Mechanisms of Orientation Selectivity in the Primary Visual Cortex

Astrocyte coverage of excitatory synapses correlates to measures of synapse structure and function in ferret primary visual cortex

Most excitatory synapses in the mammalian brain are contacted or ensheathed by astrocyte processes, forming tripartite synapses. Astrocytes are thought to be critical regulators of the structural and functional dynamics of synapses. While the degree of synaptic coverage by astrocytes is known to vary across brain regions and animal species, the reason for and implications of this variability remains unknown. Further, how astrocyte coverage of synapses relates to in vivo functional properties of individual synapses has not been investigated. Here, we characterized astrocyte coverage of synapses of pyramidal neurons in the ferret visual cortex and, using correlative light and electron microscopy, examined their relationship to synaptic strength and sensory-evoked Ca2+ activity. Nearly, all synapses were contacted by astrocytes, and most were contacted along the axon-spine interface. Structurally, we found that the degree of synaptic astrocyte coverage directly scaled with synapse size and postsynaptic density complexity. Functionally, we found that the amount of astrocyte coverage scaled with how selectively a synapse responds to a particular visual stimulus and, at least for the largest synapses, scaled with the reliability of visual stimuli to evoke postsynaptic Ca2+ events. Our study shows astrocyte coverage is highly correlated with structural metrics of synaptic strength of excitatory synapses in the visual cortex and demonstrates a previously unknown relationship between astrocyte coverage and reliable sensory activation.

Decoding dynamic visual scenes across the brain hierarchy

Understanding the computational mechanisms that underlie the encoding and decoding of environmental stimuli is a crucial investigation in neuroscience. Central to this pursuit is the exploration of how the brain represents visual information across its hierarchical architecture. A prominent challenge resides in discerning the neural underpinnings of the processing of dynamic natural visual scenes. Although considerable research efforts have been made to characterize individual components of the visual pathway, a systematic understanding of the distinctive neural coding associated with visual stimuli, as they traverse this hierarchical landscape, remains elusive. In this study, we leverage the comprehensive Allen Visual Coding-Neuropixels dataset and utilize the capabilities of deep learning neural network models to study neural coding in response to dynamic natural visual scenes across an expansive array of brain regions. Our study reveals that our decoding model adeptly deciphers visual scenes from neural spiking patterns exhibited within each distinct brain area. A compelling observation arises from the comparative analysis of decoding performances, which manifests as a notable encoding proficiency within the visual cortex and subcortical nuclei, in contrast to a relatively reduced encoding activity within hippocampal neurons. Strikingly, our results unveil a robust correlation between our decoding metrics and well-established anatomical and functional hierarchy indexes. These findings corroborate existing knowledge in visual coding related to artificial visual stimuli and illuminate the functional role of these deeper brain regions using dynamic stimuli. Consequently, our results suggest a novel perspective on the utility of decoding neural network models as a metric for quantifying the encoding quality of dynamic natural visual scenes represented by neural responses, thereby advancing our comprehension of visual coding within the complex hierarchy of the brain.

Stereotyped spatiotemporal dynamics of spontaneous activity in visual cortex prior to eye-opening

Over the course of development, functional sensory representations emerge in the visual cortex. Prior to eye-opening, modular patterns of spontaneous activity form long-range networks that may serve as a precursor for mature network organization. Although the spatial structure of these networks has been well studied, their temporal features, which may contribute to their continued plasticity and development, remain largely uncharacterized. To address this, we imaged hours of spontaneous network activity in the visual cortex of developing ferrets of both sexes utilizing a fast calcium indicator (GCaMP8m) and widefield imaging at high temporal resolution (50Hz), then segmented out spatiotemporal events. The spatial structure of this activity was highly modular, exhibiting spatially segregated active domains consistent with prior work. We found that the vast majority of events showed a clear dynamic component in which modules activated sequentially across the field of view, but only a minority of events were well-fit with a linear traveling wave. We found that spatiotemporal events occur in repeated and stereotyped motifs, reoccurring across hours of imaging. Finally, we found that the most frequently occurring single-frame spatial activity patterns were predictive of future activity patterns over hundreds of milliseconds. Together, our results demonstrate that spontaneous activity in the early developing cortex exhibits a rich spatiotemporal structure, suggesting a potential role in the maturation and refinement of future functional representations.

Dose-dependent changes in orientation amplitude maps in the cat visual cortex after propofol bolus injections

A general intravenous anesthetic propofol (2,6-diisopropylphenol) is widely used in clinical, veterinary practice and animal experiments. It activates gamma- aminobutyric acid (GABAa) receptors. Though the cerebral cortex is one of the major targets of propofol action, no study of dose dependency of propofol action on cat visual cortex was performed yet. Also, no such investigation was done until now using intrinsic signal optical imaging. Here, we report for the first time on the dependency of optical signal in the visual cortex (area 17/area 18) on the propofol dose. Optical imaging of intrinsic responses to visual stimuli was performed in cats before and after propofol bolus injections at different doses on the background of continuous propofol infusion. Orientation amplitude maps were recorded. We found that amplitude of optical signal significantly decreased after a bolus dose of propofol. The effect was dose- and time-dependent producing stronger suppression of optical signal under the highest bolus propofol doses and short time interval after injection. In each hemisphere, amplitude at cardinal and oblique orientations decreased almost equally. However, surprisingly, amplitude at cardinal orientations in the ipsilateral hemisphere was depressed stronger than in contralateral cortex at most time intervals. As the magnitude of optical signal represents the strength of orientation tuned component, these our data give new insights on the mechanisms of generation of orientation selectivity. Our results also provide new data toward understanding brain dynamics under anesthesia and suggest a recommendation for conducting intrinsic signal optical imaging experiments on cortical functioning under propofol anesthesia.

Parallel pathways carrying direction-and orientation-selective retinal signals to layer 4 of the mouse visual cortex

Parallel visual pathways from the retina to the primary visual cortex (V1) via the lateral geniculate nucleus are common to many mammalian species, including mice, carnivores, and primates. However, it remains unclear which visual features present in both retina and V1 may be inherited from parallel pathways versus extracted by V1 circuits in the mouse. Here, using calcium imaging and rabies circuit tracing, we explore the relationships between tuning of layer 4 (L4) V1 neurons and their retinal ganglion cell (RGC) inputs. We find that subpopulations of L4 V1 neurons differ in their tuning for direction, orientation, spatial frequency, temporal frequency, and speed. Furthermore, we find that direction-tuned L4 V1 neurons receive input from direction-selective RGCs, whereas orientation-tuned L4 V1 neurons receive input from orientation-selective RGCs. These results suggest that direction and orientation tuning of V1 neurons may be partly inherited from parallel pathways originating in the retina.

The mediodorsal thalamus in executive control

Executive control, the ability to organize thoughts and action plans in real time, is a defining feature of higher cognition. Classical theories have emphasized cortical contributions to this process, but recent studies have reinvigorated interest in the role of the thalamus. Although it is well established that local thalamic damage diminishes cognitive capacity, such observations have been difficult to inform functional models. Recent progress in experimental techniques is beginning to enrich our understanding of the anatomical, physiological, and computational substrates underlying thalamic engagement in executive control. In this review, we discuss this progress and particularly focus on the mediodorsal thalamus, which regulates the activity within and across frontal cortical areas. We end with a synthesis that highlights frontal thalamocortical interactions in cognitive computations and discusses its functional implications in normal and pathological conditions.

Non-uniform contextual interactions in the visual cortex place fundamental limits on spatial vision

A prevailing assumption in our understanding of how neurons in the primary visual cortex (V1) integrate contextual information is that such processes are spatially uniform. Conversely, perceptual phenomena such as visual crowding, the impaired ability to accurately recognize a target stimulus among distractors, suggest that interactions among stimuli are distinctly non-uniform. Prior studies have shown flankers at specific spatial geometries exert differential effects on target perception. To resolve this discrepancy, we investigated how flanker geometry impacted the representation of a target stimulus in the laminar microcircuits of V1. Our study reveals flanker location differentially impairs stimulus representation in excitatory neurons in the superficial and input layers of V1 by tuned suppression and untuned facilitation of orientation responses. Mechanistically, this effect can be explained by asymmetrical spatial kernels in a normalization model of cortical activity. Strikingly, these non-uniform modulations of neural representation mirror perceptual anisotropies. These results establish the non-uniform spatial integration of information in the earliest stages of cortical processing as a fundamental limitation of spatial vision.

Parallel pathways carrying direction and orientation selective retinal signals to layer 4 of mouse visual cortex

Parallel functional and anatomical visual pathways from the retina to primary visual cortex (V1) via the lateral geniculate nucleus (LGN) are common to many mammalian species, including mice, carnivores and primates. However, the much larger number of retinal ganglion cell (RGC) types that project to the LGN, as well as the more limited lamination of both the LGN and the thalamocortical-recipient layer 4 (L4) in mice, leaves considerable uncertainty about which visual features present in both retina and V1 might be inherited from parallel pathways versus extracted by V1 circuits in the mouse visual system. Here, we explored the relationships between functional properties of L4 V1 neurons and their RGC inputs by taking advantage of two Cre-expressing mouse lines - Nr5a1-Cre and Scnn1a-Tg3-Cre - that each label functionally and anatomically distinct populations of L4 neurons. Visual tuning properties of L4 V1 neurons were evaluated using Cre-dependent expression of GCaMP6s followed by 2-photon calcium imaging. RGCs providing input to these neurons (via LGN) were labeled and characterized using Cre-dependent trans-synaptic retrograde labeling with G-deleted rabies virus. We find significant differences in the tuning of Nr5a1-Cre versus Scnn1a-Tg3-Cre neurons for direction, orientation, spatial frequency, temporal frequency, and speed. Strikingly, a subset of the RGCs had tuning properties that matched the direction and orientation tuning properties of the L4 V1 neurons to which they provided input. Altogether, these results suggest that direction and orientation tuning of V1 neurons may be at least partly inherited from parallel pathways originating in the retina.

Convolutional neural network models of neuronal responses in macaque V1 reveal limited non-linear processing

Computational models of the primary visual cortex (V1) have suggested that V1 neurons behave like Gabor filters followed by simple non-linearities. However, recent work employing convolutional neural network (CNN) models has suggested that V1 relies on far more non-linear computations than previously thought. Specifically, unit responses in an intermediate layer of VGG-19 were found to best predict macaque V1 responses to thousands of natural and synthetic images. Here, we evaluated the hypothesis that the poor performance of lower-layer units in VGG-19 might be attributable to their small receptive field size rather than to their lack of complexity per se. We compared VGG-19 with AlexNet, which has much larger receptive fields in its lower layers. Whereas the best-performing layer of VGG-19 occurred after seven non-linear steps, the first convolutional layer of AlexNet best predicted V1 responses. Although VGG-19's predictive accuracy was somewhat better than standard AlexNet, we found that a modified version of AlexNet could match VGG-19's performance after only a few non-linear computations. Control analyses revealed that decreasing the size of the input images caused the best-performing layer of VGG-19 to shift to a lower layer, consistent with the hypothesis that the relationship between image size and receptive field size can strongly affect model performance. We conducted additional analyses using a Gabor pyramid model to test for non-linear contributions of normalization and contrast saturation. Overall, our findings suggest that the feedforward responses of V1 neurons can be well explained by assuming only a few non-linear processing stages.

Stimulus edges induce orientation tuning in superior colliculus

Orientation columns exist in the primary visual cortex (V1) of cat and primates but not mouse. Intriguingly, some recent studies reported the presence of orientation and direction columns in the mouse superficial superior colliculus (sSC), while others reported a lack of columnar organization therein. Using in vivo calcium imaging of sSC in the awake mouse brain, we found that the presence of columns is highly stimulus dependent. Specifically, we observed orientation and direction columns formed by sSC neurons retinotopically mapped to the edge of grating stimuli. For both excitatory and inhibitory neurons in sSC, orientation selectivity can be induced by the edge with their preferred orientation perpendicular to the edge orientation. Furthermore, we found that this edge-induced orientation selectivity is associated with saliency encoding. These findings indicate that the tuning properties of sSC neurons are not fixed by circuit architecture but rather dependent on the spatiotemporal properties of the stimulus.

Cortical recurrence supports resilience to sensory variance in the primary visual cortex

Our daily endeavors occur in a complex visual environment, whose intrinsic variability challenges the way we integrate information to make decisions. By processing myriads of parallel sensory inputs, our brain is theoretically able to compute the variance of its environment, a cue known to guide our behavior. Yet, the neurobiological and computational basis of such variance computations are still poorly understood. Here, we quantify the dynamics of sensory variance modulations of cat primary visual cortex neurons. We report two archetypal neuronal responses, one of which is resilient to changes in variance and co-encodes the sensory feature and its variance, improving the population encoding of orientation. The existence of these variance-specific responses can be accounted for by a model of intracortical recurrent connectivity. We thus propose that local recurrent circuits process uncertainty as a generic computation, advancing our understanding of how the brain handles naturalistic inputs.

Why do children with autism spectrum disorder have abnormal visual perception?

Autism spectrum disorder (ASD) is associated with severe impairment in social functioning. Visual information processing provides nonverbal cues that support social interactions. ASD children exhibit abnormalities in visual orientation, continuous visual exploration, and visual-spatial perception, causing social dysfunction, and mechanisms underlying these abnormalities remain unclear. Transmission of visual information depends on the retina-lateral geniculate nucleus-visual cortex pathway. In ASD, developmental abnormalities occur in rapid expansion of the visual cortex surface area with constant thickness during early life, causing abnormal transmission of the peak of the visual evoked potential (P100). We hypothesized that abnormal visual perception in ASD are related to the abnormal visual information transmission and abnormal development of visual cortex in early life, what's more, explored the mechanisms of abnormal visual symptoms to provide suggestions for future research.

Excitation-inhibition imbalance disrupts visual familiarity in amyloid and non-pathology conditions

Neuronal hyperactivity induces memory deficits in Alzheimer's disease. However, how hyperactivity disrupts memory is unclear. Using in vivo synaptic imaging in the mouse visual cortex, we show that structural excitatory-inhibitory synapse imbalance in the apical dendrites favors hyperactivity in early amyloidosis. Consistent with this, natural images elicit neuronal hyperactivity in these mice. Compensatory changes that maintain activity homeostasis disrupt functional connectivity and increase population sparseness such that a small fraction of neurons dominates population activity. These properties reduce the selectivity of neural response to natural images and render visual recognition memory vulnerable to interference. Deprivation of non-specific visual experiences improves the neural representation and behavioral expression of visual familiarity. In contrast, in non-pathological conditions, deprivation of non-specific visual experiences induces disinhibition, increases excitability, and disrupts visual familiarity. We show that disrupted familiarity occurs when the fraction of high-responsive neurons and the persistence of neural representation of a memory-associated stimulus are not constrained.

Strong tuning for stereoscopic depth indicates orientation-specific recurrent circuitry in tree shrew V1

Neurons in the primary visual cortex (V1) are tuned to specific disparities between the two retinal images, which form the neural substrate for stereoscopic vision. We show that V1 neurons in tree shrews, but not in mice, display highly selective responses to narrow ranges of disparity in random-dot stereograms. Surprisingly, V1 neurons in both species show similarly strong tuning to gratings of varying interocular phase differences. This stimulus-dependent dissociation of disparity tuning can be explained by a network model that combines both feedforward and recurrent connections. The features of the model connections are supported by cortical organizations specific to each species. We validate this model by identifying putative inhibitory neurons and confirming their predicted disparity tuning in both species. Together, our studies establish a foundation for using tree shrews in studying binocular vision and raise an exciting possibility of how cortical columns could be uniquely important in computing stereoscopic depth.

Psychophysical Reverse Correlation Revealed Broader Orientation Tuning and Prolonged Reaction Time in Amblyopia

Purpose

Neural selectivity of orientation is a fundamental property of visual system. We aim to investigate whether and how the orientation selectivity changes in amblyopia.

Methods

Seventeen patients with amblyopia (27.1 ± 7.1 years) and 18 healthy participants (25.1 ± 2.7 years) took part in this study. They were asked to continuously detect vertical gratings embedded in a stream of randomly oriented gratings. Using a technique of subspace reverse correlation, the orientation-time perceptive field (PF) for the atypical grating detection task was derived for each participant. Detailed comparisons were made between the PFs measured with the amblyopic and healthy eyes.

Results

The PF of the amblyopic eyes showed significant differences in orientation and time domain compared with that of the normal eyes (cluster-based permutation test, ps < 0.05), with broader bandwidth of orientation tuning (31.41 ± 10.59 degrees [mean ± SD] vs. 24.76 ± 6.85 degrees, P = 0.039) and delayed temporal dynamics (483 ± 68 ms vs. 425 ± 58 ms, P = 0.015). None of the altered PF properties correlated with the contrast sensitivity at 1 cycle per degree (c/deg) in amblyopia. No difference in PFs between the dominant and non-dominant eyes in the healthy group was found.

Conclusions

The altered orientation-time PF to the low spatial frequency and high contrast stimuli suggests amblyopes had coarser orientation selectivity and prolonged reaction time. The broader orientation tuning probably reflects the abnormal lateral interaction in the primary visual cortex, whereas the temporal delay might indicate a high level deficit.

Orientation and direction tuning align with dendritic morphology and spatial connectivity in mouse visual cortex

The functional properties of neocortical pyramidal cells (PCs), such as direction and orientation selectivity in visual cortex, predominantly derive from their excitatory and inhibitory inputs. For layer 2/3 (L2/3) PCs, the detailed relationship between their functional properties and how they sample and integrate information across cortical space is not fully understood. Here, we study this relationship by combining functional in vivo two-photon calcium imaging, in vitro functional circuit mapping, and dendritic reconstruction of the same L2/3 PCs in mouse visual cortex. Our work reveals direct correlations between dendritic morphology and functional input connectivity and the orientation as well as direction tuning of L2/3 PCs. First, the apical dendritic tree is elongated along the postsynaptic preferred orientation, considering the representation of visual space in the cortex as determined by its retinotopic organization. Additionally, sharply orientation-tuned cells show a less complex apical tree compared with broadly tuned cells. Second, in direction-selective L2/3 PCs, the spatial distribution of presynaptic partners is offset from the soma opposite to the preferred direction. Importantly, although the presynaptic excitatory and inhibitory input distributions spatially overlap on average, the excitatory input distribution is spatially skewed along the preferred direction, in contrast to the inhibitory distribution. Finally, the degree of asymmetry is positively correlated with the direction selectivity of the postsynaptic L2/3 PC. These results show that the dendritic architecture and the spatial arrangement of excitatory and inhibitory presynaptic cells of L2/3 PCs play important roles in shaping their orientation and direction tuning.

Shape analysis of gamma rhythm supports a superlinear inhibitory regime in an inhibition-stabilized network

Visual inspection of stimulus-induced gamma oscillations (30–70 Hz) often reveals a non-sinusoidal shape. Such distortions are a hallmark of non-linear systems and are also observed in mean-field models of gamma oscillations. A thorough characterization of the shape of the gamma cycle can therefore provide additional constraints on the operating regime of such models. However, the gamma waveform has not been quantitatively characterized, partially because the first harmonic of gamma, which arises because of the non-sinusoidal nature of the signal, is typically weak and gets masked due to a broadband increase in power related to spiking. To address this, we recorded local field potential (LFP) from the primary visual cortex (V1) of two awake female macaques while presenting full-field gratings or iso-luminant chromatic hues that produced huge gamma oscillations with prominent peaks at harmonic frequencies in the power spectra. We found that gamma and its first harmonic always maintained a specific phase relationship, resulting in a distinctive shape with a sharp trough and a shallow peak. Interestingly, a Wilson-Cowan (WC) model operating in an inhibition stabilized mode could replicate this shape, but only when the inhibitory population operated in the super-linear regime, as predicted recently. However, another recently developed model of gamma that operates in a linear regime driven by stochastic noise failed to produce salient harmonics or the observed shape. Our results impose additional constraints on models that generate gamma oscillations and their operating regimes.

Gamma rhythm is not sinusoidal. Understanding these distortions could provide clues about the cortical network that generates the rhythm. Here, we use harmonic phase analysis to describe these waveforms quantitatively and show that gamma rhythm recorded from the primary visual cortex of macaques has a signature arch shaped waveform, with a sharp trough and a shallow peak, when visual stimuli such as full-screen plain hues and achromatic gratings are presented. This arch shaped waveform is observed over a wide range of stimuli, despite the variation in power and frequency of the rhythm. We then compare two population rate models that have been used to accurately describe the stimulus dependencies of gamma rhythm and show that this arch shaped waveform is obtained only in one of those models. Further, the waveform shape is dependent on the operating domain of the system. Therefore, shape analysis provides additional constraints on cortical models and their operating regimes.

Mechanism underpinning the sharpening of orientation and spatial frequency selectivities in the tree shrew (Tupaia belangeri) primary visual cortex

Most neurons in the primary visual cortex (V1) of mammals show sharp orientation selectivity and band-pass spatial frequency tuning. Here, we examine whether sharpening of the broad tuning that exists subcortically, namely in the retina and the lateral geniculate nucleus (LGN), underlie the sharper tuning seen for both the above features in tree shrew V1. Since the transition from poor feature selectivity to sharp tuning occurs entirely within V1 in tree shrews, we examined the orientation selectivity and spatial frequency tuning of neurons within individual electrode penetrations. We found that most layer 4 and layer 2/3 neurons in the same cortical column preferred the same stimulus orientation. However, a subset of layer 3c neurons close to the layer 4 border preferred near orthogonal orientations, suggesting that layer 2/3 neurons may inherit the orientation preferences of their layer 4 input neurons and also receive cross-orientation inhibition from layer 3c neurons. We also found that layer 4 neurons showed sharper orientation selectivity at higher spatial frequencies, suggesting that attenuation of low spatial frequency responses by spatially broad inhibition acting on layer 4 inputs to layer 2/3 neurons can enhance both orientation and spatial frequency selectivities. However, in a proportion of layer 2/3 neurons, the sharper tuning of layer 2/3 neurons appeared to arise also or even mainly from inhibition specific to high spatial frequencies acting on the layer 4 inputs to layer 2/3. Overall, our results are consistent with the suggestion that in tree shrews, sharp feature selectivity in layer 2/3 can be established by intracortical mechanisms that sharpen biases observed in layer 4, which are in turn inherited presumably from thalamic afferents.

Plasticity in visual cortex is disrupted in a mouse model of tauopathy

Alzheimer's disease and other dementias are thought to underlie a progressive impairment of neural plasticity. Previous work in mouse models of Alzheimer's disease shows pronounced changes in artificially-induced plasticity in hippocampus, perirhinal and prefrontal cortex. However, it is not known how degeneration disrupts intrinsic forms of brain plasticity. Here we characterised the impact of tauopathy on a simple form of intrinsic plasticity in the visual system, which allowed us to track plasticity at both long (days) and short (minutes) timescales. We studied rTg4510 transgenic mice at early stages of tauopathy (5 months) and a more advanced stage (8 months). We recorded local field potentials in the primary visual cortex while animals were repeatedly exposed to a stimulus over 9 days. We found that both short- and long-term visual plasticity were already disrupted at early stages of tauopathy, and further reduced in older animals, such that it was abolished in mice expressing mutant tau. Additionally, visually evoked behaviours were disrupted in both younger and older mice expressing mutant tau. Our results show that visual cortical plasticity and visually evoked behaviours are disrupted in the rTg4510 model of tauopathy. This simple measure of plasticity may help understand how tauopathy disrupts neural circuits, and offers a translatable platform for detection and tracking of the disease.

Development of Functional Properties in the Early Visual System: New Appreciations of the Roles of Lateral Geniculate Nucleus

In the years following Hubel and Wiesel's first reports on ocular dominance plasticity and amblyopia, much attention has been focused on understanding the role of cortical circuits in developmental and experience-dependent plasticity. Initial studies found few differences between retinal ganglion cells and neurons in the lateral geniculate nucleus and uncovered little evidence for an impact of altered visual experience on the functional properties of lateral geniculate nucleus neurons. In the last two decades, however, studies have revealed that the connectivity between the retina and lateral geniculate nucleus is much richer than was previously appreciated, even revealing visual plasticity - including ocular dominance plasticity - in lateral geniculate nucleus neurons. Here we review the development of the early visual system and the impact of experience with a distinct focus on recent discoveries about lateral geniculate nucleus, its connectivity, and evidence for its plasticity and rigidity during development.

Anatomical and functional connectomes underlying hierarchical visual processing in mouse visual system

Over the last 10 years, there has been a surge in interest in the rodent visual system resulting from the discovery of visual processing functions shared with primates V1, and of a complex anatomical structure in the extrastriate visual cortex. This surprisingly intricate visual system was elucidated by recent investigations using rapidly growing genetic tools primarily available in the mouse. Here, we examine the structural and functional connections of visual areas that have been identified in mice mostly during the past decade, and the impact of these findings on our understanding of brain functions associated with vision. Special attention is paid to structure-function relationships arising from the hierarchical organization, which is a prominent feature of the primate visual system. Recent evidence supports the existence of a hierarchical organization in rodents that contains levels that are poorly resolved relative to those observed in primates. This shallowness of the hierarchy indicates that the mouse visual system incorporates abundant non-hierarchical processing. Thus, the mouse visual system provides a unique opportunity to study non-hierarchical processing and its relation to hierarchical processing.

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.

Active dendrites enable strong but sparse inputs to determine orientation selectivity

The dendrites of neocortical pyramidal neurons are excitable. However, it is unknown how synaptic inputs engage nonlinear dendritic mechanisms during sensory processing in vivo, and how they in turn influence action potential output. Here, we provide a quantitative account of the relationship between synaptic inputs, nonlinear dendritic events, and action potential output. We developed a detailed pyramidal neuron model constrained by in vivo dendritic recordings. We drive this model with realistic input patterns constrained by sensory responses measured in vivo and connectivity measured in vitro. We show mechanistically that under realistic conditions, dendritic Na+ and NMDA spikes are the major determinants of neuronal output in vivo. We demonstrate that these dendritic spikes can be triggered by a surprisingly small number of strong synaptic inputs, in some cases even by single synapses. We predict that dendritic excitability allows the 1% strongest synaptic inputs of a neuron to control the tuning of its output. Active dendrites therefore allow smaller subcircuits consisting of only a few strongly connected neurons to achieve selectivity for specific sensory features.

Emergence of local and global synaptic organization on cortical dendrites

Synaptic inputs on cortical dendrites are organized with remarkable subcellular precision at the micron level. This organization emerges during early postnatal development through patterned spontaneous activity and manifests both locally where nearby synapses are significantly correlated, and globally with distance to the soma. We propose a biophysically motivated synaptic plasticity model to dissect the mechanistic origins of this organization during development and elucidate synaptic clustering of different stimulus features in the adult. Our model captures local clustering of orientation in ferret and receptive field overlap in mouse visual cortex based on the receptive field diameter and the cortical magnification of visual space. Including action potential back-propagation explains branch clustering heterogeneity in the ferret and produces a global retinotopy gradient from soma to dendrite in the mouse. Therefore, by combining activity-dependent synaptic competition and species-specific receptive fields, our framework explains different aspects of synaptic organization regarding stimulus features and spatial scales.

Spatial connectivity matches direction selectivity in visual cortex

The selectivity of neuronal responses arises from the architecture of excitatory and inhibitory connections. In the primary visual cortex, the selectivity of a neuron in layer 2/3 for stimulus orientation and direction is thought to arise from intracortical inputs that are similarly selective^1-8. However, the excitatory inputs of a neuron can have diverse stimulus preferences^1-4,6,7,9, and inhibitory inputs can be promiscuous¹⁰ and unselective¹¹. Here we show that the excitatory and inhibitory intracortical connections to a layer 2/3 neuron accord with its selectivity by obeying precise spatial patterns. We used rabies tracing^1,12 to label and functionally image the excitatory and inhibitory inputs to individual pyramidal neurons of layer 2/3 of the mouse visual cortex. Presynaptic excitatory neurons spanned layers 2/3 and 4 and were distributed coaxial to the preferred orientation of the postsynaptic neuron, favouring the region opposite to its preferred direction. By contrast, presynaptic inhibitory neurons resided within layer 2/3 and favoured locations near the postsynaptic neuron and ahead of its preferred direction. The direction selectivity of a postsynaptic neuron was unrelated to the selectivity of presynaptic neurons, but correlated with the spatial displacement between excitatory and inhibitory presynaptic ensembles. Similar asymmetric connectivity establishes direction selectivity in the retina^13-17. This suggests that this circuit motif might be canonical in sensory processing.

Vision Changes the Cellular Composition of Binocular Circuitry during the Critical Period

High acuity stereopsis emerges during an early postnatal critical period when binocular neurons in the primary visual cortex sharpen their receptive field tuning properties. We find that this sharpening is achieved by dismantling the binocular circuit present at critical period onset and building it anew. Longitudinal imaging of receptive field tuning (e.g., orientation selectivity) of thousands of neurons reveals that most binocular neurons present in layer 2/3 at critical period onset are poorly tuned and are rendered monocular. In parallel, new binocular neurons are established by conversion of well-tuned monocular neurons as they gain matched input from the other eye. These improvements in binocular tuning in layer 2/3 are not inherited from layer 4 but are driven by the experience-dependent sharpening of ipsilateral eye responses. Thus, vision builds a new and more sharply tuned binocular circuit in layer 2/3 by cellular exchange and not by refining the original circuit.

Gabor patterns as stimuli in a rodent visual attention task

BACKGROUND

Gabor patterns are defined as the product of a sinusoid function and a Gaussian envelope and are commonly used in visual and attentional research due to their ability to selectively stimulate the primary visual cortex. The aim of this study was to investigate whether Gabor patterns can be used as visual stimuli in the rodent continuous performance test (rCPT), a newly developed task to study attentional function and impulsivity.

METHODS

Sixteen male C57BL/6 J mice were trained in the rCPT using Gabor patterns as visual stimuli and their performance was compared to sixteen mice that were trained using traditional high-contrast pattern stimuli. Mice were compared during training, baseline, and a variable stimulus duration probe.

RESULTS

The Gabor pattern group required more training sessions to reach criteria than the group with high-contrast patterns. At baseline, the Gabor pattern group showed a higher false alarm rate and a lower discriminability index. As task difficulty increased during the variable stimulus duration probe, differences between groups became more pronounced. Specifically, the Gabor pattern group showed decreased hit rate and discriminability index, as well as increased false alarm rate and premature responses compared to the high-contrast pattern group.

CONCLUSION

This feasibility study showed that it is possible to use Gabor patterns as visual stimuli in the rCPT, although it increases task demands. We discuss the differences between Gabor patterns and high-contrast patterns in the context of translatability of animal models in visual and cognitive research and give two examples of applicability.

Visuospatial performance in patients with statistically-defined mild cognitive impairment

Introduction: The Oblique Effect denotes superior performance for perceiving horizontal or vertical rather than diagonal or oblique stimuli. The current research investigated responding to oblique test stimuli in patients with mild cognitive impairment (MCI).Method: Four statistically-determined groups (n = 112) were studied; patients with little to no cognitive impairment (non-MCI, n = 39); subtle cognitive impairment (SCI, n = 15); amnestic MCI (aMCI, n = 28); and a combined mixed/dysexecutive MCI (mixed/dys MCI, n = 30). The ability to respond to oblique versus non-oblique test stimuli was assessed using the Judgment of Line Orientation Test (JOLO). Comprehensive neuropsychological assessment was also obtained. Between-group differences for JOLO oblique and non-oblique test stimuli were analyzed. Hierarchical linear regression models were constructed to identify relations between accuracy for oblique and non-oblique test items and neurocognitive domains.Results: The mixed/dys MCI group demonstrated lower accuracy for oblique test items compared to non-MCI patients. Accurate responding to oblique test items was associated with better performance on tests measuring executive control, processing speed, naming/lexical retrieval, and verbal concept formation. No between-group differences were seen for non-oblique items and these items were not associated with cognition.Conclusions:Significant impairment on oblique test items distinguished patients with multi-domain/dysexecutive MCI from non-MCI patients. Accurate responding to oblique test items was associated with a complex array of neuropsychological tests suggesting that multidimensional neuropsychological skills underlie the visuospatial reasoning abilities necessary for successful oblique line identification. Research associating responding to oblique versus non-oblique test stimuli using additional neuropsychological test paradigms, and MRI-defined neuroanatomical regions of interest may provide additional information about the brain-behavior relations that underlie MCI subtypes.

Neurophysiological basis of contrast dependent BOLD orientation tuning

Recent work in early visual cortex of humans has shown that the BOLD signal exhibits contrast dependent orientation tuning, with an inverse oblique effect (oblique > cardinal) at high contrast and a horizontal effect (vertical > horizontal) at low contrast. This finding is at odds with decades of neurophysiological research demonstrating contrast invariant orientation tuning in primate visual cortex, yet the source of this discrepancy is unclear. We hypothesized that contrast dependent BOLD orientation tuning may arise due to contrast dependent influences of feedforward (FF) and feedback (FB) synaptic activity, indexed through gamma and alpha rhythms, respectively. To quantify this, we acquired EEG and BOLD in healthy humans to generate and compare orientation tuning curves across all neural frequency bands with BOLD. As expected, BOLD orientation selectivity in V1 was contrast dependent, preferring oblique orientations at high contrast and vertical at low contrast. On the other hand, EEG orientation tuning was contrast invariant, though frequency-specific, with an inverse-oblique effect in the gamma band (FF) and a horizontal effect in the alpha band (FB). Therefore, high-contrast BOLD orientation tuning closely matched FF activity, while at low contrast, BOLD best resembled FB orientation tuning. These results suggest that contrast dependent BOLD orientation tuning arises due to the reduced contribution of FF input to overall neurophysiological activity at low contrast, shifting BOLD orientation tuning towards the orientation preferences of FB at low contrast.

Competing rhythmic neural representations of orientations during concurrent attention to multiple orientation features

When a feature is attended, all locations containing this feature are enhanced throughout the visual field. However, how the brain concurrently attends to multiple features remains unknown and cannot be easily deduced from classical attention theories. Here, we recorded human magnetoencephalography signals when subjects concurrently attended to two spatially overlapping orientations. A time-resolved multivariate inverted encoding model was employed to track the ongoing temporal courses of the neural representations of the attended orientations. We show that the two orientation representations alternate with each other and undergo a theta-band (~4 Hz) rhythmic fluctuation over time. Similar temporal profiles are also revealed in the orientation discrimination performance. Computational modeling suggests a tuning competition process between the two neuronal populations that are selectively tuned to one of the attended orientations. Taken together, our findings reveal for the first time a rhythm-based, time-multiplexing neural machinery underlying concurrent multi-feature attention.

The neural mechanisms for concurrently attending to multiple features in the visual stimuli are not well understood. Here, the authors show that the neural representations for two overlapping stimulus features alternate with each other at a ~4 Hz rhythm that was also observed in fluctuations in the task performance.

Content Tuning in the Medial Temporal Lobe Cortex: Voxels that Perceive, Retrieve

How do we recall vivid details from our past based only on sparse cues? Research suggests that the phenomenological reinstatement of past experiences is accompanied by neural reinstatement of the original percept. This process critically depends on the medial temporal lobe (MTL). Within the MTL, perirhinal cortex (PRC) and parahippocampal cortex (PHC) are thought to support encoding and recall of objects and scenes, respectively, with the hippocampus (HC) serving as a content-independent hub. If the fidelity of recall indeed arises from neural reinstatement of perceptual activity, then successful recall should preferentially draw upon those neural populations within content-sensitive MTL cortex that are tuned to the same content during perception. We tested this hypothesis by having eighteen human participants undergo functional MRI (fMRI) while they encoded and recalled objects and scenes paired with words. Critically, recall was cued with the words only. While HC distinguished successful from unsuccessful recall of both objects and scenes, PRC and PHC were preferentially engaged during successful versus unsuccessful object and scene recall, respectively. Importantly, within PRC and PHC, this content-sensitive recall was predicted by content tuning during perception: Across PRC voxels, we observed a positive relationship between object tuning during perception and successful object recall, while across PHC voxels, we observed a positive relationship between scene tuning during perception and successful scene recall. Our results thus highlight content-based roles of MTL cortical regions for episodic memory and reveal a direct mapping between content-specific tuning during perception and successful recall.

If perception is probabilistic, why does it not seem probabilistic?

The success of the Bayesian perspective in explaining perceptual phenomena has motivated the view that perceptual representation is probabilistic. But if perceptual representation is probabilistic, why does normal conscious perception not reflect the full probability functions that the probabilistic point of view endorses? For example, neurons in cortical area MT that respond to the direction of motion are broadly tuned: a patch of cortex that is tuned to vertical motion also responds to horizontal motion, but when we see vertical motion, foveally, in good conditions, it does not look at all horizontal. The standard solution in terms of sampling runs into the problem that sampling is an account of perceptual decision rather than perception. This paper argues that the best Bayesian approach to this problem does not require probabilistic representation.This article is part of the theme issue 'Perceptual consciousness and cognitive access'.

Color and orientation are jointly coded and spatially organized in primate primary visual cortex

Previous studies support the textbook model that shape and color are extracted by distinct neurons in primate primary visual cortex (V1). However, rigorous testing of this model requires sampling a larger stimulus space than previously possible. We used stable GCaMP6f expression and two-photon calcium imaging to probe a very large spatial and chromatic visual stimulus space and map functional microarchitecture of thousands of neurons with single-cell resolution. Notable proportions of V1 neurons strongly preferred equiluminant color over achromatic stimuli and were also orientation selective, indicating that orientation and color in V1 are mutually processed by overlapping circuits. Single neurons could precisely and unambiguously code for both color and orientation. Further analyses revealed systematic spatial relationships between color tuning, orientation selectivity, and cytochrome oxidase histology.

A Retinal Circuit Generating a Dynamic Predictive Code for Oriented Features

Sensory systems must reduce the transmission of redundant information to function efficiently. One strategy is to continuously adjust the sensitivity of neurons to suppress responses to common features of the input while enhancing responses to new ones. Here we image the excitatory synaptic inputs and outputs of retinal ganglion cells to understand how such dynamic predictive coding is implemented in the analysis of spatial patterns. Synapses of bipolar cells become tuned to orientation through presynaptic inhibition, generating lateral antagonism in the orientation domain. Individual ganglion cells receive excitatory synapses tuned to different orientations, but feedforward inhibition generates a high-pass filter that only transmits the initial activation of these inputs, removing redundancy. These results demonstrate how a dynamic predictive code can be implemented by circuit motifs common to many parts of the brain.

Sound Induces Change in Orientation Preference of V1 Neurons: Audio-Visual Cross-Influence

In the cortex, demarcated unimodal sensory regions often respond to unforeseen sensory stimuli and exhibit plasticity. The goal of the current investigation was to test evoked responses of primary visual cortex (V1) neurons when an adapting auditory stimulus is applied in isolation. Using extracellular recordings in anesthetized cats, we demonstrate that, unlike the prevailing observation of only slight modulations in the firing rates of the neurons, sound imposition in isolation entirely shifted the peaks of orientation tuning curves of neurons in both supra- and infragranular layers of V1. Our results suggest that neurons specific to either layer dynamically integrate features of sound and modify the organization of the orientation map of V1. Intriguingly, these experiments present novel findings that the mere presentation of a prolonged auditory stimulus may drastically recalibrate the tuning properties of the visual neurons and highlight the phenomenal neuroplasticity of V1 neurons.

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.

Stochastic neural field model of stimulus-dependent variability in cortical neurons

We use stochastic neural field theory to analyze the stimulus-dependent tuning of neural variability in ring attractor networks. We apply perturbation methods to show how the neural field equations can be reduced to a pair of stochastic nonlinear phase equations describing the stochastic wandering of spontaneously formed tuning curves or bump solutions. These equations are analyzed using a modified version of the bivariate von Mises distribution, which is well-known in the theory of circular statistics. We first consider a single ring network and derive a simple mathematical expression that accounts for the experimentally observed bimodal (or M-shaped) tuning of neural variability. We then explore the effects of inter-network coupling on stimulus-dependent variability in a pair of ring networks. These could represent populations of cells in two different layers of a cortical hypercolumn linked via vertical synaptic connections, or two different cortical hypercolumns linked by horizontal patchy connections within the same layer. We find that neural variability can be suppressed or facilitated, depending on whether the inter-network coupling is excitatory or inhibitory, and on the relative strengths and biases of the external stimuli to the two networks. These results are consistent with the general observation that increasing the mean firing rate via external stimuli or modulating drives tends to reduce neural variability.

Contrast and luminance adaptation alter neuronal coding and perception of stimulus orientation

Sensory systems face a barrage of stimulation that continually changes along multiple dimensions. These simultaneous changes create a formidable problem for the nervous system, as neurons must dynamically encode each stimulus dimension, despite changes in other dimensions. Here, we measured how neurons in visual cortex encode orientation following changes in luminance and contrast, which are critical for visual processing, but nuisance variables in the context of orientation coding. Using information theoretic analysis and population decoding approaches, we find that orientation discriminability is luminance and contrast dependent, changing over time due to firing rate adaptation. We also show that orientation discrimination in human observers changes during adaptation, in a manner consistent with the neuronal data. Our results suggest that adaptation does not maintain information rates per se, but instead acts to keep sensory systems operating within the limited dynamic range afforded by spiking activity, despite a wide range of possible inputs.

Sensory systems produce stable stimulus representations despite constant changes across multiple stimulus dimensions. Here, the authors reveal dynamic neural coding mechanisms by testing how coding of one dimension (orientation) changes with adaptations to other dimensions (luminance and contrast).

Distinct frequency bands in the local field potential are differently tuned to stimulus drift rate

Local field potential (LFP) recorded with a microelectrode reflects the activity of several neural processes, including afferent synaptic inputs, microcircuit-level computations, and spiking activity. Objectively probing their contribution requires a design that allows dissociation between these potential contributors. Earlier reports have shown that the primate lateral geniculate nucleus (LGN) has a higher temporal frequency (drift rate) cutoff than the primary visual cortex (V1), such that at higher drift rates inputs into V1 from the LGN continue to persist, whereas output ceases, permitting partial dissociation. Using chronic microelectrode arrays, we recorded spikes and LFP from V1 of passively fixating macaques while presenting sinusoidal gratings drifting over a wide range. We further optimized the gratings to produce strong gamma oscillations, since recent studies in rodent V1 have reported LGN-dependent narrow-band gamma oscillations. Consistent with earlier reports, power in higher LFP frequencies (above ~140 Hz) tracked the population firing rate and were tuned to preferred drift rates similar to those for spikes. Significantly, power in the lower (up to ~40 Hz) frequencies increased transiently in the early epoch after stimulus onset, even at high drift rates, and had preferred drift rates higher than for spikes/high gamma. Narrow-band gamma (50-80 Hz) power was not strongly correlated with power in high or low frequencies and had much lower preferred temporal frequencies. Our results demonstrate that distinct frequency bands of the V1 LFP show diverse tuning profiles, which may potentially convey different attributes of the underlying neural activity. NEW & NOTEWORTHY In recent years the local field potential (LFP) has been increasingly studied, but interpreting its rich frequency content has been difficult. We use a stimulus manipulation that generates different tuning profiles for low, gamma, and high frequencies of the LFP, suggesting contributions from potentially different sources. Our results have possible implications for design of better neural prosthesis systems and brain-machine interfacing applications.

Transformation of Feature Selectivity From Membrane Potential to Spikes in the Mouse Superior Colliculus

Neurons in the visual system display varying degrees of selectivity for stimulus features such as orientation and direction. Such feature selectivity is generated and processed by intricate circuit and synaptic mechanisms. A key factor in this process is the input-output transformation from membrane potential (V_m) to spikes in individual neurons. Here, we use in vivo whole-cell recording to study V_m-to-spike transformation of visual feature selectivity in the superficial neurons of the mouse superior colliculus (SC). As expected from the spike threshold effect, direction and orientation selectivity increase from V_m to spike responses. The degree of this increase is highly variable, and interestingly, it is correlated with the receptive field size of the recorded neurons. We find that the relationships between V_m and spike rate and between V_m dynamics and spike initiation are also correlated with receptive field size, which likely contribute to the observed input-output transformation of feature selectivity. Together, our findings provide useful information for understanding information processing and visual transformation in the mouse SC.

Organization of Neural Population Code in Mouse Visual System

The mammalian visual system consists of several anatomically distinct areas, layers, and cell types. To understand the role of these subpopulations in visual information processing, we analyzed neural signals recorded from excitatory neurons from various anatomical and functional structures. For each of 186 mice, one of six genetically tagged cell types and one of six visual areas were targeted while the mouse was passively viewing various visual stimuli. We trained linear classifiers to decode one of six visual stimulus categories with distinct spatiotemporal structures from the population neural activity. We found that neurons in both the primary visual cortex and secondary visual areas show varying degrees of stimulus-specific decodability, and neurons in superficial layers tend to be more informative about the stimulus categories. Additional decoding analyses of directional motion were consistent with these findings. We observed synergy in the population code of direction in several visual areas suggesting area-specific organization of information representation across neurons. These differences in decoding capacities shed light on the specialized organization of neural information processing across anatomically distinct subpopulations, and further establish the mouse as a model for understanding visual perception.

Hierarchical stimulus processing in rodent primary and lateral visual cortex as assessed through neuronal selectivity and repetition suppression

Similar to primates, visual cortex in rodents appears to be organized in two distinct hierarchical streams. However, there is still little known about how visual information is processed along those streams in rodents. In this study, we examined how repetition suppression and position and clutter tolerance of the neuronal representations evolve along the putative ventral visual stream in rats. To address this question, we recorded multiunit spiking activity in primary visual cortex (V1) and the more downstream visual laterointermediate (LI) area of head-restrained Long-Evans rats. We employed a paradigm reminiscent of the continuous carry-over design used in human neuroimaging. In both areas, stimulus repetition attenuated the early phase of the neuronal response to the repeated stimulus, with this response suppression being greater in area LI. Furthermore, stimulus preferences were more similar across positions (position tolerance) in area LI than in V1, even though the absolute responses in both areas were very sensitive to changes in position. In contrast, the neuronal representations in both areas were equally good at tolerating the presence of limited visual clutter, as modeled by the presentation of a single flank stimulus. When probing tolerance of the neuronal representations with stimulus-specific adaptation, we detected no position tolerance in either examined brain area, whereas, on the contrary, we revealed clutter tolerance in both areas. Overall, our data demonstrate similarities and discrepancies in processing of visual information along the ventral visual stream of rodents and primates. Moreover, our results stress caution in using neuronal adaptation to probe tolerance of the neuronal representations. NEW & NOTEWORTHY Rodents are emerging as a popular animal model that complement primates for studying higher level visual functions. Similar to findings in primates, we demonstrate a greater repetition suppression and position tolerance of the neuronal representations in the downstream laterointermediate area of Long-Evans rats compared with primary visual cortex. However, we report no difference in the degree of clutter tolerance between the areas. These findings provide additional evidence for hierarchical processing of visual stimuli in rodents.

Action and learning shape the activity of neuronal circuits in the visual cortex

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Arousal and locomotion modulate neuronal activity in primary visual cortex.

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Neurons in primary visual cortex respond to visuomotor mismatch.

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Experience shapes neuronal responses to familiar stimuli, reward and object location.

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Neuronal representations of visual stimuli are modulated according to the behavioural relevance of the stimuli.

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Neuromodulatory, top-down and thalamocortical inputs convey arousal-related and motor-related signals to primary visual cortex.

Nonsensory variables strongly influence neuronal activity in the adult mouse primary visual cortex. Neuronal responses to visual stimuli are modulated by behavioural state, such as arousal and motor activity, and are shaped by experience. This dynamic process leads to neural representations in the visual cortex that reflect stimulus familiarity, expectations of reward and object location, and mismatch between self-motion and visual-flow. The recent development of genetic tools and recording techniques in awake behaving mice has enabled the investigation of the circuit mechanisms underlying state-dependent and experience-dependent neuronal representations in primary visual cortex. These neuronal circuits involve neuromodulatory, top-down cortico-cortical and thalamocortical pathways. The functions of nonsensory signals at this early stage of visual information processing are now beginning to be unravelled.

Relationship between the Dynamics of Orientation Tuning and Spatiotemporal Receptive Field Structures of Cat LGN Neurons

Simple cells in the cat primary visual cortex usually have elongated receptive fields (RFs), and their orientation selectivity can be largely predicted by their RFs. As to the relay cells in cats' lateral geniculate nucleus (LGN), they also have weak but significant orientation bias (OB). It is thus of interest to investigate the fine spatiotemporal receptive field (STRF) properties in LGN, compare them with the dynamics of orientation tuning, and examine the dynamic relationship between STRF and orientation sensitivity in LGN. We mapped the STRFs of the LGN neurons in cats with white noise and characterized the dynamics of the orientation tuning by flashing gratings. We found that most of the LGN neurons showed elongated RFs and that the elongation axes were consistent with the preferred orientations. STRFs and the dynamics of orientation tuning were closely correlated temporally: the elongation of RFs and OB emerged, peaked and decayed at the same pace, with unchanged elongation axis of RF and preferred orientation but consistently changing aspect ratio of RF and OB strength across time. Importantly, the above consistency between RF and orientation tuning was not influenced by the ablation of the primary visual cortex. Furthermore, biased orientation tuning emerged 20-30 ms earlier than those in the primary visual cortex. These data demonstrated that similar to the primary visual cortex, the orientation sensitivity was closely reflected by the RF properties in LGN. However, the elongated RF and OB in LGN did not originate from the primary visual cortex feedback.

Orientation-Selective Retinal Circuits in Vertebrates

Visual information is already processed in the retina before it is transmitted to higher visual centers in the brain. This includes the extraction of salient features from visual scenes, such as motion directionality or contrast, through neurons belonging to distinct neural circuits. Some retinal neurons are tuned to the orientation of elongated visual stimuli. Such ‘orientation-selective’ neurons are present in the retinae of most, if not all, vertebrate species analyzed to date, with species-specific differences in frequency and degree of tuning. In some cases, orientation-selective neurons have very stereotyped functional and morphological properties suggesting that they represent distinct cell types. In this review, we describe the retinal cell types underlying orientation selectivity found in various vertebrate species, and highlight their commonalities and differences. In addition, we discuss recent studies that revealed the cellular, synaptic and circuit mechanisms at the basis of retinal orientation selectivity. Finally, we outline the significance of these findings in shaping our current understanding of how this fundamental neural computation is implemented in the visual systems of vertebrates.