<p><a></a><a>The visual system is capable of interpreting immense sensory complexity, allowing us to quickly identify behaviorally relevant stimuli in the environment. It performs this task with a hierarchical organization that works to detect, relay, and integrate visual stimulus features into an interpretable form. To understand the complexities of this system, visual neuroscientists have benefited from the many advantages of using mice as visual models. Despite their poor visual acuity, these animals possess surprisingly complex visual systems, and have been instrumental in understanding how visual features are processed in the primary visual cortex (V1). However, a growing body of literature has shown that primary sensory areas like V1 are capable of more than basic feature detection, but can express neural activity patterns related to learning, memory, categorization, and prediction. </a></p> <p>Visual experience fundamentally changes the encoding and perception of visual stimuli at many scales, and allows us to become familiar with environmental cues. However, the neural processes that govern visual familiarity are poorly understood. By exposing awake mice to repetitively presented visual stimuli over several days, we observed the emergence of low frequency oscillations in the primary visual cortex (V1). The oscillations emerged in population level responses known as visually evoked potentials (VEPs), as well as single-unit responses, and were not observed before the perceptual experience had occurred. They were also not evoked by novel visual stimuli, suggesting that they represent a new form of visual familiarity in the form of low frequency oscillations. The oscillations also required the muscarinic acetylcholine receptors (mAChRs) for their induction and expression, highlighting the importance of the cholinergic system in this learning and memory-based phenomenon. Ongoing visually evoked oscillations were also shown to increase the VEP amplitude of incoming visual stimuli if the stimuli were presented at the high excitability phase of the oscillations, demonstrating how neural activity with unique temporal dynamics can be used to influence visual processing.</p> <p>Given the necessity of perceptual experience for the strong expression of these oscillations and their dependence on the cholinergic system, it was clear we had discovered a phenomenon grounded in visual learning or memory. To further validate this, we characterized this response in a mouse model of Fragile X syndrome (FX), the most common inherited form of autism and a condition with known visual perceptual learning deficits. Using a multifaceted experimental approach, a number of neurophysiological differences were found in the oscillations displayed in FX mice. Extracellular recordings revealed shorter durations and lower power oscillatory activity in FX mice. Furthermore, we found that the frequency of peak oscillatory activity was significantly decreased in FX mice, demonstrating a unique temporal neural impairment not previously reported in FX. In collaboration with Dr. Christopher J. Quinn at Purdue, we performed functional connectivity analysis on the extracellularly recorded spikes from WT and FX mice. This analysis revealed significant impairments in functional connections from multiple layers in FX mice after the perceptual experience; some of which were validated by another graduate student (Qiuyu Wu) using Channelrhodopsin-2 assisted circuit mapping (CRACM). Together, these results shed new light on how visual stimulus familiarity is differentially encoded in FX via persistent oscillations, and allowed us to identify impairments in cross layer connectivity that may underlie these differences. </p> <p>Finally, we asked whether these oscillations are observable in other brain areas or are intrinsic to V1. Furthermore, we sought to determine if the oscillating unit populations in V1 possess uniform firing dynamics, or contribute differentially to the population level response. By performing paired recordings, we did not find prominent oscillatory activity in two visual thalamic nuclei (dLGN and LP) or a nonvisual area (RSC) connected to V1, suggesting the oscillations may not propagate with similar dynamics via cortico-thalamic connections or retrosplenial connections, <a>but may either be uniquely distributed across the visual hierarchy or predominantly</a> restricted to V1. Using K-means clustering on a large population of oscillating units in V1, we found unique temporal profiles of visually evoked responses, demonstrating distinct contributions of different unit sub-populations to the oscillation response dynamics.</p>

<div>The visual system is responsible for processing visual input, inferring its environmental causes, and assessing its behavioral significance that eventually relates to visual perception and guides animal behavior. There is emerging evidence that visual perception does not simply mirror the outside world but is heavily influenced by contextual information. Specifically, context might refer to the sensory, cognitive, and/or behavioral cues that help to assess the behavioral relevance of image features. One of the most famous examples of such behavior is visual or optical illusions. These illusions contain sensory cues that induce a subjective percept that is not aligned with the physical nature of the stimulation, which, in turn, suggests that a visual system is not a passive filter of the outside world but rather an active inference machine.</div><div>Such robust behavior of the visual system is achieved through intricate neural computations spanning several brain regions that allow dynamic visual processing. Despite the numerous attempts to gain insight into those computations, it has been challenging to decipher the circuit-level implementation of contextual processing due to technological limitations. These questions are of great importance not only for basic research purposes but also for gaining deeper insight into neurodevelopmental disorders that are characterized by altered sensory experiences. Recent advances in genetic engineering and neurotechnology made the mouse an attractive model to study the visual system and enabled other researchers and us to gain unprecedented cellular and circuit-level insights into neural mechanisms underlying contextual processing.</div><div>We first investigated how familiarity modifies the neural representation of stimuli in the mouse primary visual cortex (V1). Using silicon probe recordings and pupillometry, we probed neural activity in naive mice and after animals were exposed to the same stimulus over the course of several days. We have discovered that familiar stimuli evoke low-frequency oscillations in V1. Importantly, those oscillations were specific to the spatial frequency content of the familiar stimulus. To further validate our findings, we investigated how this novel form of visual learning is represented in serotonin-transporter (SERT) deficient mice. These transgenic animals have been previously found to have various neurophysiological alterations. We found that SERT-deficient animals showed longer oscillatory spiking activity and impaired cortical tuning after visual learning. Taken together, we discovered a novel phenomenon of familiarity-evoked oscillations in V1 and utilized it to reveal altered perceptual learning in SERT-deficient mice.</div><div>16</div><div>Next, we investigated how spatial context influences sensory processing. Visual illusions provide a great opportunity to investigate spatial contextual modulation in early visual areas. Leveraging behavioral training, high-density silicon probe recordings, and optogenetics, we provided evidence for an interplay of feedforward and feedback pathways during illusory processing in V1. We first designed an operant behavioral task to investigate illusory perception in mice. Kanizsa illusory contours paradigm was then adapted from primate studies to mouse V1 to elucidate neural correlates of illusory responses in V1. These experiments provided behavioral and neurophysiological evidence for illusory perception in mice. Using optogenetics, we then showed that suppression of the lateromedial area inhibits illusory responses in mouse V1. Taken together, we demonstrated illusory responses in mice and their dependence on the top-down feedback from higher-order visual areas.</div><div>Finally, we investigated how temporal context modulates neural responses by combining silicon probe recordings and a novel visual oddball paradigm that utilizes spatial frequency filtered stimuli. Our work extended prior oddball studies by investigating how adaptation and novelty processing depends on the tuning properties of neurons and their laminar position. Furthermore, given that reduced adaptation and sensory hypersensitivity are one of the hallmarks of altered sensory experiences in autism, we investigated the effects of temporal context on visual processing in V1 of a mouse model of fragile X syndrome (FX), a leading monogenetic cause of autism. We first showed that adaptation was modulated by tuning properties of neurons in both genotypes, however, it was more confined to neurons preferring the adapted feature in FX mice. Oddball responses, on the other hand, were modulated by the laminar position of the neurons in WT with the strongest novelty responses in superficial layers, however, they were uniformly distributed across the cortical column in FX animals. Lastly, we observed differential processing of omission responses in FX vs. WT mice. Overall, our findings suggest that reduced adaptation and increased oddball processing might contribute to altered perceptual experiences in FX and autism.</div>