Orientation-selective Neurons Research Articles

Retinal origin of orientation but not direction selective maps in the superior colliculus

Neurons in the mouse superior colliculus ("colliculus") are arranged in ordered spatial maps. While orientation-selective (OS) neurons form a concentric map aligned to the center of vision, direction-selective (DS) neurons are arranged in patches with changing preferences across the visual field. It remains unclear whether these maps are a consequence of feedforward input from the retina or local computations in the colliculus. To determine whether these maps originate in the retina, we mapped the local and global distribution of OS and DS retinal ganglion cell axon boutons using invivo two-photon calcium imaging. We found that OS boutons formed patches that matched the distribution of OS neurons within the colliculus. DS boutons displayed fewer regional specializations, better reflecting the organization of DS neurons in the retina. Both eyes convey similar orientation but different DS inputs to the colliculus, as shown in recordings from retinal explants. These data demonstrate that orientation and direction maps within the colliculus are independent, where orientation maps are likely inherited from the retina, but direction maps require additional computations.

Invited Session IV: Studies of the visual cortex with sub-millimeter resolution: Imaging the visual brain at high spatiotemporal resolution.

Since the discovery of orientation-selective neurons in the cat primary visual cortex (V1), how the mammalian nervous system computes the orientation of visual stimuli has been a flagship question in neuroscience. With the recent advances in in vivo imaging of neural activity using genetically encoded indicators and two-photon fluorescence microscopy, we can now achieve synapse-resolving functional imaging and kilohertz imaging of membrane voltage in the mouse V1. I will describe our recent advancements in imaging visual processing at high spatiotemporal resolution, as well as two studies on the orientation selectivity of neurons in the mouse visual pathway.

Experience dependent plasticity of higher visual cortical areas in the mouse.

Experience dependent plasticity in the visual cortex is a key paradigm for the study of mechanisms underpinning learning and memory. Despite this, studies involving manipulating visual experience have largely been limited to the primary visual cortex, V1, across various species. Here we investigated the effects of monocular deprivation (MD) on the ocular dominance (OD) and orientation selectivity of neurons in four visual cortical areas in the mouse: the binocular zone of V1 (V1b), the putative "ventral stream" area LM and the putative "dorsal stream" areas AL and PM. We employed two-photon calcium imaging to record neuronal responses in young adult mice before MD, immediately after MD, and following binocular recovery. OD shifts following MD were greatest in LM and smallest in AL and PM; in LM and AL, these shifts were mediated primarily through a reduction of deprived-eye responses, in V1b and LM through an increase in response through the non-deprived eye. The OD index recovered to pre-MD levels within 2weeks in V1 only. MD caused a reduction in orientation selectivity of deprived-eye responses in V1b and LM only. Our results suggest that changes in OD in higher visual areas are not uniformly inherited from V1.

Single-layer perceptron artificial visual system for orientation detection.

Orientation detection is an essential function of the visual system. In our previous works, we have proposed a new orientation detection mechanism based on local orientation-selective neurons. We assume that there are neurons solely responsible for orientation detection, with each neuron dedicated to detecting a specific local orientation. The global orientation is inferred from the local orientation information. Based on this mechanism, we propose an artificial visual system (AVS) by utilizing a single-layer of McCulloch-Pitts neurons to realize these local orientation-sensitive neurons and a layer of sum pooling to realize global orientation detection neurons. We demonstrate that such a single-layer perceptron artificial visual system (AVS) is capable of detecting global orientation by identifying the orientation with the largest number of activated orientation-selective neurons as the global orientation. To evaluate the effectiveness of this single-layer perceptron AVS, we perform computer simulations. The results show that the AVS works perfectly for global orientation detection, aligning with the majority of physiological experiments and models. Moreover, we compare the performance of the single-layer perceptron AVS with that of a traditional convolutional neural network (CNN) on orientation detection tasks. We find that the single-layer perceptron AVS outperforms CNN in various aspects, including identification accuracy, noise resistance, computational and learning cost, hardware implementation feasibility, and biological plausibility.

Perception is rich and probabilistic

When we see a stimulus, e.g. a star-shaped object, our intuition is that we should perceive a single, coherent percept (even if it is inaccurate). But the neural processes that support perception are complex and probabilistic. Simple lines cause orientation-selective neurons across a population to fire in a probabilistic-like manner. Does probabilistic neural firing lead to non-probabilistic perception, or are the representations behind perception richer and more complex than intuition would suggest? To test this, we briefly presented a complex shape and had participants report the correct shape from a set of options. Rather than reporting a single value, we used a paradigm designed to encourage to directly report a representation over shape space—participants placed a series of Gaussian bets. We found that participants could report more than point-estimates of shape. The spread of responses was correlated with accuracy, suggesting that participants can convey a notion of relative imprecision. Critically, as participants placed more bets, the mean of responses show increased precision. The later bets were systematically biased towards the target rather than haphazardly placed around bet 1. These findings strongly indicate that participants were aware of more than just a point-estimate; Perceptual representations are rich and likely probabilistic.

Effects of Light Isoflurane Anesthesia on Organization of Direction and Orientation Selectivity in the Superficial Layer of the Mouse Superior Colliculus.

The superior colliculus (SC) is the midbrain center for integrating visual and multimodal sensory information. Neurons in the SC exhibit direction and orientation selectivity. Recent studies reported that neurons with similar preferences formed clusters in the mouse SC (Ahmadlou and Heimel, 2015; Feinberg and Meister, 2015; de Malmazet et al., 2018; Li et al., 2020). However, it remains controversial as to how these clusters are organized within the SC (Inayat et al., 2015; Chen et al., 2021). Here, we found that different brain states (i.e., awake or anesthetized with isoflurane) changed the selectivity of individual SC neurons and organizations of the neuronal population in both male and female mice. Using two-photon Ca2+ imaging, we examined both individual neuronal responses and the spatial patterns of their population responses. Under isoflurane anesthesia, orientation selectivity increased and a larger number of orientation-selective cells were observed when compared with the awake condition, whereas the proportions of direction-selective cells were similar in both conditions. Furthermore, direction- and orientation-selective cells located at closer positions showed more similar preferences, and cluster-like spatial patterns were enhanced. Inhibitory responses of direction-selective neurons were also reduced under isoflurane anesthesia. Thus, the changes in the spatial organization of response patterns were considered to be because of changes in the balance of excitation and inhibition, with excitation dominance, in the local circuits. These results provide new insights into the possibility that the functional organization of feature selectivity in the brain is affected by brain state.SIGNIFICANCE STATEMENT Recent large-scale recording studies are changing our view of visual maps in the superior colliculus (SC), including findings of cluster-like localizations of direction- and orientation-selective neurons. However, results from several laboratories are conflicting regarding the presence of cluster-like organization. Here, we demonstrated that light isoflurane anesthesia affected the direction- and orientation-tuning properties in the mouse superficial SC and that their cluster-like localization pattern was enhanced by the anesthesia. Furthermore, the effect of anesthesia on direction selectivity appeared to be different in the excitatory and inhibitory populations in the SC. Our results suggest that the functional organization of direction and orientation selectivity might be regulated by the excitation-inhibition balance that depends on the brain state.

Selective age-related changes in orientation perception.

Orientation perception is a fundamental property of the visual system and an important basic processing stage for visual scene perception. Neurophysiological studies have found broader tuning curves and increased noise in orientation-selective neurons of senescent monkeys and cats, results that suggest an age-related decline in orientation perception. However, behavioral studies in humans have found no evidence for such decline, with performance being comparable for younger and older participants in orientation detection and discrimination tasks. Crucially, previous behavioral studies assessed performance for cardinal orientation only, and it is well known that the human visual system prefers cardinal over oblique orientations, a phenomenon called the oblique effect. We hypothesized that age-related changes depend on the orientation tested. In two experiments, we investigated orientation discrimination and reproduction for a large range of cardinal and oblique orientations in younger and older adults. We found substantial age-related decline for oblique but not for cardinal orientations, thus demonstrating that orientation perception selectively declines for oblique orientations. Taken together, our results serve as the missing link between previous neurophysiological and human behavioral studies on orientation perception in healthy aging.

Orientation Preference Maps in Microcebus murinus Reveal Size-Invariant Design Principles in Primate Visual Cortex

SUMMARYOrientation preference maps (OPMs) are a prominent feature of primary visual cortex (V1) organization in many primates and carnivores. In rodents, neurons are not organized in OPMs but are instead interspersed in a “salt and pepper” fashion, although clusters of orientation-selective neurons have been reported. Does this fundamental difference reflect the existence of a lower size limit for orientation columns (OCs) below which they cannot be scaled down with decreasing V1 size? To address this question, we examined V1 of one of the smallest living primates, the 60-g prosimian mouse lemur (Microcebus murinus). Using chronic intrinsic signal imaging, we found that mouse lemur V1 contains robust OCs, which are arranged in a pinwheel-like fashion. OC size in mouse lemurs was found to be only marginally smaller compared to the macaque, suggesting that these circuit elements are nearly incompressible. The spatial arrangement of pinwheels is well described by a common mathematical design of primate V1 circuit organization. In order to accommodate OPMs, we found that the mouse lemur V1 covers one-fifth of the cortical surface, which is one of the largest V1-to-cortex ratios found in primates. These results indicate that the primate-type visual cortical circuit organization is constrained by a size limitation and raises the possibility that its emergence might have evolved by disruptive innovation rather than gradual change.

Spatial clustering of orientation preference in primary visual cortex of the large rodent agouti.

SummaryAll rodents investigated so far possess orientation-selective neurons in the primary visual cortex (V1) but – in contrast to carnivores and primates – no evidence of periodic maps with pinwheel-like structures. Theoretical studies debating whether phylogeny or universal principles determine development of pinwheels point to V1 size as a critical constraint. Thus, we set out to study maps of agouti, a big diurnal rodent with a V1 size comparable to cats'. In electrophysiology, we detected interspersed orientation and direction-selective neurons with a bias for horizontal contours, corroborated by homogeneous activation in optical imaging. Compatible with spatial clustering at short distance, nearby neurons tended to exhibit similar orientation preference. Our results argue against V1 size as a key parameter in determining the presence of periodic orientation maps. They are consistent with a phylogenetic influence on the map layout and development, potentially reflecting distinct retinal traits or interspecies differences in cortical circuitry.

Pattern Recognition of Spiking Neural Networks Based on Visual Mechanism and Supervised Synaptic Learning.

Electrophysiological studies have shown that mammalian primary visual cortex are selective for the orientations of visual stimuli. Inspired by this mechanism, we propose a hierarchical spiking neural network (SNN) for image classification. Grayscale input images are fed through a feed-forward network consisting of orientation-selective neurons, which then projected to a layer of downstream classifier neurons through the spiking-based supervised tempotron learning rule. Based on the orientation-selective mechanism of the visual cortex and tempotron learning rule, the network can effectively classify images of the extensively studied MNIST database of handwritten digits, which achieves 96% classification accuracy based on only 2000 training samples (traditional training set is 60000). Compared with other classification methods, our model not only guarantees the biological plausibility and the accuracy of image classification but also significantly reduces the needed training samples. Considering the fact that the most commonly used deep learning neural networks need big data samples and high power consumption in image recognition, this brain-inspired computational neural network model based on the layer-by-layer hierarchical image processing mechanism of the visual cortex may provide a basis for the wide application of spiking neural networks in the field of intelligent computing.

Frequency-separated principal component analysis of cortical population activity.

A hallmark of neocortical activity is the presence of low-dimensional fluctuations in firing rate that are coordinated across neurons. However, the impact of these fluctuations on sensory processing remains unclear. Here, we examined fluctuations in populations of orientation-selective neurons from anesthetized macaque primary visual cortex (V1) during stimulus viewing as well as spontaneous activity. We introduce a novel approach termed frequency-separated principal component analysis (FS-PCA) to characterize these fluctuations. This method unveiled a distribution of components with a broad range of frequencies whose eigenvalues and variance followed an approximate power law. During stimulus viewing, subpopulations of V1 neurons correlated either positively or negatively with low-dimensional fluctuations. These two subpopulations displayed distinct activation properties and noise correlations in response to sensory input. Together, results suggest that slow, low-dimensional fluctuations in V1 population activity shape the response of individual neurons to oriented stimuli and may impact the transmission of sensory information to downstream regions of the primary visual system.NEW & NOTEWORTHY A method termed frequency-separated principal component analysis (FS-PCA) is introduced for analyzing populations of simultaneously recorded neurons. This framework extends standard principal component analysis by extracting components of activity delimited to specific frequency bands. FS-PCA revealed that circuits of the primary visual cortex generate a broad range of components dominated by low-frequency activity. Furthermore, low-dimensional fluctuations in population activity modulated the response of individual neurons to sensory input.

Precise Targeting of Single Microelectrodes to Orientation Pinwheel Centers.

In the mammalian visual system, early stages of visual form perception begin with orientation selective neurons in primary visual cortex (V1). In many species (including humans, monkeys, tree shrews, cats, and ferrets), these neurons are organized in pinwheel-like orientation columns. To study the functional organization within orientation pinwheels, it is important to target pinwheel subdomains precisely. We therefore developed a technique to provide a quantitative determination of the location of pinwheel centers (PCs). Previous studies relied solely on blood vessel images of the cortical surface to guide electrode penetrations to PCs in orientation maps. However, considerable spatial error remained using this method. In the present study, we improved the accuracy of targeting PCs by ensuring perpendicularity of electrodes and by utilizing the orientation tuning of local field potentials (LFP) recorded at or near the optically determined positions.

Optimized but Not Maximized Cue Integration for 3D Visual Perception.

Reconstructing three-dimensional (3D) scenes from two-dimensional (2D) retinal images is an ill-posed problem. Despite this, 3D perception of the world based on 2D retinal images is seemingly accurate and precise. The integration of distinct visual cues is essential for robust 3D perception in humans, but it is unclear whether this is true for non-human primates (NHPs). Here, we assessed 3D perception in macaque monkeys using a planar surface orientation discrimination task. Perception was accurate across a wide range of spatial poses (orientations and distances), but precision was highly dependent on the plane's pose. The monkeys achieved robust 3D perception by dynamically reweighting the integration of stereoscopic and perspective cues according to their pose-dependent reliabilities. Errors in performance could be explained by a prior resembling the 3D orientation statistics of natural scenes. We used neural network simulations based on 3D orientation-selective neurons recorded from the same monkeys to assess how neural computation might constrain perception. The perceptual data were consistent with a model in which the responses of two independent neuronal populations representing stereoscopic cues and perspective cues (with perspective signals from the two eyes combined using nonlinear canonical computations) were optimally integrated through linear summation. Perception of combined-cue stimuli was optimal given this architecture. However, an alternative architecture in which stereoscopic cues, left eye perspective cues, and right eye perspective cues were represented by three independent populations yielded two times greater precision than the monkeys. This result suggests that, due to canonical computations, cue integration for 3D perception is optimized but not maximized.

The speed of neuronal adaptation: A perspective through the visual cortex.

The speed of neuronal adaptation: A perspective through the visual cortex.

Slow gain fluctuations limit benefits of temporal integration in visual cortex.

Sensory neurons represent stimulus information with sequences of action potentials that differ across repeated measurements. This variability limits the information that can be extracted from momentary observations of a neuron's response. It is often assumed that integrating responses over time mitigates this limitation. However, temporal response correlations can reduce the benefits of temporal integration. We examined responses of individual orientation-selective neurons in the primary visual cortex of two macaque monkeys performing an orientation-discrimination task. The signal-to-noise ratio of temporally integrated responses increased for durations up to a few hundred milliseconds but saturated for longer durations. This was true even when cells exhibited little or no adaptation in their response levels. These observations are well explained by a statistical response model in which spikes arise from a Poisson process whose stimulus-dependent rate is modulated by slow, stimulus-independent fluctuations in gain. The response variability arising from the Poisson process is reduced by temporal integration, but the slow modulatory nature of variability due to gain fluctuations is not. Slow gain fluctuations therefore impose a fundamental limit on the benefits of temporal integration.

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.

Bisphenol A exposure perturbs visual function of adult cats by remodeling the neuronal activity in the primary visual pathway.

Bisphenol A (BPA), a common environmental xenoestrogen, has been implicated in physiological and behavioral impairment, but the neuronal basis remains elusive. Although various synaptic mechanisms have been shown to mediate BPA-induced brain deficits, there are almost no reports addressing its underlying physiological mechanisms at the individual neuron level, particularly in the primary visual system. In the present study, using multiple-channel recording technique, we recorded the responses of single neurons in the primary visual system of cats to various direction stimuli both before and after BPA exposure. The results showed that the orientation selectivity of neurons in the primary visual cortex (area 17, A17) was obviously decreased after 2h of intravenous BPA administration (0.2mg/kg). Moreover, there were worse performances of information transmission of A17 neurons, presenting markedly decreased signal-to-noise ratio (SNR). To some extent, these functional decreases were attributable to the altered information inputs from lateral geniculate nucleus (LGN), which showed an increased spontaneous activity. Additionally, local injection of BPA (3.3μg/ml) in A17 resulted in an obvious increase in orientation selectivity and a decrease in neuronal activity, involving enhanced activity of fast-spiking inhibitory interneurons. In conclusion, our results first demonstrate that acute BPA exposure can restrict the visual perception of cats, mainly depending on the alteration of the LGN projection, not the intercortical interaction. Importantly, BPA-induced-brain deficits might not only be confined to the cortical level but also occur as early as at the subcortical level.

Sub-Compartments Within Orientation Columns of Primary Visual Cortex: A Proposal for a Contour Building Architecture

PURPOSE: In the mammalian visual system, early stages of visual form perception begin with orientation selective neurons in primary visual cortex (V1). In many species (including humans, monkeys, tree shrews, cats, and ferrets), these neurons are organized in beautifully arrayed orientation columns, which shift in orientation preference across V1 and are highlighted by orientation pinwheels. However, to date, the relationship of orientation architecture to the encoding of elemental aspects of visual contours is still unknown. METHODS: Using a novel highly accurate method of targeting electrode position, combining with optical image and single-unit recording, we report for the first time the presence of three functionally distinct zones within single orientation domains. RESULTS: We found evidence for three concentric sub-regions centered on the orientation-pinwheel. The central-most region contains neurons with small receptive fields and strong suppressive surrounds, while the outermost region contains neurons with larger receptive fields and weak suppressive surrounds. CONCLUSIONS: We suggest that these zones subseries computation of distinct aspects of visual contours (linear orientation, local curvature, and contour singularities). The orientation domain thus embodies a three stage visual contour processor in V1.

Feedback and Surround Modulated Boundary Detection

Edges are key components of any visual scene to the extent that we can recognise objects merely by their silhouettes. The human visual system captures edge information through neurons in the visual cortex that are sensitive to both intensity discontinuities and particular orientations. The “classical approach” assumes that these cells are only responsive to the stimulus present within their receptive fields, however, recent studies demonstrate that surrounding regions and inter-areal feedback connections influence their responses significantly. In this work we propose a biologically-inspired edge detection model in which orientation selective neurons are represented through the first derivative of a Gaussian function resembling double-opponent cells in the primary visual cortex (V1). In our model we account for four kinds of receptive field surround, i.e. full, far, iso- and orthogonal-orientation, whose contributions are contrast-dependant. The output signal from V1 is pooled in its perpendicular direction by larger V2 neurons employing a contrast-variant centre-surround kernel. We further introduce a feedback connection from higher-level visual areas to the lower ones. The results of our model on three benchmark datasets show a big improvement compared to the current non-learning and biologically-inspired state-of-the-art algorithms while being competitive to the learning-based methods.

Dissociation of Choice Formation and Choice-Correlated Activity in Macaque Visual Cortex.

Responses of individual task-relevant sensory neurons can predict monkeys' trial-by-trial choices in perceptual decision-making tasks. Choice-correlated activity has been interpreted as evidence that the responses of these neurons are causally linked to perceptual judgments. To further test this hypothesis, we studied responses of orientation-selective neurons in V1 and V2 while two macaque monkeys performed a fine orientation discrimination task. Although both animals exhibited a high level of neuronal and behavioral sensitivity, only one exhibited choice-correlated activity. Surprisingly, this correlation was negative: when a neuron fired more vigorously, the animal was less likely to choose the orientation preferred by that neuron. Moreover, choice-correlated activity emerged late in the trial, earlier in V2 than in V1, and was correlated with anticipatory signals. Together, these results suggest that choice-correlated activity in task-relevant sensory neurons can reflect postdecision modulatory signals.SIGNIFICANCE STATEMENT When observers perform a difficult sensory discrimination, repeated presentations of the same stimulus can elicit different perceptual judgments. This behavioral variability often correlates with variability in the activity of sensory neurons driven by the stimulus. Traditionally, this correlation has been interpreted as suggesting a causal link between the activity of sensory neurons and perceptual judgments. More recently, it has been argued that the correlation instead may originate in recurrent input from other brain areas involved in the interpretation of sensory signals. Here, we call both hypotheses into question. We show that choice-related activity in sensory neurons can be highly variable across observers and can reflect modulatory processes that are dissociated from perceptual decision-making.