Concurrent Repetition Enhancement and Suppression Responses in Extrastriate Visual Cortex

By Vincent de Gardelle, M. Waszczuk, Tobias Egner, Christopher Summerfield. 2012

86 citations recorded by the source corpus.

Visual cortical responses are usually attenuated by repetition, a phenomenon known as repetition suppression (RS). Here, we use multivoxel pattern analyses of functional magnetic resonance imaging (fMRI) data to show that RS co-occurs with the converse phenomenon (repetition enhancement, RE) in a single cortical region. We presented human volunteers with short sequences of repeated faces and measured brain activity using fMRI. In an independently defined face-responsive extrastriate region, the response of each voxel to repetition (RS vs. RE) was consistent across scanner runs, and multivoxel patterns for both RS and RE voxels were stable. Moreover, RS and RE voxels responded to repetition with dissociable latencies and exhibited different patterns of connectivity with lower and higher visual regions. Computational simulations demonstrated that these effects must be due to differences in repetition sensitivity, and not feature selectivity. These findings establish that 2 classes of repetition responses coexist within 1 visual region and support models acknowledging this distinction, such as predictive coding models where perception requires the computation of both predictions (which are enhanced by repetition) and prediction errors (which are suppressed by repetition).

Subfields: Cognitive Neuroscience, Sensory Systems

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Citations in the corpus

Theory of Mind: A Neural Prediction Problem (2013, positive): “The result is that the classic signature of predictive coding, reduced activity to predictable stimuli, is typically observed when averaging across large samples of neurons within a region (Meyer and Olson, 2011; Egner et al., 2010; de Gardelle et al., 2013).”
Affective Value in the Predictive Mind (2017, background): “There is only very preliminary and indirect evidence to date for the separable error and prediction populations of neurons (de Gardelle et al. 2012), as postulated by PP.”