Contrast Dependence of Suppressive Influences in Cortical Area MT of Alert Macaque

Decision-related activity and movement selection in primate visual cortex

Fluctuations in the activity of sensory neurons often predict perceptual decisions. This connection can be quantified with a metric called choice probability (CP), and there is a longstanding debate about whether CP reflects a causal influence on decisions or an echo of decision-making activity elsewhere in the brain. Here, we show that CP can reflect a third variable, namely, the movement used to indicate the decision. In a standard visual motion discrimination task, neurons in the middle temporal (MT) area of primate cortex responded more strongly during trials that involved a saccade toward their receptive fields. This variability accounted for much of the CP observed across the neuronal population, and it arose through training. Moreover, pharmacological inactivation of MT biased behavioral responses away from the corresponding visual field locations. These results demonstrate that training on a task with fixed sensorimotor contingencies introduces movement-related activity in sensory brain regions and that this plasticity can shape the neural circuitry of perceptual decision-making.

Visual surround suppression at the neural and perceptual levels

Surround suppression was initially identified as a phenomenon at the neural level in which stimuli outside the neuron's receptive field alone cannot activate responses but can modulate neural responses to stimuli covered inside the receptive field. Subsequent studies showed that surround suppression is not only a critical property of neurons across species and brain areas but also has been found in visual perceptions. More importantly, surround suppression varies across individuals and shows significant differences between normal controls and patients with certain mental disorders. Here, we combined results from related literature and summarized the findings derived from physiological and psychophysical evidence. We first outline the basic properties of surround suppression in the visual system and perceptions. Then, we mainly summarize the differences in perceptual surround suppression among different human subjects. Our review suggests that there is no consensus regarding whether the strength of perceptual surround suppression could be used as an effective index to distinguish particular populations. Then, we summarized the similar mechanisms for surround suppression and cognitive impairments to further explore the potential clinical applications of surround suppression. A clearer understanding of the mechanisms of surround suppression in neural responses and perceptions is necessary for facilitating its clinical applications.

Neural encoding of multiple motion speeds in visual cortical area MT

Segmenting objects from each other and their background is critical for vision. The speed at which objects move provides a salient cue for segmentation. However, how the visual system represents and differentiates multiple speeds is largely unknown. Here we investigated the neural encoding of multiple speeds of overlapping stimuli in the primate visual cortex. We first characterized the perceptual capacity of human and monkey subjects to segment spatially overlapping stimuli moving at different speeds. We then determined how neurons in the motion-sensitive, middle-temporal (MT) cortex of macaque monkeys encode multiple speeds. We made a novel finding that the responses of MT neurons to two speeds of overlapping stimuli showed a robust bias toward the faster speed component when both speeds were slow (≤ 20°/s). The faster-speed bias occurred even when a neuron had a slow preferred speed and responded more strongly to the slower component than the faster component when presented alone. The faster-speed bias emerged very early in neuronal response and was robust over time and to manipulations of motion direction and attention. As the stimulus speed increased, the faster-speed bias changed to response averaging. Our finding can be explained by a modified divisive normalization model, in which the weights for the speed components are proportional to the responses of a population of neurons elicited by the individual speeds. Our results suggest that the neuron population, referred to as the weighting pool, includes neurons that have a broad range of speed preferences. As a result, the response weights for the speed components are determined by the stimulus speeds and invariant to the speed preferences of individual neurons. Our findings help to define the neural encoding rule of multiple stimuli and provide new insight into the underlying neural mechanisms. The faster-speed bias would benefit behavioral tasks such as figure-ground segregation if figural objects tend to move faster than the background in the natural environment.

A sensory-motor decoder that transforms neural responses in extrastriate area MT into smooth pursuit eye movements

Visual motion drives smooth pursuit eye movements through a sensory-motor decoder that uses multiple parallel neural pathways to transform the population response in extrastriate area MT into movement. We evaluated the decoder by challenging pursuit in monkeys with reduced motion reliability created by reducing coherence of motion in patches of dots. Our strategy was to determine how reduced dot coherence changes the population response in MT. We then predicted the properties of a decoder that transforms the MT population response into dot coherence-induced deficits in the initiation of pursuit and steady-state tracking. During pursuit initiation, decreased dot coherence reduces MT population response amplitude without changing the preferred speed at its peak. The successful decoder reproduces the measured eye movements by multiplication of 1) the estimate of target speed from the peak of the population response with 2) visual-motor gain based on the amplitude of the population response. During steady-state tracking, the decoder that worked for pursuit initiation failed to reproduce the paradox that steady-state eye speeds do not accelerate to the target speed despite persistent image motion. It predicted eye acceleration to target speed even when monkeys' eye speeds were steady at well below the target speed. To account for the effect of dot coherence on steady-state eye speed, we postulate that the decoder uses sensory-motor gain to modulate the eye velocity positive feedback that normally sustains perfect steady-state tracking. Then, poor steady-state tracking persists because of balance between eye deceleration caused by low positive feedback gain and acceleration driven by MT.NEW & NOTEWORTHY By challenging a sensory-motor system with degraded sensory stimuli, we reveal how the sensory-motor decoder transforms the population response in extrastriate area MT into commands for the initiation and steady-state behavior of smooth pursuit eye movements. Conclusions are based on measuring population responses in MT for multiple target speeds and different levels of motion reliability and evaluating a decoder with a biologically motivated architecture to determine the decoder properties that create the measured eye movements.

A sensory-motor decoder that transforms neural responses in extrastriate area MT into smooth pursuit eye movements

Visual motion drives smooth pursuit eye movements through a sensory-motor decoder that uses multiple parallel components and neural pathways to transform the population response in extrastriate area MT into movement. We evaluated the decoder by challenging pursuit in monkeys with reduced motion reliability created by reducing coherence of motion in patches of dots. Reduced dot coherence caused deficits in both the initiation of pursuit and steady-state tracking, revealing the paradox of steady-state eye speeds that fail to accelerate to target speed in spite of persistent image motion. We recorded neural responses to reduced dot coherence in MT and found a decoder that transforms MT population responses into eye movements. During pursuit initiation, decreased dot coherence reduces MT population response amplitude without changing the preferred speed at the peak of the population response. The successful decoder reproduces the measured eye movements by multiplication of (i) the estimate of target speed from the peak of the population response with (ii) visual-motor gain based on the amplitude of the population response. During steady-state tracking, the decoder that worked for pursuit initiation failed. It predicted eye acceleration to target speed even when monkeys' eye speeds were steady at a level well below target speed. We can account for the effect of dot coherence on steady-state eye speed if sensorymotor gain also modulates the eye velocity positive feedback that normally sustains perfect steadystate tracking. Then, poor steady-state tracking persists because of balance between deceleration caused by low positive feedback gain and acceleration driven by MT.

Toward a Biomimetic Neural Circuit Model of Sensory-Motor Processing

Computational models have been a mainstay of research on smooth pursuit eye movements in monkeys. Pursuit is a sensory-motor system that is driven by the visual motion of small targets. It creates a smooth eye movement that accelerates up to target speed and tracks the moving target essentially perfectly. In this review of my laboratory's research, I trace the development of computational models of pursuit eye movements from the early control-theory models to the most recent neural circuit models. I outline a combined experimental and computational plan to move the models to the next level. Finally, I explain why research on nonhuman primates is so critical to the development of the neural circuit models I think we need.

Contributions of low- and high-level contextual mechanisms to human face perception

Contextual modulations at primary stages of visual processing depend on the strength of local input. Contextual modulations at high-level stages of (face) processing show a similar dependence to local input strength. Namely, the discriminability of a facial feature determines the amount of influence of the face context on that feature. How high-level contextual modulations emerge from primary mechanisms is unclear due to the scarcity of empirical research systematically addressing the functional link between the two. We tested (62) young adults' ability to process local input independent of the context using contrast detection and (upright and inverted) morphed facial feature matching tasks. We first investigated contextual modulation magnitudes across tasks to address their shared variance. A second analysis focused on the profile of performance across contextual conditions. In upright eye matching and contrast detection tasks, contextual modulations only correlated at the level of their profile (averaged Fisher-Z transformed r = 1.18, BF10 > 100), but not magnitude (r = .15, BF10 = .61), suggesting the functional independence but similar working principles of the mechanisms involved. Both the profile (averaged Fisher-Z transformed r = .32, BF10 = 9.7) and magnitude (r = .28, BF10 = 4.58) of the contextual modulations correlated between inverted eye matching and contrast detection tasks. Our results suggest that non-face-specialized high-level contextual mechanisms (inverted faces) work in connection to primary contextual mechanisms, but that the engagement of face-specialized mechanisms for upright faces obscures this connection. Such combined study of low- and high-level contextual modulations sheds new light on the functional relationship between different levels of the visual processing hierarchy, and thus on its functional organization.

The pattern glare and visual memory are disrupted in patients with major depressive disorder

BACKGROUND

Visual memory impairment is one of the most commonly complained symptoms in patients with major depressive disorder (MDD). Pattern glare is also a distorted visual phenomenon that puzzles patients with MDD. Nevertheless, how these two phenomena interact in MDD remains unknown. This study investigated the association between pattern glare and visual memory in MDD patients.

METHODS

Sixty-two patients with MDD and forty-nine age-, sex- and education level-matched healthy controls (HCs) were included in this study. The Pattern Recognition Memory (PRM) test and the Brief Visual Memory Test-Revised (BVMT-R) were applied to measure visual memory. The pattern glare test including three patterns with different spatial frequencies (SFs) was used to explore pattern glare levels.

RESULTS

Patients with MDD scored lower on the PRM-PCi, BVMT-R1, BVMT-R2, BVMT-R3, and BVMT-Rt and higher on the PRM-MCLd than HCs (all p < 0.05). Pattern glare scores for MDD patients were higher with mid-SF (p < 0.001), high-SF (p = 0.006) and mid-high SF differences (p = 0.01) than for HCs. A positive correlation between mid-SF and PRM-MCLd scores in all participants was observed (p = 0.01, r = 0.246). A negative correlation between mid-high difference scores and BVMT-R2 scores (p = 0.032, r = -0.317) was observed in HCs, but no significant correlation was observed in MDD patients.

CONCLUSIONS

The present study showed that visual memory and pattern glare are disrupted in MDD. Visual memory may be associated with pattern glare and needs to be studied in future work.

A behavioral receptive field for ocular following in monkeys: Spatial summation and its spatial frequency tuning

In human and non-human primates, reflexive tracking eye movements can be initiated at very short latency in response to a rapid shift of the image. Previous studies in humans have shown that only a part of the central visual field is optimal for driving ocular following responses. Herein, we have investigated spatial summation of motion information across a wide range of spatial frequencies and speeds of drifting gratings by recording short-latency ocular following responses in macaque monkeys. We show that optimal stimulus size for driving ocular responses cover a small (<20° diameter), central part of the visual field that shrinks with higher spatial frequency. This signature of linear motion integration remains invariant with speed and temporal frequency. For low and medium spatial frequencies, we found a strong suppressive influence from surround motion, evidenced by a decrease of response amplitude for stimulus sizes larger than optimal. Such suppression disappears with gratings at high frequencies. The contribution of peripheral motion was investigated by presenting grating annuli of increasing eccentricity. We observed an exponential decay of response amplitude with grating eccentricity, the decrease being faster for higher spatial frequencies. Weaker surround suppression can thus be explained by sparser eccentric inputs at high frequencies. A Difference-of-Gaussians model best renders the antagonistic contributions of peripheral and central motions. Its best-fit parameters coincide with several, well-known spatial properties of area MT neuronal populations. These results describe the mechanism by which central motion information is automatically integrated in a context-dependent manner to drive ocular responses.Significance statementOcular following is driven by visual motion at ultra-short latency in both humans and monkeys. Its dynamics reflect the properties of low-level motion integration. Here, we show that a strong center-surround suppression mechanism modulates initial eye velocity. Its spatial properties are dependent upon visual inputs' spatial frequency but are insensitive to either its temporal frequency or speed. These properties are best described with a Difference-of-Gaussian model of spatial integration. The model parameters reflect many spatial characteristics of motion sensitive neuronal populations in monkey area MT. Our results further outline the computational properties of the behavioral receptive field underpinning automatic, context-dependent motion integration.

Prior Expectations in Visual Speed Perception Predict Encoding Characteristics of Neurons in Area MT

Bayesian inference provides an elegant theoretical framework for understanding the characteristic biases and discrimination thresholds in visual speed perception. However, the framework is difficult to validate because of its flexibility and the fact that suitable constraints on the structure of the sensory uncertainty have been missing. Here, we demonstrate that a Bayesian observer model constrained by efficient coding not only well explains human visual speed perception but also provides an accurate quantitative account of the tuning characteristics of neurons known for representing visual speed. Specifically, we found that the population coding accuracy for visual speed in area MT ("neural prior") is precisely predicted by the power-law, slow-speed prior extracted from fitting the Bayesian observer model to psychophysical data ("behavioral prior") to the point that the two priors are indistinguishable in a cross-validation model comparison. Our results demonstrate a quantitative validation of the Bayesian observer model constrained by efficient coding at both the behavioral and neural levels.SIGNIFICANCE STATEMENT Statistical regularities of the environment play an important role in shaping both neural representations and perceptual behavior. Most previous work addressed these two aspects independently. Here we present a quantitative validation of a theoretical framework that makes joint predictions for neural coding and behavior, based on the assumption that neural representations of sensory information are efficient but also optimally used in generating a percept. Specifically, we demonstrate that the neural tuning characteristics for visual speed in brain area MT are precisely predicted by the statistical prior expectations extracted from psychophysical data. As such, our results provide a normative link between perceptual behavior and the neural representation of sensory information in the brain.

Neural structure of a sensory decoder for motor control

The transformation of sensory input to motor output is often conceived as a decoder operating on neural representations. We seek a mechanistic understanding of sensory decoding by mimicking neural circuitry in the decoder’s design. The results of a simple experiment shape our approach. Changing the size of a target for smooth pursuit eye movements changes the relationship between the variance and mean of the evoked behavior in a way that contradicts the regime of “signal-dependent noise” and defies traditional decoding approaches. A theoretical analysis leads us to propose a circuit for pursuit that includes multiple parallel pathways and multiple sources of variation. Behavioral and neural responses with biomimetic statistics emerge from a biologically-motivated circuit model with noise in the pathway that is dedicated to flexibly adjusting the strength of visual-motor transmission. Our results demonstrate the power of re-imagining decoding as processing through the parallel pathways of neural systems.

Behavioral variation is thought to result from noise in sensory representations or final motor commands. In this study, the authors investigate variability in eye movements and model that variability as resulting from noisy sensorimotor transformations occurring in the middle temporal visual area.

Common and independent processing of visual motion perception and oculomotor response

Visual motion signals are used not only to drive motion perception but also to elicit oculomotor responses. A fundamental question is whether perceptual and oculomotor processing of motion signals shares a common mechanism. This study aimed to address this question using visual motion priming, in which the perceived direction of a directionally ambiguous stimulus is biased in the same (positive priming) or opposite (negative priming) direction as that of a priming stimulus. The priming effect depends on the duration of the priming stimulus. It is assumed that positive and negative priming are mediated by high- and low-level motion systems, respectively. Participants were asked to judge the perceived direction of a π-phase-shifted test grating after a smoothly drifting priming grating during varied durations. Their eye movements were measured while the test grating was presented. The perception and eye movements were discrepant under positive priming and correlated under negative priming on a trial-by-trial basis when an interstimulus interval was inserted between the priming and test stimuli, indicating that the eye movements were evoked by the test stimulus per se. These findings suggest that perceptual and oculomotor responses are induced by a common mechanism at a low level of motion processing but by independent mechanisms at a high level of motion processing.

Spatial suppression of chromatic motion

Center-surround antagonism, as a ubiquitous feature in visual processing, usually leads to inferior perception for a large stimulus compared to a small one. For example, it is more difficult to judge the motion direction of a large high-contrast pattern than that of a small one. However, this spatial suppression in the motion dimension was only reported for luminance motion, and was not found for chromatic motion. Given that center-surround suppression only occurs for strong visual inputs, we hypothesized that previous failure in finding spatial suppression of chromatic motion might be due to weak chromatic motion being induced with stimuli of limited parameters. In this study, we used phase-shift discrimination and motion-direction discrimination tasks to measure motion spatial suppression induced by stimuli of two spatial frequencies (0.5 and 2 cpd) and two contrasts (low and high). We found that spatial suppression of the chromatic motion was stably observed for stimuli of high spatial frequency (2 cpd) and high contrast and spatial summation occurred for stimuli of low spatial frequency (0.5 cpd). Intriguingly, there was no correlations between the motion spatial suppressions of luminance motion and chromatic motion, implying that the two types of spatial suppression are not originated from the same neural processing. Our findings indicate that spatial suppression also exists for chromatic motion, and the mechanisms underlying the spatial suppression of chromatic motion is different from that of luminance motion.

Visual surround suppression in people with epilepsy correlates with attentional-executive functioning, but not with epilepsy or seizure types

PURPOSE

Following reports that an index of visual surround suppression (SI) may serve as a biomarker for an imbalance of cortical excitation and inhibition in different psychiatric and neurological disorders including epilepsy, we evaluated whether SI is associated with seizure susceptibility, seizure spread, and inhibitory effects of antiseizure medication (ASM).

METHODS

In this prospective controlled study, we examined SI with a motion discrimination task in people with genetic generalized epilepsy (GGE) and focal epilepsy with and without focal to bilateral tonic-clonic seizures. Cofactors such as GABAergic ASM, attentional-executive functioning, and depression were taken into account.

RESULTS

Data of 45 patients were included in the final analysis. Suppression index was not related to epilepsy or seizure type, GABAergic ASM treatment or mood. However, SI correlated with attentional-executive functioning (r = 0.32), which in turn was associated with ASM load (r = -0.38). Repeated task administration (N = 7) proved a high stability over a one-week interval (r_tt = 0.89).

CONCLUSIONS

Our results do not support the hypothesis that SI is a reliable biomarker for mechanisms related to inhibition of seizure spread or seizure frequency, i.e., it does not seem to reflect inhibitory capacities in epilepsy. Likewise, SI did not differentiate GGE from focal epilepsy, nor was it influenced by ASM load or mode of action. Thus, in epilepsy, no added value of including SI to routine diagnostics can be concluded.

Linking Neuronal Direction Selectivity to Perceptual Decisions About Visual Motion

Psychophysical and neurophysiological studies of responses to visual motion have converged on a consistent set of general principles that characterize visual processing of motion information. Both types of approaches have shown that the direction and speed of target motion are among the most important encoded stimulus properties, revealing many parallels between psychophysical and physiological responses to motion. Motivated by these parallels, this review focuses largely on more direct links between the key feature of the neuronal response to motion, direction selectivity, and its utilization in memory-guided perceptual decisions. These links were established during neuronal recordings in monkeys performing direction discriminations, but also by examining perceptual effects of widespread elimination of cortical direction selectivity produced by motion deprivation during development. Other approaches, such as microstimulation and lesions, have documented the importance of direction-selective activity in the areas that are active during memory-guided direction comparisons, area MT and the prefrontal cortex, revealing their likely interactions during behavioral tasks.

Selective postsaccadic enhancement of motion perception

Saccadic eye movements can drastically affect motion perception: during saccades, the stationary surround is swept rapidly across the retina and contrast sensitivity is suppressed. However, after saccades, contrast sensitivity is enhanced for color and high-spatial frequency stimuli and reflexive tracking movements known as ocular following responses (OFR) are enhanced in response to large field motion. Additionally, OFR and postsaccadic enhancement of neural activity in primate motion processing areas are well correlated. It is not yet known how this postsaccadic enhancement arises. Therefore, we tested if the enhancement can be explained by changes in the balance of centre-surround antagonism in motion processing, where spatial summation is favoured at low contrasts and surround suppression is favoured at high contrasts. We found motion perception was selectively enhanced immediately after saccades for high spatial frequency stimuli, consistent with previously reported selective postsaccadic enhancement of contrast sensitivity for flashed high spatial frequency stimuli. The observed enhancement was also associated with changes in spatial summation and suppression, as well as contrast facilitation and inhibition, suggesting that motion processing is augmented to maximise visual perception immediately after saccades. The results highlight that spatial and contrast properties of underlying neural mechanisms for motion processing can be affected by an antecedent saccade for highly detailed stimuli and are in line with studies that show behavioural and neuronal enhancement of motion processing in non-human primates.

Neural Selectivity for Visual Motion in Macaque Area V3A

The processing of visual motion is conducted by dedicated pathways in the primate brain. These pathways originate with populations of direction-selective neurons in the primary visual cortex, which projects to dorsal structures like the middle temporal (MT) and medial superior temporal (MST) areas. Anatomical and imaging studies have suggested that area V3A might also be specialized for motion processing, but there have been very few studies of single-neuron direction selectivity in this area. We have therefore performed electrophysiological recordings from V3A neurons in two macaque monkeys (one male and one female) and measured responses to a large battery of motion stimuli that includes translation motion, as well as more complex optic flow patterns. For comparison, we simultaneously recorded the responses of MT neurons to the same stimuli. Surprisingly, we find that overall levels of direction selectivity are similar in V3A and MT and moreover that the population of V3A neurons exhibits somewhat greater selectivity for optic flow patterns. These results suggest that V3A should be considered as part of the motion processing machinery of the visual cortex, in both human and non-human primates.

Reduced surround suppression in monocular motion perception

Motion discrimination of large stimuli is impaired at high contrast and short durations. This psychophysical result has been linked with the center-surround suppression found in neurons of area MT. Recent physiology results have shown that most frontoparallel MT cells respond more strongly to binocular than to monocular stimulation. Here we measured the surround suppression strength under binocular and monocular viewing. Thirty-nine participants took part in two experiments: (a) where the nonstimulated eye viewed a blank field of the same luminance (n = 8) and (b) where it was occluded with a patch (n = 31). In both experiments, we measured duration thresholds for small (1 deg diameter) and large (7 deg) drifting gratings of 1 cpd with 85% contrast. For each subject, a Motion Suppression Index (MSI) was computed by subtracting the duration thresholds in logarithmic units of the large minus the small stimulus. Results were similar in both experiments. Combining the MSI of both experiments, we found that the strength of suppression for binocular condition (MSIbinocular = 0.249 ± 0.126 log10 (ms)) is 1.79 times higher than under monocular viewing (MSImonocular = 0.139 ± 0.137 log10 (ms)). This increase is too high to be explained by the higher perceived contrast of binocular stimuli and offers a new way of testing whether MT neurons account for surround suppression. Potentially, differences in surround suppression reported in clinical populations may reflect altered binocular processing.

Adaptive Surround Modulation of MT Neurons: A Computational Model

The classical receptive field (CRF) of a spiking visual neuron is defined as the region in the visual field that can generate spikes when stimulated by a visual stimulus. Many visual neurons also have an extra-classical receptive field (ECRF) that surrounds the CRF. The presence of a stimulus in the ECRF does not generate spikes but rather modulates the response to a stimulus in the neuron's CRF. Neurons in the primate Middle Temporal (MT) area, which is a motion specialist region, can have directionally antagonistic or facilitatory surrounds. The surround's effect switches between directionally antagonistic or facilitatory based on the characteristics of the stimulus, with antagonistic effects when there are directional discontinuities but facilitatory effects when there is directional coherence. Here, we present a computational model of neurons in area MT that replicates this observation and uses computational building blocks that correlate with observed cell types in the visual pathways to explain the mechanism of this modulatory effect. The model shows that the categorization of MT neurons based on the effect of their surround depends on the input stimulus rather than being a property of the neurons. Also, in agreement with neurophysiological findings, the ECRFs of the modeled MT neurons alter their center-surround interactions depending on image contrast.

Weaker neural suppression in autism

Abnormal sensory processing has been observed in autism, including superior visual motion discrimination, but the neural basis for these sensory changes remains unknown. Leveraging well-characterized suppressive neural circuits in the visual system, we used behavioral and fMRI tasks to demonstrate a significant reduction in neural suppression in young adults with autism spectrum disorder (ASD) compared to neurotypical controls. MR spectroscopy measurements revealed no group differences in neurotransmitter signals. We show how a computational model that incorporates divisive normalization, as well as narrower top-down gain (that could result, for example, from a narrower window of attention), can explain our observations and divergent previous findings. Thus, weaker neural suppression is reflected in visual task performance and fMRI measures in ASD, and may be attributable to differences in top-down processing.

Sensory hypersensitivity is common in autism spectrum disorders. Using functional MRI, psychophysics, and computational modeling, Schallmo et al. show that differences in visual motion perception in ASD are accompanied by weaker neural suppression in visual cortex.

Anatomy and Physiology of Macaque Visual Cortical Areas V1, V2, and V5/MT: Bases for Biologically Realistic Models

The cerebral cortex of primates encompasses multiple anatomically and physiologically distinct areas processing visual information. Areas V1, V2, and V5/MT are conserved across mammals and are central for visual behavior. To facilitate the generation of biologically accurate computational models of primate early visual processing, here we provide an overview of over 350 published studies of these three areas in the genus Macaca, whose visual system provides the closest model for human vision. The literature reports 14 anatomical connection types from the lateral geniculate nucleus of the thalamus to V1 having distinct layers of origin or termination, and 194 connection types between V1, V2, and V5, forming multiple parallel and interacting visual processing streams. Moreover, within V1, there are reports of 286 and 120 types of intrinsic excitatory and inhibitory connections, respectively. Physiologically, tuning of neuronal responses to 11 types of visual stimulus parameters has been consistently reported. Overall, the optimal spatial frequency (SF) of constituent neurons decreases with cortical hierarchy. Moreover, V5 neurons are distinct from neurons in other areas for their higher direction selectivity, higher contrast sensitivity, higher temporal frequency tuning, and wider SF bandwidth. We also discuss currently unavailable data that could be useful for biologically accurate models.

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.

Development of Center-Surround Suppression in Infant Motion Processing

Motion direction of a large high-contrast pattern is more difficult to perceive than that of a small one [1]. This counterintuitive perceptual phenomenon is considered to reflect surround suppression, a receptive field property observed in the visual cortex [2-5]. Here, we demonstrate that this phenomenon can be observed in human infants. Infants at 7 to 8 months of age showed higher sensitivity for a small motion stimulus than for a large one. However, infants under 6 months showed the opposite result; motion sensitivity was higher for a large stimulus. These results suggest that suppressive surround regions beyond classical receptive fields develop in the second half of the first year. Moreover, we examined the size of spatial summation in infants and found that the spatial summation area shrinks from 3 to 8 months of age. Our findings suggest that the summation area for motion is broad with no surround suppression in early infancy and that it narrows and acquires suppressive surround regions in the first year of life, which might reflect the developmental changes in the receptive field structure.

Spatial suppression promotes rapid figure-ground segmentation of moving objects

Segregation of objects from their backgrounds is a fundamental visual function and one that is particularly effective when objects are in motion. Theoretically, suppressive center-surround mechanisms are well suited for accomplishing motion segregation. This longstanding hypothesis, however, has received limited empirical support. We report converging correlational and causal evidence that spatial suppression of background motion signals is critical for rapid segmentation of moving objects. Motion segregation ability is strongly predicted by both individual and stimulus-driven variations in spatial suppression strength. Moreover, aging-related superiority in perceiving background motion is associated with profound impairments in motion segregation. This segregation deficit is alleviated via perceptual learning, but only when motion segregation training also causes decreased sensitivity to background motion. We argue that perceptual insensitivity to large moving stimuli effectively implements background subtraction, which, in turn, enhances the visibility of moving objects and accounts for the observed link between spatial suppression and motion segregation.

The visual system excels at segregating moving objects from their backgrounds, a key visual function hypothesized to be driven by suppressive centre-surround mechanisms. Here, the authors show that spatial suppression of background motion signals is critical for rapid segmentation of moving objects.

Cognitive load effects on early visual perceptual processing

Contrast-based early visual processing has largely been considered to involve autonomous processes that do not need the support of cognitive resources. However, as spatial attention is known to modulate early visual perceptual processing, we explored whether cognitive load could similarly impact contrast-based perception. We used a dual-task paradigm to assess the impact of a concurrent working memory task on the performance of three different early visual tasks. The results from Experiment 1 suggest that cognitive load can modulate early visual processing. No effects of cognitive load were seen in Experiments 2 or 3. Together, the findings provide evidence that under some circumstances cognitive load effects can penetrate the early stages of visual processing and that higher cognitive function and early perceptual processing may not be as independent as was once thought.

Disentangling locus of perceptual learning in the visual hierarchy of motion processing

Visual perceptual learning (VPL) can lead to long-lasting perceptual improvements. One of the central topics in VPL studies is the locus of plasticity in the visual processing hierarchy. Here, we tackled this question in the context of motion processing. We took advantage of an established transition from component-dependent representations at the earliest level to pattern-dependent representations at the middle-level of cortical motion processing. Two groups of participants were trained on the same motion direction identification task using either grating or plaid stimuli. A set of pre- and post-training tests was used to determine the degree of learning specificity and generalizability. This approach allowed us to disentangle contributions from different levels of processing stages to behavioral improvements. We observed a complete bi-directional transfer of learning between component and pattern stimuli that moved to the same directions, indicating learning-induced plasticity associated with intermediate levels of motion processing. Moreover, we found that motion VPL is specific to the trained stimulus direction, speed, size, and contrast, diminishing the possibility of non-sensory decision-level enhancements. Taken together, these results indicate that, at least for the type of stimuli and the task used here, motion VPL most likely alters visual computation associated with signals at the middle stage of motion processing.

Mechanisms of Spatiotemporal Selectivity in Cortical Area MT

Cortical sensory neurons are characterized by selectivity to stimulation. This selectivity was originally viewed as a part of the fundamental "receptive field" characteristic of neurons. This view was later challenged by evidence that receptive fields are modulated by stimuli outside of the classical receptive field. Here, we show that even this modified view of selectivity needs revision. We measured spatial frequency selectivity of neurons in cortical area MT of alert monkeys and found that their selectivity strongly depends on luminance contrast, shifting to higher spatial frequencies as contrast increases. The changes of preferred spatial frequency are large at low temporal frequency, and they decrease monotonically as temporal frequency increases. That is, even interactions among basic stimulus dimensions of luminance contrast, spatial frequency, and temporal frequency strongly influence neuronal selectivity. This dynamic nature of neuronal selectivity is inconsistent with the notion of stimulus preference as a stable characteristic of cortical neurons.

A video-driven model of response statistics in the primate middle temporal area

Neurons in the primate middle temporal area (MT) encode information about visual motion and binocular disparity. MT has been studied intensively for decades, so there is a great deal of information in the literature about MT neuron tuning. In this study, our goal is to consolidate some of this information into a statistical model of the MT population response. The model accepts arbitrary stereo video as input. It uses computer-vision methods to calculate known correlates of the responses (such as motion velocity), and then predicts activity using a combination of tuning functions that have previously been used to describe data in various experiments. To construct the population response, we also estimate the distributions of many model parameters from data in the electrophysiology literature. We show that the model accounts well for a separate dataset of MT speed tuning that was not used in developing the model. The model may be useful for studying relationships between MT activity and behavior in ethologically relevant tasks. As an example, we show that the model can provide regression targets for internal activity in a deep convolutional network that performs a visual odometry task, so that its representations become more physiologically realistic.

Systematic misperceptions of 3-D motion explained by Bayesian inference

People make surprising but reliable perceptual errors. Here, we provide a unified explanation for systematic errors in the perception of three-dimensional (3-D) motion. To do so, we characterized the binocular retinal motion signals produced by objects moving through arbitrary locations in 3-D. Next, we developed a Bayesian model, treating 3-D motion perception as optimal inference given sensory noise in the measurement of retinal motion. The model predicts a set of systematic perceptual errors, which depend on stimulus distance, contrast, and eccentricity. We then used a virtual-reality headset as well as a standard 3-D desktop stereoscopic display to test these predictions in a series of perceptual experiments. As predicted, we found evidence that errors in 3-D motion perception depend on the contrast, viewing distance, and eccentricity of a stimulus. These errors include a lateral bias in perceived motion direction and a surprising tendency to misreport approaching motion as receding and vice versa. In sum, we present a Bayesian model that provides a parsimonious account for a range of systematic misperceptions of motion in naturalistic environments.

Testing the link between visual suppression and intelligence

The impairment to discriminate the motion direction of a large high contrast stimulus or to detect a stimulus surrounded by another one is called visual suppression and is the result of the normal function of our visual inhibitory mechanisms. Recently, Melnick et al. (2013), using a motion discrimination task, showed that intelligence strongly correlates with visual suppression (r = 0.71). Cook et al. (2016) also showed a strong link between contrast surround suppression and IQ (r = 0.87), this time using a contrast matching task. Our aim is to test this link using two different visual suppression tasks: a motion discrimination task and a contrast detection task. Fifty volunteers took part in the experiments. Using Bayesian staircases, we measured duration thresholds in the motion experiment and contrast thresholds in the spatial experiment. Although we found a much weaker effect, our results from the motion experiment still replicate previous results supporting the link between motion surround suppression and IQ (r = 0.43). However, our results from the spatial experiment do not support the link between contrast surround suppression and IQ (r = -0.09). Methodological differences between this study and previous studies which could explain these discrepancies are discussed.

Suppression and facilitation of human neural responses

Efficient neural processing depends on regulating responses through suppression and facilitation of neural activity. Utilizing a well-known visual motion paradigm that evokes behavioral suppression and facilitation, and combining five different methodologies (behavioral psychophysics, computational modeling, functional MRI, pharmacology, and magnetic resonance spectroscopy), we provide evidence that challenges commonly held assumptions about the neural processes underlying suppression and facilitation. We show that: (1) both suppression and facilitation can emerge from a single, computational principle – divisive normalization; there is no need to invoke separate neural mechanisms, (2) neural suppression and facilitation in the motion-selective area MT mirror perception, but strong suppression also occurs in earlier visual areas, and (3) suppression is not primarily driven by GABA-mediated inhibition. Thus, while commonly used spatial suppression paradigms may provide insight into neural response magnitudes in visual areas, they should not be used to infer neural inhibition.

A Unifying Motif for Spatial and Directional Surround Suppression

In the visual system, the response to a stimulus in a neuron's receptive field can be modulated by stimulus context, and the strength of these contextual influences vary with stimulus intensity. Recent work has shown how a theoretical model, the stabilized supralinear network (SSN), can account for such modulatory influences, using a small set of computational mechanisms. Although the predictions of the SSN have been confirmed in primary visual cortex (V1), its computational principles apply with equal validity to any cortical structure. We have therefore tested the generality of the SSN by examining modulatory influences in the middle temporal area (MT) of the macaque visual cortex, using electrophysiological recordings and pharmacological manipulations. We developed a novel stimulus that can be adjusted parametrically to be larger or smaller in the space of all possible motion directions. We found, as predicted by the SSN, that MT neurons integrate across motion directions for low-contrast stimuli, but that they exhibit suppression by the same stimuli when they are high in contrast. These results are analogous to those found in visual cortex when stimulus size is varied in the space domain. We further tested the mechanisms of inhibition using pharmacological manipulations of inhibitory efficacy. As predicted by the SSN, local manipulation of inhibitory strength altered firing rates, but did not change the strength of surround suppression. These results are consistent with the idea that the SSN can account for modulatory influences along different stimulus dimensions and in different cortical areas.SIGNIFICANCE STATEMENT Visual neurons are selective for specific stimulus features in a region of visual space known as the receptive field, but can be modulated by stimuli outside of the receptive field. The SSN model has been proposed to account for these and other modulatory influences, and tested in V1. As this model is not specific to any particular stimulus feature or brain region, we wondered whether similar modulatory influences might be observed for other stimulus dimensions and other regions. We tested for specific patterns of modulatory influences in the domain of motion direction, using electrophysiological recordings from MT. Our data confirm the predictions of the SSN in MT, suggesting that the SSN computations might be a generic feature of sensory cortex.

New insights into the role of motion and form vision in neurodevelopmental disorders

A selective deficit in processing the global (overall) motion, but not form, of spatially extensive objects in the visual scene is frequently associated with several neurodevelopmental disorders, including preterm birth. Existing theories that proposed to explain the origin of this visual impairment are, however, challenged by recent research. In this review, we explore alternative hypotheses for why deficits in the processing of global motion, relative to global form, might arise. We describe recent evidence that has utilised novel tasks of global motion and global form to elucidate the underlying nature of the visual deficit reported in different neurodevelopmental disorders. We also examine the role of IQ and how the sex of an individual can influence performance on these tasks, as these are factors that are associated with performance on global motion tasks, but have not been systematically controlled for in previous studies exploring visual processing in clinical populations. Finally, we suggest that a new theoretical framework is needed for visual processing in neurodevelopmental disorders and present recommendations for future research.

Active Dendritic Properties and Local Inhibitory Input Enable Selectivity for Object Motion in Mouse Superior Colliculus Neurons

Neurons respond to specific features of sensory stimuli. In the visual system, for example, some neurons respond to motion of small but not large objects, whereas other neurons prefer motion of the entire visual field. Separate neurons respond equally to local and global motion but selectively to additional features of visual stimuli. How and where does response selectivity emerge? Here, we show that wide-field (WF) cells in retino-recipient layers of the mouse superior colliculus (SC) respond selectively to small moving objects. Moreover, we identify two mechanisms that contribute to this selectivity. First, we show that input restricted to a small portion of the broad dendritic arbor of WF cells is sufficient to trigger dendritic spikes that reliably propagate to the soma/axon. In vivo whole-cell recordings reveal that nearly every action potential evoked by visual stimuli has characteristics of spikes initiated in dendrites. Second, inhibitory input from a different class of SC neuron, horizontal cells, constrains the range of stimuli to which WF cells respond. Horizontal cells respond preferentially to the sudden appearance or rapid movement of large stimuli. Optogenetic reduction of their activity reduces movement selectivity and broadens size tuning in WF cells by increasing the relative strength of responses to stimuli that appear suddenly or cover a large region of space. Therefore, strongly propagating dendritic spikes enable small stimuli to drive spike output in WF cells and local inhibition helps restrict responses to stimuli that are both small and moving.

SIGNIFICANCE STATEMENT

How do neurons respond selectively to some sensory stimuli but not others? In the visual system, a particularly relevant stimulus feature is object motion, which often reveals other animals. Here, we show how specific cells in the superior colliculus, one synapse downstream of the retina, respond selectively to object motion. These wide-field (WF) cells respond strongly to small objects that move slowly anywhere through a large region of space, but not to stationary objects or full-field motion. Action potential initiation in dendrites enables small stimuli to trigger visual responses and inhibitory input from cells that prefer large, suddenly appearing, or quickly moving stimuli restricts responses of WF cells to objects that are small and moving.

The Contribution of Area MT to Visual Motion Perception Depends on Training

Perceptual decisions require the transformation of raw sensory inputs into cortical representations suitable for stimulus discrimination. One of the best-known examples of this transformation involves the middle temporal area (MT) of the primate visual cortex. Area MT provides a robust representation of stimulus motion, and previous work has shown that it contributes causally to performance on motion discrimination tasks. Here we report that the strength of this contribution can be highly plastic: depending on the recent training history, pharmacological inactivation of MT can severely impair motion discrimination, or it can have little detectable influence. Further analysis of neural and behavioral data suggests that training moves the readout of motion information between MT and lower-level cortical areas. These results show that the contribution of individual brain regions to conscious perception can shift flexibly depending on sensory experience.

A Normalization Mechanism for Estimating Visual Motion across Speeds and Scales

Interacting with the natural environment leads to complex stimulations of our senses. Here we focus on the estimation of visual speed, a critical source of information for the survival of many animal species as they monitor moving prey or approaching dangers. In mammals, and in particular in primates, speed information is conceived to be represented by a set of channels sensitive to different spatial and temporal characteristics of the optic flow [1-5]. However, it is still largely unknown how the brain accurately infers the speed of complex natural scenes from this set of spatiotemporal channels [6-14]. As complex stimuli, we chose a set of well-controlled moving naturalistic textures called "compound motion clouds" (CMCs) [15, 16] that simultaneously activate multiple spatiotemporal channels. We found that CMC stimuli that have the same physical speed are perceived moving at different speeds depending on which channel combinations are activated. We developed a computational model demonstrating that the activity in a given channel is both boosted and weakened after a systematic pattern over neighboring channels. This pattern of interactions can be understood as a combination of two components oriented in speed (consistent with a slow-speed prior) and scale (sharpening of similar features). Interestingly, the interaction along scale implements a lateral inhibition mechanism, a canonical principle that hitherto was found to operate mainly in early sensory processing. Overall, the speed-scale normalization mechanism may reflect the natural tendency of the visual system to integrate complex inputs into one coherent percept.

Abnormal Size-Dependent Modulation of Motion Perception in Children with Autism Spectrum Disorder (ASD)

Excitation/Inhibition (E/I) imbalance in neural networks is now considered among the core neural underpinnings of autism psychopathology. In motion perception at least two phenomena critically depend on E/I balance in visual cortex: spatial suppression (SS), and spatial facilitation (SF) corresponding to impoverished or improved motion perception with increasing stimuli size, respectively. While SS is dominant at high contrast, SF is evident for low contrast stimuli, due to the prevalence of inhibitory contextual modulations in the former, and excitatory ones in the latter case. Only one previous study (Foss-Feig et al., 2013) investigated SS and SF in Autism Spectrum Disorder (ASD). Our study aimed to replicate previous findings, and to explore the putative contribution of deficient inhibitory influences into an enhanced SF index in ASD—a cornerstone for interpretation proposed by Foss-Feig et al. (2013). The SS and SF were examined in 40 boys with ASD, broad spectrum of intellectual abilities (63 < IQ < 127) and 44 typically developing (TD) boys, aged 6–15 years. The stimuli of small (1°) and large (12°) radius were presented under high (100%) and low (1%) contrast conditions. Social Responsiveness Scale and Sensory Profile Questionnaire were used to assess the autism severity and sensory processing abnormalities. We found that the SS index was atypically reduced, while SF index abnormally enhanced in children with ASD. The presence of abnormally enhanced SF in children with ASD was the only consistent finding between our study and that of Foss-Feig et al. While the SS and SF indexes were strongly interrelated in TD participants, this correlation was absent in their peers with ASD. In addition, the SF index but not the SS index correlated with the severity of autism and the poor registration abilities. The pattern of results is partially consistent with the idea of hypofunctional inhibitory transmission in visual areas in ASD. Nonetheless, the absence of correlation between SF and SS indexes paired with a strong direct link between abnormally enhanced SF and autism symptoms in our ASD sample emphasizes the role of the enhanced excitatory influences by themselves in the observed abnormalities in low-level visual phenomena found in ASD.

Integration of motion energy from overlapping random background noise increases perceived speed of coherently moving stimuli

The perception of visual motion can be profoundly influenced by visual context. To gain insight into how the visual system represents motion speed, we investigated how a background stimulus that did not move in a net direction influenced the perceived speed of a center stimulus. Visual stimuli were two overlapping random-dot patterns. The center stimulus moved coherently in a fixed direction, whereas the background stimulus moved randomly. We found that human subjects perceived the speed of the center stimulus to be significantly faster than its veridical speed when the background contained motion noise. Interestingly, the perceived speed was tuned to the noise level of the background. When the speed of the center stimulus was low, the highest perceived speed was reached when the background had a low level of motion noise. As the center speed increased, the peak perceived speed was reached at a progressively higher background noise level. The effect of speed overestimation required the center stimulus to overlap with the background. Increasing the background size within a certain range enhanced the effect, suggesting spatial integration. The speed overestimation was significantly reduced or abolished when the center stimulus and the background stimulus had different colors, or when they were placed at different depths. When the center- and background-stimuli were perceptually separable, speed overestimation was correlated with perceptual similarity between the center- and background-stimuli. These results suggest that integration of motion energy from random motion noise has a significant impact on speed perception. Our findings put new constraints on models regarding the neural basis of speed perception.

A neural basis for the spatial suppression of visual motion perception

In theory, sensory perception should be more accurate when more neurons contribute to the representation of a stimulus. However, psychophysical experiments that use larger stimuli to activate larger pools of neurons sometimes report impoverished perceptual performance. To determine the neural mechanisms underlying these paradoxical findings, we trained monkeys to discriminate the direction of motion of visual stimuli that varied in size across trials, while simultaneously recording from populations of motion-sensitive neurons in cortical area MT. We used the resulting data to constrain a computational model that explained the behavioral data as an interaction of three main mechanisms: noise correlations, which prevented stimulus information from growing with stimulus size; neural surround suppression, which decreased sensitivity for large stimuli; and a read-out strategy that emphasized neurons with receptive fields near the stimulus center. These results suggest that paradoxical percepts reflect tradeoffs between sensitivity and noise in neuronal populations.

DOI:http://dx.doi.org/10.7554/eLife.16167.001

People usually find it easier to see things when they are big and bright, but there are occasionally exceptions. One example concerns moving objects: when they are small, we can identify their direction of motion easily, but this becomes much more difficult for larger objects. This decreased perceptual sensitivity appears to be linked to other mental processes. For example, studies have suggested that people with high IQs have more difficulty perceiving the motion of large objects, whereas people with various psychiatric disorders, such as schizophrenia, are better able to see such movement. Although several theories have been proposed, there is currently no good explanation for these findings.

Liu et al. set out to determine why the part of the brain that is responsible for vision (the visual cortex) fails to register the direction of large moving objects and how this failure might relate to mental function in general. To do this, Liu et al. trained monkeys to report which direction different sized stimuli were moving on a screen. The electrical activity of nerve cells in the part of the visual cortex that deals with movement was recorded while the monkeys performed this task. The results of the experiments revealed that, on average, these cells responded strongly to large moving stimuli, even though the monkeys had trouble seeing their motion. However, nerve cells are “noisy” – they respond a bit differently every time they are presented with the same stimulus – and this noise was stronger for larger stimuli.

By studying the mathematical relationship between the noise and what the animals perceived, Liu et al. found that the visual cortex attempts to suppress the noise and in the process often shuts off the responses to large stimuli entirely. This suppression is likely to cause the movement of large stimuli to be poorly perceived.

If suppressing this kind of noise is really responsible for failures in perceiving motion, then this mechanism could also explain the connection between motion perception and other mental processes. Liu et al. are currently testing this idea.

DOI:http://dx.doi.org/10.7554/eLife.16167.002

Contrast Affects fMRI Activity in Middle Temporal Cortex Related to Center-Surround Interaction in Motion Perception

As the size of a high contrast drifting Gabor patch increases, perceiving its direction of motion becomes harder. However, the same behavioral effect is not observed for a low contrast Gabor patch. Neuronal mechanisms underlying this size–contrast interaction are not well understood. Here using psychophysical methods and functional magnetic resonance imaging (fMRI), we investigated the neural correlates of this behavioral effect. In the behavioral experiments, motion direction discrimination thresholds were assessed for drifting Gabor patches with different sizes and contrasts. Thresholds increased significantly as the size of the stimulus increased for high contrast (65%) but did not change for low contrast (2%) stimuli. In the fMRI experiment, cortical activity was recorded while observers viewed drifting Gabor patches with different contrasts and sizes. We found that the activity in middle temporal (MT) area increased with size at low contrast, but did not change at high contrast. Taken together, our results show that MT activity reflects the size–contrast interaction in motion perception.

Interaction effects of visual stimulus speed and contrast on postural sway

Manipulating the characteristics of visual stimuli that simulate self-motion through the environment can affect the resulting postural sway magnitude. In the present study, we address the question whether varying the contrast and speed of a linear translating dot pattern influences medial–lateral postural sway. In a first experiment, we investigated whether the postural sway magnitude increases with increasing dot speed, as was previously demonstrated for expanding and contracting stimuli. In a second experiment, we also manipulated the contrast of the stimuli. For reasons that high-contrast stimuli can be considered ‘perceptually’ stronger, we expect that higher-contrast stimuli induce more sway than lower-contrast stimuli. The results of the first experiment show that dot speed indeed influences postural sway, although in an unexpected way. For higher speeds, the sway is in the direction of the stimulus motion, yet for lower speeds the sway is in a direction opposite to the stimulus motion. The results of the second experiment show that dot contrast does affect postural sway, but that this depends on the speed of the moving dots. Interestingly, the direction of postural sway induced by a relatively low dot speed (4°/s) depends on dot contrast. Taken together, our results suggest that interactions between the visual, vestibular and proprioceptive system appear to be influenced by an internal representation of the visual stimulus, rather than being influenced by the external visual stimulus characteristics only.

Suppressive mechanisms in visual motion processing: From perception to intelligence

Perception operates on an immense amount of incoming information that greatly exceeds the brain's processing capacity. Because of this fundamental limitation, the ability to suppress irrelevant information is a key determinant of perceptual efficiency. Here, I will review a series of studies investigating suppressive mechanisms in visual motion processing, namely perceptual suppression of large, background-like motions. These spatial suppression mechanisms are adaptive, operating only when sensory inputs are sufficiently robust to guarantee visibility. Converging correlational and causal evidence links these behavioral results with inhibitory center-surround mechanisms, namely those in cortical area MT. Spatial suppression is abnormally weak in several special populations, including the elderly and individuals with schizophrenia-a deficit that is evidenced by better-than-normal direction discriminations of large moving stimuli. Theoretical work shows that this abnormal weakening of spatial suppression should result in motion segregation deficits, but direct behavioral support of this hypothesis is lacking. Finally, I will argue that the ability to suppress information is a fundamental neural process that applies not only to perception but also to cognition in general. Supporting this argument, I will discuss recent research that shows individual differences in spatial suppression of motion signals strongly predict individual variations in IQ scores.

Computational Model of Primary Visual Cortex Combining Visual Attention for Action Recognition

Humans can easily understand other people’s actions through visual systems, while computers cannot. Therefore, a new bio-inspired computational model is proposed in this paper aiming for automatic action recognition. The model focuses on dynamic properties of neurons and neural networks in the primary visual cortex (V1), and simulates the procedure of information processing in V1, which consists of visual perception, visual attention and representation of human action. In our model, a family of the three-dimensional spatial-temporal correlative Gabor filters is used to model the dynamic properties of the classical receptive field of V1 simple cell tuned to different speeds and orientations in time for detection of spatiotemporal information from video sequences. Based on the inhibitory effect of stimuli outside the classical receptive field caused by lateral connections of spiking neuron networks in V1, we propose surround suppressive operator to further process spatiotemporal information. Visual attention model based on perceptual grouping is integrated into our model to filter and group different regions. Moreover, in order to represent the human action, we consider the characteristic of the neural code: mean motion map based on analysis of spike trains generated by spiking neurons. The experimental evaluation on some publicly available action datasets and comparison with the state-of-the-art approaches demonstrate the superior performance of the proposed model.

A mechanistic cortical microcircuit of attention for amplification, normalization and suppression

Computational models of visual attention have replicated a large number of data from visual attention experiments. However, typically each computational model has been shown to account for only a few data sets. We developed a novel model of attention, particularly focused on explaining single cell recordings in multiple brain areas, to better understand the underlying computational circuits of attention involved in spatial- and feature-based biased competition, modulation of the contrast response function, modulation of the neuronal tuning curve, and modulation of surround suppression. In contrast to previous models, we use a two layer structure inspired by the layered cortical architecture which implements amplification, divisive normalization and suppression as well as spatial pooling.

Contextual modulation and stimulus selectivity in extrastriate cortex

Contextual modulation is observed throughout the visual system, using techniques ranging from single-neuron recordings to behavioral experiments. Its role in generating feature selectivity within the retina and primary visual cortex has been extensively described in the literature. Here, we describe how similar computations can also elaborate feature selectivity in the extrastriate areas of both the dorsal and ventral streams of the primate visual system. We discuss recent work that makes use of normalization models to test specific roles for contextual modulation in visual cortex function. We suggest that contextual modulation renders neuronal populations more selective for naturalistic stimuli. Specifically, we discuss contextual modulation's role in processing optic flow in areas MT and MST and for representing naturally occurring curvature and contours in areas V4 and IT. We also describe how the circuitry that supports contextual modulation is robust to variations in overall input levels. Finally, we describe how this theory relates to other hypothesized roles for contextual modulation.