to most, if not all, social and behavioral sciences. We argue that to effectively address the many topics that stem from this larger question across disciplines, it is necessary to (i) bring a "population perspective" to neuroscience and (ii) leverage neuroscience tools within population sciences, which are subdisciplines of many fields, areas, and departments focused on documenting and understanding the dynamics of human populations, including outcomes such as health, well-being, behavior, etc.

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“…The volume of the amygdala, the almond-shaped emotion centre deep in the brain, correlates with the size and complexity of a person's social network. And grey-matter density in certain parts of the temporal lobe, which is associated with social perception and associative memory, has been found to vary according to the size of volunteers' Facebook networks 7 . Some researchers, including Fratiglioni, suspect that the cognitively demanding act of socializing can actually build up the brain -like exercising builds up muscles.…”

Section: Better Togethermentioning

confidence: 99%

Social networks: Better together

Wald¹

2016

Nature

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W hen Laura Fratiglioni looked at the data her team had collected on ageing and cognitive decline, she noticed something odd: after the age of 80, women in Stockholm were more likely than men to get dementia. Other research revealed the same trend outside of Sweden, too. Could it be that women's brains were more prone to dementia than men's, or was there some other aspect of their post-80 lifestyles causing the decline?When they delved into the data, Fratiglioni and her colleagues found an irony: that women's well-known longevity was also their undoing. "Women are more frequently alone when they reach the age of 80 or 85 because women are more often married to older men -and in general, men die earlier than women," says Fratiglioni, who is a neurologist and director of the Aging Research Center of the Karolinska Institute in Stockholm. And, as Fratiglioni's team concluded in its seminal paper 1 , it is this isolation that is correlated with increased risk of dementia.

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Online social network size is reflected in human brain structure

Cited by 306 publications

References 56 publications

Neural mechanisms tracking popularity in real-world social networks

Neural mechanisms tracking popularity in real-world social networks

What is a representative brain? Neuroscience meets population science

Social networks: Better together

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