Decoding brain networks through graph measures in infancy: The case of emotional faces.

• In Event: Poster Session 08
  In Poster Session: PS 08 Topic - Cognitive Processes

Abstract

The current study aimed to disambiguate differential sets of brain activity in response to static and dynamic facial expressions of emotion in 7-months-old infants, applying graph theoretical measures to assess the topological structure of infants’ related brain functional networks.
We combined a decoding technique (i.e., the Principal Component Regression) to graph metrics computation: we decomposed infants’ EEG data and applied the Principal Component Regression to evaluate the components specific to the static vs dynamic presentation modalities of facial expressions of emotion in each EEG frequency band. Nodes’ strength was computed to probe functional networks backbones.
Results of the PCR showed a significant association between experimental condition and PCA strength components in the alpha band, χ2(4) = 24.14, p < .05), in the beta band, χ2(6) = 24.1, p < .05), in the delta band, χ2(4) = 21.6, p < .05) and in the theta band, χ2(5) = 20.56, p < .05).
Strength results in the alpha band is clearly indicate a more ventral components’ topography during static emotional stimuli presentation and a more dorsal one during dynamic emotional stimuli.
Regarding beta band results, strength components indexing activity in both the static and dynamic conditions implicate mostly the same topological areas, indexing an invariance of face processing in infants’ brains, going beyond presentation modalities. Beside invariances, we also observed a more ventral activity in response to static emotional faces and a more dorsal activity in response to dynamic emotional faces in the beta band.
Regarding results in the delta band, the topological structure of strength components underlying stimuli processing is mainly the same, with the important difference of a more frontal configuration for dynamic stimuli possibly indexing activity in reward system’s areas, elicited by dynamic facial expression (Knyazev, 2012). This hypothesized activity may index an increased perceived salience of dynamic faces, due to their more ecologically valid portrayal of emotions.
Regarding the theta band, the underlying strength structure appears to be specifically tuned toward dynamic expressions of emotion, thus indexing the increased social salience that these stimuli entail for infants (Michel et al., 2015).
Taken together, our results show that infants’ brain activity contains enough information to differentiate between the processing of static and dynamic facial expressions of emotions (Bae & Luck, 2018). Moreover our results are coherent with previous findings pointing toward differential patterns of functional network topologies across frequency bands in infants (Tóth et al., 2017), with invariances across frequency bands pointing toward an already present rudimental network structure tuned to face processing at 7-months of age.
Lastly, our results affirm the fruitfulness of the application of graph measures in developmental samples, due to their flexibility and the wealth of information they provide over infants’ networks functional organization.

Authors

• Silvia Polver, Università degli Studi di Milano-Bicocca (UNIMIB)
  Presenting Author

• Ermanno Quadrelli, University of Milan-Bicocca
  Non-Presenting Author

• Chiara Turati, Univesrità di Milano-Bicocca
  Non-Presenting Author

• Hermann Bulf, University of Milano-Bicocca
  Non-Presenting Author