Abstract

Whether subtle differences in the emotional context during threat perception can be detected by multi-voxel pattern analysis (MVPA) remains a topic of debate. To investigate this question, we compared the ability of pattern recognition analysis to discriminate between patterns of brain activity to a threatening versus a physically paired neutral stimulus in two different emotional contexts (the stimulus being directed towards or away from the viewer). The directionality of the stimuli is known to be an important factor in activating different defensive responses. Using multiple kernel learning (MKL) classification models, we accurately discriminated patterns of brain activation to threat versus neutral stimuli in the directed towards context but not during the directed away context. Furthermore, we investigated whether it was possible to decode an individual’s subjective threat perception from patterns of whole-brain activity to threatening stimuli in the different emotional contexts using MKL regression models. Interestingly, we were able to accurately predict the subjective threat perception index from the pattern of brain activation to threat only during the directed away context. These results show that subtle differences in the emotional context during threat perception can be detected by MVPA. In the directed towards context, the threat perception was more intense, potentially producing more homogeneous patterns of brain activation across individuals. In the directed away context, the threat perception was relatively less intense and more variable across individuals, enabling the regression model to successfully capture the individual differences and predict the subjective threat perception.

Highlights

  • Functional neuroimaging has provided a great opportunity to obtain insight into of how emotional representations are encoded in brain activity (Lindquist et al 2012; Murphy et al 2003)

  • The multiple kernel learning (MKL) classification model was able to accurately discriminate between patterns of brain activation to threat versus neutral stimuli in the directed towards context using both crossvalidation procedures

  • The main goal of the present study was to investigate whether the discriminability between patterns of brain activation to threat versus neutral stimuli measured by the multi-voxel pattern analysis (MVPA) performance could be influenced by subtle differences in the emotional context due to the directionality of the stimuli

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Summary

Introduction

Functional neuroimaging (fMRI) has provided a great opportunity to obtain insight into of how emotional representations are encoded in brain activity (Lindquist et al 2012; Murphy et al 2003). The most common approach used to analyze fMRI data is based on the general linear model (GLM) (Friston et al 1995) and is known as a mass-univariate analysis because it makes statistical inferences independently at each location (voxel). Brain Imaging and Behavior (2020) 14:2251–2266 identifying brain regions associated with a specific stimulus or cognitive task, mass-univariate analysis does not take into account the multivariate aspect of data, i.e., the fact that each scan contains information about brain activation at thousands of voxels that are related to each other. Multivariate analyses can improve our ability to obtain valuable information from the whole brain based on functional neuroimaging

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