Influence of contrast on orientation and temporal frequency tuning in ferret primary visual cortex

Mammals Achieve Common Neural Coverage of Visual Scenes Using Distinct Sampling Behaviors

Most vertebrates use head and eye movements to quickly change gaze orientation and sample different portions of the environment with periods of stable fixation. Visual information must be integrated across fixations to construct a complete perspective of the visual environment. In concert with this sampling strategy, neurons adapt to unchanging input to conserve energy and ensure that only novel information from each fixation is processed. We demonstrate how adaptation recovery times and saccade properties interact and thus shape spatiotemporal tradeoffs observed in the motor and visual systems of mice, cats, marmosets, macaques, and humans. These tradeoffs predict that in order to achieve similar visual coverage over time, animals with smaller receptive field sizes require faster saccade rates. Indeed, we find comparable sampling of the visual environment by neuronal populations across mammals when integrating measurements of saccadic behavior with receptive field sizes and V1 neuronal density. We propose that these mammals share a common statistically driven strategy of maintaining coverage of their visual environment over time calibrated to their respective visual system characteristics.

Mammals achieve common neural coverage of visual scenes using distinct sampling behaviors

Most vertebrates use head and eye movements to quickly change gaze orientation and sample different portions of the environment with periods of stable fixation. Visual information must be integrated across several fixations to construct a more complete perspective of the visual environment. In concert with this sampling strategy, neurons adapt to unchanging input to conserve energy and ensure that only novel information from each fixation is processed. We demonstrate how adaptation recovery times and saccade properties interact, and thus shape spatiotemporal tradeoffs observed in the motor and visual systems of different species. These tradeoffs predict that in order to achieve similar visual coverage over time, animals with smaller receptive field sizes require faster saccade rates. Indeed, we find comparable sampling of the visual environment by neuronal populations across mammals when integrating measurements of saccadic behavior with receptive field sizes and V1 neuronal density. We propose that these mammals share a common statistically driven strategy of maintaining coverage of their visual environment over time calibrated to their respective visual system characteristics.

A modeling framework for determining modulation of neural-level tuning from non-invasive human fMRI data

Many neuroscience theories assume that tuning modulation of individual neurons underlies changes in human cognition. However, non-invasive fMRI lacks sufficient resolution to visualize this modulation. To address this limitation, we developed an analysis framework called Inferring Neural Tuning Modulation (INTM) for “peering inside” voxels. Precise specification of neural tuning from the BOLD signal is not possible. Instead, INTM compares theoretical alternatives for the form of neural tuning modulation that might underlie changes in BOLD across experimental conditions. The most likely form is identified via formal model comparison, with assumed parametric Normal tuning functions, followed by a non-parametric check of conclusions. We validated the framework by successfully identifying a well-established form of modulation: visual contrast-induced multiplicative gain for orientation tuned neurons. INTM can be applied to any experimental paradigm testing several points along a continuous feature dimension (e.g., direction of motion, isoluminant hue) across two conditions (e.g., with/without attention, before/after learning).

Dynamic Distortion of Orientation Representation after Learning in the Mouse Primary Visual Cortex

Learning is an essential cognitive mechanism allowing behavioral adaptation through adjustments in neuronal processing. It is associated with changes in the activity of sensory cortical neurons evoked by task-relevant stimuli. However, the exact nature of those modifications and the computational advantages they may confer are still debated. Here, we investigated how learning an orientation discrimination task alters the neuronal representations of the cues orientations in the primary visual cortex (V1) of male and female mice. When comparing the activity evoked by the task stimuli in naive mice and the mice performing the task, we found that the representations of the orientation of the rewarded and nonrewarded cues were more accurate and stable in trained mice. This better cue representation in trained mice was associated with a distortion of the orientation representation space such that stimuli flanking the task-relevant orientations were represented as the task stimuli themselves, suggesting that those stimuli were generalized as the task cues. This distortion was context dependent as it was absent in trained mice passively viewing the task cues and enhanced in the behavioral sessions where mice performed best. Those modifications of the V1 population orientation representation in performing mice were supported by a suppression of the activity of neurons tuned for orientations neighboring the orientations of the task cues. Thus, visual processing in V1 is dynamically adapted to enhance the reliability of the representation of the learned cues and favor generalization in the task-relevant computational space.SIGNIFICANCE STATEMENT Performance improvement in a task often requires facilitating the extraction of the information necessary to its execution. Here, we demonstrate the existence of a suppression mechanism that improves the representation of the orientations of the task stimuli in the V1 of mice performing an orientation discrimination task. We also show that this mechanism distorts the V1 orientation representation space, leading stimuli flanking the task stimuli orientations to be generalized as the task stimuli themselves.

Sensory coding and contrast invariance emerge from the control of plastic inhibition over emergent selectivity

Visual stimuli are represented by a highly efficient code in the primary visual cortex, but the development of this code is still unclear. Two distinct factors control coding efficiency: Representational efficiency, which is determined by neuronal tuning diversity, and metabolic efficiency, which is influenced by neuronal gain. How these determinants of coding efficiency are shaped during development, supported by excitatory and inhibitory plasticity, is only partially understood. We investigate a fully plastic spiking network of the primary visual cortex, building on phenomenological plasticity rules. Our results suggest that inhibitory plasticity is key to the emergence of tuning diversity and accurate input encoding. We show that inhibitory feedback (random and specific) increases the metabolic efficiency by implementing a gain control mechanism. Interestingly, this led to the spontaneous emergence of contrast-invariant tuning curves. Our findings highlight that (1) interneuron plasticity is key to the development of tuning diversity and (2) that efficient sensory representations are an emergent property of the resulting network.

Synaptic plasticity is crucial for the development of efficient input representation in the different sensory cortices, such as the primary visual cortex. Efficient visual representation is determined by two factors: representational efficiency, i.e. how many different input features can be represented, and metabolic efficiency, i.e. how many spikes are required to represent a specific feature. Previous research has pointed out the importance of plasticity at excitatory synapses to achieve high representational efficiency and feedback inhibition as a gain control mechanism for controlling metabolic efficiency. However, it is only partially understood how the influence of inhibitory plasticity on excitatory plasticity can lead to an efficient representation. Using a spiking neural network, we show that plasticity at feed-forward and feedback inhibitory synapses is necessary for the emergence of well-distributed neuronal selectivity to improve representational efficiency. Further, the emergent balance between excitatory and inhibitory currents improves the metabolic efficiency, and leads to contrast-invariant tuning as an inherent network property. Extending previous work, our simulation results highlight the importance of plasticity at inhibitory synapses.

Traumatic brain injury to primary visual cortex produces long-lasting circuit dysfunction

Primary sensory areas of the mammalian neocortex have a remarkable degree of plasticity, allowing neural circuits to adapt to dynamic environments. However, little is known about the effects of traumatic brain injury on visual circuit function. Here we used anatomy and in vivo electrophysiological recordings in adult mice to quantify neuron responses to visual stimuli two weeks and three months after mild controlled cortical impact injury to primary visual cortex (V1). We found that, although V1 remained largely intact in brain-injured mice, there was ~35% reduction in the number of neurons that affected inhibitory cells more broadly than excitatory neurons. V1 neurons showed dramatically reduced activity, impaired responses to visual stimuli and weaker size selectivity and orientation tuning in vivo. Our results show a single, mild contusion injury produces profound and long-lasting impairments in the way V1 neurons encode visual input. These findings provide initial insight into cortical circuit dysfunction following central visual system neurotrauma.

Assessment of optogenetically-driven strategies for prosthetic restoration of cortical vision in large-scale neural simulation of V1

The neural encoding of visual features in primary visual cortex (V1) is well understood, with strong correlates to low-level perception, making V1 a strong candidate for vision restoration through neuroprosthetics. However, the functional relevance of neural dynamics evoked through external stimulation directly imposed at the cortical level is poorly understood. Furthermore, protocols for designing cortical stimulation patterns that would induce a naturalistic perception of the encoded stimuli have not yet been established. Here, we demonstrate a proof of concept by solving these issues through a computational model, combining (1) a large-scale spiking neural network model of cat V1 and (2) a virtual prosthetic system transcoding the visual input into tailored light-stimulation patterns which drive in situ the optogenetically modified cortical tissue. Using such virtual experiments, we design a protocol for translating simple Fourier contrasted stimuli (gratings) into activation patterns of the optogenetic matrix stimulator. We then quantify the relationship between spatial configuration of the imposed light pattern and the induced cortical activity. Our simulations in the absence of visual drive (simulated blindness) show that optogenetic stimulation with a spatial resolution as low as 100 [Formula: see text]m, and light intensity as weak as [Formula: see text] photons/s/cm[Formula: see text] is sufficient to evoke activity patterns in V1 close to those evoked by normal vision.

Contrast response in a comprehensive network model of macaque V1

The response to contrast is one of the most important functions of the macaque primary visual cortex, V1, but up to now there has not been an adequate theory for it. To fill this gap in our understanding of cortical function, we built and analyzed a new large-scale, biologically constrained model of the input layer, 4Cα, of macaque V1. We called the new model CSY2. We challenged CSY2 with a three-parameter family of visual stimuli that varied in contrast, orientation, and spatial frequency. CSY2 accurately simulated experimental data and made many new predictions. It accounted for 1) the shapes of firing-rate-versus-contrast functions, 2) orientation and spatial frequency tuning versus contrast, and 3) the approximate contrast-invariance of cortical activity maps. Post-analysis revealed that the mechanisms that were needed to produce the successful simulations of contrast response included strong recurrent excitation and inhibition that find dynamic equilibria across the cortical surface, dynamic feedback between L6 and L4, and synaptic dynamics like inhibitory synaptic depression.

Contrast-Dependence of Temporal Frequency Tuning in Mouse V1

The perception of speed is influenced by visual contrast. In primary visual cortex (V1), an early stage in the visual perception pathway, the neural tuning to speed is directly related to the neural tuning to temporal frequency of stimulus changes. The influence of contrast on speed perception can be caused by the joint dependency of neural responses in V1 on temporal frequency and contrast. Here, we investigated how tuning to contrast and temporal frequency in V1 of anesthetized mice are related. We found that temporal frequency tuning is contrast-dependent. V1 was more responsive at lower temporal frequencies than the dLGN, consistent with previous work at high contrast. The temporal frequency tuning moves toward higher temporal frequencies with increasing contrast. The low half-maximum temporal frequency does not change with contrast. The Heeger divisive normalization equation provides a good fit to many response characteristics in V1, but does not fit the dependency of temporal frequency and contrast with set of parameters for all temporal frequencies. Different mechanisms for normalization in the visual cortex may predict different relationships between temporal frequency and contrast non-linearity. Our data could help to make a model selection.

Visual Response Characteristics in Lateral and Medial Subdivisions of the Rat Pulvinar

The pulvinar is a higher-order thalamic relay and a central component of the extrageniculate visual pathway, with input from the superior colliculus and visual cortex and output to all of visual cortex. Rodent pulvinar, more commonly called the lateral posterior nucleus (LP), consists of three highly-conserved subdivisions, and offers the advantage of simplicity in its study compared to more subdivided primate pulvinar. Little is known about receptive field properties of LP, let alone whether functional differences exist between different LP subdivisions, making it difficult to understand what visual information is relayed and what kinds of computations the pulvinar might support. Here, we characterized single-cell response properties in two V1 recipient subdivisions of rat pulvinar, the rostromedial (LPrm) and lateral (LPl), and found that a fourth of the cells were selective for orientation, compared to half in V1, and that LP tuning widths were significantly broader. Response latencies were also significantly longer and preferred size more than three times larger on average than in V1; the latter suggesting pulvinar as a source of spatial context to V1. Between subdivisons, LPl cells preferred higher temporal frequencies, whereas LPrm showed a greater degree of direction selectivity and pattern motion detection. Taken together with known differences in connectivity patterns, these results suggest two separate visual feature processing channels in the pulvinar, one in LPl related to higher speed processing which likely derives from superior colliculus input, and the other in LPrm for motion processing derived through input from visual cortex. SIGNIFICANCE STATEMENT: The pulvinar has a perplexing role in visual cognition as no clear link has been found between the functional properties of its neurons and behavioral deficits that arise when it is damaged. The pulvinar, called the lateral posterior nucleus (LP) in rats, is a higher order thalamic relay with input from the superior colliculus and visual cortex and output to all of visual cortex. By characterizing single-cell response properties in anatomically distinct subdivisions we found two separate visual feature processing channels in the pulvinar, one in lateral LP related to higher speed processing which likely derives from superior colliculus input, and the other in rostromedial LP for motion processing derived through input from visual cortex.

Additive effect of contrast and velocity suggests the role of strong excitatory drive in suppression of visual gamma response

It is commonly acknowledged that gamma-band oscillations arise from interplay between neural excitation and inhibition; however, the neural mechanisms controlling the power of stimulus-induced gamma responses (GR) in the human brain remain poorly understood. A moderate increase in velocity of drifting gratings results in GR power enhancement, while increasing the velocity beyond some 'transition point' leads to GR power attenuation. We tested two alternative explanations for this nonlinear input-output dependency in the GR power. First, the GR power can be maximal at the preferable velocity/temporal frequency of motion-sensitive V1 neurons. This 'velocity tuning' hypothesis predicts that lowering contrast either will not affect the transition point or shift it to a lower velocity. Second, the GR power attenuation at high velocities of visual motion can be caused by changes in excitation/inhibition balance with increasing excitatory drive. Since contrast and velocity both add to excitatory drive, this 'excitatory drive' hypothesis predicts that the 'transition point' for low-contrast gratings would be reached at a higher velocity, as compared to high-contrast gratings. To test these alternatives, we recorded magnetoencephalography during presentation of low (50%) and high (100%) contrast gratings drifting at four velocities. We found that lowering contrast led to a highly reliable shift of the GR suppression transition point to higher velocities, thus supporting the excitatory drive hypothesis. No effects of contrast or velocity were found in the alpha-beta range. The results have implications for understanding the mechanisms of gamma oscillations and developing gamma-based biomarkers of disturbed excitation/inhibition balance in brain disorders.

Pure tones modulate the representation of orientation and direction in the primary visual cortex

Multimodal sensory integration facilitates the generation of a unified and coherent perception of the environment. It is now well established that unimodal sensory perceptions, such as vision, are improved in multisensory contexts. Whereas multimodal integration is primarily performed by dedicated multisensory brain regions such as the association cortices or the superior colliculus, recent studies have shown that multisensory interactions also occur in primary sensory cortices. In particular, sounds were shown to modulate the responses of neurons located in layers 2/3 (L2/3) of the mouse primary visual cortex (V1). Yet, the net effect of sound modulation at the V1 population level remained unclear. In the present study, we performed two-photon calcium imaging in awake mice to compare the representation of the orientation and the direction of drifting gratings by V1 L2/3 neurons in unimodal (visual only) or multimodal (audiovisual) conditions. We found that sound modulation depended on the tuning properties (orientation and direction selectivity) and response amplitudes of V1 L2/3 neurons. Sounds potentiated the responses of neurons that were highly tuned to the cue's orientation and direction but weakly active in the unimodal context, following the principle of inverse effectiveness of multimodal integration. Moreover, sound suppressed the responses of neurons untuned for the orientation and/or the direction of the visual cue. Altogether, sound modulation improved the representation of the orientation and direction of the visual stimulus in V1 L2/3. Namely, visual stimuli presented with auditory stimuli recruited a neuronal population better tuned to the visual stimulus orientation and direction than when presented alone. NEW & NOTEWORTHY The primary visual cortex (V1) receives direct inputs from the primary auditory cortex. Yet, the impact of sounds on visual processing in V1 remains controverted. We show that the modulation by pure tones of V1 visual responses depends on the orientation selectivity, direction selectivity, and response amplitudes of V1 neurons. Hence, audiovisual stimuli recruit a population of V1 neurons better tuned to the orientation and direction of the visual stimulus than unimodal visual stimuli.

Toward a Biologically Plausible Model of LGN-V1 Pathways Based on Efficient Coding

Increasing evidence supports the hypothesis that the visual system employs a sparse code to represent visual stimuli, where information is encoded in an efficient way by a small population of cells that respond to sensory input at a given time. This includes simple cells in primary visual cortex (V1), which are defined by their linear spatial integration of visual stimuli. Various models of sparse coding have been proposed to explain physiological phenomena observed in simple cells. However, these models have usually made the simplifying assumption that inputs to simple cells already incorporate linear spatial summation. This overlooks the fact that these inputs are known to have strong non-linearities such the separation of ON and OFF pathways, or separation of excitatory and inhibitory neurons. Consequently these models ignore a range of important experimental phenomena that are related to the emergence of linear spatial summation from non-linear inputs, such as segregation of ON and OFF sub-regions of simple cell receptive fields, the push-pull effect of excitation and inhibition, and phase-reversed cortico-thalamic feedback. Here, we demonstrate that a two-layer model of the visual pathway from the lateral geniculate nucleus to V1 that incorporates these biological constraints on the neural circuits and is based on sparse coding can account for the emergence of these experimental phenomena, diverse shapes of receptive fields and contrast invariance of orientation tuning of simple cells when the model is trained on natural images. The model suggests that sparse coding can be implemented by the V1 simple cells using neural circuits with a simple biologically plausible architecture.

Mechanisms of Spatiotemporal Selectivity in Cortical Area MT

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

Ferrets as a Model for Higher-Level Visual Motion Processing

Ferrets are a major developmental animal model due to their early parturition. Here we show for the first time that ferrets could be used to study development of higher-level visual processes previously identified in primates. In primates, complex motion processing involves primary visual cortex (V1), which generates local motion signals, and higher-level visual area MT, which integrates these signals over more global spatial regions. Our data show similar transformations in motion signals between ferret V1 and higher-level visual area PSS, located in the posterior bank of the suprasylvian sulcus. We found that PSS neurons, like MT neurons, were tuned for stimulus motion and showed strong suppression between opposing direction inputs. Most strikingly, PSS, like MT, exhibited robust global motion signals when tested with coherent plaids-the classic test for motion integration across multiple moving elements. These PSS responses were described well by computational models developed for MT. Our findings establish the ferret as a strong animal model for development of higher-level visual processing.

Detailed Visual Cortical Responses Generated by Retinal Sheet Transplants in Rats with Severe Retinal Degeneration

To combat retinal degeneration, healthy fetal retinal sheets have been successfully transplanted into both rodent models and humans, with synaptic connectivity between transplant and degenerated host retina having been confirmed. In rodent studies, transplants have been shown to restore responses to flashes of light in a region of the superior colliculus corresponding to the location of the transplant in the host retina. To determine the quality and detail of visual information provided by the transplant, visual responsivity was studied here at the level of visual cortex where higher visual perception is processed. For our model, we used the transgenic Rho-S334ter line-3 rat (both sexes), which loses photoreceptors at an early age and is effectively blind at postnatal day 30. These rats received fetal retinal sheet transplants in one eye between 24 and 40 d of age. Three to 10 months following surgery, visually responsive neurons were found in regions of primary visual cortex matching the transplanted region of the retina that were as highly selective as normal rat to stimulus orientation, size, contrast, and spatial and temporal frequencies. Conversely, we found that selective response properties were largely absent in nontransplanted line-3 rats. Our data show that fetal retinal sheet transplants can result in remarkably normal visual function in visual cortex of rats with a degenerated host retina and represents a critical step toward developing an effective remedy for the visually impaired human population.SIGNIFICANCE STATEMENT Age-related macular degeneration and retinitis pigmentosa lead to profound vision loss in millions of people worldwide. Many patients lose both retinal pigment epithelium and photoreceptors. Hence, there is a great demand for the development of efficient techniques that allow for long-term vision restoration. In this study, we transplanted dissected fetal retinal sheets, which can differentiate into photoreceptors and integrate with the host retina of rats with severe retinal degeneration. Remarkably, we show that transplants generated visual responses in cortex similar in quality to normal rats. Furthermore, transplants preserved connectivity within visual cortex and the retinal relay from the lateral geniculate nucleus to visual cortex, supporting their potential application in curing vision loss associated with retinal degeneration.

Having More Choices Changes How Human Observers Weight Stable Sensory Evidence

Decision-making becomes slower when more choices are available. Existing models attribute this slowing to poor sensory processing, to attenuated rates of sensory evidence accumulation, or to increases in the amount of evidence required before committing to a decision (a higher decision threshold). However, studies have not isolated the effects of having more choices on sensory and decision-related processes from changes in task difficulty and divided attention. Here, we controlled task difficulty while independently manipulating the distribution of attention and the number of choices available to male and female human observers. We used EEG to measure steady-state visually evoked potentials (SSVEPs) and a frontal late positive deflection (LPD), EEG markers of sensory and postsensory decision-related processes, respectively. We found that dividing attention decreased SSVEP and LPD amplitudes, consistent with dampened sensory responses and slower rates of evidence accumulation, respectively. In contrast, having more choices did not alter SSVEP amplitude and led to a larger LPD. These results suggest that having more options largely spares early sensory processing and slows down decision-making via a selective increase in decision thresholds.SIGNIFICANCE STATEMENT When more choices are available, decision-making becomes slower. We tested whether this phenomenon is due to poor sensory processing, to reduced rates of evidence accumulation, or to increases in the amount of evidence required before committing to a decision (a higher decision threshold). We measured choice modulations of sensory and decision-related neural responses using EEG. We also minimized potential confounds from changes in the distribution of attention and task difficulty, which often covary with having more choices. Dividing attention reduced the activity levels of both sensory and decision-related responses. However, having more choices did not change sensory processing and led to larger decision-related responses. These results suggest that having more choices spares sensory processing and selectively increases decision thresholds.

Contrast gain control and retinogeniculate communication

Visual information processed in the retina is transmitted to primary visual cortex via relay cells in the lateral geniculate nucleus (LGN) of the dorsal thalamus. Although retinal ganglion cells are the primary source of driving input to LGN neurons, not all retinal spikes are transmitted to the cortex. Here, we investigate the relationship between stimulus contrast and retinogeniculate communication and test the hypothesis that both the time course and strength of retinogeniculate interactions are dynamic and dependent on stimulus contrast. By simultaneously recording the spiking activity of synaptically connected retinal ganglion cells and LGN neurons in the cat, we show that the temporal window for retinogeniculate integration and the effectiveness of individual retinal spikes are inversely proportional to stimulus contrast. This finding provides a mechanistic understanding for the phenomenon of augmented contrast gain control in the LGN-a nonlinear receptive field property of LGN neurons whereby response gain during low-contrast stimulation is enhanced relative to response gain during high-contrast stimulation. In addition, these results support the view that network interactions beyond the retina play an essential role in transforming visual signals en route from retina to cortex.

Mechanisms of Orientation Selectivity in the Primary Visual Cortex

The mechanisms underlying the emergence of orientation selectivity in the visual cortex have been, and continue to be, the subjects of intense scrutiny. Orientation selectivity reflects a dramatic change in the representation of the visual world: Whereas afferent thalamic neurons are generally orientation insensitive, neurons in the primary visual cortex (V1) are extremely sensitive to stimulus orientation. This profound change in the receptive field structure along the visual pathway has positioned V1 as a model system for studying the circuitry that underlies neural computations across the neocortex. The neocortex is characterized anatomically by the relative uniformity of its circuitry despite its role in processing distinct signals from region to region. A combination of physiological, anatomical, and theoretical studies has shed some light on the circuitry components necessary for generating orientation selectivity in V1. This targeted effort has led to critical insights, as well as controversies, concerning how neural circuits in the neocortex perform computations.

Orientation Tuning of Correlated Activity in the Developing Lateral Geniculate Nucleus

Neural circuits and the cells that comprise them undergo developmental changes in the spatial organization of their connections and in their temporal response properties. Within the lateral geniculate nucleus (LGN) of the dorsal thalamus, these changes have pronounced effects on the spatiotemporal receptive fields (STRFs) of neurons. An open and unresolved question is how STRF maturation affects stimulus-evoked correlated activity between pairs of LGN neurons during development. This is an important question to answer because stimulus-evoked correlated activity likely plays a role in establishing the specificity of thalamocortical connectivity and the receptive fields (RFs) of postsynaptic cortical neurons. Using multielectrode recording methods and white noise stimuli, we recorded neural activity from ensembles of LGN neurons in cats across early development. As expected, there was a progressive maturation of the spatial and temporal properties of visual responses. Using drifting bar stimuli and cross-correlation analysis, we also determined the orientation-tuning bandwidth of correlated activity between pairs of LGN neurons at different stages of development (Sillito and Jones, 2002; Andolina et al., 2007; Stanley et al., 2012; Kelly et al., 2014). Despite the larger RFs and slower responses of immature LGN neurons compared with mature neurons, our results show that correlated activity in the LGN was as tightly tuned for orientation early in development as it was in the adult. Closer examination revealed this age-invariant orientation tuning of correlated activity likely involves cellular mechanisms related to spike fatigue in young animals and a progressive decrease in response latency with development.SIGNIFICANCE STATEMENT Orientation tuning is a fundamental property of neurons in primary visual cortex. An important and unresolved question is how orientation tuning emerges during brain development. This study explores a potential mechanism for the establishment of orientation tuning based on correlated activity patterns among ensembles of maturing neurons in the lateral geniculate nucleus (LGN) of the thalamus. Results show that correlated activity between pairs of LGN neurons is more tightly tuned than predictions based simply on receptive field size, indicating that correlated activity has the properties needed to play an important role in the development of geniculocortical circuits and the emergence of cortical orientation tuning.

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.

Altered visual cortical processing in a mouse model of MECP2 duplication syndrome

As an epigenetic modulator of gene expression, Methyl-CpG binding protein 2 (MeCP2) is essential for normal neurological function. Dysfunction of MeCP2 is associated with a variety of neurological disorders. MECP2 gene duplication in human causes neuropsychiatric symptoms such as mental retardation and autism. MeCP2 overexpression in mice results in neurobehavioural disorders, dendritic abnormalities, and synaptic defects. However, how gain of MeCP2 function influences cortical processing of sensory information remains unclear. In this study, we examined visual processing in a mouse model of MECP2 duplication syndrome (MECP2 Tg1 mouse) at 8 and 14 weeks, which were before and after the onset of behavioural symptoms, respectively. In vivo extracellular recordings from primary visual cortex (V1) showed that neurons in Tg1 mice at both adult ages preferred higher spatial frequencies (SFs) than those in wild-type (WT) littermate controls, and the semi-saturation contrasts of neurons were lower in Tg1 mice at 8 weeks but not at 14 weeks. Behavioural experiments showed that the performance for visual detection at high SFs and low contrasts was higher in MECP2 Tg1 mice. Thus, MeCP2 gain-of-function in mice leads to higher visual acuity and contrast sensitivity, both at the levels of cortical response and behavioural performance.

Differences in orientation tuning between pinwheel and domain neurons in primary visual cortex depend on contrast and size

Intrinsic signal optical imaging reveals a highly modular map of orientation preference in the primary visual cortex (V1) of several species. This orientation map is characterized by domains and pinwheels where local circuitry is either more or less orientation selective, respectively. It has now been repeatedly demonstrated that neurons in pinwheels tend to be more broadly tuned to orientation, likely due to the broad range of orientation preference of the neighboring neurons forming pinwheels. However, certain stimulus conditions, such as a decrease in contrast or an increase in size, significantly sharpen tuning widths of V1 neurons. Here, we find that pinwheel neuron tuning widths are broader than domain neurons only for high contrast, optimally sized stimuli, conditions that maximize excitation through feedforward, and local cortical processing. When contrast was lowered or size increased, orientation tuning width sharpened and became equal. These latter conditions are conducive to less local excitation either through lower feedforward drive or by surround suppression arising from long-range cortical circuits. Tuning width differences between pinwheel and domain neurons likely arise through more local circuitry and are overcome through recruitment of longer-range cortical circuits.

Comparison of mechanisms for contrast-invariance of orientation selectivity in simple cells

The simple cells of the visual cortex respond over a narrow range of stimulus orientations, and this tuning is invariant to the contrast at which the stimulus is presented. The inputs to a single cell derive from a population of thalamic cells that provide a bell-shaped tuning width and offset that increases with stimulus contrast. Synaptic depression, noise and inhibition have been proposed as feedforward mechanisms to explain why these increases do not appear in simple cells. The extent to which these three mechanisms contribute to contrast-invariant orientation tuning is unknown. Consequently, the aim was to test the hypothesis that these mechanisms do not contribute equally. Unlike previous studies, all mechanisms were examined using the same network model based on Banitt et al. (2007). The results showed that thalamocortical synaptic noise was essential and sufficient to widen tuning widths at low contrasts to that of higher contrasts but could not counteract the offset at higher contrasts. Thalamocortical synaptic depression could only be used to counteract a small fraction of the offset otherwise the relationship between contrast and response rate was disrupted. Only broadly tuned simple and complex cell inhibition could counteract the remaining offset for all stimulus contrasts but complex cell inhibition reduced the gain of the response. These results suggest unequal contributions of these feedforward mechanisms with thalamic synaptic noise widening tuning widths for low contrasts, synaptic depression counteracting a small component of the offset and synaptic inhibition completely removing the remaining offset to produce contrast-invariant orientation tuning.

Contrast response functions in the visual wulst of the alert burrowing owl: a single-unit study

The neuronal representation of luminance contrast has not been thoroughly studied in birds. Here we present a detailed quantitative analysis of the contrast response of 120 individual neurons recorded from the visual wulst of awake burrowing owls (Athene cunicularia). Stimuli were sine-wave gratings presented within the cell classical receptive field and optimized in terms of eye preference, direction of drift, and spatiotemporal frequency. As contrast intensity was increased from zero to near 100%, most cells exhibited a monotonic response profile with a compressive, at times saturating, nonlinearity at higher contrasts. However, contrast response functions were found to have a highly variable shape across cells. With the view to capture a systematic trend in the data, we assessed the performance of four plausible models (linear, power, logarithmic, and hyperbolic ratio) using classical goodness-of-fit measures and more rigorous statistical tools for multimodel inferences based on the Akaike information criterion. From this analysis, we conclude that a high degree of model uncertainty is present in our data, meaning that no single descriptor is able on its own to capture the heterogeneous nature of single-unit contrast responses in the wulst. We further show that the generalizability of the hyperbolic ratio model established, for example, in the primary visual cortex of cats and monkeys is not tenable in the owl wulst mainly because most neurons in this area have a much wider dynamic range that starts at low contrast. The challenge for future research will be to understand the functional implications of these findings.

Orientation selectivity in rat primary visual cortex emerges earlier with low-contrast and high-luminance stimuli

In natural vision, rapid and sustained variations in luminance and contrast change the reliability of information available about a visual scene, and markedly affect both neuronal and behavioural responses. The hallmark property of neurons in primary visual cortex (V1), orientation selectivity, is unaffected by changes in stimulus contrast, but it remains unclear how sustained differences in mean luminance and contrast affect the time-course of orientation selectivity, and the amount of information that neurons carry about orientation. We used reverse correlation with characterize the temporal dynamics of orientation selectivity in rat V1 neurons under four luminance-contrast conditions. We show that orientation selectivity and mutual information between neuronal responses and stimulus orientation are invariant to contrast or mean luminance. Critically, the time-course of the emergence of orientation selectivity was affected by both factors; response latencies were longer for low- than high-luminance gratings, and surprisingly, response latencies were also longer for high- than low-contrast gratings. Modelling suggests that luminance-modulated changes in feedforward gain, in combination with hyperpolarization caused by high contrasts can account for our physiological data. The hyperpolarization at high contrasts may increase signal-to-noise ratios, whereas a more depolarized membrane may lead to greater sensitivity to weak stimuli.

Stimulus Contrast and Retinogeniculate Signal Processing

Neuronal signals conveying luminance contrast play a key role in nearly all aspects of perception, including depth perception, texture discrimination, and motion perception. Although much is known about the retinal mechanisms responsible for encoding contrast information, relatively little is known about the relationship between stimulus contrast and the processing of neuronal signals between visual structures. Here, we describe simultaneous recordings from monosynaptically connected retinal ganglion cells and lateral geniculate nucleus (LGN) neurons in the cat to determine how stimulus contrast affects the communication of visual signals between the two structures. Our results indicate that: (1) LGN neurons typically reach their half-maximal response at lower contrasts than their individual retinal inputs and (2) LGN neurons exhibit greater contrast-dependent phase advance (CDPA) than their retinal inputs. Further analyses suggests that increased sensitivity relies on spatial convergence of multiple retinal inputs, while increased CDPA is achieved, in part, on temporal summation of arriving signals.

Canonical computations of cerebral cortex

The idea that there is a fundamental cortical circuit that performs canonical computations remains compelling though far from proven. Here we review evidence for two canonical operations within sensory cortical areas: a feedforward computation of selectivity; and a recurrent computation of gain in which, given sufficiently strong external input, perhaps from multiple sources, intracortical input largely, but not completely, cancels this external input. This operation leads to many characteristic cortical nonlinearities in integrating multiple stimuli. The cortical computation must combine such local processing with hierarchical processing across areas. We point to important changes in moving from sensory cortex to motor and frontal cortex and the possibility of substantial differences between cortex in rodents vs. species with columnar organization of selectivity.

Visual Functions of the Thalamus

The thalamus is the heavily interconnected partner of the neocortex. All areas of the neocortex receive afferent input from and send efferent projections to specific thalamic nuclei. Through these connections, the thalamus serves to provide the cortex with sensory input, and to facilitate interareal cortical communication and motor and cognitive functions. In the visual system, the lateral geniculate nucleus (LGN) of the dorsal thalamus is the gateway through which visual information reaches the cerebral cortex. Visual processing in the LGN includes spatial and temporal influences on visual signals that serve to adjust response gain, transform the temporal structure of retinal activity patterns, and increase the signal-to-noise ratio of the retinal signal while preserving its basic content. This review examines recent advances in our understanding of LGN function and circuit organization and places these findings in a historical context.

Contrast-dependent orientation discrimination in the mouse

As an important animal model to study the relationship between behaviour and neural activity, the mouse is able to perform a variety of visual tasks, such as orientation discrimination and contrast detection. However, it is not clear how stimulus contrast influences the performance of orientation discrimination in mice. In this study, we used two task designs, two-alternative forced choice (2AFC) and go/no-go, to examine the performance of mice to discriminate two orthogonal orientations at different contrasts. We found that the performance tended to increase with contrast, and the performance at high contrast was better when the stimulus set contained a single contrast than multiple contrasts. Physiological experiments in V1 showed that neural discriminability of two orthogonal orientations increased with contrast. Furthermore, orientation discriminability of V1 neurons at high contrast was higher in the single than in the multiple contrast condition, largely due to smaller response variance in the single contrast condition. Thus, the performance of mice to discriminate orientations at high contrast is adapted to the contrast range in the stimuli, partly attributed to the contrast-range dependent capacity of V1 neurons to discriminate orientations.

Contrast invariance of orientation tuning in cat primary visual cortex neurons depends on stimulus size

KEY POINTS

The process of orientation tuning is an important and well-characterized feature of neurons in primary visual cortex. The combination of ascending and descending circuits involved is not only relevant to understanding visual processing but the function of neocortex in general. The classic feed-forward model of orientation tuning predicts a broadening effect due to increasing contrast; yet, experimental results consistently report contrast invariance. We show here that contrast invariance actually depends on stimulus size such that large stimuli extending beyond the neuron's receptive field engage circuits that promote invariance, whereas optimally sized, smaller stimuli result in contrast variance that is more in line with the classical orientation tuning model. These results illustrate the importance of optimizing stimulus parameters to best reflect the sensory pathways under study and provide new clues about different circuits that may be involved in variant and invariant response properties.

ABSTRACT

Selective response to stimulus orientation is a key feature of neurons in primary visual cortex, yet the underlying mechanisms generating orientation tuning are not fully understood. The combination of feed-forward and cortical mechanisms involved is not only relevant to understanding visual processing but the function of neocortex in general. The classic feed-forward model predicts that orientation tuning should broaden considerably with increasing contrast; however, experimental results consistently report contrast invariance. We show here, in primary visual cortex of anaesthetized cats under neuromuscular blockade, that contrast invariance occurs when visual stimuli are large enough to include the extraclassical surround (ECS), which is likely to involve circuits of suppression that may not be entirely feed-forward in origin. On the other hand, when stimulus size is optimized to the classical receptive field of each neuron, the population average shows a statistically significant 40% increase in tuning width at high contrast, demonstrating that contrast variance of orientation tuning can occur. Conversely, our results also suggest that the phenomenon of contrast invariance relies in part on the presence of the ECS. Moreover, these results illustrate the importance of optimizing stimulus parameters to best reflect the neural pathways under study.

Surround suppression and temporal processing of visual signals

Extraclassical surround suppression strongly modulates responses of neurons in the retina, lateral geniculate nucleus (LGN), and primary visual cortex. Although a great deal is known about the spatial properties of extraclassical suppression and the role it serves in stimulus size tuning, relatively little is known about how extraclassical suppression shapes visual processing in the temporal domain. We recorded the spiking activity of retinal ganglion cells and LGN neurons in the cat to test the hypothesis that extraclassical suppression influences temporal features of visual responses in the early visual system. Our results demonstrate that extraclassical suppression not only shifts the distribution of interspike intervals in a manner that decreases the efficacy of neuronal communication, it also decreases the reliability of neuronal responses to visual stimuli and it decreases the duration of visual responses, an effect that underlies a rightward shift in the temporal frequency tuning of LGN neurons. Taken together, these results reveal a dynamic relationship between extraclassical suppression and the temporal features of neuronal responses.

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.

Orientation selectivity in inhibition-dominated networks of spiking neurons: effect of single neuron properties and network dynamics

The neuronal mechanisms underlying the emergence of orientation selectivity in the primary visual cortex of mammals are still elusive. In rodents, visual neurons show highly selective responses to oriented stimuli, but neighboring neurons do not necessarily have similar preferences. Instead of a smooth map, one observes a salt-and-pepper organization of orientation selectivity. Modeling studies have recently confirmed that balanced random networks are indeed capable of amplifying weakly tuned inputs and generating highly selective output responses, even in absence of feature-selective recurrent connectivity. Here we seek to elucidate the neuronal mechanisms underlying this phenomenon by resorting to networks of integrate-and-fire neurons, which are amenable to analytic treatment. Specifically, in networks of perfect integrate-and-fire neurons, we observe that highly selective and contrast invariant output responses emerge, very similar to networks of leaky integrate-and-fire neurons. We then demonstrate that a theory based on mean firing rates and the detailed network topology predicts the output responses, and explains the mechanisms underlying the suppression of the common-mode, amplification of modulation, and contrast invariance. Increasing inhibition dominance in our networks makes the rectifying nonlinearity more prominent, which in turn adds some distortions to the otherwise essentially linear prediction. An extension of the linear theory can account for all the distortions, enabling us to compute the exact shape of every individual tuning curve in our networks. We show that this simple form of nonlinearity adds two important properties to orientation selectivity in the network, namely sharpening of tuning curves and extra suppression of the modulation. The theory can be further extended to account for the nonlinearity of the leaky model by replacing the rectifier by the appropriate smooth input-output transfer function. These results are robust and do not depend on the state of network dynamics, and hold equally well for mean-driven and fluctuation-driven regimes of activity.

The effects of short-term synaptic depression at thalamocortical synapses on orientation tuning in cat V1

We examine the effects of short-term synaptic depression on the orientation tuning of the LGN input to simple cells in cat primary visual cortex (V1). The total LGN input has an untuned component as well as a tuned component, both of which grow with stimulus contrast. The untuned component is not visible in the firing rate responses of the simple cells. The suppression of the contribution of the untuned input component to firing rate responses is key to establishing orientation selectivity and its invariance with stimulus contrast. It has been argued that synaptic depression of LGN inputs could contribute to the selective suppression of the untuned component and thus contribute to the tuning observed in simple cells. We examine this using a model fit to the depression observed at thalamocortical synapses in-vivo, and compare this to an earlier model fit based on in-vitro observations. We examine the tuning of both the conductance and the firing rate induced in simple cells by the net LGN input. We find that depression causes minimal suppression of the untuned component. The primary effect of depression is to cause the contrast response curve to saturate at lower contrasts without differentially affecting the tuned vs. untuned components. This effect is slightly weaker for in-vivo vs. in-vitro parameters. Thus, synaptic depression of LGN inputs does not appreciably contribute to the orientation tuning of V1 simple cells.

BOLD signal change and contrast reversing frequency: an event-related fMRI study in human primary visual cortex

It is believed that human primary visual cortex (V1) increases activity with increasing temporal frequency of a visual stimulus. Two kinds of visual stimulus were used in the previous studies, one is patterned-flash stimulus with a fixed onset period and an increasing average luminance with the increase of temporal frequency, the other is contrast reversing flickering checkerboard or grating with a constant average luminance across different temporal frequencies. That hemodynamic responses change as a function of reversal frequency of contrast reversing checkerboard is at odds with neurophysiological studies in animals and neuroimaging studies in humans. In the present study, we addressed the relationship between reversal frequency of contrast reversing checkerboard and hemodynamic response in human V1 using an event-related experimental paradigm and found that the transient characteristics of blood oxygenation level dependent response in human V1 depended very little on the reversal frequency of a contrast reversing checkerboard.

Mean-field analysis of orientation selectivity in inhibition-dominated networks of spiking neurons

Mechanisms underlying the emergence of orientation selectivity in the primary visual cortex are highly debated. Here we study the contribution of inhibition-dominated random recurrent networks to orientation selectivity, and more generally to sensory processing. By simulating and analyzing large-scale networks of spiking neurons, we investigate tuning amplification and contrast invariance of orientation selectivity in these networks. In particular, we show how selective attenuation of the common mode and amplification of the modulation component take place in these networks. Selective attenuation of the baseline, which is governed by the exceptional eigenvalue of the connectivity matrix, removes the unspecific, redundant signal component and ensures the invariance of selectivity across different contrasts. Selective amplification of modulation, which is governed by the operating regime of the network and depends on the strength of coupling, amplifies the informative signal component and thus increases the signal-to-noise ratio. Here, we perform a mean-field analysis which accounts for this process.

Subtractive, divisive and non-monotonic gain control in feedforward nets linearized by noise and delays

The control of input-to-output mappings, or gain control, is one of the main strategies used by neural networks for the processing and gating of information. Using a spiking neural network model, we studied the gain control induced by a form of inhibitory feedforward circuitry-also known as "open-loop feedback"-, which has been experimentally observed in a cerebellum-like structure in weakly electric fish. We found, both analytically and numerically, that this network displays three different regimes of gain control: subtractive, divisive, and non-monotonic. Subtractive gain control was obtained when noise is very low in the network. Also, it was possible to change from divisive to non-monotonic gain control by simply modulating the strength of the feedforward inhibition, which may be achieved via long-term synaptic plasticity. The particular case of divisive gain control has been previously observed in vivo in weakly electric fish. These gain control regimes were robust to the presence of temporal delays in the inhibitory feedforward pathway, which were found to linearize the input-to-output mappings (or f-I curves) via a novel variability-increasing mechanism. Our findings highlight the feedforward-induced gain control analyzed here as a highly versatile mechanism of information gating in the brain.

Cumulative latency advance underlies fast visual processing in desynchronized brain state

Fast sensory processing is vital for the animal to efficiently respond to the changing environment. This is usually achieved when the animal is vigilant, as reflected by cortical desynchronization. However, the neural substrate for such fast processing remains unclear. Here, we report that neurons in rat primary visual cortex (V1) exhibited shorter response latency in the desynchronized state than in the synchronized state. In vivo whole-cell recording from the same V1 neurons undergoing the two states showed that both the resting and visually evoked conductances were higher in the desynchronized state. Such conductance increases of single V1 neurons shorten the response latency by elevating the membrane potential closer to the firing threshold and reducing the membrane time constant, but the effects only account for a small fraction of the observed latency advance. Simultaneous recordings in lateral geniculate nucleus (LGN) and V1 revealed that LGN neurons also exhibited latency advance, with a degree smaller than that of V1 neurons. Furthermore, latency advance in V1 increased across successive cortical layers. Thus, latency advance accumulates along various stages of the visual pathway, likely due to a global increase of membrane conductance in the desynchronized state. This cumulative effect may lead to a dramatic shortening of response latency for neurons in higher visual cortex and play a critical role in fast processing for vigilant animals.

Mechanisms for stable, robust, and adaptive development of orientation maps in the primary visual cortex

Development of orientation maps in ferret and cat primary visual cortex (V1) has been shown to be stable, in that the earliest measurable maps are similar in form to the eventual adult map, robust, in that similar maps develop in both dark rearing and in a variety of normal visual environments, and yet adaptive, in that the final map pattern reflects the statistics of the specific visual environment. How can these three properties be reconciled? Using mechanistic models of the development of neural connectivity in V1, we show for the first time that realistic stable, robust, and adaptive map development can be achieved by including two low-level mechanisms originally motivated from single-neuron results. Specifically, contrast-gain control in the retinal ganglion cells and the lateral geniculate nucleus reduces variation in the presynaptic drive due to differences in input patterns, while homeostatic plasticity of V1 neuron excitability reduces the postsynaptic variability in firing rates. Together these two mechanisms, thought to be applicable across sensory systems in general, lead to biological maps that develop stably and robustly, yet adapt to the visual environment. The modeling results suggest that topographic map stability is a natural outcome of low-level processes of adaptation and normalization. The resulting model is more realistic, simpler, and far more robust, and is thus a good starting point for future studies of cortical map development.

Visual nonclassical receptive field effects emerge from sparse coding in a dynamical system

Extensive electrophysiology studies have shown that many V1 simple cells have nonlinear response properties to stimuli within their classical receptive field (CRF) and receive contextual influence from stimuli outside the CRF modulating the cell's response. Models seeking to explain these non-classical receptive field (nCRF) effects in terms of circuit mechanisms, input-output descriptions, or individual visual tasks provide limited insight into the functional significance of these response properties, because they do not connect the full range of nCRF effects to optimal sensory coding strategies. The (population) sparse coding hypothesis conjectures an optimal sensory coding approach where a neural population uses as few active units as possible to represent a stimulus. We demonstrate that a wide variety of nCRF effects are emergent properties of a single sparse coding model implemented in a neurally plausible network structure (requiring no parameter tuning to produce different effects). Specifically, we replicate a wide variety of nCRF electrophysiology experiments (e.g., end-stopping, surround suppression, contrast invariance of orientation tuning, cross-orientation suppression, etc.) on a dynamical system implementing sparse coding, showing that this model produces individual units that reproduce the canonical nCRF effects. Furthermore, when the population diversity of an nCRF effect has also been reported in the literature, we show that this model produces many of the same population characteristics. These results show that the sparse coding hypothesis, when coupled with a biophysically plausible implementation, can provide a unified high-level functional interpretation to many response properties that have generally been viewed through distinct mechanistic or phenomenological models.

Simple cells in the primary visual cortex (V1) demonstrate many response properties that are either nonlinear or involve response modulations (i.e., stimuli that do not cause a response in isolation alter the cell's response to other stimuli). These non-classical receptive field (nCRF) effects are generally modeled individually and their collective role in biological vision is not well understood. Previous work has shown that classical receptive field (CRF) properties of V1 cells (i.e., the spatial structure of the visual field responsive to stimuli) could be explained by the sparse coding hypothesis, which is an optimal coding model that conjectures a neural population should use the fewest number of cells simultaneously to represent each stimulus. In this paper, we have performed extensive simulated physiology experiments to show that many nCRF response properties are simply emergent effects of a dynamical system implementing this same sparse coding model. These results suggest that rather than representing disparate information processing operations themselves, these nCRF effects could be consequences of an optimal sensory coding strategy that attempts to represent each stimulus most efficiently. This interpretation provides a potentially unifying high-level functional interpretation to many response properties that have generally been viewed through distinct models.

On the relation between receptive field structure and stimulus selectivity in the tree shrew primary visual cortex

There are notable differences in functional properties of primary visual cortex (V1) neurons among mammalian species, particularly those concerning the occurrence of simple and complex cells and the generation of orientation selectivity. Here, we present quantitative data on receptive field (RF) structure, response modulation, and orientation tuning for single neurons in V1 of the tree shrew, a close relative of primates. We find that spatial RF subfield segregation, a criterion for identifying simple cells, was exceedingly small in the tree shrew V1. In contrast, many neurons exhibited elevated F1/F0 modulation that is often used as a simple cell marker. This apparent discrepancy can be explained by the robust stimulus polarity preference in tree shrew V1, which inflates F1/F0 ratio values. RF structure mapped with sparse-noise-which is spatially restricted and emphasizes thalamo-cortical feed-forward inputs-appeared unrelated to orientation selectivity. However, RF structure mapped using the Hartley subspace stimulus-which covers a large area of the visual field and recruits considerable intracortical processing-did predict orientation preference. Our findings reveal a number of striking similarities in V1 functional organization between tree shrews and primates, emphasizing the important role of intracortical recurrent processing in shaping V1 response properties in these species.

Broadening of inhibitory tuning underlies contrast-dependent sharpening of orientation selectivity in mouse visual cortex

Orientation selectivity (OS) in the visual cortex has been found to be invariant to increases in stimulus contrast, a finding that cannot be accounted for by the original, purely excitatory Hubel and Wiesel model. This property of OS may be important for preserving the quality of perceived stimulus across a range of stimulus intensity. The synaptic mechanisms that can prevent a broadening of OS caused by contrast-dependent strengthening of excitatory inputs to cortical neurons remain unknown. Using in vivo loose-patch recordings, we found in excitatory neurons in layer 4 of mouse primary visual cortex (V1) that the spike response to the preferred orientation was elevated as contrast increased while that to the orthogonal orientation remained unchanged, resulting in an overall sharpening rather than a weakening of OS. Whole-cell voltage-clamp recordings further revealed that contrast increases resulted in a scaling up of excitatory conductance at all stimulus orientations. Inhibitory conductance was enhanced at a similar level as excitation for the preferred orientation, but at a significantly higher level for the orthogonal orientation. Modeling revealed that the resulting broadening of inhibitory tuning is critical for maintaining and sharpening OS at high contrast. Finally, two-photon imaging guided recordings from parvalbumin-positive (PV) inhibitory neurons revealed that the broadening of inhibition can be attributed to a contrast-dependent broadening of spike-response tuning of PV neurons. Together our results suggest that modulation of synaptic inhibition in the mouse V1 cortical circuit preserves the sharpness of response selectivity during changes of stimulus strength.

Integrate-and-fire vs Poisson models of LGN input to V1 cortex: noisier inputs reduce orientation selectivity

One of the reasons the visual cortex has attracted the interest of computational neuroscience is that it has well-defined inputs. The lateral geniculate nucleus (LGN) of the thalamus is the source of visual signals to the primary visual cortex (V1). Most large-scale cortical network models approximate the spike trains of LGN neurons as simple Poisson point processes. However, many studies have shown that neurons in the early visual pathway are capable of spiking with high temporal precision and their discharges are not Poisson-like. To gain an understanding of how response variability in the LGN influences the behavior of V1, we study response properties of model V1 neurons that receive purely feedforward inputs from LGN cells modeled either as noisy leaky integrate-and-fire (NLIF) neurons or as inhomogeneous Poisson processes. We first demonstrate that the NLIF model is capable of reproducing many experimentally observed statistical properties of LGN neurons. Then we show that a V1 model in which the LGN input to a V1 neuron is modeled as a group of NLIF neurons produces higher orientation selectivity than the one with Poisson LGN input. The second result implies that statistical characteristics of LGN spike trains are important for V1's function. We conclude that physiologically motivated models of V1 need to include more realistic LGN spike trains that are less noisy than inhomogeneous Poisson processes.

Mechanisms of neuronal computation in mammalian visual cortex

Orientation selectivity in the primary visual cortex (V1) is a receptive field property that is at once simple enough to make it amenable to experimental and theoretical approaches and yet complex enough to represent a significant transformation in the representation of the visual image. As a result, V1 has become an area of choice for studying cortical computation and its underlying mechanisms. Here we consider the receptive field properties of the simple cells in cat V1--the cells that receive direct input from thalamic relay cells--and explore how these properties, many of which are highly nonlinear, arise. We have found that many receptive field properties of V1 simple cells fall directly out of Hubel and Wiesel's feedforward model when the model incorporates realistic neuronal and synaptic mechanisms, including threshold, synaptic depression, response variability, and the membrane time constant.

Effects of contrast and contrast adaptation on static receptive field features in macaque area V1

The spatiotemporal features of the “static” receptive field (RF), as revealed with flashing bars or spots, determine other RF properties. We examined how some of these static RF features vary with contrast and contrast adaptation in area V1 of the anesthetized macaque monkey. RFs were mapped with light and dark flashing bars presented at three different contrasts, with the low and medium contrasts eliciting approximately 1/3 and 2/3 of the high-contrast response amplitude. The main results are as follows: 1) RF widths decreased when contrast decreased; however, the amount of decrease was less than that expected from an iceberg model and closer to the expectation of a contrast invariance of the RF width. 2) Area tuning experiments with drifting gratings showed an opposite effect of contrast: an increase in preferred stimulus diameter when contrast decreased. This implies that the effect of contrast on preferred stimulus size is not predictable from the static RF. 3) Contrast adaptation attenuated the effect of contrast on RF amplitude but did not significantly modify RF width. 4) RF subregion overlap was only marginally affected by changes in contrast and contrast adaptation; the classification of cells as simple and complex, when established from subregion overlap, appears to be robust with respect to changes in contrast and adaptation state. Previous studies have shown that the spatiotemporal features of the RF depend largely on the stimuli used to map the RF. This study shows that contrast is one elemental feature that contributes to the dynamics of the RF.