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Causal Mapping of Emotion Networks in the Human Brain: Framework and Preliminary Findings
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Causal Mapping of Emotion Networks in the Human Brain: Framework and Preliminary Findings

Julien Dubois, Hiroyuki Oya, J. Michael Tyszka, Matthew Howard III, Frederick Eberhardt and Ralph Adolphs
bioRxiv: the preprint server for biology
Cold Spring Harbor Laboratory
11/05/2017
DOI: 10.1101/214486
url
https://doi.org/10.1101/214486View
Preprint (Author's original)This preprint has not been evaluated by subject experts through peer review. Preprints may undergo extensive changes and/or become peer-reviewed journal articles. Open Access

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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.

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