Neural correlates of the natural observation of an emotionally loaded video.

Melanni Nanni,Fernando A Barrios,Leopoldo Gonzalez-Santos,Joel Martínez-Soto,Wang Zhan

doi:10.1371/journal.pone.0198731

Melanni Nanni, Fernando A Barrios + Show 3 more

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https://doi.org/10.1371/journal.pone.0198731

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Abstract

Studies based on a paradigm of free or natural viewing have revealed characteristics that allow us to know how the brain processes stimuli within a natural environment. This method has been little used to study brain function. With a connectivity approach, we examine the processing of emotions using an exploratory method to analyze functional magnetic resonance imaging (fMRI) data. This research describes our approach to modeling stress paradigms suitable for neuroimaging environments. We showed a short film (4.54 minutes) with high negative emotional valence and high arousal content to 24 healthy male subjects (36.42 years old; SD = 12.14) during fMRI. Independent component analysis (ICA) was used to identify networks based on spatial statistical independence. Through this analysis we identified the sensorimotor system and its influence on the dorsal attention and default-mode networks, which in turn have reciprocal activity and modulate networks described as emotional.

Highlights

Understanding how the human brain processes information in a natural environment reveals information about its integral functioning during daily life
Using Independent component analysis (ICA) we were able to document the dynamics that exist between the BOLD activity of each network detected while a stressful video was being viewed
What stood out the most in this study was the identification of the dorsal attention network (DAN) and the Default Mode Network (DMN)

Summary

Introduction

Understanding how the human brain processes information in a natural environment reveals information about its integral functioning during daily life. Under conditions simulating normal life certain areas of the brain function as networks participating in coding complex stimuli, such as natural vision [1]. This brain activity reflects characteristics similar to those evoked in the natural human environment. FMRI has been used to measure brain activity, primarily in the context of highly controlled experiments using purposefully design stimuli [3]. In these cases, researchers use pre-determined, static, and isolated-object images that are flashed on the screen in image acquisition synchronized paradigms [4].

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