Neuronal Adaptation Reveals a Suboptimal Decoding of Orientation Tuned Populations in the Mouse Visual Cortex

Abstract

Sensory information is encoded by populations of cortical neurons. Yet, it is unknown how this information is used for even simple perceptual choices such as discriminating orientation. To determine the computation underlying this perceptual choice, we took advantage of the robust visual adaptation in mouse primary visual cortex (V1). We first designed a stimulus paradigm in which we could vary the degree of neuronal adaptation measured in V1 during an orientation discrimination task. We then determined how adaptation affects task performance for mice of both sexes and tested which neuronal computations are most consistent with the behavioral results given the adapted population responses in V1. Despite increasing the reliability of the population representation of orientation among neurons, and improving the ability of a variety of optimal decoders to discriminate target from distractor orientations, adaptation increases animals' behavioral thresholds. Decoding the animals' choice from neuronal activity revealed that this unexpected effect on behavior could be explained by an overreliance of the perceptual choice circuit on target preferring neurons and a failure to appropriately discount the activity of neurons that prefer the distractor. Consistent with this all-positive computation, we find that animals' task performance is susceptible to subtle perturbations of distractor orientation and optogenetic suppression of neuronal activity in V1. This suggests that to solve this task the circuit has adopted a suboptimal and task-specific computation that discards important task-related information.

Mouse higher visual areas provide both distributed and discrete contributions to visually guided behaviors

“…Stimulus orientation is a fundamental feature that is robustly encoded in the visual system of most species, including mouse V1 and the HVAs [18,19]. While V1 is known to be required for tasks involving discrimination of stimulus orientation [30,32–34], it is not known which, if any, higher visual areas are necessary for the perception of this distributed representation.…”

“…Therefore, we trained mice to perform a go/no-go orientation discrimination task ( Figure 2A , [33,34]). In this task, the mice press a lever to initiate the trial and trigger the repeated presentation of a vertically oriented distractor (0°, 2-10 distractors, 100 ms duration, 250-750 ms inter-stimulus interval (ISI)) followed by the presentation of a target orientation (8-90° counter-clockwise difference from the distractor).…”

“…This difference between the medial and lateral HVAs begs the question of what might support the difference in the readout of information. One possibility is the difference in downstream connectivity [55]; another possibility is that the outputs of these areas are differentially integrated by their targets to drive a decision [34,60]. Understanding how each area performs its discrete role will help us understand the computations that link sensation and action.…”

Learning to Control the Brain through Adaptive Closed-Loop Patterned Stimulation

“…Therefore, to test the physiological similarity between electrically-evoked and visually-evoked responses, we tested whether electrically-evoked responses adapted to visual stimuli. Previous work has shown that the neural response to a visual stimulus is reduced when the stimulus is repeated (Jin et al, 2019). This 'adaptation' of the neural response has been used to measure the similarity of neural responses to visual stimuli (Leopold et al, 2001).…”

“…Trials were separated by 4500-5000ms intertrial interval (ITI). ISI and ITI values were chosen based on previous studies (Jin et al, 2019) . Each trial type was repeated 30 times and the trial order was random.…”