Contrast and luminance adaptation alter neuronal coding and perception of stimulus orientation

Tau-Cell-Based Analog Silicon Retina With Spatio- Temporal Filtering and Contrast Gain Control

Developing precise artificial retinas is crucial because they hold the potential to restore vision, improve visual prosthetics, and enhance computer vision systems. Emulating the luminance and contrast adaption features of the retina is essential to improve visual perception and efficiency to provide an environment realistic representation to the user. In this article, we introduce an artificial retina model that leverages its potent adaptation to luminance and contrast to enhance vision sensing and information processing. The model has the ability to achieve the realization of both tonic and phasic cells in the simplest manner. We have implemented the retina model using 0.18 μm process technology and validated the accuracy of the hardware implementation through circuit simulation that closely matches the software retina model. Additionally, we have characterized a single pixel fabricated using the same 0.18 μm process. This pixel demonstrates an 87.7-% ratio of variance with the temporal software model and operates with a power consumption of 369 nW.

Adaptive coding across visual features during free-viewing and fixation conditions

Theoretical studies have long proposed that adaptation allows the brain to effectively use the limited response range of sensory neurons to encode widely varying natural inputs. However, despite this influential view, experimental studies have exclusively focused on how the neural code adapts to a range of stimuli lying along a single feature axis, such as orientation or contrast. Here, we performed electrical recordings in macaque visual cortex (area V4) to reveal significant adaptive changes in the neural code of single cells and populations across multiple feature axes. Both during free viewing and passive fixation, populations of cells improved their ability to encode image features after rapid exposure to stimuli lying on orthogonal feature axes even in the absence of initial tuning to these stimuli. These results reveal a remarkable adaptive capacity of visual cortical populations to improve network computations relevant for natural viewing despite the modularity of the functional cortical architecture.

Moving bar of light evokes vectorial spatial selectivity in the immobile rat hippocampus

Visual cortical neurons encode the position and motion direction of specific stimuli retrospectively, without any locomotion or task demand¹. The hippocampus, which is a part of the visual system, is hypothesized to require self-motion or a cognitive task to generate allocentric spatial selectivity that is scalar, abstract^2,3 and prospective^4-7. Here we measured rodent hippocampal selectivity to a moving bar of light in a body-fixed rat to bridge these seeming disparities. About 70% of dorsal CA1 neurons showed stable activity modulation as a function of the angular position of the bar, independent of behaviour and rewards. One-third of tuned cells also encoded the direction of revolution. In other experiments, neurons encoded the distance of the bar, with preference for approaching motion. Collectively, these demonstrate visually evoked vectorial selectivity (VEVS). Unlike place cells, VEVS was retrospective. Changes in the visual stimulus or its predictability did not cause remapping but only caused gradual changes. Most VEVS-tuned neurons behaved like place cells during spatial exploration and the two selectivities were correlated. Thus, VEVS could form the basic building block of hippocampal activity. When combined with self-motion, reward or multisensory stimuli⁸, it can generate the complexity of prospective representations including allocentric space⁹, time^10,11 and episodes¹².

Lateral inhibition between banks of orientation selective channels predicts shape context effects: A tilt-illusion field

The perceived shapes of almost circular paths are modified by concentrically placed context paths. These induced changes have previously been attributed to curvature masking. This paper shows that, instead, they can be explained by the impacts of local tilt illusions. First, the tilt-illusion was measured over the full range of orientation differences between short test and context lines and it was shown that the resulting function can be predicted by a model based on a vectorial population response of a bank of orientation selective channels, provided lateral inhibition between channels with the same orientation selectivity and adjacent receptive fields was postulated. Subsequently, it was demonstrated that, if the perceived shape of a test path were modified to accommodate the predicted local tilt-illusion, then this could account for previously reported changes in the detectability of a path sinusoidally modulated in radius. Further, we measured points of subjective vertical in test lines and points of subjective circularity in test paths when surrounded by modulated context paths. The tilt required to null the tilt-illusion approximated the maximum orientation difference from circular measured in the modulated paths at their point of subjective circularity, supporting the proposal that the illusory shape change is due to local changes in the position of the path arising from a response to local tilt illusions induced by the orientation context. An important corollary to this result is that such effects will generalize to all paths which are adjacent.

Rapid Cortical Adaptation and the Role of Thalamic Synchrony during Wakefulness

Rapid sensory adaptation is observed across all sensory systems, and strongly shapes sensory percepts in complex sensory environments. Yet despite its ubiquity and likely necessity for survival, the mechanistic basis is poorly understood. A wide range of primarily in vitro and anesthetized studies have demonstrated the emergence of adaptation at the level of primary sensory cortex, with only modest signatures in earlier stages of processing. The nature of rapid adaptation and how it shapes sensory representations during wakefulness, and thus the potential role in perceptual adaptation, is underexplored, as are the mechanisms that underlie this phenomenon. To address these knowledge gaps, we recorded spiking activity in primary somatosensory cortex (S1) and the upstream ventral posteromedial (VPm) thalamic nucleus in the vibrissa pathway of awake male and female mice, and quantified responses to whisker stimuli delivered in isolation and embedded in an adapting sensory background. We found that cortical sensory responses were indeed adapted by persistent sensory stimulation; putative excitatory neurons were profoundly adapted, and inhibitory neurons only modestly so. Further optogenetic manipulation experiments and network modeling suggest this largely reflects adaptive changes in synchronous thalamic firing combined with robust engagement of feedforward inhibition, with little contribution from synaptic depression. Taken together, these results suggest that cortical adaptation in the regime explored here results from changes in the timing of thalamic input, and the way in which this differentially impacts cortical excitation and feedforward inhibition, pointing to a prominent role of thalamic gating in rapid adaptation of primary sensory cortex.SIGNIFICANCE STATEMENT Rapid adaptation of sensory activity strongly shapes representations of sensory inputs across all sensory pathways over the timescale of seconds, and has profound effects on sensory perception. Despite its ubiquity and theoretical role in the efficient encoding of complex sensory environments, the mechanistic basis is poorly understood, particularly during wakefulness. In this study in the vibrissa pathway of awake mice, we show that cortical representations of sensory inputs are strongly shaped by rapid adaptation, and that this is mediated primarily by adaptive gating of the thalamic inputs to primary sensory cortex and the differential way in which these inputs engage cortical subpopulations of neurons.

Functional reallocation of sensory processing resources caused by long-term neural adaptation to altered optics

The eye’s optics are a major determinant of visual perception. Elucidating how long-term exposure to optical defects affects visual processing is key to understanding the capacity for, and limits of, sensory plasticity. Here, we show evidence of functional reallocation of sensory processing resources following long-term exposure to poor optical quality. Using adaptive optics to bypass all optical defects, we assessed visual processing in neurotypically-developed adults with healthy eyes and with keratoconus – a corneal disease causing severe optical aberrations. Under fully-corrected optical conditions, keratoconus patients showed altered contrast sensitivity, with impaired sensitivity for fine spatial details and better-than-typical sensitivity for coarse spatial details. Both gains and losses in sensitivity were more pronounced in patients experiencing poorer optical quality in their daily life and mediated by changes in signal enhancement mechanisms. These findings show that adult neural processing adapts to better match the changes in sensory inputs caused by long-term exposure to altered optics.

Visual response characteristics of neurons in the second visual area of marmosets

The physiological characteristics of the marmoset second visual area (V2) are poorly understood compared with those of the primary visual area (V1). In this study, we observed the physiological response characteristics of V2 neurons in four healthy adult marmosets using intracortical tungsten microelectrodes. We recorded 110 neurons in area V2, with receptive fields located between 8° and 15° eccentricity. Most (88.2%) of these neurons were orientation selective, with half-bandwidths typically ranging between 10° and 30°. A significant proportion of neurons (28.2%) with direction selectivity had a direction index greater than 0.5. The vast majority of V2 neurons had separable spatial frequency and temporal frequency curves and, according to this criterion, they were not speed selective. The basic functional response characteristics of neurons in area V2 resemble those found in area V1. Our findings show that area V2 together with V1 are important in primate visual processing, especially in locating objects in space and in detecting an object’s direction of motion. The methods used in this study were approved by the Monash University Animal Ethics Committee, Australia (MARP 2009-2011) in 2009.

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.

Low rank mechanisms underlying flexible visual representations

Neuronal population responses to sensory stimuli are remarkably flexible. The responses of neurons in visual cortex have heterogeneous dependence on stimulus properties (e.g., contrast), processes that affect all stages of visual processing (e.g., adaptation), and cognitive processes (e.g., attention or task switching). Understanding whether these processes affect similar neuronal populations and whether they have similar effects on entire populations can provide insight into whether they utilize analogous mechanisms. In particular, it has recently been demonstrated that attention has low rank effects on the covariability of populations of visual neurons, which impacts perception and strongly constrains mechanistic models. We hypothesized that measuring changes in population covariability associated with other sensory and cognitive processes could clarify whether they utilize similar mechanisms or computations. Our experimental design included measurements in multiple visual areas using four distinct sensory and cognitive processes. We found that contrast, adaptation, attention, and task switching affect the variability of responses of populations of neurons in primate visual cortex in a similarly low rank way. These results suggest that a given circuit may use similar mechanisms to perform many forms of modulation and likely reflects a general principle that applies to a wide range of brain areas and sensory, cognitive, and motor processes.

Comparison of pop-out responses to luminance and motion contrasting stimuli of tectal neurons in pigeons

The emergence of visual saliency has been widely studied in the primary visual cortex and the superior colliculus (SC) in mammals. There are fewer studies on the pop-out response to motion direction contrasting stimuli taken in the optic tectum (OT, homologous to mammalian SC), and these are mainly of owls and fish. To our knowledge the influence of spatial luminance has not been reported. In this study, we have recorded multi-units in pigeon OT and analyzed the tectal response to spatial luminance contrasting, motion direction contrasting, and contrasting stimuli from both feature dimensions. The comparison results showed that 1) the tectal response would pop-out in either motion direction or spatial luminance contrasting conditions. 2) The modulation from motion direction contrasting was independent of the temporal luminance variation of the visual stimuli. 3) When both spatial luminance and motion direction were salient, the response of tectal neurons was modulated more intensely by motion direction than by spatial luminance. The phenomenon was consistent with the innate instinct of avians in their natural environment. This study will help to deepen the understanding of mechanisms involved in bottom-up visual information processing and selective attention in the avian.

Weighting neurons by selectivity produces near-optimal population codes

Perception is produced by "reading out" the representation of a sensory stimulus contained in the activity of a population of neurons. To examine experimentally how populations code information, a common approach is to decode a linearly weighted sum of the neurons' spike counts. This approach is popular because of the biological plausibility of weighted, nonlinear integration. For neurons recorded in vivo, weights are highly variable when derived through optimization methods, but it is unclear how the variability affects decoding performance in practice. To address this, we recorded from neurons in the middle temporal area (MT) of anesthetized marmosets (Callithrix jacchus) viewing stimuli comprising a sheet of dots that moved coherently in 1 of 12 different directions. We found that high peak response and direction selectivity both predicted that a neuron would be weighted more highly in an optimized decoding model. Although learned weights differed markedly from weights chosen according to a priori rules based on a neuron's tuning profile, decoding performance was only marginally better for the learned weights. In the models with a priori rules, selectivity is the best predictor of weighting, and defining weights according to a neuron's preferred direction and selectivity improves decoding performance to very near the maximum level possible, as defined by the learned weights. NEW & NOTEWORTHY We examined which aspects of a neuron's tuning account for its contribution to sensory coding. Strongly direction-selective neurons are weighted most highly by optimal decoders trained to discriminate motion direction. Models with predefined decoding weights demonstrate that this weighting scheme causally improved direction representation by a neuronal population. Optimizing decoders (using a generalized linear model or Fisher's linear discriminant) led to only marginally better performance than decoders based purely on a neuron's preferred direction and selectivity.