Categorical Biases in Human Occipitoparietal Cortex

Abstract

Categorization allows organisms to generalize existing knowledge to novel stimuli and to discriminate between physically similar yet conceptually different stimuli. Humans, nonhuman primates, and rodents can readily learn arbitrary categories defined by low-level visual features, and learning distorts perceptual sensitivity for category-defining features such that differences between physically similar yet categorically distinct exemplars are enhanced, whereas differences between equally similar but categorically identical stimuli are reduced. We report a possible basis for these distortions in human occipitoparietal cortex. In three experiments, we used an inverted encoding model to recover population-level representations of stimuli from multivoxel and multielectrode patterns of human brain activity while human participants (both sexes) classified continuous stimulus sets into discrete groups. In each experiment, reconstructed representations of to-be-categorized stimuli were systematically biased toward the center of the appropriate category. These biases were largest for exemplars near a category boundary, predicted participants' overt category judgments, emerged shortly after stimulus onset, and could not be explained by mechanisms of response selection or motor preparation. Collectively, our findings suggest that category learning can influence processing at the earliest stages of cortical visual processing.

Delay-period activity in frontal, parietal, and occipital cortex tracks noise and biases in visual working memory

“…In comparison to the IPS and PFC, although the effects were generally weaker, delay-period activity in the LO showed an opposite trend, in that it was more sensitive to load-related changes in drift to particular stimulus values (i.e., to attractor strength) than it was to loadrelated changes in diffusion. This result is consistent with other demonstrations of bias in visual cognition, such as the influence of prior expectation on the representation of motion [22] and the influence of learning on representations of category boundaries in visual cortex [23]. Because our current study did not involve a learning intervention and did not focus on stimulus-specific representations, our results suggest that what we already know about the neural bases of the biasing effects of recent experience on visual cognition may extend to more trait-like "preexisting" attractor landscapes that have been sculpted through a life-time of experience with the visual world.…”

Belief states and categorical-choice biases determine reward-based learning under perceptual uncertainty

“…Candidate areas involved in perceptual uncertainty computations from the perceptual decision-making literature are sensory, parietal, and frontal cortex (Kiani and Shadlen, 2009;Mulder et al, 2012;Summerfield and Koechlin, 2010;Van Bergen and Jehee, 2017;Van Bergen et al, 2015). There is some evidence to suggest that categorical biases emerging from the choice history are already reflected in early visual areas (Ester et al, 2020;Nienborg and Cumming, 2009). Moreover, Peters et al (2017) showed that meta-cognitive confidence representations of choice-congruent evidence, which, as argued above, could be related to the categorical-choice bias, are distributed across multiple brain areas.…”

Abstract Neural Representations of Category Membership beyond Information Coding Stimulus or Response

“…Previous studies have found strong stimulus coding and category-related modulation stimulus representations during concept or perceptual learning (Ester, Sprague, & Serences, 2020;Braunlich & Love, 2019;Kuai, Levi, & Kourtzi, 2013;Mack et al, 2013;Zhang & Kourtzi, 2010;Freedman & Assad, 2006;Kourtzi, Betts, Sarkheil, & Welchman, 2005). For example, concept learning studies that used object stimuli have shown strong modulation of sensory signals in the lateral occipital cortex after learning (Braunlich & Love, 2019;Kuai et al, 2013;Mack et al, 2013).…”