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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Predicting affective valence using cortical hemodynamic signals

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Trambaiolli, Lucas R. [1] ; Biazoli, Jr., Claudinei E. [1] ; Cravo, Andre M. [1] ; Sato, Joao R. [1]
Total Authors: 4
[1] Fed Univ ABC UFABC, CMCC, Rua Santa Adelia 166, BR-09210170 Santo Andre, SP - Brazil
Total Affiliations: 1
Document type: Journal article
Source: SCIENTIFIC REPORTS; v. 8, MAR 29 2018.
Web of Science Citations: 3

Ascribing affective valence to stimuli or mental states is a fundamental property of human experiences. Recent neuroimaging meta-analyses favor the workspace hypothesis for the neural underpinning of valence, in which both positive and negative values are encoded by overlapping networks but are associated with different patterns of activity. In the present study, we further explored this framework using functional near-infrared spectroscopy (fNIRS) in conjunction with multivariate analyses. We monitored the fronto-temporal and occipital hemodynamic activity of 49 participants during the viewing of affective images (passive condition) and during the imagination of affectively loaded states (active condition). Multivariate decoding techniques were applied to determine whether affective valence is encoded in the cortical areas assessed. Prediction accuracies of 89.90 +/- 13.84% and 85.41 +/- 14.43% were observed for positive versus neutral comparisons, and of 91.53 +/- 13.04% and 81.54 +/- 16.05% for negative versus neutral comparisons (passive/active conditions, respectively). Our results are consistent with previous studies using other neuroimaging modalities that support the affective workspace hypothesis and the notion that valence is instantiated by the same network, regardless of whether the affective experience is passively or actively elicited. (AU)

FAPESP's process: 15/17406-5 - Emotional decoding and neuromodulation of the prefrontal cortex with NIRS-EEG
Grantee:Lucas Remoaldo Trambaiolli
Support type: Scholarships in Brazil - Doctorate