Adaptation changes the direction tuning of macaque MT neurons

Viewpoint adaptation revealed potential representational differences between 2D images and 3D objects

For convenience and experimental control, cognitive science has relied largely on images as stimuli rather than the real, tangible objects encountered in the real world. Recent evidence suggests that the cognitive processing of images may differ from real objects, especially in the processing of spatial locations and actions, thought to be mediated by the dorsal visual stream. Perceptual and semantic processing in the ventral visual stream, however, has been assumed to be largely unaffected by the realism of objects. Several studies have found that one key difference accounting for differences between real objects and images is actability; however, less research has investigated another potential difference - the three-dimensional nature of real objects as conveyed by cues like binocular disparity. To investigate the extent to which perception is affected by the realism of a stimulus, we compared viewpoint adaptation when stimuli (a face or a kettle) were 2D (flat images without binocular disparity) vs. 3D (i.e., real, tangible objects or stereoscopic images with binocular disparity). For both faces and kettles, adaptation to 3D stimuli induced stronger viewpoint aftereffects than adaptation to 2D images when the adapting orientation was rightward. A computational model suggested that the difference in aftereffects could be explained by broader viewpoint tuning for 3D compared to 2D stimuli. Overall, our finding narrowed the gap between understanding the neural processing of visual images and real-world objects by suggesting that compared to 2D images, real and simulated 3D objects evoke more broadly tuned neural representations, which may result in stronger viewpoint invariance.

Adaptation in the visual system: Networked fatigue or suppressed prediction error signalling?

Our brains are constantly adapting to changes in our visual environments. Neural adaptation exerts a persistent influence on the activity of sensory neurons and our perceptual experience, however there is a lack of consensus regarding how adaptation is implemented in the visual system. One account describes fatigue-based mechanisms embedded within local networks of stimulus-selective neurons (networked fatigue models). Another depicts adaptation as a product of stimulus expectations (predictive coding models). In this review, I evaluate neuroimaging and psychophysical evidence that poses fundamental problems for predictive coding models of neural adaptation. Specifically, I discuss observations of distinct repetition and expectation effects, as well as incorrect predictions of repulsive adaptation aftereffects made by predictive coding accounts. Based on this evidence, I argue that networked fatigue models provide a more parsimonious account of adaptation effects in the visual system. Although stimulus expectations can be formed based on recent stimulation history, any consequences of these expectations are likely to co-occur (or interact) with effects of fatigue-based adaptation. I conclude by proposing novel, testable hypotheses relating to interactions between fatigue-based adaptation and other predictive processes, focusing on stimulus feature extrapolation phenomena.

Adaptation of the inferior temporal neurons and efficient visual processing

Numerous studies examining the responses of individual neurons in the inferior temporal (IT) cortex have revealed their characteristics such as two-dimensional or three-dimensional shape tuning, objects, or category selectivity. While these basic selectivities have been studied assuming that their response to stimuli is relatively stable, physiological experiments have revealed that the responsiveness of IT neurons also depends on visual experience. The activity changes of IT neurons occur over various time ranges; among these, repetition suppression (RS), in particular, is robustly observed in IT neurons without any behavioral or task constraints. I observed a similar phenomenon in the ventral visual neurons in macaque monkeys while they engaged in free viewing and actively fixated on one consistent object multiple times. This observation indicates that the phenomenon also occurs in natural situations during which the subject actively views stimuli without forced fixation, suggesting that this phenomenon is an everyday occurrence and widespread across regions of the visual system, making it a default process for visual neurons. Such short-term activity modulation may be a key to understanding the visual system; however, the circuit mechanism and the biological significance of RS remain unclear. Thus, in this review, I summarize the observed modulation types in IT neurons and the known properties of RS. Subsequently, I discuss adaptation in vision, including concepts such as efficient and predictive coding, as well as the relationship between adaptation and psychophysical aftereffects. Finally, I discuss some conceptual implications of this phenomenon as well as the circuit mechanisms and the models that may explain adaptation as a fundamental aspect of visual processing.

Decoding contextual influences on auditory perception from primary auditory cortex

Perception can be highly dependent on stimulus context, but whether and how sensory areas encode the context remains uncertain. We used an ambiguous auditory stimulus - a tritone pair - to investigate the neural activity associated with a preceding contextual stimulus that strongly influenced the tritone pair's perception: either as an ascending or a descending step in pitch. We recorded single-unit responses from a population of auditory cortical cells in awake ferrets listening to the tritone pairs preceded by the contextual stimulus. We find that the responses adapt locally to the contextual stimulus, consistent with human MEG recordings from the auditory cortex under the same conditions. Decoding the population responses demonstrates that cells responding to pitch-class-changes are able to predict well the context-sensitive percept of the tritone pairs. Conversely, decoding the individual pitch-class representations and taking their distance in the circular Shepard tone space predicts the opposite of the percept. The various percepts can be readily captured and explained by a neural model of cortical activity based on populations of adapting, pitch-class and pitch-class-direction cells, aligned with the neurophysiological responses. Together, these decoding and model results suggest that contextual influences on perception may well be already encoded at the level of the primary sensory cortices, reflecting basic neural response properties commonly found in these areas.

Adaptation-induced sharpening of orientation tuning curves in the mouse visual cortex

OBJECTIVE

Orientation selectivity is an emergent property of visual neurons across species with columnar and noncolumnar organization of the visual cortex. The emergence of orientation selectivity is more established in columnar cortical areas than in noncolumnar ones. Thus, how does orientation selectivity emerge in noncolumnar cortical areas after an adaptation protocol? Adaptation refers to the constant presentation of a nonoptimal stimulus (adapter) to a neuron under observation for a specific time. Previously, it had been shown that adaptation has varying effects on the tuning properties of neurons, such as orientation, spatial frequency, motion and so on.

BASIC METHODS

We recorded the mouse primary visual neurons (V1) at different orientations in the control (preadaptation) condition. This was followed by adapting neurons uninterruptedly for 12 min and then recording the same neurons postadaptation. An orientation selectivity index (OSI) for neurons was computed to compare them pre- and post-adaptation.

MAIN RESULTS

We show that 12-min adaptation increases the OSI of visual neurons ( n  = 113), that is, sharpens their tuning. Moreover, the OSI postadaptation increases linearly as a function of the OSI preadaptation.

CONCLUSION

The increased OSI postadaptation may result from a specific dendritic neural mechanism, potentially facilitating the rapid learning of novel features.

The interplay of motor adaptation and groupitizing in numerosity perception: Insights from visual motion adaptation and proprioceptive motor adaptation

Groupitizing is a well-established strategy in numerosity perception that enhances speed and sensory precision. Building on the ATOM theory, Anobile proposed the sensorimotor numerosity system, which posits a strong link between number and action. Previous studies using motor adaptation technology have shown that high-frequency motor adaptation leads to underestimation of numerosity perception, while low-frequency adaptation leads to overestimation. However, the impact of motor adaptation on groupitizing, and whether visual motion adaptation produces similar effects, remain unclear. In this study, we investigate the persistence of the advantage of groupitizing after motor adaptation and explore the effects of visual motion adaptation. Surprisingly, our findings reveal that proprioceptive motor adaptation weakens the advantage of groupitizing, indicating a robust effect of motor adaptation even when groupitizing is employed. Moreover, we observe a bidirectional relationship, as groupitizing also weakens the adaptation effect. These results highlight the complex interplay between motor adaptation and groupitizing in numerosity perception. Furthermore, our study provides evidence that visual motion adaptation also has an adaptation effect, but does not fully replicate the effects of proprioceptive motor adaptation on groupitizing. In conclusion, our research underscores the importance of groupitizing as a valuable strategy in numerosity perception, and sheds light on the influence of motion adaptation on this strategy.

Bounded contribution of human early visual cortex to the topographic anisotropy in spatial extent perception

To interact successfully with objects, it is crucial to accurately perceive their spatial extent, an enclosed region they occupy in space. Although the topographic representation of space in the early visual cortex (EVC) has been favored as a neural correlate of spatial extent perception, its exact nature and contribution to perception remain unclear. Here, we inspect the topographic representations of human individuals' EVC and perception in terms of how much their anisotropy is influenced by the orientation (co-axiality) and radial position (radiality) of stimuli. We report that while the anisotropy is influenced by both factors, its direction is primarily determined by radiality in EVC but by co-axiality in perception. Despite this mismatch, the individual differences in both radial and co-axial anisotropy are substantially shared between EVC and perception. Our findings suggest that spatial extent perception builds on EVC's spatial representation but requires an additional mechanism to transform its topographic bias.

Feedforward attentional selection in sensory cortex

Salient objects grab attention because they stand out from their surroundings. Whether this phenomenon is accomplished by bottom-up sensory processing or requires top-down guidance is debated. We tested these alternative hypotheses by measuring how early and in which cortical layer(s) neural spiking distinguished a target from a distractor. We measured synaptic and spiking activity across cortical columns in mid-level area V4 of male macaque monkeys performing visual search for a color singleton. A neural signature of attentional capture was observed in the earliest response in the input layer 4. The magnitude of this response predicted response time and accuracy. Errant behavior followed errant selection. Because this response preceded top-down influences and arose in the cortical layer not targeted by top-down connections, these findings demonstrate that feedforward activation of sensory cortex can underlie attentional priority.

On why we lack confidence in some signal-detection-based analyses of confidence

Signal-detection theory (SDT) is one of the most popular frameworks for analyzing data from studies of human behavior - including investigations of confidence. SDT-based analyses of confidence deliver both standard estimates of sensitivity (d'), and a second estimate informed by high-confidence decisions - meta d'. The extent to which meta d' estimates fall short of d' estimates is regarded as a measure of metacognitive inefficiency, quantifying the contamination of confidence by additional noise. These analyses rely on a key but questionable assumption - that repeated exposures to an input will evoke a normally-shaped distribution of perceptual experiences (the normality assumption). Here we show, via analyses inspired by an experiment and modelling, that when distributions of experience do not conform with the normality assumption, meta d' can be systematically underestimated relative to d'. Our data highlight that SDT-based analyses of confidence do not provide a ground truth measure of human metacognitive inefficiency. We explain why deviance from the normality assumption is especially a problem for some popular SDT-based analyses of confidence, in contrast to other analyses inspired by the SDT framework, which are more robust to violations of the normality assumption.

Prior expectation enhances sensorimotor behavior by modulating population tuning and subspace activity in sensory cortex

Prior knowledge facilitates our perception and goal-directed behaviors, particularly when sensory input is lacking or noisy. However, the neural mechanisms underlying the improvement in sensorimotor behavior by prior expectations remain unknown. In this study, we examine the neural activity in the middle temporal (MT) area of visual cortex while monkeys perform a smooth pursuit eye movement task with prior expectation of the visual target's motion direction. Prior expectations discriminately reduce the MT neural responses depending on their preferred directions, when the sensory evidence is weak. This response reduction effectively sharpens neural population direction tuning. Simulations with a realistic MT population demonstrate that sharpening the tuning can explain the biases and variabilities in smooth pursuit, suggesting that neural computations in the sensory area alone can underpin the integration of prior knowledge and sensory evidence. State-space analysis further supports this by revealing neural signals of prior expectations in the MT population activity that correlate with behavioral changes.

Rapid adaptation of primate LGN neurons to drifting grating stimulation

The visual system needs to dynamically adapt to changing environments. Much is known about the adaptive effects of constant stimulation over prolonged periods. However, there are open questions regarding adaptation to stimuli that are changing over time, interrupted, or repeated. Feature-specific adaptation to repeating stimuli has been shown to occur as early as primary visual cortex (V1), but there is also evidence for more generalized, fatigue-like adaptation that might occur at an earlier stage of processing. Here, we show adaptation in the lateral geniculate nucleus (LGN) of awake, fixating monkeys following brief (1 s) exposure to repeated cycles of a 4-Hz drifting grating. We examined the relative change of each neuron's response across successive (repeated) grating cycles. We found that neurons from all cell classes (parvocellular, magnocellular, and koniocellular) showed significant adaptation. However, only magnocellular neurons showed adaptation when responses were averaged to a population response. In contrast to firing rates, response variability was largely unaffected. Finally, adaptation was comparable between monocular and binocular stimulation, suggesting that rapid LGN adaptation is monocular in nature.NEW & NOTEWORTHY Neural adaptation can be defined as reduction of spiking responses following repeated or prolonged stimulation. Adaptation helps adjust neural responsiveness to avoid saturation and has been suggested to improve perceptual selectivity, information transmission, and predictive coding. Here, we report rapid adaptation to repeated cycles of gratings drifting over the receptive field of neurons at the earliest site of postretinal processing, the lateral geniculate nucleus of the thalamus.

Unsupervised approach to decomposing neural tuning variability

Neural representation is often described by the tuning curves of individual neurons with respect to certain stimulus variables. Despite this tradition, it has become increasingly clear that neural tuning can vary substantially in accordance with a collection of internal and external factors. A challenge we are facing is the lack of appropriate methods to accurately capture the moment-to-moment tuning variability directly from the noisy neural responses. Here we introduce an unsupervised statistical approach, Poisson functional principal component analysis (Pf-PCA), which identifies different sources of systematic tuning fluctuations, moreover encompassing several current models (e.g.,multiplicative gain models) as special cases. Applying this method to neural data recorded from macaque primary visual cortex- a paradigmatic case for which the tuning curve approach has been scientifically essential- we discovered a simple relationship governing the variability of orientation tuning, which unifies different types of gain changes proposed previously. By decomposing the neural tuning variability into interpretable components, our method enables discovery of unexpected structure of the neural code, capturing the influence of the external stimulus drive and internal states simultaneously.

Temporal continuity shapes visual responses of macaque face patch neurons

Macaque inferior temporal cortex neurons respond selectively to complex visual images, with recent work showing that they are also entrained reliably by the evolving content of natural movies. To what extent does temporal continuity itself shape the responses of high-level visual neurons? We addressed this question by measuring how cells in face-selective regions of the macaque visual cortex were affected by the manipulation of a movie's temporal structure. Sampling a 5-min movie at 1 s intervals, we measured neural responses to randomized, brief stimuli of different lengths, ranging from 800 ms dynamic movie snippets to 100 ms static frames. We found that the disruption of temporal continuity strongly altered neural response profiles, particularly in the early response period after stimulus onset. The results suggest that models of visual system function based on discrete and randomized visual presentations may not translate well to the brain's natural modes of operation.

Temporal stability of human heading perception

Humans are capable of accurately judging their heading from optic flow during straight forward self-motion. Despite the global coherence in the optic flow field, however, visual clutter and other naturalistic conditions create constant flux on the eye. This presents a problem that must be overcome to accurately perceive heading from optic flow-the visual system must maintain sensitivity to optic flow variations that correspond with actual changes in self-motion and disregard those that do not. One solution could involve integrating optic flow over time to stabilize heading signals while suppressing transient fluctuations. Stability, however, may come at the cost of sluggishness. Here, we investigate the stability of human heading perception when subjects judge their heading after the simulated direction of self-motion changes. We found that the initial heading exerted an attractive influence on judgments of the final heading. Consistent with an evolving heading representation, bias toward the initial heading increased with the size of the heading change and as the viewing duration of the optic flow consistent with the final heading decreased. Introducing periods of sensory dropout (blackouts) later in the trial increased bias whereas an earlier one did not. Simulations of a neural model, the Competitive Dynamics Model, demonstrates that a mechanism that produces an evolving heading signal through recurrent competitive interactions largely captures the human data. Our findings characterize how the visual system balances stability in heading perception with sensitivity to change and support the hypothesis that heading perception evolves over time.

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.

Body and visual instabilities functionally modulate implicit reaching corrections

Hierarchical brain-information-processing schemes have frequently assumed that the flexible but slow voluntary action modulates a direct sensorimotor process that can quickly generate a reaction in dynamical interaction. Here we show that the quick visuomotor process for manual movement is modulated by postural and visual instability contexts that are related but remote and prior states to manual movements. A preceding unstable postural context significantly enhanced the reflexive manual response induced by a large-field visual motion during hand reaching while the response was evidently weakened by imposing a preceding random-visual-motion context. These modulations are successfully explained by the Bayesian optimal formulation in which the manual response elicited by visual motion is ascribed to the compensatory response to the estimated self-motion affected by the preceding contextual situations. Our findings suggest an implicit and functional mechanism that links the variability and uncertainty of remote states to the quick sensorimotor transformation.

Visual motion perception as online hierarchical inference

Identifying the structure of motion relations in the environment is critical for navigation, tracking, prediction, and pursuit. Yet, little is known about the mental and neural computations that allow the visual system to infer this structure online from a volatile stream of visual information. We propose online hierarchical Bayesian inference as a principled solution for how the brain might solve this complex perceptual task. We derive an online Expectation-Maximization algorithm that explains human percepts qualitatively and quantitatively for a diverse set of stimuli, covering classical psychophysics experiments, ambiguous motion scenes, and illusory motion displays. We thereby identify normative explanations for the origin of human motion structure perception and make testable predictions for future psychophysics experiments. The proposed online hierarchical inference model furthermore affords a neural network implementation which shares properties with motion-sensitive cortical areas and motivates targeted experiments to reveal the neural representations of latent structure.

Attractive and repulsive effects of sensory history concurrently shape visual perception

BACKGROUND

Sequential effects of environmental stimuli are ubiquitous in most behavioral tasks involving magnitude estimation, memory, decision making, and emotion. The human visual system exploits continuity in the visual environment, which induces two contrasting perceptual phenomena shaping visual perception. Previous work reported that perceptual estimation of a stimulus may be influenced either by attractive serial dependencies or repulsive aftereffects, with a number of experimental variables suggested as factors determining the direction and magnitude of sequential effects. Recent studies have theorized that these two effects concurrently arise in perceptual processing, but empirical evidence that directly supports this hypothesis is lacking, and it remains unclear whether and how attractive and repulsive sequential effects interact in a trial. Here we show that the two effects concurrently modulate estimation behavior in a typical sequence of perceptual tasks.

RESULTS

We first demonstrate that observers' estimation error as a function of both the previous stimulus and response cannot be fully described by either attractive or repulsive bias but is instead well captured by a summation of repulsion from the previous stimulus and attraction toward the previous response. We then reveal that the repulsive bias is centered on the observer's sensory encoding of the previous stimulus, which is again repelled away from its own preceding trial, whereas the attractive bias is centered precisely on the previous response, which is the observer's best prediction about the incoming stimuli.

CONCLUSIONS

Our findings provide strong evidence that sensory encoding is shaped by dynamic tuning of the system to the past stimuli, inducing repulsive aftereffects, and followed by inference incorporating the prediction from the past estimation, leading to attractive serial dependence.

Attention to visual motion suppresses neuronal and behavioral sensitivity in nearby feature space

Background

Feature-based attention prioritizes the processing of the attended feature while strongly suppressing the processing of nearby ones. This creates a non-linearity or “attentional suppressive surround” predicted by the Selective Tuning model of visual attention. However, previously reported effects of feature-based attention on neuronal responses are linear, e.g., feature-similarity gain. Here, we investigated this apparent contradiction by neurophysiological and psychophysical approaches.

Results

Responses of motion direction-selective neurons in area MT/MST of monkeys were recorded during a motion task. When attention was allocated to a stimulus moving in the neurons’ preferred direction, response tuning curves showed its minimum for directions 60–90° away from the preferred direction, an attentional suppressive surround. This effect was modeled via the interaction of two Gaussian fields representing excitatory narrowly tuned and inhibitory widely tuned inputs into a neuron, with feature-based attention predominantly increasing the gain of inhibitory inputs. We further showed using a motion repulsion paradigm in humans that feature-based attention produces a similar non-linearity on motion discrimination performance.

Conclusions

Our results link the gain modulation of neuronal inputs and tuning curves examined through the feature-similarity gain lens to the attentional impact on neural population responses predicted by the Selective Tuning model, providing a unified framework for the documented effects of feature-based attention on neuronal responses and behavior.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01428-7.

A neural correlate of perceptual segmentation in macaque middle temporal cortical area

High-resolution vision requires fine retinal sampling followed by integration to recover object properties. Importantly, accuracy is lost if local samples from different objects are intermixed. Thus, segmentation, grouping of image regions for separate processing, is crucial for perception. Previous work has used bi-stable plaid patterns, which can be perceived as either a single or multiple moving surfaces, to study this process. Here, we report a relationship between activity in a mid-level site in the primate visual pathways and segmentation judgments. Specifically, we find that direction selective middle temporal neurons are sensitive to texturing cues used to bias the perception of bi-stable plaids and exhibit a significant trial-by-trial correlation with subjective perception of a constant stimulus. This correlation is greater in units that signal global motion in patterns with multiple local orientations. Thus, we conclude the middle temporal area contains a signal for segmenting complex scenes into constituent objects and surfaces.

Direction-selective modulation of visual motion rivalry by collocated tactile motion

Early models of multisensory integration posited that cross-modal signals only converged in higher-order association cortices and that vision automatically dominates. However, recent studies have challenged this view. In this study, the significance of the alignment of motion axes and spatial alignment across visual and tactile stimuli, as well as the effect of hand visibility on visuo-tactile interactions were examined. Using binocular rivalry, opposed motions were presented to each eye and participants were required to track the perceived visual direction. A tactile motion that was either a leftward or rightward sweep across the fingerpad was intermittently presented. Results showed that tactile effects on visual percepts were dependent on the alignment of motion axes: rivalry between up/down visual motions was not modulated at all by left/right tactile motion. On the other hand, visual percepts could be altered by tactile motion signals when both modalities shared a common axis of motion: a tactile stimulus could maintain the dominance duration of a congruent visual stimulus and shorten its suppression period. The effects were also conditional on the spatial alignment of the visual and tactile stimuli, being eliminated when the tactile device was displaced 15 cm away to the right of the visual stimulus. In contrast, visibility of the hand touching the tactile stimulus facilitated congruent switches relative to a visual-only baseline but did not present a significant advantage overall. In sum, these results show a low-level sensory interaction that is conditional on visual and tactile stimuli sharing a common motion axis and location in space.

Explaining Orientation Adaptation in V1 by Updating the State of a Spatial Model

In this work, we extend an influential statistical model based on the spatial classical receptive field (CRF) and non-classical receptive field (nCRF) interactions (Coen-Cagli et al., 2012) to explain the typical orientation adaptation effects observed in V1. If we assume that the temporal adaptation modifies the “state” of the model, the spatial statistical model can explain all of the orientation adaptation effects in the context of neuronal output using small and large grating observed in neurophysiological experiments in V1. The “state” of the model represents the internal parameters such as the prior and the covariance trained on a mixed dataset that totally determine the response of the model. These two parameters, respectively, reflect the probability of the orientation component and the connectivity among neurons between CRF and nCRF. Specifically, we have two key findings: First, neural adapted results using a small grating that just covers the CRF can be predicted by the change of the prior of our model. Second, the change of the prior can also predict most of the observed results using a large grating that covers both CRF and nCRF of a neuron. However, the prediction of the novel attractive adaptation using large grating covering both CRF and nCRF also necessitates the involvement of a connectivity change of the center-surround RFs. In addition, our paper contributes a new prior-based winner-take-all (WTA) working mechanism derived from the statistical-based model to explain why and how all of these orientation adaptation effects can be predicted by relying on this spatial model without modifying its structure, a novel application of the spatial model. The research results show that adaptation may link time and space by changing the “state” of the neural system according to a specific adaptor. Furthermore, different forms of stimulus used for adaptation can cause various adaptation effects, such as an a priori shift or a connectivity change, depending on the specific stimulus size.

Electrophysiological correlates of perceptual prediction error are attenuated in dyslexia

A perceptual adaptation deficit often accompanies reading difficulty in dyslexia, manifesting in poor perceptual learning of consistent stimuli and reduced neurophysiological adaptation to stimulus repetition. However, it is not known how adaptation deficits relate to differences in feedforward or feedback processes in the brain. Here we used electroencephalography (EEG) to interrogate the feedforward and feedback contributions to neural adaptation as adults with and without dyslexia viewed pairs of faces and words in a paradigm that manipulated whether there was a high probability of stimulus repetition versus a high probability of stimulus change. We measured three neural dependent variables: expectation (the difference between prestimulus EEG power with and without the expectation of stimulus repetition), feedforward repetition (the difference between event-related potentials (ERPs) evoked by an expected change and an unexpected repetition), and feedback-mediated prediction error (the difference between ERPs evoked by an unexpected change and an expected repetition). Expectation significantly modulated prestimulus theta- and alpha-band EEG in both groups. Unexpected repetitions of words, but not faces, also led to significant feedforward repetition effects in the ERPs of both groups. However, neural prediction error when an unexpected change occurred instead of an expected repetition was significantly weaker in dyslexia than the control group for both faces and words. These results suggest that the neural and perceptual adaptation deficits observed in dyslexia reflect the failure to effectively integrate perceptual predictions with feedforward sensory processing. In addition to reducing perceptual efficiency, the attenuation of neural prediction error signals would also be deleterious to the wide range of perceptual and procedural learning abilities that are critical for developing accurate and fluent reading skills.

Visual Cortical Area MT Is Required for Development of the Dorsal Stream and Associated Visuomotor Behaviors

The middle temporal (MT) area of the extrastriate visual cortex has long been studied in adulthood for its distinctive physiological properties and function as a part of the dorsal stream, yet interestingly it possesses a similar maturation profile as the primary visual cortex (V1). Here, we examined whether an early-life lesion in MT of marmoset monkeys (six female, two male) altered the dorsal stream development and the behavioral precision of reaching-to-grasp sequences. We observed permanent changes in the anatomy of cortices associated with both reaching (parietal and medial intraparietal areas) and grasping (anterior intraparietal area), as well as in reaching-and-grasping behaviors. In addition, we observed a significant impact on the anatomy of V1 and the direction sensitivity of V1 neurons in the lesion projection zone. These findings indicate that area MT is a crucial node in the development of primate vision, affecting both V1 and areas in the dorsal visual pathway known to mediate visually guided manual behaviors.SIGNIFICANCE STATEMENT Previous studies have identified a role for the MT area of the visual cortex in perceiving motion, yet none have examined its central role in the development of the visual cortex and in the establishment of visuomotor behaviors. To address this, we used a unilateral MT lesion model in neonatal marmosets before examining the anatomic, physiological, and behavioral consequences. In adulthood, we observed perturbations in goal-orientated reach-and-grasp behavior, altered direction selectivity of V1 neurons, and changes in the cytoarchitecture throughout dorsal stream areas. This study highlights the importance of MT as a central node in visual system development and consequential visuomotor activity.

Normative Principles for Decision-Making in Natural Environments

The decisions we make are shaped by a lifetime of learning. Past experience guides the way that we encode information in neural systems for perception and valuation, and determines the information we retrieve when making decisions. Distinct literatures have discussed how lifelong learning and local context shape decisions made about sensory signals, propositional information, or economic prospects. Here, we build bridges between these literatures, arguing for common principles of adaptive rationality in perception, cognition, and economic choice. We discuss how a single common framework, based on normative principles of efficient coding and Bayesian inference, can help us understand a myriad of human decision biases, including sensory illusions, adaptive aftereffects, choice history biases, central tendency effects, anchoring effects, contrast effects, framing effects, congruency effects, reference-dependent valuation, nonlinear utility functions, and discretization heuristics. We describe a simple computational framework for explaining these phenomena. Expected final online publication date for the Annual Review of Psychology, Volume 73 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Rats spontaneously perceive global motion direction of drifting plaids

Computing global motion direction of extended visual objects is a hallmark of primate high-level vision. Although neurons selective for global motion have also been found in mouse visual cortex, it remains unknown whether rodents can combine multiple motion signals into global, integrated percepts. To address this question, we trained two groups of rats to discriminate either gratings (G group) or plaids (i.e., superpositions of gratings with different orientations; P group) drifting horizontally along opposite directions. After the animals learned the task, we applied a visual priming paradigm, where presentation of the target stimulus was preceded by the brief presentation of either a grating or a plaid. The extent to which rat responses to the targets were biased by such prime stimuli provided a measure of the spontaneous, perceived similarity between primes and targets. We found that gratings and plaids, when used as primes, were equally effective at biasing the perception of plaid direction for the rats of the P group. Conversely, for the G group, only the gratings acted as effective prime stimuli, while the plaids failed to alter the perception of grating direction. To interpret these observations, we simulated a decision neuron reading out the representations of gratings and plaids, as conveyed by populations of either component or pattern cells (i.e., local or global motion detectors). We concluded that the findings for the P group are highly consistent with the existence of a population of pattern cells, playing a functional role similar to that demonstrated in primates. We also explored different scenarios that could explain the failure of the plaid stimuli to elicit a sizable priming magnitude for the G group. These simulations yielded testable predictions about the properties of motion representations in rodent visual cortex at the single-cell and circuitry level, thus paving the way to future neurophysiology experiments.

An observer model of tilt perception, sensitivity and confidence

Humans experience levels of confidence in perceptual decisions that tend to scale with the precision of their judgements; but not always. Sometimes precision can be held constant while confidence changes-leading researchers to assume precision and confidence are shaped by different types of information (e.g. perceptual and decisional). To assess this, we examined how visual adaptation to oriented inputs changes tilt perception, perceptual sensitivity and confidence. Some adaptors had a greater detrimental impact on measures of confidence than on precision. We could account for this using an observer model, where precision and confidence rely on different magnitudes of sensory information. These data show that differences in perceptual sensitivity and confidence can therefore emerge, not because these factors rely on different types of information, but because they rely on different magnitudes of sensory information.

On the origin of the Ebbinghaus illusion: The role of figural extent and spatial frequency of stimuli

An object is perceived as larger when it is surrounded by smaller context objects than when it is surrounded by larger context objects. The origin of this well-known phenomenon, called as Ebbinghaus or Titchener circles illusion, is still puzzling. Here we introduce a basic explanation of how this illusion could emerge and provide some preliminary empirical support for this idea. In essence, we suggest that changes in the figural extent and in the spatial frequency of the stimulus pattern entail adjustments of the size and resolution of the attentional field, which are accompanied by changes in spatial coding. This approach is consistent with previous observations and can enable a deeper understanding of geometric illusions.

The Face Module Emerged in a Deep Convolutional Neural Network Selectively Deprived of Face Experience

Can we recognize faces with zero experience on faces? This question is critical because it examines the role of experiences in the formation of domain-specific modules in the brain. Investigation with humans and non-human animals on this issue cannot easily dissociate the effect of the visual experience from that of the hardwired domain-specificity. Therefore, the present study built a model of selective deprivation of the experience on faces with a representative deep convolutional neural network, AlexNet, by removing all images containing faces from its training stimuli. This model did not show significant deficits in face categorization and discrimination, and face-selective modules automatically emerged. However, the deprivation reduced the domain-specificity of the face module. In sum, our study provides empirical evidence on the role of nature vs. nurture in developing the domain-specific modules that domain-specificity may evolve from non-specific experience without genetic predisposition, and is further fine-tuned by domain-specific experience.

Adaptation to one perceived motion direction can generate multiple velocity aftereffects

Sensory adaptation is a useful tool to identify the links between perceptual effects and neural mechanisms. Even though motion adaptation is one of the earliest and most documented aftereffects, few studies have investigated the perception of direction and speed of the aftereffect at the same time, that is the perceived velocity. Using a novel experimental paradigm, we simultaneously recorded the perceived direction and speed of leftward or rightward moving random dots before and after adaptation. For the adapting stimulus, we chose a horizontally-oriented broadband grating moving upward behind a circular aperture. Because of the aperture problem, the interpretation of this stimulus is ambiguous, being consistent with multiple velocities, and yet it is systematically perceived as moving at a single direction and speed. Here we ask whether the visual system adapts to the multiple velocities of the adaptor or to just the single perceived velocity. Our results show a strong repulsion aftereffect, away from the adapting velocity (downward and slower), that increases gradually for faster test stimuli as long as these stimuli include some velocities that match some of the ambiguous ones of the adaptor. In summary, the visual system seems to adapt to the multiple velocities of an ambiguous stimulus even though a single velocity is perceived. Our findings can be well described by a computational model that assumes a joint encoding of direction and speed and that includes an extended adaptation component that can represent all the possible velocities of the ambiguous stimulus.

Short-latency ocular following responses to motion stimuli are strongly affected by temporal modulations of the visual content during the initial fixation period

Neuronal and psychophysical responses to a visual stimulus are known to depend on the preceding history of visual stimulation, but the effect of stimulation history on reflexive eye movements has received less attention. Here, we quantify these effects using short-latency ocular following responses (OFRs), a valuable tool for studying early motion processing. We recorded, in human subjects, the horizontal OFRs induced by drifting vertical 1D pink noise. The stimulus was preceded by 600 to 1000 ms of maintained fixation (on a visible cross), and we explored the effect of different stimuli (“fixation patterns”) presented during the fixation period. We found that any temporal modulation present during the fixation period reduced the magnitude of the subsequent OFRs. Even changes in the overall luminance during the fixation period induced significant suppression. The magnitude of the effect was a function of both spatial and temporal structure of the fixation pattern. Suppression that was selective for both relative orientation and relative spatial frequency accounted for a considerable fraction of total suppression. Finally, changes in stimulus temporal structure alone (i.e. “flicker” versus “transparent motion”) led to changes in the spatial frequency tuning of suppression. In the time domain, the suppression developed quickly: 100 ms of temporal modulation in the fixation pattern produced up to 80% of maximal suppression. Recovery from suppression was instead more gradual, taking up to several seconds. By presenting transparent motion during the fixation period, with opposite motion signals having different spatial frequency content, we also discovered a direction-selective component of suppression, which depended on both the frequency and the direction of the moving stimulus.

Examining cross-modal fMRI adaptation for observed and executed actions in the monkey brain

While mirror neurons have been found in several monkey brain regions, their existence in the human brain is still largely inferred from indirect non-invasive measurements like functional MRI. It has been proposed that, beyond showing overlapping brain responses during action observation and execution tasks, candidate mirror neuron regions should demonstrate cross-modal action specificity, in line with a defining physiological characteristic of these neurons in the monkey brain. Although cross-modal fMRI adaptation has been put forward as a suited method to test this key feature of cross-modal action specificity in the human brain, so far, the overall usefulness of this technique to demonstrate mirror neuron activity remains unclear. To date, it has never been tested to what extent monkey brain regions known to house mirror neurons, would yield uni- and/or cross-modal fMRI adaptation effects. We therefore performed an fMRI adaptation experiment while male rhesus macaques either performed or observed two different goal-directed hand actions. Executing grasp/lift or touch/press actions in the dark, as well as observing videos of these monkey hand actions, yielded robust responses throughout the brain, including overlapping fMRI responses in parietal and premotor mirror neuron regions. Uni-modal adaptation effects were mostly restricted to the visual modality and the early visual cortices. Both frequentist and Bayesian statistical analyses however suggested no evidence for cross-modal fMRI adaptation effects in monkey parietal and premotor mirror neuron regions. Overall, these findings suggest monkey mirror neuron activity does not readily translate into cross-modal repetition suppression effects that can be detected by fMRI.

Expectations about motion direction affect perception and anticipatory smooth pursuit differently

Smooth pursuit eye movements and visual motion perception rely on the integration of current sensory signals with past experience. Experience shapes our expectation of current visual events and can drive eye movement responses made in anticipation of a target, such as anticipatory pursuit. Previous research revealed consistent effects of expectation on anticipatory pursuit-eye movements follow the expected target direction or speed-and contrasting effects on motion perception, but most studies considered either eye movement or perceptual responses. The current study directly compared effects of direction expectation on perception and anticipatory pursuit within the same direction discrimination task to investigate whether both types of responses are affected similarly or differently. Observers (n = 10) viewed high-coherence random-dot kinematograms (RDKs) moving rightward and leftward with a probability of 50%, 70%, or 90% in a given block of trials to build up an expectation of motion direction. They were asked to judge motion direction of interleaved low-coherence RDKs (0%-15%). Perceptual judgements were compared with changes in anticipatory pursuit eye movements as a function of probability. Results show that anticipatory pursuit velocity scaled with probability and followed direction expectation (attraction bias), whereas perceptual judgments were biased opposite to direction expectation (repulsion bias). Control experiments suggest that the repulsion bias in perception was not caused by retinal slip induced by anticipatory pursuit, or by motion adaptation. We conclude that direction expectation can be processed differently for perception and anticipatory pursuit.NEW & NOTEWORTHY We show that expectations about motion direction that are based on long-term trial history affect perception and anticipatory pursuit differently. Whereas anticipatory pursuit direction was coherent with the expected motion direction (attraction bias), perception was biased opposite to the expected direction (repulsion bias). These opposite biases potentially reveal different ways in which perception and action utilize prior information and support the idea of different information processing for perception and pursuit.

Adaptation to visual numerosity changes neural numerosity selectivity

Perceiving numerosity, i.e. the set size of a group of items, is an evolutionarily preserved ability found in humans and animals. A useful method to infer the neural underpinnings of a given perceptual property is sensory adaptation. Like other primary perceptual attributes, numerosity is susceptible to adaptation. Recently, we have shown numerosity-selective neural populations with a topographic organization in the human brain. Here, we investigated whether numerosity adaptation can affect the numerosity selectivity of these populations using ultra-high field (7 Tesla) functional magnetic resonance imaging (fMRI). Participants viewed stimuli of changing numerosity (1 to 7 dots), which allowed the mapping of numerosity selectivity. We interleaved a low or high numerosity adapter stimulus with these mapping stimuli, repeatedly presenting 1 or 20 dots respectively to adapt the numerosity-selective neural populations. We analyzed the responses using custom-build population receptive field neural models of numerosity encoding and compared estimated numerosity preferences between adaptation conditions. We replicated our previous studies where we found several topographic maps of numerosity-selective responses. We found that overall, numerosity adaptation altered the preferred numerosities within the numerosity maps, resulting in predominantly attractive biases towards the numerosity of the adapter. The differential biases could be explained by the difference between the unadapted preferred numerosity and the numerosity of the adapter, with attractive biases being observed with higher difference. The results could link perceptual numerosity adaptation effects to changes in neural numerosity selectivity.

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.

Detecting (Un)seen Change: The Neural Underpinnings of (Un)conscious Prediction Errors

Detecting changes in the environment is fundamental for our survival. According to predictive coding theory, detecting these irregularities relies both on incoming sensory information and our top-down prior expectations (or internal generative models) about the world. Prediction errors (PEs), detectable in event-related potentials (ERPs), occur when there is a mismatch between the sensory input and our internal model (i.e., a surprise event). Many changes occurring in our environment are irrelevant for survival and may remain unseen. Such changes, even if subtle, can nevertheless be detected by the brain without emerging into consciousness. What remains unclear is how these changes are processed in the brain at the network level. Here, we used a visual oddball paradigm in which participants engaged in a central letter task during electroencephalographic (EEG) recordings while presented with task-irrelevant high- or low-coherence background, random-dot motion. Critically, once in a while, the direction of the dots changed. After the EEG session, we confirmed that changes in motion direction at high- and low-coherence were visible and invisible, respectively, using psychophysical measurements. ERP analyses revealed that changes in motion direction elicited PE regardless of the visibility, but with distinct spatiotemporal patterns. To understand these responses, we applied dynamic causal modeling (DCM) to the EEG data. Bayesian Model Averaging showed visible PE relied on a release from adaptation (repetition suppression) within bilateral MT+, whereas invisible PE relied on adaptation at bilateral V1 (and left MT+). Furthermore, while feedforward upregulation was present for invisible PE, the visible change PE also included downregulation of feedback between right MT+ to V1. Our findings reveal a complex interplay of modulation in the generative network models underlying visible and invisible motion changes.

Complementary Inhibitory Weight Profiles Emerge from Plasticity and Allow Flexible Switching of Receptive Fields

Cortical areas comprise multiple types of inhibitory interneurons, with stereotypical connectivity motifs that may follow specific plasticity rules. Yet, their combined effect on postsynaptic dynamics has been largely unexplored. Here, we analyze the response of a single postsynaptic model neuron receiving tuned excitatory connections alongside inhibition from two plastic populations. Synapses from each inhibitory population change according to distinct plasticity rules. We tested different combinations of three rules: Hebbian, anti-Hebbian, and homeostatic scaling. Depending on the inhibitory plasticity rule, synapses become unspecific (flat), anticorrelated to, or correlated with excitatory synapses. Crucially, the neuron's receptive field (i.e., its response to presynaptic stimuli) depends on the modulatory state of inhibition. When both inhibitory populations are active, inhibition balances excitation, resulting in uncorrelated postsynaptic responses regardless of the inhibitory tuning profiles. Modulating the activity of a given inhibitory population produces strong correlations to either preferred or nonpreferred inputs, in line with recent experimental findings that show dramatic context-dependent changes of neurons' receptive fields. We thus confirm that a neuron's receptive field does not follow directly from the weight profiles of its presynaptic afferents. Our results show how plasticity rules in various cell types can interact to shape cortical circuit motifs and their dynamics.SIGNIFICANCE STATEMENT Neurons in sensory areas of the cortex are known to respond to specific features of a given input (e.g., specific sound frequencies), but recent experimental studies show that such responses (i.e., their receptive fields) depend on context. Inspired by the cortical connectivity, we built models of excitatory and inhibitory inputs onto a single neuron, to study how receptive fields may change on short and long time scales. We show how various synaptic plasticity rules allow for the emergence of diverse connectivity profiles and, moreover, how their dynamic interaction creates a mechanism by which postsynaptic responses can quickly change. Our work emphasizes multiple roles of inhibition in cortical processing and provides a first mechanistic model for flexible receptive fields.

Incorporating intrinsic suppression in deep neural networks captures dynamics of adaptation in neurophysiology and perception

Adaptation is a fundamental property of sensory systems that can change subjective experiences in the context of recent information. Adaptation has been postulated to arise from recurrent circuit mechanisms or as a consequence of neuronally intrinsic suppression. However, it is unclear whether intrinsic suppression by itself can account for effects beyond reduced responses. Here, we test the hypothesis that complex adaptation phenomena can emerge from intrinsic suppression cascading through a feedforward model of visual processing. A deep convolutional neural network with intrinsic suppression captured neural signatures of adaptation including novelty detection, enhancement, and tuning curve shifts, while producing aftereffects consistent with human perception. When adaptation was trained in a task where repeated input affects recognition performance, an intrinsic mechanism generalized better than a recurrent neural network. Our results demonstrate that feedforward propagation of intrinsic suppression changes the functional state of the network, reproducing key neurophysiological and perceptual properties of adaptation.

Effects of visual adaptation on orientation selectivity in cat secondary visual cortex

Neuron orientation selectivity, otherwise known as the ability to respond optimally to a preferred orientation, has been extensively described in both primary and secondary visual cortices. This orientation selectivity, conserved through all cortical layers of a given column, is the primary basis for cortical organization and functional network emergence. While this selectivity is programmed and acquired since critical period, it has always been believed that in a mature brain, neurons' inherent functional features could not be changed. However, a plurality of studies has investigated the mature brain plasticity in V1, by changing the cells' orientation selectivity with visual adaptation. Using electrophysiological data in both V1 and V2 areas, this study aims to investigate the effects of adaptation on simultaneously recorded cells in both areas. Visual adaptation had an enhanced effect on V2 units, as they exhibited greater tuning curve shifts and a more pronounced decrease of their OSI. Not only did adaptation have a different effect on V2 neurons, it also elicited a different response depending on the neuron's cortical depth. Indeed, in V2, cells in layers II-III were more affected by visual adaptation, while infragranular layer V units exhibited little to no effect at all.

Persistent Firing and Adaptation in Optic-Flow-Sensitive Descending Neurons

A general principle of sensory systems is that they adapt to prolonged stimulation by reducing their response over time. Indeed, in many visual systems, including higher-order motion sensitive neurons in the fly optic lobes and the mammalian visual cortex, a reduction in neural activity following prolonged stimulation occurs. In contrast to this phenomenon, the response of the motor system controlling flight maneuvers persists following the offset of visual motion. It has been suggested that this gap is caused by a lingering calcium signal in the output synapses of fly optic lobe neurons. However, whether this directly affects the responses of the post-synaptic descending neurons, leading to the observed behavioral output, is not known. We use extracellular electrophysiology to record from optic-flow-sensitive descending neurons in response to prolonged wide-field stimulation. We find that, as opposed to most sensory and visual neurons, and in particular to the motion vision sensitive neurons in the brains of both flies and mammals, the descending neurons show little adaption during stimulus motion. In addition, we find that the optic-flow-sensitive descending neurons display persistent firing, or an after-effect, following the cessation of visual stimulation, consistent with the lingering calcium signal hypothesis. However, if the difference in after-effect is compensated for, subsequent presentation of stimuli in a test-adapt-test paradigm reveals adaptation to visual motion. Our results thus show a combination of adaptation and persistent firing in the neurons that project to the thoracic ganglia and thereby control behavioral output.

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.

Attention amplifies neural representations of changes in sensory input at the expense of perceptual accuracy

Attention enhances the neural representations of behaviorally relevant stimuli, typically by a push-pull increase of the neuronal response gain to attended vs. unattended stimuli. This selectively improves perception and consequently behavioral performance. However, to enhance the detectability of stimulus changes, attention might also distort neural representations, compromising accurate stimulus representation. We test this hypothesis by recording neural responses in the visual cortex of rhesus monkeys during a motion direction change detection task. We find that attention indeed amplifies the neural representation of direction changes, beyond a similar effect of adaptation. We further show that humans overestimate such direction changes, providing a perceptual correlate of our neurophysiological observations. Our results demonstrate that attention distorts the neural representations of abrupt sensory changes and consequently perceptual accuracy. This likely represents an evolutionary adaptive mechanism that allows sensory systems to flexibly forgo accurate representation of stimulus features to improve the encoding of stimulus change.

Where and when to look: Sequential effects at the millisecond level

Learning and imitating a complex motor action requires to visually follow complex movements, but conscious perception seems too slow for such tasks. Recent findings suggest that visual perception has a higher temporal resolution at an unconscious than at a conscious level. Here we investigate whether high-temporal resolution in visual perception relies on prediction mechanisms and attention shifts based on recently experienced sequences of visual information. To that aim we explore sequential effects during four different simultaneity/asynchrony discrimination tasks. Two stimuli are displayed on each trial with varying stimulus onset asynchronies (SOA). Subjects decide whether the stimuli are simultaneous or asynchronous and give manual responses. The main finding is an advantage for different-order over same-order trials, when subjects decided that stimuli had been simultaneous on Trial t - 1 , and when Trial t is with an SOA slightly larger than Trial t - 1, or equivalent. The advantage for different-order trials disappears when the stimuli change eccentricity but not direction between trials (Experiment 2), and persists with stimuli displayed in the centre and unlikely to elicit a sense of direction (Experiment 4). It is still observed when asynchronies on Trial t - 1 are small and undetected (Experiment 3). The findings can be explained by an attention shift that is precisely planned in time and space and that incidentally allows subjects to detect an isolated stimulus on the screen, thus helping them to detect an asynchrony.

Visual Motion Processing in Macaque V2

In the primate visual system, direction-selective (DS) neurons are critical for visual motion perception. While DS neurons in the dorsal visual pathway have been well characterized, the response properties of DS neurons in other major visual areas are largely unexplored. Recent optical imaging studies in monkey visual cortex area 2 (V2) revealed clusters of DS neurons. This imaging method facilitates targeted recordings from these neurons. Using optical imaging and single-cell recording, we characterized detailed response properties of DS neurons in macaque V2. Compared with DS neurons in the dorsal areas (e.g., middle temporal area [MT]), V2 DS neurons have a smaller receptive field and a stronger antagonistic surround. They do not code speed or plaid motion but are sensitive to motion contrast. Our results suggest that V2 DS neurons play an important role in figure-ground segregation. The clusters of V2 DS neurons are likely specialized functional systems for detecting motion contrast.

A neural basis of probabilistic computation in visual cortex

Bayesian models of behavior suggest that organisms represent uncertainty associated with sensory variables. However, the neural code of uncertainty remains elusive. A central hypothesis is that uncertainty is encoded in the population activity of cortical neurons in the form of likelihood functions. We tested this hypothesis by simultaneously recording population activity from primate visual cortex during a visual categorization task in which trial-to-trial uncertainty about stimulus orientation was relevant for the decision. We decoded the likelihood function from the trial-to-trial population activity and found that it predicted decisions better than a point estimate of orientation. This remained true when we conditioned on the true orientation, suggesting that internal fluctuations in neural activity drive behaviorally meaningful variations in the likelihood function. Our results establish the role of population-encoded likelihood functions in mediating behavior and provide a neural underpinning for Bayesian models of perception.

Effects of ketamine on orientation selectivity and variability of neuronal responses in primary visual cortex

The plasticity of the adult brain is one of the most highly evolving areas of recent neuroscience research. It has been acknowledged that the visual cortex in adulthood can adapt and restructure the neuronal connections in response to a sensory experience or to an imposed input such as in adaptation or ocular deprivation protocols. In order to understand the basic cellular mechanisms of plasticity in the primary visual cortex (V1), we examined the effects of ketamine, a non-competitive, glutamatergic NMDAR (N-methyl-D-aspartate receptor) antagonist, on the orientation of cortical cells by measuring their response variability and the Gaussian tuning curves in adult anesthetised mouse and cat. Neurons were recorded extracellularly using glass electrodes. The ketamine was applied locally by placing a custom-cut filter paper (1x1mm) soaked in ketamine solution (10 mg/ml) on the cortical surface next the site of the recording tip, in both species. Our results show that the local and acute exposure of ketamine on V1 changes the preferred orientation of the visual neurons established during the critical period of development. Furthermore, ketamine also leads to a decrease in the orientation selectivity (measured by orientation selectivity index, OSI) and the variability of neuronal evoked responses (measured by Fano factor), but does not affect spontaneous activity. These results suggest that ketamine induces plasticity in V1 neurons that might be operated by a different pathway than that of NMDARs.

Temporal tuning of repetition suppression across the visual cortex

The visual system adapts to its recent history. A phenomenon related to this is repetition suppression (RS), a reduction in neural responses to repeated compared with nonrepeated visual input. An intriguing hypothesis is that the timescale over which RS occurs across the visual hierarchy is tuned to the temporal statistics of visual input features, which change rapidly in low-level areas but are more stable in higher level areas. Here, we tested this hypothesis by studying the influence of the temporal lag between successive visual stimuli on RS throughout the visual system using functional (f)MRI. Twelve human volunteers engaged in four fMRI sessions in which we characterized the blood oxygen level-dependent response to pairs of repeated and nonrepeated natural images with interstimulus intervals (ISI) ranging from 50 to 1,000 ms to quantify the temporal tuning of RS along the posterior-anterior axis of the visual system. As expected, RS was maximal for short ISIs and decayed with increasing ISI. Crucially, however, and against our hypothesis, RS decayed at a similar rate in early and late visual areas. This finding challenges the prevailing view that the timescale of RS increases along the posterior-anterior axis of the visual system and suggests that RS is not tuned to temporal input regularities.NEW & NOTEWORTHY Visual areas show reduced neural responses to repeated compared with nonrepeated visual input, a phenomenon termed repetition suppression (RS). Here we show that RS decays at a similar rate in low- and high-level visual areas, suggesting that the short-term decay of RS across the visual hierarchy is not tuned to temporal input regularities. This may limit the specificity with which the mechanisms underlying RS could optimize the processing of input features across the visual hierarchy.

Ocular Dominance Plasticity of Areas 17 and 21a in the Cat

The visual system is organized in a parallel and hierarchical architecture. However, the plasticity in hierarchical neural networks is controversial across different response features and at different levels. In this study, we recorded areas 17 and 21a, earlier and intermediate stages of the visual cortex in the cat, respectively, by single-unit recording and intrinsic-signal optical imaging. We found that ocular dominance (OD) plasticity evoked by monocular deprivation (MD) was stronger in area 21a than in area 17 in the critical period (CP), and this plasticity became weaker but still persisted in area 21a while it disappeared in area 17 beyond the CP. These results suggest a diversified functional plasticity along the visual information processing pathways in a hierarchical neural network.

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

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.SIGNIFICANCE STATEMENT A major goal in systems neuroscience is to understand how sensory signals are used to guide behavior. This requires determining what information in sensory cortical areas is used, and how it is combined, by downstream perceptual choice circuits. Here we demonstrate that when performing a go/no-go orientation discrimination task, mice suboptimally integrate signals from orientation tuned visual cortical neurons. While they appropriately positively weight target-preferring neurons, they fail to negatively weight distractor-preferring neurons. We propose that this all-positive computation may be adopted because of its simple learning rules and faster processing, and may be a common approach to perceptual decision-making when task conditions allow.