4.7 Article

Modulation of α Power and Functional Connectivity during Facial Affect Recognition

Journal

JOURNAL OF NEUROSCIENCE
Volume 33, Issue 14, Pages 6018-6026

Publisher

SOC NEUROSCIENCE
DOI: 10.1523/JNEUROSCI.2763-12.2013

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Funding

  1. Deutsche Forschungsgemeinschaft [Ro 805/14-2]

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Research has linked oscillatory activity in the alpha frequency range, particularly in sensorimotor cortex, to processing of social actions. Results further suggest involvement of sensorimotor alpha in the processing of facial expressions, including affect. The sensorimotor face area may be critical for perception of emotional face expression, but the role it plays is unclear. The present study sought to clarify how oscillatory brain activity contributes to or reflects processing of facial affect during changes in facial expression. Neuromagnetic oscillatory brain activity was monitored while 30 volunteers viewed videos of human faces that changed their expression from neutral to fearful, neutral, or happy expressions. Induced changes in alpha power during the different morphs, source analysis, and graph-theoretic metrics served to identify the role of alpha power modulation and cross-regional coupling by means of phase synchrony during facial affect recognition. Changes from neutral to emotional faces were associated with a 10 - 15 Hz power increase localized in bilateral sensorimotor areas, together with occipital power decrease, preceding reported emotional expression recognition. Graph-theoretic analysis revealed that, in the course of a trial, the balance between sensorimotor power increase and decrease was associated with decreased and increased transregional connectedness as measured by node degree. Results suggest that modulations in alpha power facilitate early registration, with sensorimotor cortex including the sensorimotor face area largely functionally decoupled and thereby protected from additional, disruptive input and that subsequent alpha power decrease together with increased connectedness of sensorimotor areas facilitates successful facial affect recognition.

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