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 speechlike 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.

Disrupting inferior frontal cortex activity alters affect decoding efficiency from clear but not from ambiguous affective speech

“…Affective voice discrimination as opposed to categorization would on the other hand depend on a different IFG subregions, namely the bilateral IFG pars opercularis (4), to which only residual TMS current could be transmitted due to the cTBS procedure and coil location in our study (see Methods). According to our results and to the literature (4,6,11,48), the right and potentially the left IFG pars triangularis (49) could therefore be highly selective to categorization, by flagging the outcome of cognitive-driven affective evaluation processes with some level of uncertainty (50,51).…”

Categorization and discrimination of human and non-human primate affective vocalizations: investigation of the frontal cortex activity through fNIRS

“…Interestingly, and perhaps, contradictorily, we initially expected more activation in IFG tri for the categorization task (unbiased choice) because of the existing literature on human affective voices (Dricu et al, 2017; Gruber et al, 2020). However, taking into account our behavioural results showing higher recognition performances in discrimination compared to categorization, more activity in IFG tri appears to be required to enable participants to perform better during the discrimination of primate vocalizations.…”

“…Second, the involvement of IFG has often been demonstrated in the literature for the recognition of emotional voices contrasted with neutral ones (e.g. Frühholz et al, 2012; Frühholz & Grandjean, 2013; Gruber et al, 2020; Sander et al, 2005; Zhang et al, 2018). Yet, in our study, we did not include such stimuli, comparing cerebral activations across the affective contents.…”

“…For instance, Zhang and colleagues reported a strong involvement of the human PFC and IFG during the discrimination of affective voices (Zhang et al, 2018). Similarly, Gruber and colleagues highlighted the modulation of IFG activity depending on the categorization or the discrimination of affects in auditory stimuli (Gruber et al, 2020). Hence, more investigations on PFC and IFG activations are necessary to improve our knowledge of affective decoding.…”

Human-Centric Emotion Estimation Based on Correlation Maximization Considering Changes With Time in Visual Attention and Brain Activity

“…Moreover, fNIRS equipment has few behavioral or physical restrictions on users [36]. Therefore, several studies focus on the relationship between human emotions and fNIRS signals [37]- [39], and we use fNIRS signals with eye gaze data in this study. There have been some studies in which both fNIRS and eye gaze data were used [40]- [42].…”