Opposing influences of affective state valence on visual cortical encoding.
Positive and negative emotional states are thought to have originated from fundamentally opposing approach and avoidance behaviors. Furthermore, affective valence has been hypothesized to exert opposing biases in cognitive control. Here we examined with functional magnetic resonance imaging whether the opposing influences of positive and negative states extend to perceptual encoding in the visual cortices. Based on prior behavioral research, we hypothesized that positive states would broaden and negative states would narrow visual field of view (FOV). Positive, neutral, and negative states were induced on alternating blocks. To index FOV, observers then viewed brief presentations (300 ms) of face/place concentric center/surround stimuli on interleaved blocks. Central faces were attended, rendering the place surrounds unattended. As face and place information was presented at different visual eccentricities, our physiological metric of FOV was a valence-dependent modulation of place processing in the parahippocampal place area (PPA). Consistent with our hypotheses, positive affective states increased and negative states decreased PPA response to novel places as well as adaptation to repeated places. Individual differences in self-reported positive and negative affect correlated inversely with PPA encoding of peripheral places, as well as with activation in the mesocortical prefrontal cortex and amygdala. Psychophysiological interaction analyses further demonstrated that valence-dependent responses in the PPA arose from opponent coupling with extrafoveal regions of the primary visual cortex during positive and negative states. These findings collectively suggest that affective valence differentially biases gating of early visual inputs, fundamentally altering the scope of perceptual encoding.
Schmitz
Taylor W
TW
Department of Psychology, University of Toronto, Toronto, Ontario M5S 3G3, Canada. taylor@aclab.ca
De Rosa
Eve
E
Anderson
Adam K
AK
D000339:Affect / Q000145:classification* / Q000502:physiology*; D000704:Analysis of Variance; D001931:Brain Mapping; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D015233:Models, Statistical; D009483:Neuropsychological Tests; D010100:Oxygen / Q000097:blood; D010364:Pattern Recognition, Visual / Q000502:physiology; D010775:Photic Stimulation / Q000379:methods; D011601:Psychophysics; D011930:Reaction Time / Q000502:physiology; D013997:Time Factors; D014793:Visual Cortex / Q000098:blood supply / Q000502:physiology*; D055815:Young Adult
D010100:Oxygen