Directed network discovery with dynamic network modelling
Name
nihms858037.pdf
Description
Accepted version
Size
676.1 KB
Format
Adobe PDF
Checksum (MD5)
b7b9a10b847f136f978010dc15b7ea65
Author(s)
Anzellotti, Stefano
Kliemann, Dorit
Jacoby, Nir
Saxe, Rebecca
Date Issued
2017
Journal
Neuropsychologia
Publisher
Elsevier BV
Citation
Anzellotti, S., et al. "Directed Network Discovery with Dynamic Network Modelling." Neuropsychologia 99 (2017): 1-11.
Version
Author's final manuscript
Abstract
© 2017 Elsevier Ltd Cognitive tasks recruit multiple brain regions. Understanding how these regions influence each other (the network structure) is an important step to characterize the neural basis of cognitive processes. Often, limited evidence is available to restrict the range of hypotheses a priori, and techniques that sift efficiently through a large number of possible network structures are needed (network discovery). This article introduces a novel modelling technique for network discovery (Dynamic Network Modelling or DNM) that builds on ideas from Granger Causality and Dynamic Causal Modelling introducing three key changes: (1) efficient network discovery is implemented with statistical tests on the consistency of model parameters across participants, (2) the tests take into account the magnitude and sign of each influence, and (3) variance explained in independent data is used as an absolute (rather than relative) measure of the quality of the network model. In this article, we outline the functioning of DNM, we validate DNM in simulated data for which the ground truth is known, and we report an example of its application to the investigation of influences between regions during emotion recognition, revealing top-down influences from brain regions encoding abstract representations of emotions (medial prefrontal cortex and superior temporal sulcus) onto regions engaged in the perceptual analysis of facial expressions (occipital face area and fusiform face area) when participants are asked to switch between reporting the emotional valence and the age of a face.
MIT Department
Simons Center for the Social Brain (Massachusetts Institute of Technology)
Center for Brains, Minds, and Machines
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
McGovern Institute for Brain Research at MIT
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/J.NEUROPSYCHOLOGIA.2017.02.006
