A neurophysiological signature of dynamic emotion recognition associated with social communication skills and cortical gamma-aminobutyric acid levels in children

Daniela Sousa; Ana Ferreira; Diana Rodrigues; Helena Catarina Pereira; Joana Amaral; Joana Crisostomo; Marco Simoes; Mário Ribeiro; Marta Teixeira; Miguel Castelo-Branco

doi:10.3389/fnins.2023.1295608

A neurophysiological signature of dynamic emotion recognition associated with social communication skills and cortical gamma-aminobutyric acid levels in children

Front Neurosci. 2023 Dec 18:17:1295608. doi: 10.3389/fnins.2023.1295608. eCollection 2023.

Authors

Daniela Sousa^{1

2

3}, Ana Ferreira^{1

2

3}, Diana Rodrigues^{1

2}, Helena Catarina Pereira^{1

2

3}, Joana Amaral^{1

2

3}, Joana Crisostomo^{1

2

3}, Marco Simoes^{1

2

3

4}, Mário Ribeiro^{1

2}, Marta Teixeira^{1

2}, Miguel Castelo-Branco^{1

2

3

5}

Affiliations

¹ Coimbra Institute for Biomedical Imaging and Translational Research CIBIT, University of Coimbra, Coimbra, Portugal.
² Institute for Nuclear Sciences Applied to Health ICNAS, University of Coimbra, Coimbra, Portugal.
³ Faculty of Medicine, University of Coimbra, Coimbra, Portugal.
⁴ Centre for Informatics and Systems, University of Coimbra, Coimbra, Portugal.
⁵ Department of Psychology, University of Maastricht, Maastricht, Netherlands.

Abstract

Introduction: Emotion recognition is a core feature of social perception. In particular, perception of dynamic facial emotional expressions is a major feature of the third visual pathway. However, the classical N170 visual evoked signal does not provide a pure correlate of such processing. Indeed, independent component analysis has demonstrated that the N170 component is already active at the time of the P100, and is therefore distorted by early components. Here we implemented, a dynamic face emotional paradigm to isolate a more pure face expression selective N170. We searched for a neural correlate of perception of dynamic facial emotional expressions, by starting with a face baseline from which a facial expression evolved. This allowed for a specific facial expression contrast signal which we aimed to relate with social communication abilities and cortical gamma-aminobutyric acid (GABA) levels.

Methods: We recorded event-related potentials (ERPs) and Magnetic Resonance (MRS) measures in 35 typically developing (TD) children, (10-16 years) sex-matched, during emotion recognition of an avatar morphing/unmorphing from neutral to happy/sad expressions. This task allowed for the elimination of the contribution low-level visual components, in particular the P100, by morphing baseline isoluminant neutral faces into specific expressions, isolating dynamic emotion recognition. Therefore, it was possible to isolate a dynamic face sensitive N170 devoid of interactions with earlier components.

Results: We found delayed N170 and P300, with a hysteresis type of dependence on stimulus trajectory (morphing/unmorphing), with hemispheric lateralization. The delayed N170 is generated by an extrastriate source, which can be related to the third visual pathway specialized in biological motion processing. GABA levels in visual cortex were related with N170 amplitude and latency and predictive of worse social communication performance (SCQ scores). N170 latencies reflected delayed processing speed of emotional expressions and related to worse social communication scores.

Discussion: In sum, we found a specific N170 electrophysiological signature of dynamic face processing related to social communication abilities and cortical GABA levels. These findings have potential clinical significance supporting the hypothesis of a spectrum of social communication abilities and the identification of a specific face-expression sensitive N170 which can potentially be used in the development of diagnostic and intervention tools.

Keywords: GABA; dynamic emotional expressions; event-related potentials; social cognition; social communication; typically developing children.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by FCT – Portuguese national funding agency for science, research, and technology by the FCT/UIDP&B/4950 and Grants: PAC MEDPERSYST, POCI-01-0145-FEDER-016428, BIGDATIMAGE, CENTRO-01-0145-FEDER-000016 financed by Centro 2020 FEDER, FCT/DSAIPA/DS/0041/2020, FCT/PTDC/PSI-GER/1326/2020 and STIPED European Union’s Horizon 2020 research and innovation program under grant agreement n° 731827. JA, JC, HP and MR were financed by European Union’s Horizon 2020 research and innovation program under grant agreement n° 731827 (STIPED). DS (Ref. 2021.05559.BD) and AF holds a PhD Grant (Ref. 2020.08597.BD), co-funded by FCT, the European Social Fund (FSE) Program and the Centro 2020.