Cortical Balance Between ON and OFF Visual Responses Is Modulated by the Spatial Properties of the Visual Stimulus

Contrast Sensitivity of ON and OFF Human Retinal Pathways in Myopia

The human visual cortex processes light and dark stimuli with ON and OFF pathways that are differently modulated by luminance contrast. We have previously demonstrated that ON cortical pathways have higher contrast sensitivity than OFF cortical pathways and the difference increases with luminance range (defined as the maximum minus minimum luminance in the scene). Here, we demonstrate that these ON-OFF cortical differences are already present in the human retina and that retinal responses measured with electroretinography are more affected by reductions in luminance range than cortical responses measured with electroencephalography. Moreover, we show that ON-OFF pathway differences measured with electroretinography become more pronounced in myopia, a visual disorder that elongates the eye and blurs vision at far distance. We find that, as the eye axial length increases across subjects, ON retinal pathways become less responsive, slower in response latency, less sensitive, and less effective and slower at driving pupil constriction. Based on these results, we conclude that myopia is associated with a deficit in ON pathway function that decreases the ability of the retina to process low contrast and regulate retinal illuminance in bright environments.

Dynamic Recruitment of the Feedforward and Recurrent Mechanism for Black-White Asymmetry in the Primary Visual Cortex

Black and white information is asymmetrically distributed in natural scenes, evokes asymmetric neuronal responses, and causes asymmetric perceptions. Recognizing the universality and essentiality of black-white asymmetry in visual information processing, the neural substrates for black-white asymmetry remain unclear. To disentangle the role of the feedforward and recurrent mechanisms in the generation of cortical black-white asymmetry, we recorded the V1 laminar responses and LGN responses of anesthetized cats of both sexes. In a cortical column, we found that black-white asymmetry starts at the input layer and becomes more pronounced in the output layer. We also found distinct dynamics of black-white asymmetry between the output layer and the input layer. Specifically, black responses dominate in all layers after stimulus onset. After stimulus offset, black and white responses are balanced in the input layer, but black responses still dominate in the output layer. Compared with that in the input layer, the rebound response in the output layer is significantly suppressed. The relative suppression strength evoked by white stimuli is notably stronger and depends on the location within the ON-OFF cortical map. A model with delayed and polarity-selective cortical suppression explains black-white asymmetry in the output layer, within which prominent recurrent connections are identified by Granger causality analysis. In addition to black-white asymmetry in response strength, the interlaminar differences in spatial receptive field varied dynamically. Our findings suggest that the feedforward and recurrent mechanisms are dynamically recruited for the generation of black-white asymmetry in V1.SIGNIFICANCE STATEMENT Black-white asymmetry is universal and essential in visual information processing, yet the neural substrates for cortical black-white asymmetry remain unknown. Leveraging V1 laminar recordings, we provided the first laminar pattern of black-white asymmetry in cat V1 and found distinct dynamics of black-white asymmetry between the output layer and the input layer. Comparing black-white asymmetry across three visual hierarchies, the LGN, V1 input layer, and V1 output layer, we demonstrated that the feedforward and recurrent mechanisms are dynamically recruited for the generation of cortical black-white asymmetry. Our findings not only enhance our understanding of laminar processing within a cortical column but also elucidate how feedforward connections and recurrent connections interact to shape neuronal response properties.

State-of-the-art image and video quality assessment with a metric based on an intrinsically non-linear neural summation model

The development of automatic methods for image and video quality assessment that correlate well with the perception of human observers is a very challenging open problem in vision science, with numerous practical applications in disciplines such as image processing and computer vision, as well as in the media industry. In the past two decades, the goal of image quality research has been to improve upon classical metrics by developing models that emulate some aspects of the visual system, and while the progress has been considerable, state-of-the-art quality assessment methods still share a number of shortcomings, like their performance dropping considerably when they are tested on a database that is quite different from the one used to train them, or their significant limitations in predicting observer scores for high framerate videos. In this work we propose a novel objective method for image and video quality assessment that is based on the recently introduced Intrinsically Non-linear Receptive Field (INRF) formulation, a neural summation model that has been shown to be better at predicting neural activity and visual perception phenomena than the classical linear receptive field. Here we start by optimizing, on a classic image quality database, the four parameters of a very simple INRF-based metric, and proceed to test this metric on three other databases, showing that its performance equals or surpasses that of the state-of-the-art methods, some of them having millions of parameters. Next, we extend to the temporal domain this INRF image quality metric, and test it on several popular video quality datasets; again, the results of our proposed INRF-based video quality metric are shown to be very competitive.

ON and OFF receptive field processing in the presence of optical scattering

The balance of ON/OFF pathway activation in the retina plays a role in emmetropization. A new myopia control lens design uses contrast reduction to down-regulate a hypothesized enhanced ON contrast sensitivity in myopes. The study thus examined ON/OFF receptive field processing in myopes and non-myopes and the impact of contrast reduction. A psychophysical approach was used to measure the combined retinal-cortical output in the form of low-level ON and OFF contrast sensitivity with and without contrast reduction in 22 participants. ON responses were lower than OFF responses (ON 1.25 ± 0.03 vs. OFF 1.39 ± 0.03 log(CS); p < 0.0001) and myopes showed generally reduced sensitivities (myopes 1.25 ± 0.05 vs. non-myopes 1.39 ± 0.05 log(CS); p = 0.05). These findings remained unaffected by contrast reduction (p > 0.05). The study suggests that perceptual differences in ON and OFF signal processing between myopes and non-myopes exist but cannot explain how contrast reduction can inhibit myopia development.

Differences in visual stimulation between reading and walking and implications for myopia development

Visual input plays an important role in the development of myopia (nearsightedness), a visual disorder that blurs vision at far distances. The risk of myopia progression increases with the time spent reading and decreases with outdoor activity for reasons that remain poorly understood. To investigate the stimulus parameters driving this disorder, we compared the visual input to the retina of humans performing two tasks associated with different risks of myopia progression, reading and walking. Human subjects performed the two tasks while wearing glasses with cameras and sensors that recorded visual scenes and visuomotor activity. When compared with walking, reading black text in white background reduced spatiotemporal contrast in central vision and increased it in peripheral vision, leading to a pronounced reduction in the ratio of central/peripheral strength of visual stimulation. It also made the luminance distribution heavily skewed toward negative dark contrast in central vision and positive light contrast in peripheral vision, decreasing the central/peripheral stimulation ratio of ON visual pathways. It also decreased fixation distance, blink rate, pupil size, and head-eye coordination reflexes dominated by ON pathways. Taken together with previous work, these results support the hypothesis that reading drives myopia progression by understimulating ON visual pathways.

Model-Based Approach Shows ON Pathway Afferents Elicit a Transient Decrease of V1 Responses

Neurons in the primary visual cortex (V1) receive excitation and inhibition from distinct parallel pathways processing lightness (ON) and darkness (OFF). V1 neurons overall respond more strongly to dark than light stimuli, consistent with a preponderance of darker regions in natural images, as well as human psychophysics. However, it has been unclear whether this "dark-dominance" is because of more excitation from the OFF pathway or more inhibition from the ON pathway. To understand the mechanisms behind dark-dominance, we record electrophysiological responses of individual simple-type V1 neurons to natural image stimuli and then train biologically inspired convolutional neural networks to predict the neurons' responses. Analyzing a sample of 71 neurons (in anesthetized, paralyzed cats of either sex) has revealed their responses to be more driven by dark than light stimuli, consistent with previous investigations. We show that this asymmetry is predominantly because of slower inhibition to dark stimuli rather than to stronger excitation from the thalamocortical OFF pathway. Consistent with dark-dominant neurons having faster responses than light-dominant neurons, we find dark-dominance to solely occur in the early latencies of neurons' responses. Neurons that are strongly dark-dominated also tend to be less orientation-selective. This novel approach gives us new insight into the dark-dominance phenomenon and provides an avenue to address new questions about excitatory and inhibitory integration in cortical neurons.SIGNIFICANCE STATEMENT Neurons in the early visual cortex respond on average more strongly to dark than to light stimuli, but the mechanisms behind this bias have been unclear. Here we address this issue by combining single-unit electrophysiology with a novel machine learning model to analyze neurons' responses to natural image stimuli in primary visual cortex. Using these techniques, we find slower inhibition to light than to dark stimuli to be the leading mechanism behind stronger dark responses. This slower inhibition to light might help explain other empirical findings, such as why orientation selectivity is weaker at earlier response latencies. These results demonstrate how imbalances in excitation versus inhibition can give rise to response asymmetries in cortical neuron responses.

Luminance Contrast Shifts Dominance Balance between ON and OFF Pathways in Human Vision

Human vision processes light and dark stimuli in visual scenes with separate ON and OFF neuronal pathways. In nature, stimuli lighter or darker than their local surround have different spatial properties and contrast distributions (Ratliff et al., 2010; Cooper and Norcia, 2015; Rahimi-Nasrabadi et al., 2021). Similarly, in human vision, we show that luminance contrast affects the perception of lights and darks differently. At high contrast, human subjects of both sexes locate dark stimuli faster and more accurately than light stimuli, which is consistent with a visual system dominated by the OFF pathway. However, at low contrast, they locate light stimuli faster and more accurately than dark stimuli, which is consistent with a visual system dominated by the ON pathway. Luminance contrast was strongly correlated with multiple ON/OFF dominance ratios estimated from light/dark ratios of performance errors, missed targets, or reaction times (RTs). All correlations could be demonstrated at multiple eccentricities of the central visual field with an ON-OFF perimetry test implemented in a head-mounted visual display. We conclude that high-contrast stimuli are processed faster and more accurately by OFF pathways than ON pathways. However, the OFF dominance shifts toward ON dominance when stimulus contrast decreases, as expected from the higher-contrast sensitivity of ON cortical pathways (Kremkow et al., 2014; Rahimi-Nasrabadi et al., 2021). The results highlight the importance of contrast polarity in visual field measurements and predict a loss of low-contrast vision in humans with ON pathway deficits, as demonstrated in animal models (Sarnaik et al., 2014).SIGNIFICANCE STATEMENT ON and OFF retino-thalamo-cortical pathways respond differently to luminance contrast. In both animal models and humans, low contrasts drive stronger responses from ON pathways, whereas high contrasts drive stronger responses from OFF pathways. We demonstrate that these ON-OFF pathway differences have a correlate in human vision. At low contrast, humans locate light targets faster and more accurately than dark targets but, as contrast increases, dark targets become more visible than light targets. We also demonstrate that contrast is strongly correlated with multiple light/dark ratios of visual performance in central vision. These results provide a link between neuronal physiology and human vision while emphasizing the importance of stimulus polarity in measurements of visual fields and contrast sensitivity.

Preferential Loss of Contrast Decrement Responses in Human Glaucoma

Purpose

The purpose of this study was to determine whether glaucoma in human patients produces preferential damage to OFF visual pathways, as suggested by animal experimental models, patient electroretinogram (ERG), and retinal imaging data.

Methods

Steady-state visual evoked potentials (SSVEPs) were recorded monocularly from 50 patients with glaucoma and 28 age-similar controls in response to equal Weber contrast increments and decrements presented using 2.73 hertz (Hz) sawtooth temporal waveforms.

Results

The eyes of patients with glaucoma were separated into mild (better than -6 decibel [dB] mean deviation; n = 28) and moderate to severe (worse than -6 dB mean deviation, n = 22) groups based on their Humphrey 24-2 visual field measurements. Response amplitudes and phases from the two glaucoma-severity groups were compared to controls at the group level. SSVEP amplitudes were depressed in both glaucoma groups, more so in the moderate to severe glaucoma group. The differences between controls and the moderate-severe glaucoma groups were more statistically reliable for decrements than for increments. Mean responses to decremental sawtooth stimuli were larger than those to increments in controls and in the mild glaucoma but not in the moderate to severe glaucoma group at the first harmonic. OFF/decrement responses at the first harmonic were faster in controls, but not in patients.

Conclusions

The observed pattern of preferential loss of decremental responses in human glaucoma is consistent with prior reports of selective damage to OFF retinal ganglion cells in murine models and in data from human ERG and retinal imaging. These data motivate pursuit of SSVEP as a biomarker for glaucoma progression.

Cortical mechanisms of visual brightness

The primary visual cortex signals the onset of light and dark stimuli with ON and OFF cortical pathways. Here, we demonstrate that both pathways generate similar response increments to large homogeneous surfaces and their response average increases with surface brightness. We show that, in cat visual cortex, response dominance from ON or OFF pathways is bimodally distributed when stimuli are smaller than one receptive field center but unimodally distributed when they are larger. Moreover, whereas small bright stimuli drive opposite responses from ON and OFF pathways (increased versus suppressed activity), large bright surfaces drive similar response increments. We show that this size-brightness relation emerges because strong illumination increases the size of light surfaces in nature and both ON and OFF cortical neurons receive input from ON thalamic pathways. We conclude that visual scenes are perceived as brighter when the average response increments from ON and OFF cortical pathways become stronger.

Mazade et al. find that the visual cortex encodes brightness differently for small than large stimuli. Bright small stimuli drive cortical pathways signaling lights and suppress cortical pathways signaling darks. Conversely, large surfaces drive response increments from both pathways and appear brightest when the response average is strongest.

More than the end: OFF response plasticity as a mnemonic signature of a sound’s behavioral salience

In studying how neural populations in sensory cortex code dynamically varying stimuli to guide behavior, the role of spiking after stimuli have ended has been underappreciated. This is despite growing evidence that such activity can be tuned, experience-and context-dependent and necessary for sensory decisions that play out on a slower timescale. Here we review recent studies, focusing on the auditory modality, demonstrating that this so-called OFF activity can have a more complex temporal structure than the purely phasic firing that has often been interpreted as just marking the end of stimuli. While diverse and still incompletely understood mechanisms are likely involved in generating phasic and tonic OFF firing, more studies point to the continuing post-stimulus activity serving a short-term, stimulus-specific mnemonic function that is enhanced when the stimuli are particularly salient. We summarize these results with a conceptual model highlighting how more neurons within the auditory cortical population fire for longer duration after a sound’s termination during an active behavior and can continue to do so even while passively listening to behaviorally salient stimuli. Overall, these studies increasingly suggest that tonic auditory cortical OFF activity holds an echoic memory of specific, salient sounds to guide behavioral decisions.

Spatial modulation of dark versus bright stimulus responses in the mouse visual system

A fundamental task of the visual system is to respond to both increases and decreases of luminance with action potentials (ON and OFF responses1-4). OFF responses are stronger, faster, and more salient than ON responses in primary visual cortex (V1) of both cats5,6 and primates,7,8 but in ferrets9 and mice,10 ON responses can be stronger, weaker,11 or balanced12 in comparison to OFF responses. These discrepancies could arise from differences in species, experimental techniques, or stimulus properties, particularly retinotopic location in the visual field, as has been speculated;9 however, the role of retinotopy for ON/OFF dominance has not been systematically tested across multiple scales of neural activity within species. Here, we measured OFF versus ON responses across large portions of visual space with silicon probe and whole-cell patch-clamp recordings in mouse V1 and lateral geniculate nucleus (LGN). We found that OFF responses dominated in the central visual field, whereas ON and OFF responses were more balanced in the periphery. These findings were consistent across local field potential (LFP), spikes, and subthreshold membrane potential in V1, and were aligned with spatial biases in ON and OFF responses in LGN. Our findings reveal that retinotopy may provide a common organizing principle for spatial modulation of OFF versus ON processing in mammalian visual systems.

Visual processing: Systematic variation in light-dark bias across visual space

Detecting changes in luminance is a fundamental property of the visual system. A new study shows that lights and darks are represented differently across visual space, with strong OFF bias in central vision and balanced ON/OFF in the periphery.

From Receptive to Perceptive Fields: Size-Dependent Asymmetries in Both Negative Afterimages and Subcortical On and Off Post-Stimulus Responses

Negative afterimages are perceptual phenomena that occur after physical stimuli disappear from sight. Their origin is linked to transient post-stimulus responses of visual neurons. The receptive fields (RFs) of these subcortical ON- and OFF-center neurons exhibit antagonistic interactions between central and surrounding visual space, resulting in selectivity for stimulus polarity and size. These two features are closely intertwined, yet their relationship to negative afterimage perception remains unknown. Here we tested whether size differentially affects the perception of bright and dark negative afterimages in humans of both sexes, and how this correlates with neural mechanisms in subcortical ON and OFF cells. Psychophysically, we found a size-dependent asymmetry whereby dark disks produce stronger and longer-lasting negative afterimages than bright disks of equal contrast at sizes >0.8°. Neurophysiological recordings from retinal and relay cells in female cat dorsal lateral geniculate nucleus showed that subcortical ON cells exhibited stronger sustained post-stimulus responses to dark disks, than OFF cells to bright disks, at sizes >1°. These sizes agree with the emergence of center-surround antagonism, revealing stronger suppression to opposite-polarity stimuli for OFF versus ON cells, particularly in dorsal lateral geniculate nucleus. Using a network-based retino-geniculate model, we confirmed stronger antagonism and temporal transience for OFF-cell post-stimulus rebound responses. A V1 population model demonstrated that both strength and duration asymmetries can be propagated to downstream cortical areas. Our results demonstrate how size-dependent antagonism impacts both the neuronal post-stimulus response and the resulting afterimage percepts, thereby supporting the idea of perceptual RFs reflecting the underlying neuronal RF organization of single cells.SIGNIFICANCE STATEMENT Visual illusions occur when sensory inputs and perceptual outcomes do not match, and provide a valuable tool to understand transformations from neural to perceptual responses. A classic example are negative afterimages that remain visible after a stimulus is removed from view. Such perceptions are linked to responses in early visual neurons, yet the details remain poorly understood. Combining human psychophysics, neurophysiological recordings in cats and retino-thalamo-cortical computational modeling, our study reveals how stimulus size and the receptive-field structure of subcortical ON and OFF cells contributes to the parallel asymmetries between neural and perceptual responses to bright versus dark afterimages. Thus, this work provides a deeper link from the underlying neural mechanisms to the resultant perceptual outcomes.

Matching visual induction effects on screens of different size

In the film industry, the same movie is expected to be watched on displays of vastly different sizes, from cinema screens to mobile phones. But visual induction, the perceptual phenomenon by which the appearance of a scene region is affected by its surroundings, will be different for the same image shown on two displays of different dimensions. This phenomenon presents a practical challenge for the preservation of the artistic intentions of filmmakers, because it can lead to shifts in image appearance between viewing destinations. In this work, we show that a neural field model based on the efficient representation principle is able to predict induction effects and how, by regularizing its associated energy functional, the model is still able to represent induction but is now invertible. From this finding, we propose a method to preprocess an image in a screen-size dependent way so that its perception, in terms of visual induction, may remain constant across displays of different size. The potential of the method is demonstrated through psychophysical experiments on synthetic images and qualitative examples on natural images.

Representational Content of Oscillatory Brain Activity during Object Recognition: Contrasting Cortical and Deep Neural Network Hierarchies

Numerous theories propose a key role for brain oscillations in visual perception. Most of these theories postulate that sensory information is encoded in specific oscillatory components (e.g., power or phase) of specific frequency bands. These theories are often tested with whole-brain recording methods of low spatial resolution (EEG or MEG), or depth recordings that provide a local, incomplete view of the brain. Opportunities to bridge the gap between local neural populations and whole-brain signals are rare. Here, using representational similarity analysis (RSA) in human participants we explore which MEG oscillatory components (power and phase, across various frequency bands) correspond to low or high-level visual object representations, using brain representations from fMRI, or layer-wise representations in seven recent deep neural networks (DNNs), as a template for low/high-level object representations. The results showed that around stimulus onset and offset, most transient oscillatory signals correlated with low-level brain patterns (V1). During stimulus presentation, sustained β (∼20 Hz) and γ (>60 Hz) power best correlated with V1, while oscillatory phase components correlated with IT representations. Surprisingly, this pattern of results did not always correspond to low-level or high-level DNN layer activity. In particular, sustained β band oscillatory power reflected high-level DNN layers, suggestive of a feed-back component. These results begin to bridge the gap between whole-brain oscillatory signals and object representations supported by local neuronal activations.

Different roles of subcortical inputs in V1 responses to luminance and contrast

Cells in the primary visual cortex (V1) generally respond weakly to large uniform luminance stimuli. Only a subset of V1 cells is thought to encode uniform luminance information. In natural scenes, local luminance is an important feature for defining an object that varies and coexists with local spatial contrast. However, the strategies used by V1 cells to encode local mean luminance for spatial contrast stimuli remain largely unclear. Here, using extracellular recordings in anesthetized cats, we investigated the responses of V1 cells by comparing with those of retinal ganglion (RG) cells and lateral geniculate nucleus (LGN) cells to simultaneous and rapid changes in luminance and spatial contrast. Almost all V1 cells exhibited a strong monotonic increasing luminance tuning when they were exposed to high spatial contrast. Thus, V1 cells encode the luminance carried by spatial contrast stimuli with the monotonically increasing response function. Moreover, high contrast decreased luminance tuning of OFF cells but increased that of in ON cells in RG and LGN. The luminance and contrast tunings of LGN ON cells were highly separable as V1 cells, whereas those of LGN OFF cells were lowly separable. These asymmetrical effects of spatial contrast on ON/OFF channels might underlie the robust ability of V1 cells to perform luminance tuning when exposed to spatial contrast stimuli.

Distinct neuron phenotypes may serve object feature sensing in the electrosensory lobe of Gymnotus omarorum

Early sensory relay circuits in the vertebrate medulla often adopt a cerebellum-like organization specialized for comparing primary afferent inputs with central expectations. These circuits usually have a dual output, carried by center ON and center OFF neurons responding in opposite ways to the same stimulus at the center of their receptive fields. Here, we show in the electrosensory lateral line lobe of Gymnotiform weakly electric fish that basilar pyramidal neurons, representing 'ON' cells, and non-basilar pyramidal neurons, representing 'OFF' cells, have different intrinsic electrophysiological properties. We used classical anatomical techniques and electrophysiological in vitro recordings to compare these neurons. Basilar neurons are silent at rest, have a high threshold to intracellular stimulation, delayed responses to steady-state depolarization and low pass responsiveness to membrane voltage variations. They respond to low-intensity depolarizing stimuli with large, isolated spikes. As stimulus intensity increases, the spikes are followed by a depolarizing after-potential from which phase-locked spikes often arise. Non-basilar neurons show a pacemaker-like spiking activity, smoothly modulated in frequency by slow variations of stimulus intensity. Spike-frequency adaptation provides a memory of their recent firing, facilitating non-basilar response to stimulus transients. Considering anatomical and functional dimensions, we conclude that basilar and non-basilar pyramidal neurons are clear-cut, different anatomo-functional phenotypes. We propose that, in addition to their role in contrast processing, basilar pyramidal neurons encode sustained global stimuli such as those elicited by large or distant objects while non-basilar pyramidal neurons respond to transient stimuli due to movement of objects with a textured surface.

Neural correlates of metacontrast masking across different contrast polarities

Metacontrast masking is a powerful illusion to investigate the dynamics of perceptual processing and to control conscious visual perception. However, the neural mechanisms underlying this fundamental investigative tool are still debated. In the present study, we examined metacontrast masking across different contrast polarities by employing a contour discrimination task combined with EEG (Electroencephalography). When the target and mask had the same contrast polarity, a typical U-shaped metacontrast function was observed. A change in mask polarity (i.e., opposite mask polarity) shifted this masking function to a monotonic increasing function such that the target visibility was strongly suppressed at stimulus onset asynchronies less than 50 ms. This transition in metacontrast function has been typically interpreted as an increase in intrachannel inhibition of the sustained activities functionally linked to object visibility and identity. Our EEG analyses revealed an early (160-300 ms) and a late (300-550 ms) spatiotemporal cluster associated with this effect of polarity. The early cluster was mainly over occipital and parieto-occipital scalp sites. On the other hand, the later modulations of the evoked activities were centered over parietal and centro-parietal sites. Since both of these clusters were beyond 160 ms, the EEG results point to late recurrent inhibitory mechanisms. Although the findings here do not directly preclude other proposed mechanisms for metacontrast, they highlight the involvement of recurrent intrachannel inhibition in metacontrast masking.

Image luminance changes contrast sensitivity in visual cortex

Accurate measures of contrast sensitivity are important for evaluating visual disease progression and for navigation safety. Previous measures suggested that cortical contrast sensitivity was constant across widely different luminance ranges experienced indoors and outdoors. Against this notion, here, we show that luminance range changes contrast sensitivity in both cat and human cortex, and the changes are different for dark and light stimuli. As luminance range increases, contrast sensitivity increases more within cortical pathways signaling lights than those signaling darks. Conversely, when the luminance range is constant, light-dark differences in contrast sensitivity remain relatively constant even if background luminance changes. We show that a Naka-Rushton function modified to include luminance range and light-dark polarity accurately replicates both the statistics of light-dark features in natural scenes and the cortical responses to multiple combinations of contrast and luminance. We conclude that differences in light-dark contrast increase with luminance range and are largest in bright environments.

Motion-Based Acuity Task: Full Visual Field Measurement of Shape and Motion Perception

Purpose

Damage of retinal representation of the visual field affects its local features and the spared, unaffected parts. Measurements of visual deficiencies in ophthalmological patients are separated for central (shape) or peripheral (motion and space perception) properties, and acuity tasks rely on stationary stimuli. We explored the benefit of measuring shape and motion perception simultaneously using a new motion-based acuity task.

Methods

Eight healthy control subjects, three patients with retinitis pigmentosa (RP; tunnel vision), and 2 patients with Stargardt disease (STGD) juvenile macular degeneration were included. To model the peripheral loss, we narrowed the visual field in controls to 10 degrees. Negative and positive contrast of motion signals were tested in random-dot kinematograms (RDKs), where shapes were separated from the background by the motion of dots based on coherence, direction, or velocity. The task was to distinguish a circle from an ellipse. The difficulty of the task increased as ellipse became more circular until reaching the acuity limit.

Results

High velocity, negative contrast was more difficult for all, and for patients with STGD, it was too difficult to participate. A slower velocity improved acuity for all participants.

Conclusions

Proposed acuity testing not only allows for the full assessment of vision but also advances the capability of standard testing with the potential to detect spare visual functions.

Translational Relevance

The motion-based acuity task might be a practical tool for assessing vision loss and revealing undetected, undamaged, or strengthened properties of the injured visual system by standard testing, as suggested here for two patients with STGD and three patients with RP.

Evidence for the intrinsically nonlinear nature of receptive fields in vision

The responses of visual neurons, as well as visual perception phenomena in general, are highly nonlinear functions of the visual input, while most vision models are grounded on the notion of a linear receptive field (RF). The linear RF has a number of inherent problems: it changes with the input, it presupposes a set of basis functions for the visual system, and it conflicts with recent studies on dendritic computations. Here we propose to model the RF in a nonlinear manner, introducing the intrinsically nonlinear receptive field (INRF). Apart from being more physiologically plausible and embodying the efficient representation principle, the INRF has a key property of wide-ranging implications: for several vision science phenomena where a linear RF must vary with the input in order to predict responses, the INRF can remain constant under different stimuli. We also prove that Artificial Neural Networks with INRF modules instead of linear filters have a remarkably improved performance and better emulate basic human perception. Our results suggest a change of paradigm for vision science as well as for artificial intelligence.

Color illusions also deceive CNNs for low-level vision tasks: Analysis and implications

The study of visual illusions has proven to be a very useful approach in vision science. In this work we start by showing that, while convolutional neural networks (CNNs) trained for low-level visual tasks in natural images may be deceived by brightness and color illusions, some network illusions can be inconsistent with the perception of humans. Next, we analyze where these similarities and differences may come from. On one hand, the proposed linear eigenanalysis explains the overall similarities: in simple CNNs trained for tasks like denoising or deblurring, the linear version of the network has center-surround receptive fields, and global transfer functions are very similar to the human achromatic and chromatic contrast sensitivity functions in human-like opponent color spaces. These similarities are consistent with the long-standing hypothesis that considers low-level visual illusions as a by-product of the optimization to natural environments. Specifically, here human-like features emerge from error minimization. On the other hand, the observed differences must be due to the behavior of the human visual system not explained by the linear approximation. However, our study also shows that more 'flexible' network architectures, with more layers and a higher degree of nonlinearity, may actually have a worse capability of reproducing visual illusions. This implies, in line with other works in the vision science literature, a word of caution on using CNNs to study human vision: on top of the intrinsic limitations of the L + NL formulation of artificial networks to model vision, the nonlinear behavior of flexible architectures may easily be markedly different from that of the visual system.

Functional Specialization of ON and OFF Cortical Pathways for Global-Slow and Local-Fast Vision

Visual information is processed in the cortex by ON and OFF pathways that respond to light and dark stimuli. Responses to darks are stronger, faster, and driven by a larger number of cortical neurons than responses to lights. Here, we demonstrate that these light-dark cortical asymmetries reflect a functional specialization of ON and OFF pathways for different stimulus properties. We show that large long-lasting stimuli drive stronger cortical responses when they are light, whereas small fast stimuli drive stronger cortical responses when they are dark. Moreover, we show that these light-dark asymmetries are preserved under a wide variety of luminance conditions that range from photopic to low mesopic light. Our results suggest that ON and OFF pathways extract different spatiotemporal information from visual scenes, making OFF local-fast signals better suited to maximize visual acuity and ON global-slow signals better suited to guide the eye movements needed for retinal image stabilization.

Multiple-target tracking in human and machine vision

Humans are able to track multiple objects at any given time in their daily activities—for example, we can drive a car while monitoring obstacles, pedestrians, and other vehicles. Several past studies have examined how humans track targets simultaneously and what underlying behavioral and neural mechanisms they use. At the same time, computer-vision researchers have proposed different algorithms to track multiple targets automatically. These algorithms are useful for video surveillance, team-sport analysis, video analysis, video summarization, and human–computer interaction. Although there are several efficient biologically inspired algorithms in artificial intelligence, the human multiple-target tracking (MTT) ability is rarely imitated in computer-vision algorithms. In this paper, we review MTT studies in neuroscience and biologically inspired MTT methods in computer vision and discuss the ways in which they can be seen as complementary.

Multiple-target tracking (MTT) is a challenging task vital for both a human’s daily life and for many artificial intelligent systems, such as those used for urban traffic control. Neuroscientists are interested in discovering the underlying neural mechanisms that successfully exploit cognitive resources, e.g., spatial attention or memory, during MTT. Computer-vision specialists aim to develop powerful MTT algorithms based on advanced models or data-driven computational methods. In this paper, we review MTT studies from both communities and discuss how findings from cognitive studies can inspire developers to construct higher performing MTT algorithms. Moreover, some directions have been proposed through which MTT algorithms could raise new questions in the cognitive science domain, and answering them can shed light on neural processes underlying MTT.

Luminance potentiates human visuocortical responses

Our visual system is tasked with transforming variations in light within our environment into a coherent percept, typically described using properties such as luminance and contrast. Models of vision often downplay the importance of luminance in shaping cortical responses, instead prioritizing representations that do not covary with overall luminance (i.e., contrast), and yet visuocortical response properties that may reflect luminance encoding remain poorly understood. In this study, we examined whether well-established visuocortical response properties may also reflect luminance encoding, challenging the idea that luminance information itself plays no significant role in supporting visual perception. To do so, we measured functional activity in human visual cortex when presenting stimuli varying in contrast and mean luminance, and found that luminance response functions are strongly contrast dependent between 50 and 250 cd/m², confirmed with a subsequent experiment. High-contrast stimuli produced linearly increasing responses as luminance increased logarithmically for all early visual areas, whereas low-contrast stimuli produced either flat (V1) or assorted positive linear (V2 and V3) response profiles. These results reveal that the mean luminance information of a visual signal persists within visuocortical representations, potentially reflecting an inherent imbalance of excitatory and inhibitory components that can be either contrast dependent (V1 and V2) or contrast invariant (V3). The role of luminance should be considered when the aim is to drive potent visually evoked responses and when activity is compared across studies. More broadly, overall luminance should be weighed heavily as a core feature of the visual system and should play a significant role in cortical models of vision.NEW & NOTEWORTHY This neuroimaging study investigates the influence of overall luminance on population activity in human visual cortex. We discovered that the response to a particular stimulus contrast level is reliant, in part, on the mean luminance of a signal, revealing that the mean luminance information of our environment is represented within the visual cortex. The results challenge a long-standing misconception about the role of luminance information in the processing of visual information at the cortical level.

Stimulus-Specific Adaptation Decreases the Coupling of Spikes to LFP Phase

Stimulus repetition suppresses the neural activity in different sensory areas of the brain. This mechanism of so-called stimulus-specific adaptation (SSA) has been observed in both spiking activity and local field potential (LFP) responses. However, much remains to be known about the effect of SSA on the spike–LFP relation. In this study, we approached this issue by investigating the spike-phase coupling (SPC) in control and adapting paradigms. For the control paradigm, pure tones were presented in a random unbiased sequence. In the adapting paradigm, the same stimuli were presented in a random pattern but it was biased to an adapter stimulus. In fact, the adapter occupied 80% of the adapting sequence. During the tasks, LFP and multi-unit activity were recorded simultaneously from the primary auditory cortex of 15 anesthetized rats. To clarify the effect of adaptation on the relation between spike and LFP responses, the SPC of the adapter stimulus in these two paradigms was evaluated. Here, we employed phase locking value method for calculating the SPC. Our data show a strong coupling of spikes to LFP phase most prominently in beta band. This coupling was observed to decrease in the adapting condition compared to the control one. Importantly, we found that adaptation reduces spikes dominantly from the preferred phase of LFP in which spikes are more likely to be present there. As a result, the preferred phase of LFP may play a key role in coordinating neuronal spiking activity in neural adaptation mechanism. This finding is important for interpretation of the underlying neural mechanism of adaptation and also can be used in the context of the network and related connectivity models.

Amblyopia Affects the ON Visual Pathway More than the OFF

Visual information reaches the cerebral cortex through parallel ON and OFF pathways that signal the presence of light and dark stimuli in visual scenes. We have previously demonstrated that optical blur reduces visual salience more for light than dark stimuli because it removes the high spatial frequencies from the stimulus, and low spatial frequencies drive weaker ON than OFF cortical responses. Therefore, we hypothesized that sustained optical blur during brain development should weaken ON cortical pathways more than OFF, increasing the dominance of darks in visual perception. Here we provide support for this hypothesis in humans with anisometropic amblyopia who suffered sustained optical blur early after birth in one of the eyes. In addition, we show that the dark dominance in visual perception also increases in strabismic amblyopes that have their vision to high spatial frequencies reduced by mechanisms not associated with optical blur. Together, we show that amblyopia increases visual dark dominance by 3-10 times and that the increase in dark dominance is strongly correlated with amblyopia severity. These results can be replicated with a computational model that uses greater luminance/response saturation in ON than OFF pathways and, as a consequence, reduces more ON than OFF cortical responses to stimuli with low spatial frequencies. We conclude that amblyopia affects the ON cortical pathway more than the OFF, a finding that could have implications for future amblyopia treatments.SIGNIFICANCE STATEMENT Amblyopia is a loss of vision that affects 2-5% of children across the world and originates from a deficit in visual cortical circuitry. Current models assume that amblyopia affects similarly ON and OFF visual pathways, which signal light and dark features in visual scenes. Against this current belief, here we demonstrate that amblyopia affects the ON visual pathway more than the OFF, a finding that could have implications for new amblyopia treatments targeted at strengthening a weak ON visual pathway.