Adaptation to stimulus orientation in mouse primary visual cortex

A power law describes the magnitude of adaptation in neural populations of primary visual cortex

How do neural populations adapt to the time-varying statistics of sensory input? We used two-photon imaging to measure the activity of neurons in mouse primary visual cortex adapted to different sensory environments, each defined by a distinct probability distribution over a stimulus set. We find that two properties of adaptation capture how the population response to a given stimulus, viewed as a vector, changes across environments. First, the ratio between the response magnitudes is a power law of the ratio between the stimulus probabilities. Second, the response direction to a stimulus is largely invariant. These rules could be used to predict how cortical populations adapt to novel, sensory environments. Finally, we show how the power law enables the cortex to preferentially signal unexpected stimuli and to adjust the metabolic cost of its sensory representation to the entropy of the environment.

Repeated passive visual experience modulates spontaneous and non-familiar stimuli-evoked neural activity

Familiarity creates subjective memory of repeated innocuous experiences, reduces neural and behavioral responsiveness to those experiences, and enhances novelty detection. The neural correlates of the internal model of familiarity and the cellular mechanisms of enhanced novelty detection following multi-day repeated passive experience remain elusive. Using the mouse visual cortex as a model system, we test how the repeated passive experience of a 45° orientation-grating stimulus for multiple days alters spontaneous and non-familiar stimuli evoked neural activity in neurons tuned to familiar or non-familiar stimuli. We found that familiarity elicits stimulus competition such that stimulus selectivity reduces in neurons tuned to the familiar 45° stimulus; it increases in those tuned to the 90° stimulus but does not affect neurons tuned to the orthogonal 135° stimulus. Furthermore, neurons tuned to orientations 45° apart from the familiar stimulus dominate local functional connectivity. Interestingly, responsiveness to natural images, which consists of familiar and non-familiar orientations, increases subtly in neurons that exhibit stimulus competition. We also show the similarity between familiar grating stimulus-evoked and spontaneous activity increases, indicative of an internal model of altered experience.

Repeated passive visual experience modulates spontaneous and non-familiar stimulievoked neural activity

Familiarity creates subjective memory of repeated innocuous experiences, reduces neural and behavioral responsiveness to those experiences, and enhances novelty detection. The neural correlates of the internal model of familiarity and the cellular mechanisms of enhanced novelty detection following multi-day repeated passive experience remain elusive. Using the mouse visual cortex as a model system, we test how the repeated passive experience of a 45° orientation-grating stimulus for multiple days alters spontaneous and non-familiar stimuli evoked neural activity in neurons tuned to familiar or non-familiar stimuli. We found that familiarity elicits stimulus competition such that stimulus selectivity reduces in neurons tuned to the familiar 45° stimulus; it increases in those tuned to the 90° stimulus but does not affect neurons tuned to the orthogonal 135° stimulus. Furthermore, neurons tuned to orientations 45° apart from the familiar stimulus dominate local functional connectivity. Interestingly, responsiveness to natural images, which consists of familiar and non-familiar orientations, increases subtly in neurons that exhibit stimulus competition. We also show the similarity between familiar grating stimulus-evoked and spontaneous activity increases, indicative of an internal model of altered experience.

A power law of cortical adaptation

How do neural populations adapt to the time-varying statistics of sensory input? To investigate, we measured the activity of neurons in primary visual cortex adapted to different environments, each associated with a distinct probability distribution over a stimulus set. Within each environment, a stimulus sequence was generated by independently sampling form its distribution. We find that two properties of adaptation capture how the population responses to a given stimulus, viewed as vectors, are linked across environments. First, the ratio between the response magnitudes is a power law of the ratio between the stimulus probabilities. Second, the response directions are largely invariant. These rules can be used to predict how cortical populations adapt to novel, sensory environments. Finally, we show how the power law enables the cortex to preferentially signal unexpected stimuli and to adjust the metabolic cost of its sensory representation to the entropy of the environment.

Excitation-inhibition imbalance disrupts visual familiarity in amyloid and non-pathology conditions

Neuronal hyperactivity induces memory deficits in Alzheimer's disease. However, how hyperactivity disrupts memory is unclear. Using in vivo synaptic imaging in the mouse visual cortex, we show that structural excitatory-inhibitory synapse imbalance in the apical dendrites favors hyperactivity in early amyloidosis. Consistent with this, natural images elicit neuronal hyperactivity in these mice. Compensatory changes that maintain activity homeostasis disrupt functional connectivity and increase population sparseness such that a small fraction of neurons dominates population activity. These properties reduce the selectivity of neural response to natural images and render visual recognition memory vulnerable to interference. Deprivation of non-specific visual experiences improves the neural representation and behavioral expression of visual familiarity. In contrast, in non-pathological conditions, deprivation of non-specific visual experiences induces disinhibition, increases excitability, and disrupts visual familiarity. We show that disrupted familiarity occurs when the fraction of high-responsive neurons and the persistence of neural representation of a memory-associated stimulus are not constrained.

The effects of distractors on brightness perception based on a spiking network

Visual perception can be modified by the surrounding context. Particularly, experimental observations have demonstrated that visual perception and primary visual cortical responses could be modified by properties of surrounding distractors. However, the underlying mechanism remains unclear. To simulate primary visual cortical activities in this paper, we design a k-winner-take-all (k-WTA) spiking network whose responses are generated through probabilistic inference. In simulations, images with the same target and various surrounding distractors perform as stimuli. Distractors are designed with multiple varying properties, including the luminance, the sizes and the distances to the target. Simulations for each varying property are performed with other properties fixed. Each property could modify second-layer neural responses and interactions in the network. To the same target in the designed images, the modified network responses could simulate distinguishing brightness perception consistent with experimental observations. Our model provides a possible explanation of how the surrounding distractors modify primary visual cortical responses to induce various brightness perception of the given target.

Top-down influence affects the response adaptation of V1 neurons in cats

The visual system lowers its perceptual sensitivity to a prolonged presentation of the same visual signal. This brain plasticity, called visual adaptation, is generally attributed to the response adaptation of neurons in the visual cortex. Although well-studied in the neurons of the primary visual cortex (V1), the contribution of high-level visual cortical regions to the response adaptation of V1 neurons is unclear. In the present study, we measured the response adaptation strength of V1 neurons before and after the top-down influence of the area 21a (A21a), a higher-order visual cortex homologous to the primate V4 area, was modulated with a noninvasive tool of transcranial direct current stimulation (tDCS). Our results showed that the response adaptation of V1 neurons enhanced significantly after applying anode (a-) tDCS in A21a when compared with that before a-tDCS, whereas the response adaptation of V1 neurons weakened after cathode (c-) tDCS relative to before c-tDCS in A21a. By contrast, sham (s-) tDCS in A21a had no significant impact on the response adaptation of V1 neurons. Further analysis indicated that a-tDCS in A21a significantly increased both the initial response (IR) of V1 neurons to the first several (five) trails of visual stimulation and the plateau response (PR) to the prolonged visual stimulation; the increase in PR was lower than in IR, which caused an enhancement in response adaptation. Conversely, c-tDCS significantly decreased both IR and PR of V1 neurons; the reduction in PR was smaller than in IR, which resulted in a weakness in response adaptation. Furthermore, the tDCS-induced changes of V1 neurons in response and response adaptation could recover after tDCS effect vanished, but did not occur after the neuronal activity in A21a was silenced by electrolytic lesions. These results suggest that the top-down influence of A21a may alter the response adaptation of V1 neurons through activation of local inhibitory circuitry, which enhances network inhibition in the V1 area upon an increased top-down input, weakens inhibition upon a decreased top-down input, and thus maintains homeostasis of V1 neurons in response to the long-presenting visual signals.

Magnitude, time course, and specificity of rapid adaptation across mouse visual areas

Adaptation is a ubiquitous feature of sensory processing whereby recent experience shapes future responses. The mouse primary visual cortex (V1) is particularly sensitive to recent experience, where a brief stimulus can suppress subsequent responses for seconds. This rapid adaptation profoundly impacts perception, suggesting that its effects are propagated along the visual hierarchy. To understand how rapid adaptation influences sensory processing, we measured its effects at key nodes in the visual system: in V1, three higher visual areas (HVAs: lateromedial, anterolateral, and posteromedial), and the superior colliculus (SC) in awake mice of both sexes using single-unit recordings. Consistent with the feed-forward propagation of adaptation along the visual hierarchy, we find that neurons in layer 4 adapt less strongly than those in other layers of V1. Furthermore, neurons in the HVAs adapt more strongly, and recover more slowly, than those in V1. The magnitude and time course of adaptation was comparable in each of the HVAs and in the SC, suggesting that adaptation may not linearly accumulate along the feed-forward visual processing hierarchy. Despite the increase in adaptation in the HVAs compared with V1, the effects were similarly orientation specific across all areas. These data reveal that adaptation profoundly shapes cortical processing, with increasing impact at higher levels in the cortical hierarchy, and also strongly influencing computations in the SC. Thus, we find robust, brain-wide effects of rapid adaptation on sensory processing.NEW & NOTEWORTHY Rapid adaptation dynamically alters sensory signals to account for recent experience. To understand how adaptation affects sensory processing and perception, we must determine how it impacts the diverse set of cortical and subcortical areas along the hierarchy of the mouse visual system. We find that rapid adaptation strongly impacts neurons in primary visual cortex, the higher visual areas, and the colliculus, consistent with its profound effects on behavior.

Motion Discrimination and the Motion Aftereffect in Mouse Vision

Prolonged exposure to motion in one direction often leads to the illusion of motion in the opposite direction for stationary objects. This motion aftereffect likely arises across several visual areas from adaptive changes in the balance of activity and competitive interactions. We examined whether or not the mouse was susceptible to this same illusion to determine whether it would be a suitable model for learning about the neural representation of the motion aftereffect. Under a classical conditioning paradigm, mice learned to lick when presented with motion in one direction and not the opposite direction. When the mice were adapted to motion preceding this test, their lick behavior for zero coherence motion was biased for motion in the opposite direction of the adapting stimulus. Overall, lick count versus motion coherence shifted in the opposite direction of the adapting stimulus. This suggests that although the mouse has a simpler visual system compared with primates, it still is subject to the motion aftereffect and may elucidate the underlying circuitry.