Sensory uncertainty decoded from visual cortex predicts behavior.
Bayesian theories of neural coding propose that sensory uncertainty is represented by a probability distribution encoded in neural population activity, but direct neural evidence supporting this hypothesis is currently lacking. Using fMRI in combination with a generative model-based analysis, we found that probability distributions reflecting sensory uncertainty could reliably be estimated from human visual cortex and, moreover, that observers appeared to use knowledge of this uncertainty in their perceptual decisions.
Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, the Netherlands.
Ruben S
RS
van Bergen
Center for Neural Science and Department of Psychology, New York University, New York, New York, USA.
Wei Ji
WJ
Ma
Department of Psychology, Mississippi State University, Mississippi State, Mississippi, USA.
Michael S
MS
Pratte
Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, the Netherlands.
Janneke F M
JF
Jehee
D000328:Adult; D005260:Female; D005544:Forecasting; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D009949:Orientation / Q000502:physiology*; D010775:Photic Stimulation / Q000379:methods*; D035501:Uncertainty; D014793:Visual Cortex / Q000378:metabolism*; D014796:Visual Perception / Q000502:physiology*; D055815:Young Adult