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Causal mapping of emotion networks in the human brain: Framework and initial findings
Journal article   Peer reviewed

Causal mapping of emotion networks in the human brain: Framework and initial findings

Julien Dubois, Hiroyuki Oya, J. Michael Tyszka, Matthew Howard, Frederick Eberhardt and Ralph Adolphs
Neuropsychologia, Vol.145, pp.106571-106571
08/2020
DOI: 10.1016/j.neuropsychologia.2017.11.015
PMCID: PMC5949245
PMID: 29146466

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Abstract

Emotions involve many cortical and subcortical regions, prominently including the amygdala. It remains unknown how these multiple network components interact, and it remains unknown how they cause the behavioral, autonomic, and experiential effects of emotions. Here we describe a framework for combining a novel technique, concurrent electrical stimulation with fMRI (es-fMRI), together with a novel analysis, inferring causal structure from fMRI data (causal discovery). We outline a research program for investigating human emotion with these new tools, and provide initial findings from two large resting-state datasets as well as case studies in neurosurgical patients with electrical stimulation of the amygdala. The overarching goal is to use causal discovery methods on fMRI data to infer causal graphical models of how brain regions interact, and then to further constrain these models with direct stimulation of specific brain regions and concurrent fMRI. We conclude by discussing limitations and future extensions. The approach could yield anatomical hypotheses about brain connectivity, motivate rational strategies for treating mood disorders with deep brain stimulation, and could be extended to animal studies that use combined optogenetic fMRI. •a novel causal discovery algorithm is used.•concurrent electrical stimulation and fMRI reveal amygdala connections.•a framework and initial data show causal emotion networks.
Neuroimaging fMRI Emotion Amygdala Causality

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