Human Discrimination and Categorization of Emotions in Voices: A Functional Near-Infrared Spectroscopy (fNIRS) Study

Abstract

Functional Near-Infrared spectroscopy (fNIRS) is a neuroimaging tool that has been recently used in a variety of cognitive paradigms. Yet, it remains unclear whether fNIRS is suitable to study complex cognitive processes such as categorization or discrimination. Previously, functional imaging has suggested a role of both inferior frontal cortices in attentive decoding and cognitive evaluation of emotional cues in human vocalizations. Here, we extended paradigms used in functional magnetic resonance imaging (fMRI) to investigate the suitability of fNIRS to study frontal lateralization of human emotion vocalization processing during explicit and implicit categorization and discrimination using mini-blocks and event-related stimuli. Participants heard speech-like but semantically meaningless pseudowords spoken in various tones and evaluated them based on their emotional or linguistic content. Behaviorally, participants were faster to discriminate than to categorize; and processed the linguistic faster than the emotional content of stimuli. Interactions between condition (emotion/word), task (discrimination/categorization) and emotion content (anger, fear, neutral) influenced accuracy and reaction time. At the brain level, we found a modulation of the Oxy-Hb changes in IFG depending on condition, task, emotion and hemisphere (right or left), highlighting the involvement of the right hemisphere to process fear stimuli, and of both hemispheres to treat anger stimuli. Our results show that fNIRS is suitable to study vocal emotion evaluation, fostering its application to complex cognitive paradigms.