Review
The social brain in adolescence: Evidence from functional magnetic resonance imaging and behavioural studies

https://doi.org/10.1016/j.neubiorev.2010.10.011Get rights and content

Abstract

Social cognition is the collection of cognitive processes required to understand and interact with others. The term ‘social brain’ refers to the network of brain regions that underlies these processes. Recent evidence suggests that a number of social cognitive functions continue to develop during adolescence, resulting in age differences in tasks that assess cognitive domains including face processing, mental state inference and responding to peer influence and social evaluation. Concurrently, functional and structural magnetic resonance imaging (MRI) studies show differences between adolescent and adult groups within parts of the social brain. Understanding the relationship between these neural and behavioural observations is a challenge. This review discusses current research findings on adolescent social cognitive development and its functional MRI correlates, then integrates and interprets these findings in the context of hypothesised developmental neurocognitive and neurophysiological mechanisms.

Introduction

Humans are an intensely social species. Humans show a repertoire of social abilities – from rapidly and automatically detecting the presence of another human in our environment, to making inferences about their emotions, beliefs and enduring character traits, and finally using this knowledge to guide interactions (Frith and Frith, 2008, Frith and Frith, 2010). The last two decades have seen significant progress in understanding the neural underpinnings of human social abilities. The non-invasive in vivo neuroimaging technique functional magnetic resonance imaging (fMRI) has played an important role in this research. Recently, fMRI studies have begun to reveal how the functional neural correlates of social cognition change during development.

The collection of brain regions subserving social cognition is referred to as the ‘social brain’ (Brothers, 1990, Frith, 2007) (see Fig. 1). The social brain includes the fusiform face area (FFA), posterior superior temporal sulcus (pSTS), amygdala, temporo-parietal junction (TPJ), anterior rostral medial prefrontal cortex (MPFC), the anterior cingulate cortex (ACC) and anterior temporal cortex (ATC). Functional MRI studies show differences between adolescence and adulthood in patterns of activity within these regions and, more recently, in their patterns of functional connectivity. Anatomical MRI studies indicate continuing structural brain development across the period of adolescence, including within certain regions of the social brain.

Behavioural studies are vital to interpret and qualify developmental neuroimaging findings in terms of preserved vs. changing cognitive abilities. It is reasonable to hypothesise that neuroanatomical reorganisation within social brain regions may alter their functionality, causing changes at a cognitive/behavioural level. At present, the experimental picture is incomplete, although a number of models relating adolescent social cognition to structural and functional development of the social brain have been proposed (see Sections 3 Theoretical models of adolescent neurocognitive development, 4 Structure–function relationships in the adolescent social brain).

In the following section, research on adolescent social cognitive development and its functional neural correlates is summarised, beginning with research on face processing, and proceeding to mentalising, peer influence and then social evaluation. Subsequently, Section 3 summarises current theoretical neurocognitive models accounting for adolescent behavioural and functional neuroimaging changes. Finally, Section 4 evaluates evidence relating to the interpretation of adolescent fMRI findings in the context of structural MRI findings, with consideration of potential neurophysiological mechanisms.

Section snippets

Basic face processing

A fundamental requirement for social interaction is the ability to rapidly note the presence of another human being, from visual, auditory and other cues. A particularly salient source of person information is the presence of visual cues indicating a face. Behavioural work with newborn infants has shown a preferential tuning towards face-like objects within hours of being born, with photographs and cartoons of faces being preferred over inverted or non-face objects (Morton and Johnson, 1991,

Theoretical models of adolescent neurocognitive development

Several models have been proposed in which key behavioural and cognitive characteristics of adolescence, as well as the corresponding patterns of fMRI activity, are accounted for as a consequence of neural and hormonal development. These models include the Social Information Processing Network (SIPN) model (Nelson et al., 2005), the Triadic model (Ernst and Fudge, 2009) and other Developmental Mismatch models (e.g. Casey et al., 2008, Steinberg, 2008). The models are broadly compatible,

Structural MRI findings

MRI studies show continuing neuroanatomical development during adolescence (Giedd et al., 1999, Sowell et al., 1999, Gogtay et al., 2004). Two main age-associated changes have been described in volumetric MRI studies. Firstly, cortical grey matter measures (volume, density, thickness; Ashburner and Friston, 2000) decrease across adolescence in a region-specific and commonly non-linear manner (Paus, 2005, Shaw et al., 2008, Tamnes et al., 2009, Ostby et al., 2009). Secondly, white matter volume

Conclusions

Neuroimaging studies have shown that the social brain – the complex network of brain regions that participate in understanding and interacting with social agents – continues to develop during adolescence. Using a number of social cognition tasks, fMRI studies have shown changes in functional brain activity, which occurrs alongside emerging social cognitive proficiency and neuroanatomical development.

Evidence is awaited that will shed light on the causal links between adolescent social cognitive

Acknowledgments

The authors are grateful to David Attwell, Geoffrey Bird, Marieke Scholvinck and Hauke Hillebrandt for helpful comments on early versions of this manuscript. SJB has a Royal Society University Research Fellowship. SB was funded by a Wellcome Trust four-year PhD in Neuroscience. CS was funded by the BBSRC. KCK is funded by the ESRC.

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