Orientation and direction selectivity of neurons in V1 of alert monkeys: functional relationships and laminar distributions

Cortical direction selectivity increases from the input to the output layers of visual cortex

Sensitivity to motion direction is a feature of visual neurons that is essential for motion perception. Recent studies have suggested that direction selectivity is re-established at multiple stages throughout the visual hierarchy, which contradicts the traditional assumption that direction selectivity in later stages largely derives from that in earlier stages. By recording laminar responses in areas 17 and 18 of anesthetized cats of both sexes, we aimed to understand how direction selectivity is processed and relayed across 2 successive stages: the input layers and the output layers within the early visual cortices. We found a strong relationship between the strength of direction selectivity in the output layers and the input layers, as well as the preservation of preferred directions across the input and output layers. Moreover, direction selectivity was enhanced in the output layers compared to the input layers, with the response strength maintained in the preferred direction but reduced in other directions and under blank stimuli. We identified a direction-tuned gain mechanism for interlaminar signal transmission, which likely originated from both feedforward connections across the input and output layers and recurrent connections within the output layers. This direction-tuned gain, coupled with nonlinearity, contributed to the enhanced direction selectivity in the output layers. Our findings suggest that direction selectivity in later cortical stages partially inherits characteristics from earlier cortical stages and is further refined by intracortical connections.

Dependence of Contextual Modulation in Macaque V1 on Interlaminar Signal Flow

In visual cortex, neural correlates of subjective perception can be generated by modulation of activity from beyond the classical receptive field (CRF). In macaque V1, activity generated by nonclassical receptive field (nCRF) stimulation involves different intracortical circuitry than activity generated by CRF stimulation, suggesting that interactions between neurons across V1 layers differ under CRF and nCRF stimulus conditions. Using Neuropixels probes, we measured border ownership modulation within large, local populations of V1 neurons. We found that neurons in single columns preferred the same side of objects located outside of the CRF. In addition, we found that cross-correlations between pairs of neurons situated across feedback/horizontal and input layers differed between CRF and nCRF stimulation. Furthermore, independent of the comparison with CRF stimulation, we observed that the magnitude of border ownership modulation increased with the proportion of information flow from feedback/horizontal layers to input layers. These results demonstrate that the flow of signals between layers covaries with the degree to which neurons integrate information from beyond the CRF.

Comparison of orientation encoding across layers within single columns of primate V1 revealed by high-density recordings

Primary visual cortex (V1) has been the focus of extensive neurophysiological investigations, with its laminar organization serving as a crucial model for understanding the functional logic of neocortical microcircuits. Utilizing newly developed high-density, Neuropixels probes, we measured visual responses from large populations of simultaneously recorded neurons distributed across layers of macaque V1. Within single recordings, myriad differences in the functional properties of neuronal subpopulations could be observed. Notably, while standard measurements of orientation selectivity showed only minor differences between laminar compartments, decoding stimulus orientation from layer 4C responses outperformed both superficial and deep layers within the same cortical column. The superior orientation discrimination within layer 4C was associated with greater response reliability of individual neurons rather than lower correlated activity within neuronal populations. Our results underscore the efficacy of high-density electrophysiology in revealing the functional organization and network properties of neocortical microcircuits within single experiments.

Nonuniform and pathway-specific laminar processing of spatial frequencies in the primary visual cortex of primates

The neocortex comprises six cortical layers that play a crucial role in information processing; however, it remains unclear whether laminar processing is consistent across all regions within a single cortex. In this study, we demonstrate diverse laminar response patterns in the primary visual cortex (V1) of three male macaque monkeys when exposed to visual stimuli at different spatial frequencies (SFs). These response patterns can be categorized into two groups. One group exhibit suppressed responses in the output layers for all SFs, while the other type shows amplified responses specifically at high SFs. Further analysis suggests that both magnocellular (M) and parvocellular (P) pathways contribute to the suppressive effect through feedforward mechanisms, whereas amplification is specific to local recurrent mechanisms within the parvocellular pathway. These findings highlight the non-uniform distribution of neural mechanisms involved in laminar processing and emphasize how pathway-specific amplification selectively enhances representations of high-SF information in primate V1.

Computational components of visual predictive coding circuitry

If a full visual percept can be said to be a 'hypothesis', so too can a neural 'prediction' - although the latter addresses one particular component of image content (such as 3-dimensional organisation, the interplay between lighting and surface colour, the future trajectory of moving objects, and so on). And, because processing is hierarchical, predictions generated at one level are conveyed in a backward direction to a lower level, seeking to predict, in fact, the neural activity at that prior stage of processing, and learning from errors signalled in the opposite direction. This is the essence of 'predictive coding', at once an algorithm for information processing and a theoretical basis for the nature of operations performed by the cerebral cortex. Neural models for the implementation of predictive coding invoke specific functional classes of neuron for generating, transmitting and receiving predictions, and for producing reciprocal error signals. Also a third general class, 'precision' neurons, tasked with regulating the magnitude of error signals contingent upon the confidence placed upon the prediction, i.e., the reliability and behavioural utility of the sensory data that it predicts. So, what is the ultimate source of a 'prediction'? The answer is multifactorial: knowledge of the current environmental context and the immediate past, allied to memory and lifetime experience of the way of the world, doubtless fine-tuned by evolutionary history too. There are, in consequence, numerous potential avenues for experimenters seeking to manipulate subjects' expectation, and examine the neural signals elicited by surprising, and less surprising visual stimuli. This review focuses upon the predictive physiology of mouse and monkey visual cortex, summarising and commenting on evidence to date, and placing it in the context of the broader field. It is concluded that predictive coding has a firm grounding in basic neuroscience and that, unsurprisingly, there remains much to learn.

Motion direction is represented as a bimodal probability distribution in the human visual cortex

Humans infer motion direction from noisy sensory signals. We hypothesize that to make these inferences more precise, the visual system computes motion direction not only from velocity but also spatial orientation signals - a 'streak' created by moving objects. We implement this hypothesis in a Bayesian model, which quantifies knowledge with probability distributions, and test its predictions using psychophysics and fMRI. Using a probabilistic pattern-based analysis, we decode probability distributions of motion direction from trial-by-trial activity in the human visual cortex. Corroborating the predictions, the decoded distributions have a bimodal shape, with peaks that predict the direction and magnitude of behavioral errors. Interestingly, we observe similar bimodality in the distribution of the observers' behavioral responses across trials. Together, these results suggest that observers use spatial orientation signals when estimating motion direction. More broadly, our findings indicate that the cortical representation of low-level visual features, such as motion direction, can reflect a combination of several qualitatively distinct signals.

Prefrontal cortex encodes value pop-out in visual search

Recent evidence demonstrates that long-term object value association can enhance visual search efficiency, a phenomenon known as value pop-out. However, the neural mechanism underlying this effect is not fully understood. Given the known role of the ventrolateral prefrontal cortex (vlPFC) in visual search and value memory, we recorded its single-unit activity (n = 526) in two macaque monkeys while they engaged in the value-driven search. Monkeys had to determine whether a high-value target was present within a variable number of low-value objects. Differential neural firing, as well as gamma-band power, indicated the presence of a target within ∼150ms of display onset. Notably, this differential activity was negatively correlated with search time and had reduced set-size dependence during efficient search. On the other hand, neural firing and its variability were higher in inefficient search. These findings implicate vlPFC in rapid detection of valuable targets which would be a crucial skill in competitive environments.

Improving the validity of neuroimaging decoding tests of invariant and configural neural representation

Many research questions in sensory neuroscience involve determining whether the neural representation of a stimulus property is invariant or specific to a particular stimulus context (e.g., Is object representation invariant to translation? Is the representation of a face feature specific to the context of other face features?). Between these two extremes, representations may also be context-tolerant or context-sensitive. Most neuroimaging studies have used operational tests in which a target property is inferred from a significant test against the null hypothesis of the opposite property. For example, the popular cross-classification test concludes that representations are invariant or tolerant when the null hypothesis of specificity is rejected. A recently developed neurocomputational theory suggests two insights regarding such tests. First, tests against the null of context-specificity, and for the alternative of context-invariance, are prone to false positives due to the way in which the underlying neural representations are transformed into indirect measurements in neuroimaging studies. Second, jointly performing tests against the nulls of invariance and specificity allows one to reach more precise and valid conclusions about the underlying representations, particularly when the null of invariance is tested using the fine-grained information from classifier decision variables rather than only accuracies (i.e., using the decoding separability test). Here, we provide empirical and computational evidence supporting both of these theoretical insights. In our empirical study, we use encoding of orientation and spatial position in primary visual cortex as a case study, as previous research has established that these properties are encoded in a context-sensitive way. Using fMRI decoding, we show that the cross-classification test produces false-positive conclusions of invariance, but that more valid conclusions can be reached by jointly performing tests against the null of invariance. The results of two simulations further support both of these conclusions. We conclude that more valid inferences about invariance or specificity of neural representations can be reached by jointly testing against both hypotheses, and using neurocomputational theory to guide the interpretation of results.

Attention differentially modulates multiunit activity in the lateral geniculate nucleus and V1 of macaque monkeys

Attention promotes the selection of behaviorally relevant sensory signals from the barrage of sensory information available. Visual attention modulates the gain of neuronal activity in all visual brain areas examined, although magnitudes of gain modulations vary across areas. For example, attention gain magnitudes in the dorsal lateral geniculate nucleus (LGN) and primary visual cortex (V1) vary tremendously across fMRI measurements in humans and electrophysiological recordings in behaving monkeys. We sought to determine whether these discrepancies are due simply to differences in species or measurement, or more nuanced properties unique to each visual brain area. We also explored whether robust and consistent attention effects, comparable to those measured in humans with fMRI, are observable in the LGN or V1 of monkeys. We measured attentional modulation of multiunit activity in the LGN and V1 of macaque monkeys engaged in a contrast change detection task requiring shifts in covert visual spatial attention. Rigorous analyses of LGN and V1 multiunit activity revealed robust and consistent attentional facilitation throughout V1, with magnitudes comparable to those observed with fMRI. Interestingly, attentional modulation in the LGN was consistently negligible. These findings demonstrate that discrepancies in attention effects are not simply due to species or measurement differences. We also examined whether attention effects correlated with the feature selectivity of recorded multiunits. Distinct relationships suggest that attentional modulation of multiunit activity depends upon the unique structure and function of visual brain areas.

Surround Modulation Properties of Tectal Neurons in Pigeons Characterized by Moving and Flashed Stimuli

Simple Summary

Surround modulation is a basic visual attribute of sensory neurons in many species and has been extensively characterized in mammal primary visual cortex, lateral geniculate nucleus, and superior colliculus. Little attention has been paid to birds, which have a highly developed visual system. We undertook a systematic analysis on surround modulation properties of tectal neurons in pigeons (Columba livia). This study complements existing studies on surrounding modulation properties in non-mammalian species and deepens the understanding of mechanisms of figure–background segmentation performed by avians.

Abstract

Surround modulation has been abundantly studied in several mammalian brain areas, including the primary visual cortex, lateral geniculate nucleus, and superior colliculus (SC), but systematic analysis is lacking in the avian optic tectum (OT, homologous to mammal SC). Here, multi-units were recorded from pigeon (Columba livia) OT, and responses to different sizes of moving, flashed squares, and bars were compared. The statistical results showed that most tectal neurons presented suppressed responses to larger stimuli in both moving and flashed paradigms, and suppression induced by flashed squares was comparable with moving ones when the stimuli center crossed the near classical receptive field (CRF) center, which corresponded to the full surrounding condition. Correspondingly, the suppression grew weaker when the stimuli center moved across the CRF border, equivalent to partially surrounding conditions. Similarly, suppression induced by full surrounding flashed squares was more intense than by partially surrounding flashed bars. These results suggest that inhibitions performed on tectal neurons appear to be full surrounding rather than locally lateral. This study enriches the understanding of surround modulation properties of avian tectum neurons and provides possible hypotheses about the arrangement of inhibitions from other nuclei, both of which are important for clarifying the mechanism of target detection against clutter background performed by avians.

Analytic Model for Feature Maps in the Primary Visual Cortex

A compact analytic model is proposed to describe the combined orientation preference (OP) and ocular dominance (OD) features of simple cells and their mutual constraints on the spatial layout of the combined OP-OD map in the primary visual cortex (V1). This model consists of three parts: (i) an anisotropic Laplacian (AL) operator that represents the local neural sensitivity to the orientation of visual inputs; and (ii) obtain a receptive field (RF) operator that models the anisotropic spatial projection from nearby neurons to a given V1 cell over scales of a few tenths of a millimeter and combines with the AL operator to give an overall OP operator; and (iii) a map that describes how the parameters of these operators vary approximately periodically across V1. The parameters of the proposed model maximize the neural response at a given OP with an OP tuning curve fitted to experimental results. It is found that the anisotropy of the AL operator does not significantly affect OP selectivity, which is dominated by the RF anisotropy, consistent with Hubel and Wiesel's original conclusions that orientation tuning width of V1 simple cell is inversely related to the elongation of its RF. A simplified and idealized OP-OD map is then constructed to describe the approximately periodic local OP-OD structure of V1 in a compact form. It is shown explicitly that the OP map can be approximated by retaining its dominant spatial Fourier coefficients, which are shown to suffice to reconstruct its basic spatial structure. Moreover, this representation is a suitable form to analyze observed OP maps compactly and to be used in neural field theory (NFT) for analyzing activity modulated by the OP-OD structure of V1. Application to independently simulated V1 OP structure shows that observed irregularities in the map correspond to a spread of dominant coefficients in a circle in Fourier space. In addition, there is a strong bias toward two perpendicular directions when only a small patch of local map is included. The bias is decreased as the amount of V1 included in the Fourier transform is increased.

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

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

Microendoscopic calcium imaging of the primary visual cortex of behaving macaques

In vivo calcium imaging with genetically encoded indicators has recently been applied to macaque brains to monitor neural activities from a large population of cells simultaneously. Microendoscopic calcium imaging combined with implantable gradient index lenses captures neural activities from deep brain areas with a compact and convenient setup; however, this has been limited to rodents and marmosets. Here, we developed miniature fluorescent microscopy to image neural activities from the primary visual cortex of behaving macaques. We found tens of clear fluorescent signals from three of the six brain hemispheres. A subset of these neurons showed clear retinotopy and orientation tuning. Moreover, we successfully decoded the stimulus orientation and tracked the cells across days. These results indicate that microendoscopic calcium imaging is feasible and reasonable for investigating neural circuits in the macaque brain by monitoring fluorescent signals from a large number of neurons.

A Distinct Population of L6 Neurons in Mouse V1 Mediate Cross-Callosal Communication

Through the corpus callosum, interhemispheric communication is mediated by callosal projection (CP) neurons. Using retrograde labeling, we identified a population of layer 6 (L6) excitatory neurons as the main conveyer of transcallosal information in the monocular zone of the mouse primary visual cortex (V1). Distinct from L6 corticothalamic (CT) population, V1 L6 CP neurons contribute to an extensive reciprocal network across multiple sensory cortices over two hemispheres. Receiving both local and long-range cortical inputs, they encode orientation, direction, and receptive field information, while are also highly spontaneous active. The spontaneous activity of L6 CP neurons exhibits complex relationships with brain states and stimulus presentation, distinct from the spontaneous activity patterns of the CT population. The anatomical and functional properties of these L6 CP neurons enable them to broadcast visual and nonvisual information across two hemispheres, and thus may play a role in regulating and coordinating brain-wide activity events.

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

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

A Diversity of Intrinsic Timescales Underlie Neural Computations

Neural processing occurs across a range of temporal scales. To facilitate this, the brain uses fast-changing representations reflecting momentary sensory input alongside more temporally extended representations, which integrate across both short and long temporal windows. The temporal flexibility of these representations allows animals to behave adaptively. Short temporal windows facilitate adaptive responding in dynamic environments, while longer temporal windows promote the gradual integration of information across time. In the cognitive and motor domains, the brain sets overarching goals to be achieved within a long temporal window, which must be broken down into sequences of actions and precise movement control processed across much shorter temporal windows. Previous human neuroimaging studies and large-scale artificial network models have ascribed different processing timescales to different cortical regions, linking this to each region's position in an anatomical hierarchy determined by patterns of inter-regional connectivity. However, even within cortical regions, there is variability in responses when studied with single-neuron electrophysiology. Here, we review a series of recent electrophysiology experiments that demonstrate the heterogeneity of temporal receptive fields at the level of single neurons within a cortical region. This heterogeneity appears functionally relevant for the computations that neurons perform during decision-making and working memory. We consider anatomical and biophysical mechanisms that may give rise to a heterogeneity of timescales, including recurrent connectivity, cortical layer distribution, and neurotransmitter receptor expression. Finally, we reflect on the computational relevance of each brain region possessing a heterogeneity of neuronal timescales. We argue that this architecture is of particular importance for sensory, motor, and cognitive computations.

Dose-dependent sensorimotor impairment in human ocular tracking after acute low-dose alcohol administration

Key points

Oculomotor behaviours are commonly used to evaluate sensorimotor disruption due to ethanol (EtOH).

The current study demonstrates the dose‐dependent impairment in oculomotor and ocular behaviours across a range of ultra‐low BACs (<0.035%).

Processing of target speed and direction, as well as pursuit eye movements, are significantly impaired at 0.015% BAC, suggesting impaired neural activity within brain regions associated with the visual processing of motion.

Catch‐up saccades during steady visual tracking of the moving target compensate for the reduced vigour of smooth eye movements that occurs with the ingestion of low‐dose alcohol.

Saccade dynamics start to become ‘sluggish’ at as low as 0.035% BAC.

Pupillary light responses appear unaffected at BAC levels up to 0.065%.

Abstract

Changes in oculomotor behaviours are often used as metrics of sensorimotor disruption due to ethanol (EtOH); however, previous studies have focused on deficits at blood‐alcohol concentrations (BACs) above about 0.04%. We investigated the dose dependence of the impairment in oculomotor and ocular behaviours caused by EtOH administration across a range of ultra‐low BACs (≤0.035%). We took repeated measures of oculomotor and ocular performance from sixteen participants, both pre‐ and post‐EtOH administration. To assess the neurological impacts across a wide range of brain areas and pathways, our protocol measured 21 largely independent performance metrics extracted from a range of behavioural responses ranging from ocular tracking of radial step‐ramp stimuli, to eccentric gaze holding, to pupillary responses evoked by light flashes. Our results show significant impairment of pursuit and visual motion processing at 0.015% BAC, reflecting degraded neural processing within extrastriate cortical pathways. However, catch‐up saccades largely compensate for the tracking displacement shortfall caused by low pursuit gain, although there still is significant residual retinal slip and thus degraded dynamic acuity. Furthermore, although saccades are more frequent, their dynamics are more sluggish (i.e. show lower peak velocities) starting at BAC levels as low as 0.035%. Small effects in eccentric gaze holding and no effect in pupillary response dynamics were observed at levels below 0.07%, showing the higher sensitivity of the pursuit response to very low levels of blood alcohol, under the conditions of our study.

Oculomotor behaviours are commonly used to evaluate sensorimotor disruption due to ethanol (EtOH).

The current study demonstrates the dose‐dependent impairment in oculomotor and ocular behaviours across a range of ultra‐low BACs (<0.035%).

Processing of target speed and direction, as well as pursuit eye movements, are significantly impaired at 0.015% BAC, suggesting impaired neural activity within brain regions associated with the visual processing of motion.

Catch‐up saccades during steady visual tracking of the moving target compensate for the reduced vigour of smooth eye movements that occurs with the ingestion of low‐dose alcohol.

Saccade dynamics start to become ‘sluggish’ at as low as 0.035% BAC.

Pupillary light responses appear unaffected at BAC levels up to 0.065%.

Laminar Subnetworks of Response Suppression in Macaque Primary Visual Cortex

Cortical inhibition plays an important role in information processing in the brain. However, the mechanisms by which inhibition and excitation are coordinated to generate functions in the six layers of the cortex remain unclear. Here, we measured laminar-specific responses to stimulus orientations in primary visual cortex (V1) of awake monkeys (male, Macaca mulatta). We distinguished inhibitory effects (suppression) from excitation, by taking advantage of the separability of excitation and inhibition in the orientation and time domains. We found two distinct types of suppression governing different layers. Fast suppression (FS) was strongest in input layers (4C and 6), and slow suppression (SS) was 3 times stronger in output layers (2/3 and 5). Interestingly, the two types of suppression were correlated with different functional properties measured with drifting gratings. FS was primarily correlated with orientation selectivity in input layers (r = -0.65, p < 10-9), whereas SS was primarily correlated with surround suppression in output layers (r = 0.61, p < 10-4). The earliest SS in layer 1 indicates the origin of cortical feedback for SS, in contrast to the feedforward/recurrent origin of FS. Our results reveal two V1 laminar subnetworks with different response suppression that may provide a general framework for laminar processing in other sensory cortices.SIGNIFICANCE STATEMENT This study sought to understand inhibitory effects (suppression) and their relationships with functional properties in the six different layers of the cortex. We found that the diversity of neural responses across layers in primary visual cortex (V1) could be fully explained by one excitatory and two suppressive components (fast and slow suppression). The distinct laminar distributions, origins, and functional roles of the two types of suppression provided a simplified representation of the differences between two V1 subnetworks (input network and output network). These results not only help to elucidate computational principles in macaque V1, but also provide a framework for general computation of cortical laminae in other sensory cortices.

Role of Feedback Connections in Central Visual Processing

The physiological response properties of neurons in the visual system are inherited mainly from feedforward inputs. Interestingly, feedback inputs often outnumber feedforward inputs. Although they are numerous, feedback connections are weaker, slower, and considered to be modulatory, in contrast to fast, high-efficacy feedforward connections. Accordingly, the functional role of feedback in visual processing has remained a fundamental mystery in vision science. At the core of this mystery are questions about whether feedback circuits regulate spatial receptive field properties versus temporal responses among target neurons, or whether feedback serves a more global role in arousal or attention. These proposed functions are not mutually exclusive, and there is compelling evidence to support multiple functional roles for feedback. In this review, the role of feedback in vision will be explored mainly from the perspective of corticothalamic feedback. Further generalized principles of feedback applicable to corticocortical connections will also be considered.

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.

Coding of low-level position and orientation information in human naturalistic vision

Orientation and position of small image segments are considered to be two fundamental low-level attributes in early visual processing, yet their encoding in complex natural stimuli is underexplored. By measuring the just-noticeable differences in noise perturbation, we investigated how orientation and position information of a large number of local elements (Gabors) were encoded separately or jointly. Importantly, the Gabors composed various classes of naturalistic stimuli that were equated by all low-level attributes and differed only in their higher-order configural complexity and familiarity. Although unable to consciously tell apart the type of perturbation, observers detected orientation and position noise significantly differently. Furthermore, when the Gabors were perturbed by both types of noise simultaneously, performance adhered to a reliability-based optimal probabilistic combination of individual attribute noises. Our results suggest that orientation and position are independently coded and probabilistically combined for naturalistic stimuli at the earliest stage of visual processing.

Nonlinear Processing of Shape Information in Rat Lateral Extrastriate Cortex

In rodents, the progression of extrastriate areas located laterally to primary visual cortex (V1) has been assigned to a putative object-processing pathway (homologous to the primate ventral stream), based on anatomical considerations. Recently, we found functional support for such attribution (Tafazoli et al., 2017), by showing that this cortical progression is specialized for coding object identity despite view changes, the hallmark property of a ventral-like pathway. Here, we sought to clarify what computations are at the base of such specialization. To this aim, we performed multielectrode recordings from V1 and laterolateral area LL (at the apex of the putative ventral-like hierarchy) of male adult rats, during the presentation of drifting gratings and noise movies. We found that the extent to which neuronal responses were entrained to the phase of the gratings sharply dropped from V1 to LL, along with the quality of the receptive fields inferred through reverse correlation. Concomitantly, the tendency of neurons to respond to different oriented gratings increased, whereas the sharpness of orientation tuning declined. Critically, these trends are consistent with the nonlinear summation of visual inputs that is expected to take place along the ventral stream, according to the predictions of hierarchical models of ventral computations and a meta-analysis of the monkey literature. This suggests an intriguing homology between the mechanisms responsible for building up shape selectivity and transformation tolerance in the visual cortex of primates and rodents, reasserting the potential of the latter as models to investigate ventral stream functions at the circuitry level.SIGNIFICANCE STATEMENT Despite the growing popularity of rodents as models of visual functions, it remains unclear whether their visual cortex contains specialized modules for processing shape information. To addresses this question, we compared how neuronal tuning evolves from rat primary visual cortex (V1) to a downstream visual cortical region (area LL) that previous work has implicated in shape processing. In our experiments, LL neurons displayed a stronger tendency to respond to drifting gratings with different orientations while maintaining a sustained response across the whole duration of the drift cycle. These trends match the increased complexity of pattern selectivity and the augmented tolerance to stimulus translation found in monkey visual temporal cortex, thus revealing a homology between shape processing in rodents and primates.

A multi-scale layer-resolved spiking network model of resting-state dynamics in macaque visual cortical areas

Cortical activity has distinct features across scales, from the spiking statistics of individual cells to global resting-state networks. We here describe the first full-density multi-area spiking network model of cortex, using macaque visual cortex as a test system. The model represents each area by a microcircuit with area-specific architecture and features layer- and population-resolved connectivity between areas. Simulations reveal a structured asynchronous irregular ground state. In a metastable regime, the network reproduces spiking statistics from electrophysiological recordings and cortico-cortical interaction patterns in fMRI functional connectivity under resting-state conditions. Stable inter-area propagation is supported by cortico-cortical synapses that are moderately strong onto excitatory neurons and stronger onto inhibitory neurons. Causal interactions depend on both cortical structure and the dynamical state of populations. Activity propagates mainly in the feedback direction, similar to experimental results associated with visual imagery and sleep. The model unifies local and large-scale accounts of cortex, and clarifies how the detailed connectivity of cortex shapes its dynamics on multiple scales. Based on our simulations, we hypothesize that in the spontaneous condition the brain operates in a metastable regime where cortico-cortical projections target excitatory and inhibitory populations in a balanced manner that produces substantial inter-area interactions while maintaining global stability.

The mammalian cortex fulfills its complex tasks by operating on multiple temporal and spatial scales from single cells to entire areas comprising millions of cells. These multi-scale dynamics are supported by specific network structures at all levels of organization. Since models of cortex hitherto tend to concentrate on a single scale, little is known about how cortical structure shapes the multi-scale dynamics of the network. We here present dynamical simulations of a multi-area network model at neuronal and synaptic resolution with population-specific connectivity based on extensive experimental data which accounts for a wide range of dynamical phenomena. Our model elucidates relationships between local and global scales in cortex and provides a platform for future studies of cortical function.

Binocular summation for reflexive eye movements

Psychophysical studies and our own subjective experience suggest that, in natural viewing conditions (i.e., at medium to high contrasts), monocularly and binocularly viewed scenes appear very similar, with the exception of the improved depth perception provided by stereopsis. This phenomenon is usually described as a lack of binocular summation. We show here that there is an exception to this rule: Ocular following eye movements induced by the sudden motion of a large stimulus, which we recorded from three human subjects, are much larger when both eyes see the moving stimulus, than when only one eye does. We further discovered that this binocular advantage is a function of the interocular correlation between the two monocular images: It is maximal when they are identical, and reduced when the two eyes are presented with different images. This is possible only if the neurons that underlie ocular following are sensitive to binocular disparity.

Slot-like capacity and resource-like coding in a neural model of multiple-item working memory

For the past decade, research on the storage limitations of working memory has been dominated by two fundamentally different hypotheses. On the one hand, the contents of working memory may be stored in a limited number of "slots," each with a fixed resolution. On the other hand, any number of items may be stored but with decreasing resolution. These two hypotheses have been invaluable in characterizing the computational structure of working memory, but neither provides a complete account of the available experimental data or speaks to the neural basis of the limitations it characterizes. To address these shortcomings, we simulated a multiple-item working memory task with a cortical network model, the cellular resolution of which allowed us to quantify the coding fidelity of memoranda as a function of memory load, as measured by the discriminability, regularity, and reliability of simulated neural spiking. Our simulations account for a wealth of neural and behavioral data from human and nonhuman primate studies, and they demonstrate that feedback inhibition lowers both capacity and coding fidelity. Because the strength of inhibition scales with the number of items stored by the network, increasing this number progressively lowers fidelity until capacity is reached. Crucially, the model makes specific, testable predictions for neural activity on multiple-item working memory tasks. NEW & NOTEWORTHY Working memory is the ability to keep information in mind and is fundamental to cognition. It is actively debated whether the storage limitations of working memory reflect a small number of storage units (slots) or a decrease in coding resolution as a limited resource is allocated to more items. In a cortical model, we found that slot-like capacity and resource-like neural coding resulted from the same mechanism, offering an integrated explanation for storage limitations.

A cross-species comparison of corticogeniculate structure and function

The corticogeniculate circuit is an evolutionarily conserved pathway linking the primary visual cortex with the visual thalamus in the feedback direction. While the corticogeniculate circuit is anatomically robust, the impact of corticogeniculate feedback on the visual response properties of visual thalamic neurons is subtle. Accordingly, discovering the function of corticogeniculate feedback in vision has been a particularly challenging task. In this review, the morphology, organization, physiology, and function of corticogeniculate feedback is compared across mammals commonly studied in visual neuroscience: primates, carnivores, rabbits, and rodents. Common structural and organizational motifs are present across species, including the organization of corticogeniculate feedback into parallel processing streams in highly visual mammals.

Serotonin Decreases the Gain of Visual Responses in Awake Macaque V1

Serotonin, an important neuromodulator in the brain, is implicated in affective and cognitive functions. However, its role even for basic cortical processes is controversial. For example, in the mammalian primary visual cortex (V1), heterogenous serotonergic modulation has been observed in anesthetized animals. Here, we combined extracellular single-unit recordings with iontophoresis in awake animals. We examined the role of serotonin on well-defined tuning properties (orientation, spatial frequency, contrast, and size) in V1 of two male macaque monkeys. We find that in the awake macaque the modulatory effect of serotonin is surprisingly uniform: it causes a mainly multiplicative decrease of the visual responses and a slight increase in the stimulus-selective response latency. Moreover, serotonin neither systematically changes the selectivity or variability of the response, nor the interneuronal correlation unexplained by the stimulus ("noise-correlation"). The modulation by serotonin has qualitative similarities with that for a decrease in stimulus contrast, but differs quantitatively from decreasing contrast. It can be captured by a simple additive change to a threshold-linear spiking nonlinearity. Together, our results show that serotonin is well suited to control the response gain of neurons in V1 depending on the animal's behavioral or motivational context, complementing other known state-dependent gain-control mechanisms.SIGNIFICANCE STATEMENT Serotonin is an important neuromodulator in the brain and a major target for drugs used to treat psychiatric disorders. Nonetheless, surprisingly little is known about how it shapes information processing in sensory areas. Here we examined the serotonergic modulation of visual processing in the primary visual cortex of awake behaving macaque monkeys. We found that serotonin mainly decreased the gain of the visual responses, without systematically changing their selectivity, variability, or covariability. This identifies a simple computational function of serotonin for state-dependent sensory processing, depending on the animal's affective or motivational state.

The divisive normalization model of V1 neurons: a comprehensive comparison of physiological data and model predictions

The physiological responses of simple and complex cells in the primary visual cortex (V1) have been studied extensively and modeled at different levels. At the functional level, the divisive normalization model (DNM; Heeger DJ. Vis Neurosci 9: 181-197, 1992) has accounted for a wide range of single-cell recordings in terms of a combination of linear filtering, nonlinear rectification, and divisive normalization. We propose standardizing the formulation of the DNM and implementing it in software that takes static grayscale images as inputs and produces firing rate responses as outputs. We also review a comprehensive suite of 30 empirical phenomena and report a series of simulation experiments that qualitatively replicate dozens of key experiments with a standard parameter set consistent with physiological measurements. This systematic approach identifies novel falsifiable predictions of the DNM. We show how the model simultaneously satisfies the conflicting desiderata of flexibility and falsifiability. Our key idea is that, while adjustable parameters are needed to accommodate the diversity across neurons, they must be fixed for a given individual neuron. This requirement introduces falsifiable constraints when this single neuron is probed with multiple stimuli. We also present mathematical analyses and simulation experiments that explicate some of these constraints.

Feature-Selective Attentional Modulations in Human Frontoparietal Cortex

Control over visual selection has long been framed in terms of a dichotomy between "source" and "site," where top-down feedback signals originating in frontoparietal cortical areas modulate or bias sensory processing in posterior visual areas. This distinction is motivated in part by observations that frontoparietal cortical areas encode task-level variables (e.g., what stimulus is currently relevant or what motor outputs are appropriate), while posterior sensory areas encode continuous or analog feature representations. Here, we present evidence that challenges this distinction. We used fMRI, a roving searchlight analysis, and an inverted encoding model to examine representations of an elementary feature property (orientation) across the entire human cortical sheet while participants attended either the orientation or luminance of a peripheral grating. Orientation-selective representations were present in a multitude of visual, parietal, and prefrontal cortical areas, including portions of the medial occipital cortex, the lateral parietal cortex, and the superior precentral sulcus (thought to contain the human homolog of the macaque frontal eye fields). Additionally, representations in many-but not all-of these regions were stronger when participants were instructed to attend orientation relative to luminance. Collectively, these findings challenge models that posit a strict segregation between sources and sites of attentional control on the basis of representational properties by demonstrating that simple feature values are encoded by cortical regions throughout the visual processing hierarchy, and that representations in many of these areas are modulated by attention.

SIGNIFICANCE STATEMENT

Influential models of visual attention posit a distinction between top-down control and bottom-up sensory processing networks. These models are motivated in part by demonstrations showing that frontoparietal cortical areas associated with top-down control represent abstract or categorical stimulus information, while visual areas encode parametric feature information. Here, we show that multivariate activity in human visual, parietal, and frontal cortical areas encode representations of a simple feature property (orientation). Moreover, representations in several (though not all) of these areas were modulated by feature-based attention in a similar fashion. These results provide an important challenge to models that posit dissociable top-down control and sensory processing networks on the basis of representational properties.

Attentional Modulation of Neuronal Activity Depends on Neuronal Feature Selectivity

Attention exerts a powerful influence on visual perception. The impact of attention on neuronal activity manifests at early visual information processing stages and progressively increases throughout the visual cortical hierarchy. However, the neuronal mechanisms of attention are unresolved. In particular, the rules governing attentional modulation of individual neurons, whether they are facilitated by or suppressed by attention, are not known. To obtain a more granular or neuron- and circuit-level understanding of the mechanisms of attention and to directly test the feature similarity gain model in V1, we compared attentional modulation with neuronal feature selectivity across a large population of V1 neurons in alert and behaving macaque monkeys trained on an attention-demanding contrast-change detection task. We utilized emerging multi-electrode array technology to record simultaneously from V1 neurons spanning all six cortical layers so that we could characterize the laminar position and physiological response properties of diverse V1 neuronal populations. We found significant relationships between attentional modulation and neuronal position within the cortical hierarchy, neuronal physiology, and neuronal feature selectivity. Our results support the feature similarity gain model and further suggest that attentional modulation depends critically upon the match between neuronal feature selectivity and the features required for the task.

The anatomical and physiological properties of the visual cortex argue against cognitive penetration

We are consciously aware of visual objects together with the minute details that characterize each object. Those details are perceived instantaneously and in parallel. V1 is the only visual area with spatial resolution and topographical exactitude matching perceptual abilities. For cognition to penetrate perception, it needs to affect V1 image representation. That is unlikely because of the detailed parallel V1 organization and the nature of top-down connections, which can influence only large parts of the visual field.

Neural Elements for Predictive Coding

Predictive coding theories of sensory brain function interpret the hierarchical construction of the cerebral cortex as a Bayesian, generative model capable of predicting the sensory data consistent with any given percept. Predictions are fed backward in the hierarchy and reciprocated by prediction error in the forward direction, acting to modify the representation of the outside world at increasing levels of abstraction, and so to optimize the nature of perception over a series of iterations. This accounts for many ‘illusory’ instances of perception where what is seen (heard, etc.) is unduly influenced by what is expected, based on past experience. This simple conception, the hierarchical exchange of prediction and prediction error, confronts a rich cortical microcircuitry that is yet to be fully documented. This article presents the view that, in the current state of theory and practice, it is profitable to begin a two-way exchange: that predictive coding theory can support an understanding of cortical microcircuit function, and prompt particular aspects of future investigation, whilst existing knowledge of microcircuitry can, in return, influence theoretical development. As an example, a neural inference arising from the earliest formulations of predictive coding is that the source populations of forward and backward pathways should be completely separate, given their functional distinction; this aspect of circuitry – that neurons with extrinsically bifurcating axons do not project in both directions – has only recently been confirmed. Here, the computational architecture prescribed by a generalized (free-energy) formulation of predictive coding is combined with the classic ‘canonical microcircuit’ and the laminar architecture of hierarchical extrinsic connectivity to produce a template schematic, that is further examined in the light of (a) updates in the microcircuitry of primate visual cortex, and (b) rapid technical advances made possible by transgenic neural engineering in the mouse. The exercise highlights a number of recurring themes, amongst them the consideration of interneuron diversity as a spur to theoretical development and the potential for specifying a pyramidal neuron’s function by its individual ‘connectome,’ combining its extrinsic projection (forward, backward or subcortical) with evaluation of its intrinsic network (e.g., unidirectional versus bidirectional connections with other pyramidal neurons).

Efficient Receptive Field Tiling in Primate V1

The primary visual cortex (V1) encodes a diverse set of visual features, including orientation, ocular dominance (OD), and spatial frequency (SF), whose joint organization must be precisely structured to optimize coverage within the retinotopic map. Prior experiments have only identified efficient coverage based on orthogonal maps. Here we used two-photon calcium imaging to reveal an alternative arrangement for OD and SF maps in macaque V1; their gradients run parallel but with unique spatial periods, whereby low-SF regions coincide with monocular regions. Next we mapped receptive fields and found surprisingly precise micro-retinotopy that yields a smaller point-image and requires more efficient inter-map geometry, thus underscoring the significance of map relationships. While smooth retinotopy is constraining, studies suggest that it improves both wiring economy and the V1 population code read downstream. Altogether, these data indicate that connectivity within V1 is finely tuned and precise at the level of individual neurons.

Early Visual Cortex Dynamics during Top–Down Modulated Shifts of Feature-Selective Attention

Shifting attention from one color to another color or from color to another feature dimension such as shape or orientation is imperative when searching for a certain object in a cluttered scene. Most attention models that emphasize feature-based selection implicitly assume that all shifts in feature-selective attention underlie identical temporal dynamics. Here, we recorded time courses of behavioral data and steady-state visual evoked potentials (SSVEPs), an objective electrophysiological measure of neural dynamics in early visual cortex to investigate temporal dynamics when participants shifted attention from color or orientation toward color or orientation, respectively. SSVEPs were elicited by four random dot kinematograms that flickered at different frequencies. Each random dot kinematogram was composed of dashes that uniquely combined two features from the dimensions color (red or blue) and orientation (slash or backslash). Participants were cued to attend to one feature (such as color or orientation) and respond to coherent motion targets of the to-be-attended feature. We found that shifts toward color occurred earlier after the shifting cue compared with shifts toward orientation, regardless of the original feature (i.e., color or orientation). This was paralleled in SSVEP amplitude modulations as well as in the time course of behavioral data. Overall, our results suggest different neural dynamics during shifts of attention from color and orientation and the respective shifting destinations, namely, either toward color or toward orientation.

Random Wiring, Ganglion Cell Mosaics, and the Functional Architecture of the Visual Cortex

The architecture of iso-orientation domains in the primary visual cortex (V1) of placental carnivores and primates apparently follows species invariant quantitative laws. Dynamical optimization models assuming that neurons coordinate their stimulus preferences throughout cortical circuits linking millions of cells specifically predict these invariants. This might indicate that V1's intrinsic connectome and its functional architecture adhere to a single optimization principle with high precision and robustness. To validate this hypothesis, it is critical to closely examine the quantitative predictions of alternative candidate theories. Random feedforward wiring within the retino-cortical pathway represents a conceptually appealing alternative to dynamical circuit optimization because random dimension-expanding projections are believed to generically exhibit computationally favorable properties for stimulus representations. Here, we ask whether the quantitative invariants of V1 architecture can be explained as a generic emergent property of random wiring. We generalize and examine the stochastic wiring model proposed by Ringach and coworkers, in which iso-orientation domains in the visual cortex arise through random feedforward connections between semi-regular mosaics of retinal ganglion cells (RGCs) and visual cortical neurons. We derive closed-form expressions for cortical receptive fields and domain layouts predicted by the model for perfectly hexagonal RGC mosaics. Including spatial disorder in the RGC positions considerably changes the domain layout properties as a function of disorder parameters such as position scatter and its correlations across the retina. However, independent of parameter choice, we find that the model predictions substantially deviate from the layout laws of iso-orientation domains observed experimentally. Considering random wiring with the currently most realistic model of RGC mosaic layouts, a pairwise interacting point process, the predicted layouts remain distinct from experimental observations and resemble Gaussian random fields. We conclude that V1 layout invariants are specific quantitative signatures of visual cortical optimization, which cannot be explained by generic random feedforward-wiring models.

Orientation selectivity in cat primary visual cortex: local and global measurement

In this study, we investigated orientation selectivity in cat primary visual cortex (V1) and its relationship with various parameters. We found a strong correlation between circular variance (CV) and orthogonal-topreferred response ratio (O/P ratio), and a moderate correlation between tuning width and O/P ratio. Moreover, the suppression far from the peak that accounted for the lower CV in cat V1 cells also contributed to the narrowing of the tuning width of cells. We also studied the dependence of orientation selectivity on the modulation ratio for each cell, which is consistent with robust entrainment of the neuronal response to the phase of the drifting grating stimulus. In conclusion, the CV (global measure) and tuning width (local measure) are signifi cantly correlated with the modulation ratio.

Spatial diversity of spontaneous activity in the cortex

The neocortex is a layered sheet across which a basic organization is thought to widely apply. The variety of spontaneous activity patterns is similar throughout the cortex, consistent with the notion of a basic cortical organization. However, the basic organization is only an outline which needs adjustments and additions to account for the structural and functional diversity across cortical layers and areas. Such diversity suggests that spontaneous activity is spatially diverse in any particular behavioral state. Accordingly, this review summarizes the laminar and areal diversity in cortical activity during fixation and slow oscillations, and the effects of attention, anesthesia and plasticity on the cortical distribution of spontaneous activity. Among questions that remain open, characterizing the spatial diversity in spontaneous membrane potential may help elucidate how differences in circuitry among cortical regions supports their varied functions. More work is also needed to understand whether cortical spontaneous activity not only reflects cortical circuitry, but also contributes to determining the outcome of plasticity, so that it is itself a factor shaping the functional diversity of the cortex.

Parietal and Frontal Cortex Encode Stimulus-Specific Mnemonic Representations during Visual Working Memory

Working memory (WM) enables the storage and manipulation of information in an active state. WM storage has long been associated with sustained increases in activation across a network of frontal and parietal cortical regions. However, recent evidence suggests that these regions primarily encode information related to general task goals rather than feature-selective representations of specific memoranda. These goal-related representations are thought to provide top-down feedback that coordinates the representation of fine-grained details in early sensory areas. Here, we test this model using fMRI-based reconstructions of remembered visual details from region-level activation patterns. We could reconstruct high-fidelity representations of a remembered orientation based on activation patterns in occipital visual cortex and in several sub-regions of frontal and parietal cortex, independent of sustained increases in mean activation. These results challenge models of WM that postulate disjoint frontoparietal "top-down control" and posterior sensory "feature storage" networks.

Primate area V1: largest response gain for receptive fields in the straight-ahead direction

Although neuronal responses in behaving monkeys are typically studied while the monkey fixates straight ahead, it is known that eye position modulates responses of visual neurons. The modulation has been found to enhance neuronal responses when the receptive field is placed in the straight-ahead position for neurons receiving input from the peripheral but not the central retina. We studied the effect of eye position on the responses of V1 complex cells receiving input from the central retina (1.1-5.7° eccentricity) while minimizing the effect of fixational eye movements. Contrast response functions were obtained separately with drifting light and dark bars. Data were fit with the Naka-Rushton equation: r(c)=Rmax×c/(c+c50)+s, where r(c) is mean spike rate at contrast c, Rmax is the maximum response, c50 is the contrast that elicits half of Rmax, and s is the spontaneous activity. Contrast sensitivity as measured by c50 was not affected by eye position. For dark bars, there was a statistically significant decline in the normalized Rmax with increasing deviation from straight ahead. Data for bright bars showed a similar trend with a less rapid decline. Our results indicate that neurons representing the central retina show a bias for the straight-ahead position resulting from modulation of the response gain without an accompanying modulation of contrast sensitivity. The modulation is especially obvious for dark stimuli, which might be useful for directing attention to hazardous situations such as dark holes or shadows concealing important objects (Supplement 1: Video Abstract, Supplemental digital content 1, http://links.lww.com/WNR/A295).

Neurons in cat V1 show significant clustering by degree of tuning

Neighboring neurons in cat primary visual cortex (V1) have similar preferred orientation, direction, and spatial frequency. How diverse is their degree of tuning for these properties? To address this, we used single-tetrode recordings to simultaneously isolate multiple cells at single recording sites and record their responses to flashed and drifting gratings of multiple orientations, spatial frequencies, and, for drifting gratings, directions. Orientation tuning width, spatial frequency tuning width, and direction selectivity index (DSI) all showed significant clustering: pairs of neurons recorded at a single site were significantly more similar in each of these properties than pairs of neurons from different recording sites. The strength of the clustering was generally modest. The percent decrease in the median difference between pairs from the same site, relative to pairs from different sites, was as follows: for different measures of orientation tuning width, 29-35% (drifting gratings) or 15-25% (flashed gratings); for DSI, 24%; and for spatial frequency tuning width measured in octaves, 8% (drifting gratings). The clusterings of all of these measures were much weaker than for preferred orientation (68% decrease) but comparable to that seen for preferred spatial frequency in response to drifting gratings (26%). For the above properties, little difference in clustering was seen between simple and complex cells. In studies of spatial frequency tuning to flashed gratings, strong clustering was seen among simple-cell pairs for tuning width (70% decrease) and preferred frequency (71% decrease), whereas no clustering was seen for simple-complex or complex-complex cell pairs.

A physiological perspective on fixational eye movements

For a behavioral neuroscientist, fixational eye movements are a double-edged sword. On one edge, they make control of visual stimuli difficult, but on the other edge they provide insight into the ways the visual system acquires information from the environment. We have studied macaque monkeys as models for human visual systems. Fixational eye movements of monkeys are similar to those of humans but they are more often vertically biased and spatially more dispersed. Eye movements scatter stimuli from their intended retinal locations, increase variability of neuronal responses, inflate estimates of receptive field size, and decrease measures of response amplitude. They also bias against successful stimulation of extremely selective cells. Compensating for eye movements reduced these errors and revealed a fine-grained motion pathway from V1 feeding the cortical ventral stream. Compensation is a useful tool for the experimenter, but rather than compensating for eye movements, the brain utilizes them as part of its input. The saccades and drifts that occur during fixation selectively activate different types of V1 neurons. Cells that prefer slower speeds respond during the drift periods with maintained discharges and tend to have smaller receptive fields that are selective for sign of contrast. They are well suited to code small details of the image and to enable our fine detailed vision. Cells that prefer higher speeds fire transient bursts of spikes when the receptive field leaves, crosses, or lands on a stimulus, but only the most transient ones (about one-third of our sample) failed to respond during drifts. Voluntary and fixational saccades had very similar effects, including the presence of a biphasic extraretinal modulation that interacted with stimulus-driven responses. Saccades evoke synchronous bursts that can enhance visibility but these bursts may also participate in the visual masking that contributes to saccadic suppression. Study of the small eye movements of fixation may illuminate some of the big problems in vision.

Enhanced attentional gain as a mechanism for generalized perceptual learning in human visual cortex

Learning to better discriminate a specific visual feature (i.e., a specific orientation in a specific region of space) has been associated with plasticity in early visual areas (sensory modulation) and with improvements in the transmission of sensory information from early visual areas to downstream sensorimotor and decision regions (enhanced readout). However, in many real-world scenarios that require perceptual expertise, observers need to efficiently process numerous exemplars from a broad stimulus class as opposed to just a single stimulus feature. Some previous data suggest that perceptual learning leads to highly specific neural modulations that support the discrimination of specific trained features. However, the extent to which perceptual learning acts to improve the discriminability of a broad class of stimuli via the modulation of sensory responses in human visual cortex remains largely unknown. Here, we used functional MRI and a multivariate analysis method to reconstruct orientation-selective response profiles based on activation patterns in the early visual cortex before and after subjects learned to discriminate small offsets in a set of grating stimuli that were rendered in one of nine possible orientations. Behavioral performance improved across 10 training sessions, and there was a training-related increase in the amplitude of orientation-selective response profiles in V1, V2, and V3 when orientation was task relevant compared with when it was task irrelevant. These results suggest that generalized perceptual learning can lead to modified responses in the early visual cortex in a manner that is suitable for supporting improved discriminability of stimuli drawn from a large set of exemplars.

The mechanism for processing random-dot motion at various speeds in early visual cortices

All moving objects generate sequential retinotopic activations representing a series of discrete locations in space and time (motion trajectory). How direction-selective neurons in mammalian early visual cortices process motion trajectory remains to be clarified. Using single-cell recording and optical imaging of intrinsic signals along with mathematical simulation, we studied response properties of cat visual areas 17 and 18 to random dots moving at various speeds. We found that, the motion trajectory at low speed was encoded primarily as a direction signal by groups of neurons preferring that motion direction. Above certain transition speeds, the motion trajectory is perceived as a spatial orientation representing the motion axis of the moving dots. In both areas studied, above these speeds, other groups of direction-selective neurons with perpendicular direction preferences were activated to encode the motion trajectory as motion-axis information. This applied to both simple and complex neurons. The average transition speed for switching between encoding motion direction and axis was about 31°/s in area 18 and 15°/s in area 17. A spatio-temporal energy model predicted the transition speeds accurately in both areas, but not the direction-selective indexes to random-dot stimuli in area 18. In addition, above transition speeds, the change of direction preferences of population responses recorded by optical imaging can be revealed using vector maximum but not vector summation method. Together, this combined processing of motion direction and axis by neurons with orthogonal direction preferences associated with speed may serve as a common principle of early visual motion processing.

Sample skewness as a statistical measurement of neuronal tuning sharpness

We propose using the statistical measurement of the sample skewness of the distribution of mean firing rates of a tuning curve to quantify sharpness of tuning. For some features, like binocular disparity, tuning curves are best described by relatively complex and sometimes diverse functions, making it difficult to quantify sharpness with a single function and parameter. Skewness provides a robust nonparametric measure of tuning curve sharpness that is invariant with respect to the mean and variance of the tuning curve and is straightforward to apply to a wide range of tuning, including simple orientation tuning curves and complex object tuning curves that often cannot even be described parametrically. Because skewness does not depend on a specific model or function of tuning, it is especially appealing to cases of sharpening where recurrent interactions among neurons produce sharper tuning curves that deviate in a complex manner from the feedforward function of tuning. Since tuning curves for all neurons are not typically well described by a single parametric function, this model independence additionally allows skewness to be applied to all recorded neurons, maximizing the statistical power of a set of data. We also compare skewness with other nonparametric measures of tuning curve sharpness and selectivity. Compared to these other nonparametric measures tested, skewness is best used for capturing the sharpness of multimodal tuning curves defined by narrow peaks (maximum) and broad valleys (minima). Finally, we provide a more formal definition of sharpness using a shape-based information gain measure and derive and show that skewness is correlated with this definition.

Uniformity and diversity of response properties of neurons in the primary visual cortex: selectivity for orientation, direction of motion, and stimulus size from center to far periphery

Although the primary visual cortex (V1) is one of the most extensively studied areas of the primate brain, very little is known about how the far periphery of visual space is represented in this area. We characterized the physiological response properties of V1 neurons in anaesthetized marmoset monkeys, using high-contrast drifting gratings. Comparisons were made between cells with receptive fields located in three regions of V1, defined by eccentricity: central (3-5°), near peripheral (5-15°), and far peripheral (>50°). We found that orientation selectivity of individual cells was similar from the center to the far periphery. Nonetheless, the proportion of orientation-selective neurons was higher in central visual field representation than in the peripheral representations. In addition, there were similar proportions of cells representing all orientations, with the exception of the representation of the far periphery, where we detected a bias favoring near-horizontal orientations. The proportions of direction-selective cells were similar throughout V1. When the center/surround organization of the receptive fields was tested with gratings with varying diameters, we found that the population of neurons that was suppressed by large gratings was smaller in the far periphery, although the strength of suppression in these cells tended to be stronger. In addition, the ratio between the diameters of the excitatory centers and suppressive surrounds was similar across the entire visual field. These results suggest that, superimposed on the broad uniformity of V1, there are subtle physiological differences, which indicate that spatial information is processed differently in the central versus far peripheral visual fields.

Transformation of receptive field properties from lateral geniculate nucleus to superficial V1 in the tree shrew

Tree shrew primary visual cortex (V1) exhibits a pronounced laminar segregation of inputs from different classes of relay neurons in the lateral geniculate nucleus (LGN). We examined how several receptive field (RF) properties were transformed from LGN to V1 layer 4 to V1 layer 2/3. The progression of RF properties across these stages differed markedly from that found in the cat. V1 layer 4 cells are largely similar to the the LGN cells that provide their input, being dominated by a single sign (ON or OFF) and being strongly modulated by sinusoidal gratings. Some layer 4 neurons, notably those near the edges of layer 4, exhibited increased orientation selectivity, and most layer 4 neurons exhibited a preference for lower temporal frequencies. Neurons in cortical layer 2/3 differ significantly from those in the LGN; most exhibited strong orientation tuning and both ON and OFF responses. The strength of orientation selectivity exhibited a notable sublaminar organization, with the strongest orientation tuned neurons in the most superficial parts of layer 2/3. Modulation indexes provide evidence for simple and complex cells in both layer 4 and layer 2/3. However, neurons with high modulation indexes were heterogenous in the spatial organization of ON and OFF responses, with many of them exhibiting unbalanced ON and OFF responses rather than well-segregated ON and OFF subunits. When compared to the laminar organization of V1 in other mammals, these data show that the process of natural selection can result in significantly altered structure/function relationships in homologous cortical circuits.

Emergence of orientation selectivity in the Mammalian visual pathway

Orientation selectivity is a property of mammalian primary visual cortex (V1) neurons, yet its emergence along the visual pathway varies across species. In carnivores and primates, elongated receptive fields first appear in V1, whereas in lagomorphs such receptive fields emerge earlier, in the retina. Here we examine the mouse visual pathway and reveal the existence of orientation selectivity in lateral geniculate nucleus (LGN) relay cells. Cortical inactivation does not reduce this orientation selectivity, indicating that cortical feedback is not its source. Orientation selectivity is similar for LGN relay cells spiking and subthreshold input to V1 neurons, suggesting that cortical orientation selectivity is inherited from the LGN in mouse. In contrast, orientation selectivity of cat LGN relay cells is small relative to subthreshold inputs onto V1 simple cells. Together, these differences show that although orientation selectivity exists in visual neurons of both rodents and carnivores, its emergence along the visual pathway, and thus its underlying neuronal circuitry, is fundamentally different.