Key result
fNIRS decoding of cortical hemodynamic signals predicts affective valence with ~90% accuracy during active elicitation.
Cross-Sectional (n=49)
No
Absolute Event Rate: 89.8% vs 50%
p-value: p=<0.001
Functional near-infrared spectroscopy combined with multivariate analyses can accurately predict affective valence, supporting the affective workspace hypothesis.
Supports affective workspace hypothesis; larger validation trials needed before clinical translation of fNIRS decoding.
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.
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Trambaiolli et al. (2018) conducted a cross-sectional in Healthy volunteers (n=49). Multivariate decoding of fNIRS signals vs. Chance level (50%) was evaluated on Decoding accuracy for positive versus neutral affective experiences (active elicitation) (p=<0.001). Multivariate decoding of cortical hemodynamic signals measured by fNIRS accurately predicted affective valence, achieving 89.8% accuracy for positive versus neutral experiences during active elicitation.
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