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High-frequency transcranial random noise stimulation enhances unfamiliar face matching of high resolution and pixelated faces.

Estudillo, A. J, Lee, Y. J., Álvarez-Montesinos, J. A and García-Orza, J., 2023. High-frequency transcranial random noise stimulation enhances unfamiliar face matching of high resolution and pixelated faces. Brain and Cognition, 165, 105937.

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DOI: 10.1016/j.bandc.2022.105937

Abstract

Face identification is useful for social interactions and its impairment can lead to severe social and mental problems. This ability is also remarkably important in applied settings, including eyewitness identification and ID verification. Several studies have demonstrated the potential of Transcranial Random Noise Stimulation (tRNS) to enhance different cognitive skills. However, research has produced inconclusive results about the effectiveness of tRNS to improve face identification. The present study aims to further explore the effect of tRNS on face identification using an unfamiliar face matching task. Observers firstly received either high-frequency bilateral tRNS or sham stimulation for 20 min. The stimulation targeted occipitotemporal areas, which have been previously involved in face processing. In a subsequent stage, observers were asked to perform an unfamiliar face matching task consisting of unaltered and pixelated face pictures. Compared to the sham stimulation group, the high-frequency tRNS group showed better unfamiliar face matching performance with both unaltered and pixelated faces. Our results show that a single high-frequency tRNS session might suffice to improve face identification abilities. These results have important consequences for the treatment of face recognition disorders, and potential applications in those scenarios whereby the identification of faces is primordial.

Item Type:Article
ISSN:0278-2626
Uncontrolled Keywords:Cognitive enhancement; Electrical stimulation; Face matching; Face recognition; Transcranial random noise stimulation
Group:Faculty of Science & Technology
ID Code:37917
Deposited By: Symplectic RT2
Deposited On:13 Dec 2022 10:24
Last Modified:25 Jan 2023 13:26

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