Feature selectivity explains mismatch signals in mouse visual cortex

Abstract

Sensory experience is often dependent on one's own actions, including self-motion. Theories of predictive coding postulate that actions are regulated by calculating prediction error, which is the difference between sensory experience and expectation based on self-generated actions. Signals consistent with prediction error have been reported in mouse visual cortex (V1) when visual flow coupled to running is unexpectedly perturbed. Here, we show that such signals can be elicited by visual stimuli uncoupled with the animal's running. We recorded the activity of mouse V1 neurons while presenting drifting gratings that unexpectedly stopped. We found strong responses to visual perturbations, which were enhanced during running. If these perturbation responses are signals about sensorimotor mismatch, they should be largest for front-to-back visual flow expected from the animals' running. Responses, however, did not show a bias for front-to-back visual flow. Instead, perturbation responses were strongest in the preferred orientation of individual neurons and perturbation responsive neurons were more likely to prefer slow visual speeds. Our results therefore indicate that prediction error signals can be explained by the convergence of known motor and sensory signals in visual cortex, providing a purely sensory and motor explanation for purported mismatch signals.

Not so spontaneous: Multi-dimensional representations of behaviors and context in sensory areas

“…For example, after mice hear the same tone during running for several days, auditory cortical neurons have suppressed responses to the specific running-related tone during running, suggesting the presence of a predictive processing circuit (Schneider et al, 2018). Note that evidence for predictive processing has to be carefully analyzed as both stimulus and motor changes must be controlled for experimentally (see e.g., Muzzu and Saleem, 2021). Also, given the widespread nature of these behavioral representations across brain areas, there are likely additional roles for these signals beyond predictive processing, which we will explore more in the section possible functional roles for spontaneous activity.…”

Spatial modulation of dark versus bright stimulus responses in the mouse visual system

“…Similar spatial biases were evident in ON/OFF responses elicited by sparse black or white squares. In an independent set of experiments that projected black or white squares (10 , 0.1s duration) onto a demispherical dome, 14 binocular and monocular V1 populations individually did not differ in ON versus OFF responses (binocular: 69% of log ratios < 0; p = 0.27; monocular: 61% > 0; p = 0.41), but binocular V1 neurons showed significantly greater OFF responsiveness than in monocular V1 (Figure 3B; n = 36; p = 0.015, Kolmogorov-Smirnov test). These findings reveal that neurons in binocular V1 show greater bias toward OFF responsiveness in spikes than those in monocular V1, but with considerable response heterogeneity within each population.…”