Neuroscience Special Seminar
A "predictive coding" hypothesis proposes that the brain dynamically anticipates and generates predictions about upcoming stimuli to guide perception efficiently. Here, we combined functional magnetic resonance imaging (fMRI), multi-voxel pattern decoding, and an innovative time-resolved psychophysical paradigm to assess the temporal profile and spatial distributions of this prediction process.
Strikingly, we demonstrate rhythmic population activity in several task-related brain areas. Specifically, multi-voxel activity patterns in the fusiform face area (FFA) and the parahippocampal place area (PPA) show temporal fluctuations at a theta-band (~5 Hz) rhythm that accompany effects in visual object priming. These results provide novel and essential constraints to understand the neuronal dynamics of predictive coding. Moreover, these results suggest a feasible fMRI strategy to measure temporal fluctuations of multi-voxel activity patterns in the human brain, providing a critical link between fMRI measurements and neurophysiological recordings to understand fine-scale spatiotemporal dynamics of attention and consciousness.
Biography
Ming Meng, Psychological & Brain Sciences, Dartmouth College
My work investigates neural coding of complex visual information. Human face perception is of special interest to me because faces convey critical social and emotional signals and because our relatively advanced understanding of face perception mechanisms makes face perception a prime window for addressing issues related to visual coding, more broadly. My lab combines techniques drawn from the domains of psychophysics, functional brain imaging, and machine learning. Results from my lab have yielded insights regarding the nature of visual processing that contributes to our impressive face categorization abilities, the corresponding cortical substrates, and the dynamics of information flow between cortical regions.
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