Sokolov, Arseny Alexandrovitsch;
(2020)
Effective and Structural Connectivity in the Social Brain Networks Underwriting Body Language Reading.
Doctoral thesis (Ph.D), UCL (University College London).
Abstract
Social cognition is essential in our everyday life. However, the conceptualisation of the anatomical and functional architecture of the underlying social brain networks remains rather limited. Understanding of brain structure, function and their relationship to behaviour may substantially benefit from considering the breadth of multimodal information afforded by neuroimaging, such as diffusion and functional magnetic resonance imaging (MRI). However, integration is not straightforward and has not yet been widely implemented. We use measures of structural connectivity derived from probabilistic tractography on high angular resolution diffusion imaging (HARDI) data to inform Dynamic causal modelling (DCM) analyses of task-related effective connectivity. Models of effective connectivity that are informed by structural connectivity have greater evidence than models without anatomical information. Furthermore, simulation of neurobiologically plausible asymmetric, polysynaptic anatomical connectivity by applying the graph Laplacian to HARDI data further optimises estimates offfective connectivity. From a neurobiological perspective, in the cerebro-cerebellar network for body language reading, both the detectability of WM pathways and strength of effective connections between the fusiform gyrus and superior temporal sulcus predict the visual detection of biological motion (BM). Moreover, network-level analysis of neuroimaging data reveals parallel, rather than hierarchical communication between temporal and fronto-insular components. This may explain why body language reading is relatively resilient to focal brain damage, but severely affected in neuropsychiatric conditions with more global alterations in connectivity such as autism spectrum disorder. Furthermore, DCM suggests that interplay between the amygdala and insula is not only vital for emotion processing, but also predicts the ability to infer the absence of emotional content in body language. Taken together, integrative connectivity analyses can offer a better characterisation of brain architecture, dynamics and their relationship to behaviour, both in neurotypical individuals and neuropsychiatric conditions.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Effective and Structural Connectivity in the Social Brain Networks Underwriting Body Language Reading |
| Event: | UCL |
| Language: | English |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10090845 |
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