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Decoding negative affect personality trait from patterns of brain activation to threat stimuli

Fernandes, O; Portugal, LC; Alves, RC; Arruda-Sanchez, T; Rao, A; Volchan, E; Pereira, M; ... Mourao-Miranda, J; + view all (2017) Decoding negative affect personality trait from patterns of brain activation to threat stimuli. Neuroimage , 145 (Part B) pp. 337-345. 10.1016/j.neuroimage.2015.12.050. Green open access

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Abstract

INTRODUCTION: Pattern recognition analysis (PRA) applied to functional magnetic resonance imaging (fMRI) has been used to decode cognitive processes and identify possible biomarkers for mental illness. In the present study, we investigated whether the positive affect (PA) or negative affect (NA) personality traits could be decoded from patterns of brain activation in response to a human threat using a healthy sample. METHODS: fMRI data from 34 volunteers (15 women) were acquired during a simple motor task while the volunteers viewed a set of threat stimuli that were directed either toward them or away from them and matched neutral pictures. For each participant, contrast images from a General Linear Model (GLM) between the threat versus neutral stimuli defined the spatial patterns used as input to the regression model. We applied a multiple kernel learning (MKL) regression combining information from different brain regions hierarchically in a whole brain model to decode the NA and PA from patterns of brain activation in response to threat stimuli. RESULTS: The MKL model was able to decode NA but not PA from the contrast images between threat stimuli directed away versus neutral with a significance above chance. The correlation and the mean squared error (MSE) between predicted and actual NA were 0.52 (p-value=0.01) and 24.43 (p-value=0.01), respectively. The MKL pattern regression model identified a network with 37 regions that contributed to the predictions. Some of the regions were related to perception (e.g., occipital and temporal regions) while others were related to emotional evaluation (e.g., caudate and prefrontal regions). CONCLUSION: These results suggest that there was an interaction between the individuals' NA and the brain response to the threat stimuli directed away, which enabled the MKL model to decode NA from the brain patterns. To our knowledge, this is the first evidence that PRA can be used to decode a personality trait from patterns of brain activation during emotional contexts.

Type: Article
Title: Decoding negative affect personality trait from patterns of brain activation to threat stimuli
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.neuroimage.2015.12.050
Publisher version: http://dx.doi.org/10.1016/j.neuroimage.2015.12.050
Language: English
Additional information: © 2016 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keywords: Decode, Functional magnetic resonance imaging, Multi-kernel learning, Negative affect trait, Pattern recognition analyses, Threat stimuli
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: http://discovery.ucl.ac.uk/id/eprint/1482779
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