Summary Burnett, S., Sebastian, C., Kadosh, K. C., & Blakemore, S. J. (2011). The social brain in adolescence: evidence from functional magneticresonance imaging and behavioural studies. Neuroscience & Biobehavioral Reviews,35(8), 1654-1664


With the help of neuroimaging techniques such as the functional MRI (fMRI), brain regions that are influenced in social cognition, have been determined. Social cognition is about all the cognitive processes that are required to understand and to interact with others. The term for all the regions that are involved in these processes are called the ‘social brain’. With the help of frmi, it has been shown that there are differences in these regions in adults compared to adolescents.

Social cognitive development and its functional neural correlates

Face processing

The ability to recognize a face is crucial for effective social interaction. It seems that babies who are just a few hours old, already show a preference for face-like objects. Infants also prefer to look at people who look at them, instead of looking at people who look away from them.

This does not mean that face processing does not develop over the course of life. One study has shown an improvement in face recognition during the first decade of life, with a short dip around the age of 12.  


It seems that in adults the ‘fusiform face area’ (FFA) was larger than in children. The FFA of adolescents were intermediate in size compared to that of the adults and the children. It also seems that the expansion of the FFA correlates with improvement in the recognition of faces.

Another study showed an age-related increase in the size of the face-selectivity of the FFA between childhood and adolescence and an increase in the size of the face-selective superior temporal sulcus (STS).

It also seems that with more training, the cortical networks that are involved in face processing become more fine-tuned. So, the older people get (and thus the more training they get), the better they become in processing faces. With other words, there was an increase in the functional specialization in the FFA.

When comparing face and body processing in participants from 7-32 years, researchers found the same fine-tuning effect for face processing, but not for the processing of body stimuli. This is called a double dissociation between age and skill for processing different social stimuli (bodily stimuli and face stimuli).

It also seems that processing expressed emotions in faces happens in the amygdala (automatic processing), in parts of the prefrontal cortex (action and emotion regulation) and in higher-level social processing.

It seems that for emotion processing there is also an increase with age. But this may differ for different emotions. For example, fear shows a linear improvement with age and anger shows a quadratic trend with a sharp improvement during adolescence and adulthood.


Mentalising is another name for ‘Theory of Mind’. This theory is about the ability of an individual to be able to think about what other people think, feel and/or would do in a particular situation. Research shows that there is a decrease in anterior rostral MPFC activity (the region involved with mentalising) when people get older. This may be due to the kind of tasks that are used to investigate. Dumontheil used a task which involved perspective taking and found that there seems to be a continual development during late adolescence in performance on this kind of task involved with perspective taking. But, this result can be interpreted in different ways.                     

Behavioural economic games

Behavioural economic games are used to investigate the use of mental state inferences in strategic social decision-making. It seems that there is increased activity within the reward system in the brain of adults (nucleus accumbens) during these games, which can be explained because of the tokens they win. There is also increased activity in the mentalising systems, which is important to process one’s own and other’s actions and intentions. The tendency to use mental inferences about others seems to continue to develop during adolescence. Between the ages 9 and 18 it seems that doing a generous offer is highly dependent on what they think of their co-players. Within the ages 6-9, there is a tendency to act on basic principles such as fairness and reciprocity.

Other research

It seems that adolescents take many more risks when driving in the presence of peers compared to when they were alone. For adults and children this was not true. It seems that from the ages of 14 – 18, there is an increase in ‘Resistance to Peer Influence’.

It also seems that adolescents show a hypersensitivity to social rejection. This could be due to the development of prefrontal regulatory mechanisms, which continue to develop between adolescence and adulthood. It is not clear whether females are more sensitive to social evaluation than men.

Models of adolescent neurocognitive developments

There are models such as The Social Information Processing Network Model, which states that during adolescence there is a process called ‘social reorienting’ which leads to the behavioural characteristics of adolescents. The Triadic Model distinguishes between affective-motivational and cognitive-regulatory neural systems, which develop during adolescence. In this model, there is an imbalance between the approach and avoidance nodes during adolescence and this contributes to the characteristics of adolescents (such as heightened risk-taking). The Developmental Mismatch model states that the limbic system matures earlier than the PFC, so there is a mismatch between brain regions. The biggest mismatch occurs during adolescence.

So, in these models, the assumption is that behavior during adolescence is related to changes in brain activity measured with Fmri.

During adolescence there also seems to be a decrease in cortical grey matter. This may reflect differences in synaptic density. Also, white matter volume and density increase, which may reflect processes including myelination and axon activity.

Relationship between MRI findings and the fMRIi signals

The question that remains is whether there is a meaningful relationship between structural brain development and the blood oxygenation level-dependent signal in fMRI (BOLD). It has been observed that there is a diffuse-to-focal shift in BOLD-signal between child- and adulthood. There is more research needed to determine the causes for this shift from diffuse to focal BOLD signal.


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