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.

Large Visual Stimuli Induce Two Distinct Gamma Oscillations in Primate Visual Cortex.

Recent studies have shown the existence of two gamma rhythms in the hippocampus subserving different functions but, to date, primate studies in primary visual cortex have reported a single gamma rhythm. Here, we show that large visual stimuli induce a slow gamma (25-45 Hz) in area V1 of two awake adult female bonnet monkeys and in the EEG of 15 human subjects (7 males and 8 females), in addition to the traditionally known fast gamma (45-70 Hz). The two rhythms had different tuning characteristics for stimulus orientation, contrast, drift speed, and size. Further, fast gamma had short latency, strongly entrained spikes and was coherent over short distances, reflecting short-range processing, whereas slow gamma appeared to reflect long-range processing. Together, two gamma rhythms can potentially provide better coding or communication mechanisms and a more comprehensive biomarker for diagnosis of mental disorders.SIGNIFICANCE STATEMENT Gamma rhythm has been associated with high-level cognitive functions such as attention and feature binding and has been reported to be abnormal in brain disorders such as autism and schizophrenia. Unlike previous studies that have shown a single gamma rhythm in the primate visual cortex, we found that large visual gratings induce two distinct gamma oscillations in both monkey LFP and human EEG. These rhythms, termed slow (25-45 Hz) and fast (45-70 Hz), exhibited distinct tuning preferences, latencies, and coherence profiles, potentially reflecting processing at two different ranges. Multiple gamma oscillations in visual cortex may provide a richer representation of external visual stimuli and could be used for developing brain-machine interfacing applications and screening tests for neuropsychiatric disorders.

Benchmarking laminar fMRI: Neuronal spiking and synaptic activity during top-down and bottom-up processing in the different layers of cortex.

High resolution laminar fMRI is beginning to probe responses in the different layers of cortex. What can we expect this exciting new technique to discover about cortical processing and how can we verify that it is producing an accurate picture of the underlying laminar differences in neural processing? This review will address our knowledge of laminar cortical circuitry gained from electrophysiological studies in macaque monkeys with a focus on the primary visual cortex, as this area has been most often targeted in both laminar electrophysiological and fMRI studies. We will review how recent studies are attempting to verify the accuracy of laminar fMRI by recreating the known laminar profiles of various neural tuning properties. Furthermore, we will examine how feedforward and feedback-related neural processes engage different cortical layers, producing canonical patterns of spiking and synaptic activity as estimated by the analysis of current-source density. These results provide a benchmark for recent studies aiming to examine the profiles of bottom-up and top-down processes with laminar fMRI. Finally, we will highlight particularly useful paradigms and approaches which may help us to understand processing in the different layers of the human cerebral cortex.

Complex Visual Motion Representation in Mouse Area V1.

Rodent visual cortex has a hierarchical architecture similar to that of higher mammals (Coogan and Burkhalter, 1993; Marshel et al., 2011; Wang et al., 2012). Although notable differences exist between the species in terms or receptive field sizes and orientation map organization (Dräger, 1975; Gattass et al., 1987; Van den Bergh et al., 2010), mouse V1 is thought to respond to local orientation and visual motion elements rather than to global patterns of motion, similar to V1 in higher mammals (Niell and Stryker, 2008; Bonin et al., 2011). However, recent results are inconclusive: some argue mouse V1 is analogous to monkey V1 (Juavinett and Callaway, 2015); others argue that it displays complex motion responses (Muir et al., 2015). We used type I plaids formed by the additive superposition of moving gratings (Adelson and Movshon, 1982; Movshon et al., 1985; Albright and Stoner, 1995) to investigate this question. We show that mouse V1 contains a considerably smaller fraction of component-motion-selective neurons (∼17% vs ∼84%), and a larger fraction of pattern-motion-selective neurons (∼10% vs <1.3%) compared with primate/cat V1. The direction of optokinetic nystagmus correlates with visual perception in higher mammals (Fox et al., 1975; Logothetis and Schall, 1990; Wei and Sun, 1998; Watanabe, 1999; Naber et al., 2011). Measurement of optokinetic responses to plaid stimuli revealed that mice demonstrate bistable perception, sometimes tracking individual stimulus components and others the global pattern of motion. Moreover, bistable optokinetic responses cannot be entirely attributed to subcortical circuitry as V1 lesions alter the fraction of responses occurring along pattern versus component motion. These observations suggest that area V1 input contributes to complex motion perception in the mouse. SIGNIFICANCE STATEMENT: Area V1 in the mouse is hierarchically similar but not necessarily identical to area V1 in cats and primates. Here we demonstrate that area V1 neurons process complex motion plaid stimuli differently in mice versus in cats or primates. Specifically, a smaller proportion of mouse V1 cells are sensitive to component motion, and a larger proportion to pattern motion than are found in area V1 of cats/primates. Furthermore, we demonstrate for the first time that mice exhibit bistable visual perception of plaid stimuli, and that this depends, at least in part, on area V1 input. Finally, we suggest that the relative proportion of component-motion-selective responses to pattern-motion-selective responses in mouse V1 may bias visual perception, as evidenced by changes in the direction of elicited optokinetic responses.

Cortical depth profiles of luminance contrast responses in human V1 and V2 using 7 T fMRI.

Neural activity in early visual cortex is modulated by luminance contrast. Cortical depth (i.e., laminar) contrast responses have been studied in monkey early visual cortex, but not in humans. In addition to the high spatial resolution needed and the ensuing low signal-to-noise ratio, laminar studies in humans using fMRI are hampered by the strong venous vascular weighting of the fMRI signal. In this study, we measured luminance contrast responses in human V1 and V2 with high-resolution fMRI at 7 T. To account for the effect of intracortical ascending veins, we applied a novel spatial deconvolution model to the fMRI depth profiles. Before spatial deconvolution, the contrast response in V1 showed a slight local maximum at mid cortical depth, whereas V2 exhibited a monotonic signal increase toward the cortical surface. After applying the deconvolution, both V1 and V2 showed a pronounced local maximum at mid cortical depth, with an additional peak in deep grey matter, especially in V1. Moreover, we found a difference in contrast sensitivity between V1 and V2, but no evidence for variations in contrast sensitivity as a function of cortical depth. These findings are in agreement with results obtained in nonhuman primates, but further research will be needed to validate the spatial deconvolution approach.

Neuronal nonlinearity explains greater visual spatial resolution for darks than lights.

Astronomers and physicists noticed centuries ago that visual spatial resolution is higher for dark than light stimuli, but the neuronal mechanisms for this perceptual asymmetry remain unknown. Here we demonstrate that the asymmetry is caused by a neuronal nonlinearity in the early visual pathway. We show that neurons driven by darks (OFF neurons) increase their responses roughly linearly with luminance decrements, independent of the background luminance. However, neurons driven by lights (ON neurons) saturate their responses with small increases in luminance and need bright backgrounds to approach the linearity of OFF neurons. We show that, as a consequence of this difference in linearity, receptive fields are larger in ON than OFF thalamic neurons, and cortical neurons are more strongly driven by darks than lights at low spatial frequencies. This ON/OFF asymmetry in linearity could be demonstrated in the visual cortex of cats, monkeys, and humans and in the cat visual thalamus. Furthermore, in the cat visual thalamus, we show that the neuronal nonlinearity is present at the ON receptive field center of ON-center neurons and ON receptive field surround of OFF-center neurons, suggesting an origin at the level of the photoreceptor. These results demonstrate a fundamental difference in visual processing between ON and OFF channels and reveal a competitive advantage for OFF neurons over ON neurons at low spatial frequencies, which could be important during cortical development when retinal images are blurred by immature optics in infant eyes.

Radial bias is not necessary for orientation decoding.

Multivariate pattern analysis can be used to decode the orientation of a viewed grating from fMRI signals in early visual areas. Although some studies have reported identifying multiple sources of the orientation information that make decoding possible, a recent study argued that orientation decoding is only possible because of a single source: a coarse-scale retinotopically organized preference for radial orientations. Here we aim to resolve these discrepant findings. We show that there were subtle, but critical, experimental design choices that led to the erroneous conclusion that a radial bias is the only source of orientation information in fMRI signals. In particular, we show that the reliance on a fast temporal-encoding paradigm for spatial mapping can be problematic, as effects of space and time become conflated and lead to distorted estimates of a voxel's orientation or retinotopic preference. When we implement minor changes to the temporal paradigm or to the visual stimulus itself, by slowing the periodic rotation of the stimulus or by smoothing its contrast-energy profile, we find significant evidence of orientation information that does not originate from radial bias. In an additional block-paradigm experiment where space and time were not conflated, we apply a formal model comparison approach and find that many voxels exhibit more complex tuning properties than predicted by radial bias alone or in combination with other known coarse-scale biases. Our findings support the conclusion that radial bias is not necessary for orientation decoding. In addition, our study highlights potential limitations of using temporal phase-encoded fMRI designs for characterizing voxel tuning properties.

Chromatic and Achromatic Spatial Resolution of Local Field Potentials in Awake Cortex.

Local field potentials (LFPs) have become an important measure of neuronal population activity in the brain and could provide robust signals to guide the implant of visual cortical prosthesis in the future. However, it remains unclear whether LFPs can detect weak cortical responses (e.g., cortical responses to equiluminant color) and whether they have enough visual spatial resolution to distinguish different chromatic and achromatic stimulus patterns. By recording from awake behaving macaques in primary visual cortex, here we demonstrate that LFPs respond robustly to pure chromatic stimuli and exhibit ∼2.5 times lower spatial resolution for chromatic than achromatic stimulus patterns, a value that resembles the ratio of achromatic/chromatic resolution measured with psychophysical experiments in humans. We also show that, although the spatial resolution of LFP decays with visual eccentricity as is also the case for single neurons, LFPs have higher spatial resolution and show weaker response suppression to low spatial frequencies than spiking multiunit activity. These results indicate that LFP recordings are an excellent approach to measure spatial resolution from local populations of neurons in visual cortex including those responsive to color.

Microstimulation of area V4 has little effect on spatial attention and on perception of phosphenes evoked in area V1.

Previous transcranial magnetic stimulation (TMS) studies suggested that feedback from higher to lower areas of the visual cortex is important for the access of visual information to awareness. However, the influence of cortico-cortical feedback on awareness and the nature of the feedback effects are not yet completely understood. In the present study, we used electrical microstimulation in the visual cortex of monkeys to test the hypothesis that cortico-cortical feedback plays a role in visual awareness. We investigated the interactions between the primary visual cortex (V1) and area V4 by applying microstimulation in both cortical areas at various delays. We report that the monkeys detected the phosphenes produced by V1 microstimulation but subthreshold V4 microstimulation did not influence V1 phosphene detection thresholds. A second experiment examined the influence of V4 microstimulation on the monkeys' ability to detect the dimming of one of three peripheral visual stimuli. Again, microstimulation of a group of V4 neurons failed to modulate the monkeys' perception of a stimulus in their receptive field. We conclude that conditions exist where microstimulation of area V4 has only a limited influence on visual perception.

What multiplexing means for the interpretation of functional MRI data.

Despite technology advances that have enabled routine acquisition of functional MRI data with sub-millimeter resolution, the inferences that cognitive neuroscientists must make to link fMRI data to behavior are complicated. Thus, a single dataset subjected to different analyses can be interpreted in different ways. This article presents two optical analogies that can be useful for framing fMRI analyses in a way that allows for multiple interpretations of fMRI data to be valid simultaneously without undermining each other. The first is reflection: when an object is reflected in a mirrored surface, it appears as if the reflected object is sharing space with the mirrored object, but of course it is not. This analogy can be a good guide for interpreting the fMRI signal, since even at sub-millimeter resolutions the signal is determined by a mixture of local and long-range neural computations. The second is refraction. If we view an object through a multi-faceted prism or gemstone, our view will change-sometimes dramatically-depending on our viewing angle. In the same way, interpretation of fMRI data (inference of underlying neuronal activity) can and should be different depending on the analysis approach. Rather than representing a weakness of the methodology, or the superiority of one approach over the other (for example, simple regression analysis versus multi-voxel pattern analysis), this is an expected consequence of how information is multiplexed in the neural networks of the brain: multiple streams of information are simultaneously present in each location. The fact that any one analysis typically shows only one view of the data also puts some parentheses around fMRI practitioners' constant search for ground truth against which to compare their data. By holding our interpretations lightly and understanding that many interpretations of the data can all be true at the same time, we do a better job of preparing ourselves to appreciate, and eventually understand, the complexity of the brain and the behavior it produces.

The representation of occluded image regions in area V1 of monkeys and humans.

Neuronal activity in the primary visual cortex (V1) is driven by feedforward input from within the neurons' receptive fields (RFs) and modulated by contextual information in regions surrounding the RF. The effect of contextual information on spiking activity occurs rapidly and is therefore challenging to dissociate from feedforward input. To address this challenge, we recorded the spiking activity of V1 neurons in monkeys viewing either natural scenes or scenes where the information in the RF was occluded, effectively removing the feedforward input. We found that V1 neurons responded rapidly and selectively to occluded scenes. V1 responses elicited by occluded stimuli could be used to decode individual scenes and could be predicted from those elicited by non-occluded images, indicating that there is an overlap between visually driven and contextual responses. We used representational similarity analysis to show that the structure of V1 representations of occluded scenes measured with electrophysiology in monkeys correlates strongly with the representations of the same scenes in humans measured with functional magnetic resonance imaging (fMRI). Our results reveal that contextual influences rapidly alter V1 spiking activity in monkeys over distances of several degrees in the visual field, carry information about individual scenes, and resemble those in human V1. VIDEO ABSTRACT.

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.

Effect of Cross-Orientation Normalization on Different Neural Measures in Macaque Primary Visual Cortex.

Divisive normalization is a canonical mechanism that can explain a variety of sensory phenomena. While normalization models have been used to explain spiking activity in response to different stimulus/behavioral conditions in multiple brain areas, it is unclear whether similar models can also explain modulation in population-level neural measures such as power at various frequencies in local field potentials (LFPs) or steady-state visually evoked potential (SSVEP) that is produced by flickering stimuli and popular in electroencephalogram studies. To address this, we manipulated normalization strength by presenting static as well as flickering orthogonal superimposed gratings (plaids) at varying contrasts to 2 female monkeys while recording multiunit activity (MUA) and LFP from the primary visual cortex and quantified the modulation in MUA, gamma (32-80 Hz), high-gamma (104-248 Hz) power, as well as SSVEP. Even under similar stimulus conditions, normalization strength was different for the 4 measures and increased as: spikes, high-gamma, SSVEP, and gamma. However, these results could be explained using a normalization model that was modified for population responses, by varying the tuned normalization parameter and semisaturation constant. Our results show that different neural measures can reflect the effect of stimulus normalization in different ways, which can be modeled by a simple normalization model.

Stimulus-specific plasticity of macaque V1 spike rates and gamma.

When a visual stimulus is repeated, average neuronal responses typically decrease, yet they might maintain or even increase their impact through increased synchronization. Previous work has found that many repetitions of a grating lead to increasing gamma-band synchronization. Here, we show in awake macaque area V1 that both repetition-related reductions in firing rate and increases in gamma are specific to the repeated stimulus. These effects show some persistence on the timescale of minutes. Gamma increases are specific to the presented stimulus location. Further, repetition effects on gamma and on firing rates generalize to images of natural objects. These findings support the notion that gamma-band synchronization subserves the adaptive processing of repeated stimulus encounters.

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.

Grey-Matter Thickness of the Left But Not the Right Primary Visual Area Correlates with Autism Traits in Typically Developing Adults.

We examined whether functional and structural variability in the primary visual area (V1) correlated with autism traits. Twenty-nine participants (16 males; MAge = 26.4 years, SDAge = 4.0 years) completed the autism-spectrum quotient (AQ) questionnaire prior to a magnetic resonance imaging session. The total AQ scores was used to assess the degree of self-reported autism traits. The average functional activation in V1 to visual stimulation and its average grey-matter thickness were calculated. There were no correlations between functional activation in V1 and autism traits. Conversely, grey-matter thickness of the left but not the right V1 correlated with autism traits. We conclude that structural changes in the left V1 could be a marker for the presence of autism traits.

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.

A Model of Motion Processing in the Visual Cortex Using Neural Field With Asymmetric Hebbian Learning.

Neurons in the dorsal pathway of the visual cortex are thought to be involved in motion processing. The first site of motion processing is the primary visual cortex (V1), encoding the direction of motion in local receptive fields, with higher order motion processing happening in the middle temporal area (MT). Complex motion properties like optic flow are processed in higher cortical areas of the Medial Superior Temporal area (MST). In this study, a hierarchical neural field network model of motion processing is presented. The model architecture has an input layer followed by either one or cascade of two neural fields (NF): the first of these, NF1, represents V1, while the second, NF2, represents MT. A special feature of the model is that lateral connections used in the neural fields are trained by asymmetric Hebbian learning, imparting to the neural field the ability to process sequential information in motion stimuli. The model was trained using various traditional moving patterns such as bars, squares, gratings, plaids, and random dot stimulus. In the case of bar stimuli, the model had only a single NF, the neurons of which developed a direction map of the moving bar stimuli. Training a network with two NFs on moving square and moving plaids stimuli, we show that, while the neurons in NF1 respond to the direction of the component (such as gratings and edges) motion, the neurons in NF2 (analogous to MT) responding to the direction of the pattern (plaids, square object) motion. In the third study, a network with 2 NFs was simulated using random dot stimuli (RDS) with translational motion, and show that the NF2 neurons can encode the direction of the concurrent dot motion (also called translational flow motion), independent of the dot configuration. This translational RDS flow motion is decoded by a simple perceptron network (a layer above NF2) with an accuracy of 100% on train set and 90% on the test set, thereby demonstrating that the proposed network can generalize to new dot configurations. Also, the response properties of the model on different input stimuli closely resembled many of the known features of the neurons found in electrophysiological studies.

Effect of Stimulus Contrast and Visual Attention on Spike-Gamma Phase Relationship in Macaque Primary Visual Cortex.

Brain signals often show rhythmic activity in the so-called gamma range (30-80 Hz), whose magnitude and center frequency are modulated by properties of the visual stimulus such as size and contrast, as well as by cognitive processes such as attention. How gamma rhythm can potentially influence cortical processing remains unclear; previous studies have proposed a scheme called phase coding, in which the intensity of the incoming stimulus is coded in the position of the spike relative to the rhythm. Using chronically implanted microelectrode arrays in the primary visual cortex (area V1) of macaques engaged in an attention task while presenting stimuli of varying contrasts, we tested whether the phase of the gamma rhythm relative to spikes varied as a function of stimulus contrast and attentional state. A previous study had found no evidence of gamma phase coding for either contrast or attention in V1, but in that study spikes and local field potential (LFP) were recorded from the same electrode, due to which spike-gamma phase estimation could have been biased. Further, the filtering operation to obtain LFP could also have biased the gamma phase. By analyzing spikes and LFP from different electrodes, we found a weak but significant effect of attention, but not stimulus contrast, on gamma phase relative to spikes. The results remained consistent even after correcting the filter induced lags, although the absolute magnitude of gamma phase shifted by up to ~15°. Although we found a significant effect of attention, we argue that a small magnitude of phase shift as well as the dependence of phase angles on gamma power and center frequency limits a potential role of gamma in phase coding in V1.