Cells In Lateral Geniculate Nucleus Research Articles

Impact of acute visual experience on development of LGN receptive fields in the ferret.

Selectivity for direction of motion is a key feature of primary visual cortical neurons. Visual experience is required for direction selectivity in carnivore and primate visual cortex, but the circuit mechanisms of its formation remain incompletely understood. Here we examined how developing lateral geniculate nucleus (LGN) neurons may contribute to cortical direction selectivity. Using in vivo electrophysiology techniques, we examined LGN receptive field properties of visually naïve female ferrets before and after exposure to 6 hours of motion stimuli in order to assess the effect of acute visual experience on LGN cell development. We found that acute experience with motion stimuli did not significantly affect the weak orientation or direction selectivity of LGN neurons. In addition, we found that neither latency nor sustainedness or transience of LGN neurons significantly changed with acute experience. These results suggest that the direction selectivity that emerges in cortex after acute experience is computed in cortex and cannot be explained by changes in LGN cells.SIGNIFICANCE STATEMENT:The development of typical neural circuitry requires experience-independent and experience-dependent factors. In the visual cortex of carnivores and primates, selectivity for motion arises as a result of experience, but we do not understand whether the major brain area that sits between the retina and the visual cortex - the lateral geniculate nucleus of the thalamus - also participates. Here we found that lateral geniculate neurons do not exhibit changes as a result of several hours of visual experience with moving stimuli, at a time when visual cortical neurons undergo a rapid change. We conclude that lateral geniculate neurons do not participate in this plasticity, and that changes in cortex are likely responsible for the development of direction selectivity in carnivores and primates.

3D electron microscopy and volume-based bouton sorting reveal the selectivity of inputs onto geniculate relay cell and interneuron dendrite segments.

The visual signals evoked at the retinal ganglion cells are modified and modulated by various synaptic inputs that impinge on lateral geniculate nucleus cells before they are sent to the cortex. The selectivity of geniculate inputs for clustering or forming microcircuits on discrete dendritic segments of geniculate cell types may provide the structural basis for network properties of the geniculate circuitry and differential signal processing through the parallel pathways of vision. In our study, we aimed to reveal the patterns of input selectivity on morphologically discernable relay cell types and interneurons in the mouse lateral geniculate nucleus. We used two sets of Scanning Blockface Electron Microscopy (SBEM) image stacks and Reconstruct software to manually reconstruct of terminal boutons and dendrite segments. First, using an unbiased terminal sampling (UTS) approach and statistical modeling, we identified the criteria for volume-based sorting of geniculate boutons into their putative origins. Geniculate terminal boutons that were sorted in retinal and non-retinal categories based on previously described mitochondrial morphology, could further be sorted into multiple subpopulations based on their bouton volume distributions. Terminals deemed non-retinal based on the morphological criteria consisted of five distinct subpopulations, including small-sized putative corticothalamic and cholinergic boutons, two medium-sized putative GABAergic inputs, and a large-sized bouton type that contains dark mitochondria. Retinal terminals also consisted of four distinct subpopulations. The cutoff criteria for these subpopulations were then applied to datasets of terminals that synapse on reconstructed dendrite segments of relay cells or interneurons. Using a network analysis approach, we found an almost complete segregation of retinal and cortical terminals on putative X-type cell dendrite segments characterized by grape-like appendages and triads. On these cells, interneuron appendages intermingle with retinal and other medium size terminals to form triads within glomeruli. In contrast, a second, presumed Y-type cell displayed dendrodendritic puncta adherentia and received all terminal types without a selectivity for synapse location; these were not engaged in triads. Furthermore, the contribution of retinal and cortical synapses received by X-, Y- and interneuron dendrites differed such that over 60% of inputs to interneuron dendrites were from the retina, as opposed to 20% and 7% to X- and Y-type cells, respectively. The results underlie differences in network properties of synaptic inputs from distinct origins on geniculate cell types.

An Array of Light‐Stimulated Two‐Terminal Synaptic Devices with the Modulation of Electric Polarity

AbstractNeuromorphic visual systems based on optoelectronic synaptic devices have been recently studied to simulate the retina and visual cortex of a human being. Now it is shown that an array of optoelectronic synaptic devices based on the two‐terminal structure of Si/perovskite/Au may mimic the functionalities of lateral geniculate nucleus (LGN) cells. Benefiting from the photovoltaic effect, the devices can work under a self‐powered mode. Diverse synaptic functionalities such as postsynaptic current, paired‐pulse facilitation/depression, spike duration‐dependent plasticity, spike number‐dependent plasticity, and spike rate‐dependent plasticity have been simulated. By modulating the electric bias of the devices in the array the simulation of the positional and orientational recognition of the LGN cells is demonstrated.

Dynamics of Temporal Integration in the Lateral Geniculate Nucleus.

Before visual information from the retina reaches primary visual cortex (V1), it is dynamically filtered by the lateral geniculate nucleus (LGN) of the thalamus, the first location within the visual hierarchy at which nonretinal structures can significantly influence visual processing. To explore the form and dynamics of geniculate filtering we used data from monosynpatically connected pairs of retinal ganglion cells (RGCs) and LGN relay cells in the cat that, under anesthetized conditions, were stimulated with binary white noise and/or drifting sine-wave gratings to train models of increasing complexity to predict which RGC spikes were relayed to cortex, what we call “relay status.” In addition, we analyze and compare a smaller dataset recorded in the awake state to assess how anesthesia might influence our results. Consistent with previous work, we find that the preceding retinal interspike interval (ISI) is the primary determinate of relay status with only modest contributions from longer patterns of retinal spikes. Including the prior activity of the LGN cell further improved model predictions, primarily by indicating epochs of geniculate burst activity in recordings made under anesthesia, and by allowing the model to capture gain control-like behavior within the awake LGN. Using the same modeling framework, we further demonstrate that the form of geniculate filtering changes according to the level of activity within the early visual circuit under certain stimulus conditions. This finding suggests a candidate mechanism by which a stimulus specific form of gain control may operate within the LGN.

A Computational Model of Direction Selectivity in Macaque V1 Cortex Based on Dynamic Differences between On and Off Pathways.

This paper is about neural mechanisms of direction selectivity (DS) in macaque primary visual cortex, V1. We present data (on male macaque) showing strong DS in a majority of simple cells in V1 layer 4Cα, the cortical layer that receives direct afferent input from the magnocellular division of the lateral geniculate nucleus (LGN). Magnocellular LGN cells are not direction-selective. To understand the mechanisms of DS, we built a large-scale, recurrent model of spiking neurons called DSV1. Like its predecessors, DSV1 reproduces many visual response properties of V1 cells including orientation selectivity. Two important new features of DSV1 are (1) DS is initiated by small, consistent dynamic differences in the visual responses of OFF and ON Magnocellular LGN cells, and (2) DS in the responses of most model simple cells is increased over those of their feedforward inputs; this increase is achieved through dynamic interaction of feedforward and intracortical synaptic currents without the use of intracortical direction-specific connections. The DSV1 model emulates experimental data in the following ways: (1) most 4Cα Simple cells were highly direction-selective but 4Cα Complex cells were not; (2) the preferred directions of the model's direction-selective Simple cells were invariant with spatial and temporal frequency (TF); (3) the distribution of the preferred/opposite ratio across the model's population of cells was very close to that found in experiments. The strong quantitative agreement between DS in data and in model simulations suggests that the neural mechanisms of DS in DSV1 may be similar to those in the real visual cortex.SIGNIFICANCE STATEMENT Motion perception is a vital part of our visual experience of the world. In monkeys, whose vision resembles that of humans, the neural computation of the direction of a moving target starts in the primary visual cortex, V1, in layer 4Cα that receives input from the eye through the lateral geniculate nucleus (LGN). How direction selectivity (DS) is generated in layer 4Cα is an outstanding unsolved problem in theoretical neuroscience. In this paper, we offer a solution based on plausible biological mechanisms. We present a new large-scale circuit model in which DS originates from slightly different LGN ON/OFF response time-courses and is enhanced in cortex without the need for direction-specific intracortical connections. The model's DS is in quantitative agreement with experiments.

Emergence of Lie Symmetries in Functional Architectures Learned by CNNs.

In this paper we study the spontaneous development of symmetries in the early layers of a Convolutional Neural Network (CNN) during learning on natural images. Our architecture is built in such a way to mimic some properties of the early stages of biological visual systems. In particular, it contains a pre-filtering step ℓ0 defined in analogy with the Lateral Geniculate Nucleus (LGN). Moreover, the first convolutional layer is equipped with lateral connections defined as a propagation driven by a learned connectivity kernel, in analogy with the horizontal connectivity of the primary visual cortex (V1). We first show that the ℓ0 filter evolves during the training to reach a radially symmetric pattern well approximated by a Laplacian of Gaussian (LoG), which is a well-known model of the receptive profiles of LGN cells. In line with previous works on CNNs, the learned convolutional filters in the first layer can be approximated by Gabor functions, in agreement with well-established models for the receptive profiles of V1 simple cells. Here, we focus on the geometric properties of the learned lateral connectivity kernel of this layer, showing the emergence of orientation selectivity w.r.t. the tuning of the learned filters. We also examine the short-range connectivity and association fields induced by this connectivity kernel, and show qualitative and quantitative comparisons with known group-based models of V1 horizontal connections. These geometric properties arise spontaneously during the training of the CNN architecture, analogously to the emergence of symmetries in visual systems thanks to brain plasticity driven by external stimuli.

Spatial Resolution of Suprachoroidal-Transretinal Stimulation Estimated by Recording Single-Unit Activity From the Cat Lateral Geniculate Nucleus.

Retinal prostheses are devices used to restore visual sensation in patients suffering from photoreceptor degeneration, such as retinitis pigmentosa. Suprachoroidal–transretinal stimulation (STS) is a prosthesis with retinal electrodes located in the sclera. STS has the advantage that it is safer than epiretinal or subretinal prostheses, as the implant is not directly attached to the retinal tissue. We have previously reported feasibility of STS with animal experiments and clinical trials. However, functional evaluation with neurophysiological experiments is still largely missing. To estimate the spatial resolution of STS, single-unit activities in response to STS were recorded from relay cells in the dorsal lateral geniculate nucleus of cats, and the response probability of the units was analyzed in relation to the distance between the stimulus location and the receptive field of each recorded unit. A platinum electrode was attached to the sclera after lamellar resection, and the return electrode was placed in the vitreous. The stimulating current, which ranged from 50 to 500 μA, was applied between these electrodes, and the probability of spike responses occurring just after retinal stimulation was measured. The distance at half-maximum of response was determined from the collected response probabilities as a function of stimulus intensity for all units characterized by their distances from the receptive field center to the stimulation point. As the stimulation became weaker, this distance decreased to 1.8° at 150 and 100 μA. As another estimation, the radius of 25% response probability was 1.4° at 100 μA. The diameter of the stimulated cat retinal area, 3.6° or 2.8°, corresponds to human visual acuity of 0.005 or 0.007, or finger counting. Considering the lower hazard to the retina of STS and its potentially large visual field coverage, STS is an attractive method for retinal prosthetic device development.

LGN-CNN: A biologically inspired CNN architecture

In this paper we introduce a biologically inspired Convolutional Neural Network (CNN) architecture called LGN-CNN that has a first convolutional layer composed of a single filter that mimics the role of the Lateral Geniculate Nucleus (LGN). The first layer of the neural network shows a rotational symmetric pattern justified by the structure of the net itself that turns up to be an approximation of a Laplacian of Gaussian (LoG). The latter function is in turn a good approximation of the receptive field profiles (RFPs) of the cells in the LGN. The analogy with the visual system is established, emerging directly from the architecture of the neural network. A proof of rotation invariance of the first layer is given on a fixed LGN-CNN architecture and the computational results are shown. Thus, contrast invariance capability of the LGN-CNN is investigated and a comparison between the Retinex effects of the first layer of LGN-CNN and the Retinex effects of a LoG is provided on different images. A statistical study is done on the filters of the second convolutional layer with respect to biological data. In conclusion, the model we have introduced approximates well the RFPs of both LGN and V1 attaining similar behavior as regards long range connections of LGN cells that show Retinex effects.

A theory of direction selectivity for macaque primary visual cortex

This paper offers a theory for the origin of direction selectivity (DS) in the macaque primary visual cortex, V1. DS is essential for the perception of motion and control of pursuit eye movements. In the macaque visual pathway, neurons with DS first appear in V1, in the Simple cell population of the Magnocellular input layer 4Cα. The lateral geniculate nucleus (LGN) cells that project to these cortical neurons, however, are not direction selective. We hypothesize that DS is initiated in feed-forward LGN input, in the summed responses of LGN cells afferent to a cortical cell, and it is achieved through the interplay of 1) different visual response dynamics of ON and OFF LGN cells and 2) the wiring of ON and OFF LGN neurons to cortex. We identify specific temporal differences in the ON/OFF pathways that, together with item 2, produce distinct response time courses in separated subregions; analysis and simulations confirm the efficacy of the mechanisms proposed. To constrain the theory, we present data on Simple cells in layer 4Cα in response to drifting gratings. About half of the cells were found to have high DS, and the DS was broadband in spatial and temporal frequency (SF and TF). The proposed theory includes a complete analysis of how stimulus features such as SF and TF interact with ON/OFF dynamics and LGN-to-cortex wiring to determine the preferred direction and magnitude of DS.

From Receptive to Perceptive Fields: Size-Dependent Asymmetries in Both Negative Afterimages and Subcortical On and Off Post-Stimulus Responses.

Negative afterimages are perceptual phenomena that occur after physical stimuli disappear from sight. Their origin is linked to transient post-stimulus responses of visual neurons. The receptive fields (RFs) of these subcortical ON- and OFF-center neurons exhibit antagonistic interactions between central and surrounding visual space, resulting in selectivity for stimulus polarity and size. These two features are closely intertwined, yet their relationship to negative afterimage perception remains unknown. Here we tested whether size differentially affects the perception of bright and dark negative afterimages in humans of both sexes, and how this correlates with neural mechanisms in subcortical ON and OFF cells. Psychophysically, we found a size-dependent asymmetry whereby dark disks produce stronger and longer-lasting negative afterimages than bright disks of equal contrast at sizes >0.8°. Neurophysiological recordings from retinal and relay cells in female cat dorsal lateral geniculate nucleus showed that subcortical ON cells exhibited stronger sustained post-stimulus responses to dark disks, than OFF cells to bright disks, at sizes >1°. These sizes agree with the emergence of center-surround antagonism, revealing stronger suppression to opposite-polarity stimuli for OFF versus ON cells, particularly in dorsal lateral geniculate nucleus. Using a network-based retino-geniculate model, we confirmed stronger antagonism and temporal transience for OFF-cell post-stimulus rebound responses. A V1 population model demonstrated that both strength and duration asymmetries can be propagated to downstream cortical areas. Our results demonstrate how size-dependent antagonism impacts both the neuronal post-stimulus response and the resulting afterimage percepts, thereby supporting the idea of perceptual RFs reflecting the underlying neuronal RF organization of single cells.SIGNIFICANCE STATEMENT Visual illusions occur when sensory inputs and perceptual outcomes do not match, and provide a valuable tool to understand transformations from neural to perceptual responses. A classic example are negative afterimages that remain visible after a stimulus is removed from view. Such perceptions are linked to responses in early visual neurons, yet the details remain poorly understood. Combining human psychophysics, neurophysiological recordings in cats and retino-thalamo-cortical computational modeling, our study reveals how stimulus size and the receptive-field structure of subcortical ON and OFF cells contributes to the parallel asymmetries between neural and perceptual responses to bright versus dark afterimages. Thus, this work provides a deeper link from the underlying neural mechanisms to the resultant perceptual outcomes.

The relativity of color perception

Physical colors, i.e. reflected or emitted lights entering the eyes from a visual environment, are converted into perceived colors sensed by humans by neurophysiological mechanisms. These processes involve both three types of photoreceptors, the LMS cones, and spectrally opponent and non-opponent interactions resulting from the activity rates of ganglion and lateral geniculate nucleus cells. Thus, color perception is a phenomenon inherently linked to an experimental environment (the visual scene) and an observing apparatus (the human visual system). This is clearly reminiscent of the conceptual foundation of both relativity and quantum mechanics, where the link is between a physical system and the measuring instruments. The relationship between color perception and relativity was explicitly examined for the first time by the physicist H. Yilmaz in 1962 from an experimental point of view. The main purpose of this contribution is to present a rigorous mathematical model that, by taking into account both trichromacy and color opponency, permits to explain on a purely theoretical basis the relativistic color perception phenomena argued by Yilmaz. Instead of relying directly on relativistic considerations, we base our theory on a quantum interpretation of color perception together with just one assumption, called trichromacy axiom, that summarizes well-established properties of trichromatic color vision within the framework of Jordan algebras. We show how this approach allows us to reconcile trichromacy with Hering’s opponency and also to derive the relativistic properties of perceived colors without any additional mathematical or experimental assumption. In doing so, we also introduce several novel and mathematically rigorous definitions of chromatic attributes and discuss their counterparts in classical colorimetry. Finally, we underline the important role played by the Hilbert metric in our framework and its compatibility with known experimental data.

Extensive cone-dependent spectral opponency within a discrete zone of the lateral geniculate nucleus supporting mouse color vision

SummaryColor vision, originating with opponent processing of spectrally distinct photoreceptor signals, plays important roles in animal behavior.1, 2, 3, 4 Surprisingly, however, comparatively little is understood about color processing in the brain, including in widely used laboratory mammals such as mice. The retinal gradient in S- and M-cone opsin (co-)expression has traditionally been considered an impediment to mouse color vision.5, 6, 7, 8 However, recent data indicate that mice exhibit robust chromatic discrimination within the central-upper visual field.9 Retinal color opponency has been reported to emerge from superimposing inhibitory surround receptive fields on the cone opsin expression gradient, and by introducing opponent rod signals in retinal regions with sparse M-cone opsin expression.10, 11, 12, 13 The relative importance of these proposed mechanisms in determining the properties of neurons at higher visual processing stages remains unknown. We address these questions using multielectrode recordings from the lateral geniculate nucleus (LGN) in mice with altered M-cone spectral sensitivity (Opn1mwR) and multispectral stimuli that allow selective modulation of signaling by individual opsin classes. Remarkably, we find many (∼25%) LGN cells are color opponent, that such cells are localized to a distinct medial LGN zone and that their properties cannot simply be explained by the proposed retinal opponent mechanisms. Opponent responses in LGN can be driven solely by cones, independent of cone-opsin expression gradients and rod input, with many cells exhibiting spatially congruent antagonistic receptive fields. Our data therefore suggest previously unidentified mechanisms may support extensive and sophisticated color processing in the mouse LGN.

Different roles of subcortical inputs in V1 responses to luminance and contrast.

Cells in the primary visual cortex (V1) generally respond weakly to large uniform luminance stimuli. Only a subset of V1 cells is thought to encode uniform luminance information. In natural scenes, local luminance is an important feature for defining an object that varies and coexists with local spatial contrast. However, the strategies used by V1 cells to encode local mean luminance for spatial contrast stimuli remain largely unclear. Here, using extracellular recordings in anesthetized cats, we investigated the responses of V1 cells by comparing with those of retinal ganglion (RG) cells and lateral geniculate nucleus (LGN) cells to simultaneous and rapid changes in luminance and spatial contrast. Almost all V1 cells exhibited a strong monotonic increasing luminance tuning when they were exposed to high spatial contrast. Thus, V1 cells encode the luminance carried by spatial contrast stimuli with the monotonically increasing response function. Moreover, high contrast decreased luminance tuning of OFF cells but increased that of in ON cells in RG and LGN. The luminance and contrast tunings of LGN ON cells were highly separable as V1 cells, whereas those of LGN OFF cells were lowly separable. These asymmetrical effects of spatial contrast on ON/OFF channels might underlie the robust ability of V1 cells to perform luminance tuning when exposed to spatial contrast stimuli.

A cell model in the ventral visual pathway for the detection of circles of curvature constituting figures

The contour of an arbitrary figure can be represented as a group of circles of curvature in contact with it, with each curvature circle represented by its center OC and radius r. We propose a series of cell models for detecting this circle, which is composed of a lateral geniculate nucleus (LGN) cell, nondirectionally selective (NDS) simple cell, and curvature-circle detection cell (CDC). The LGN and NDS simple cells were previously modeled. The CDC has been modeled as follows. Each tangent in contact with this circle is detected by an NDS simple cell that performs the Hough transformation of LGN cell responses, and then this tangent is transformed to a three-dimensional (3D) normal line in a CDC column. This transformation has been named a 3D normal-line transform. Performing this transformation for all tangents causes a CDC at the intersection of these normal lines to fire most intensively, and thus the OC and r of the circle is detected as the coordinates of this intersection. Therefore, the CDC has been modeled as this 3D normal-line transform. Based on this CDC, we model two types of constancy CDC: a position-invariant CDC and a curvature-invariant CDC. These three types of CDC reflect the response to various stimuli in actual area V4 cells. In order to validate these CDC types neurophysiologically, we propose an experimental method using microelectrodes. Cell models previously reported correspond to this hierarchy: the S1, S2, and C2 cells correspond to the NDS simple cell, CDC, and position-invariant CDC, respectively.

Fractal brain dynamics: from Mandelbrot to marmosets.

Fractal brain dynamics: from Mandelbrot to marmosets.

Fractal spike dynamics and neuronal coupling in the primate visual system.

We measured fractal (self-similar) fluctuations in ongoing spiking activity in subcortical (lateral geniculate nucleus, LGN) and cortical (area MT) visual areas in anaesthetised marmosets. Cells in the evolutionary ancient koniocellular LGN pathway and in area MT show high-amplitude fractal fluctuations, whereas evolutionarily newer parvocellular and magnocellular LGN cells do not. Spiking activity in koniocellular cells and MT cells shows substantial correlation to the local population activity, whereas activity in parvocellular and magnocellular cells is less correlated with local activity. We develop a model consisting of a fractal process and a global rate modulation which can reproduce and explain the fundamental relationship between fractal fluctuations and population coupling in LGN and MT. The model provides a unified account of apparently disparate aspects of neural spiking activity and can improve our understanding of information processing in evolutionary ancient and modern visual pathways. The brain represents and processes information through patterns of spiking activity, which is influenced by local and widescale brain circuits as well as intrinsic neural dynamics. Whether these influences have independent or linked effects on spiking activity is, however, not known. Here we measured spiking activity in two visual centres, the lateral geniculate nucleus (LGN) and cortical area MT, in marmoset monkeys. By combining the Fano-factor time curve, power spectral analysis and rescaled range analysis, we reveal inherent fractal fluctuations of spiking activity in LGN and MT. We found that the evolutionary ancient koniocellular (K) pathway in LGN and area MT exhibits strong fractal fluctuations at short (<1s) time scales. Parvocellular (P) and magnocellular (M) LGN cells show weaker fractal fluctuations at longer (multi-second) time scales. In both LGN and MT, the amplitude and time scale of fractal fluctuations can explain short and long time scale spiking dynamics. We further show differential neuronal coupling of LGN and MT cells to local population spiking activity. The population coupling is intrinsically linked to fractal fluctuations: neurons showing stronger fluctuations are more strongly correlated to the local population activity. To understand this relationship, we modelled spiking activity using a fractal inhomogeneous Poisson process with dynamic rate, which is the product of an intrinsic stochastic fractal rate and a global modulatory gain. Our model explains the intrinsic links between neuronal spike rate and population coupling in LGN and MT, and establishes a unified account of dynamic spiking properties in afferent visual pathways.

Relation of koniocellular layers of dorsal lateral geniculate to inferior pulvinar nuclei in common marmosets.

Traditionally, the dorsal lateral geniculate nucleus (LGN) and the inferior pulvinar (IPul) nucleus are considered as anatomically and functionally distinct thalamic nuclei. However, in several primate species it has also been established that the koniocellular (K) layers of LGN and parts of the IPul have a shared pattern of immunoreactivity for the calcium-binding protein calbindin. These calbindin-rich cells constitute a thalamic matrix system which is implicated in thalamocortical synchronisation. Further, the K layers and IPul are both involved in visual processing and have similar connections with retina and superior colliculus. Here, we confirmed the continuity between calbindin-rich cells in LGN K layers and the central lateral division of IPul (IPulCL) in marmoset monkeys. By employing a high-throughput neuronal tracing method, we found that both the K layers and IPulCL form comparable patterns of connections with striate and extrastriate cortices; these connections are largely different to those of the parvocellular and magnocellular laminae of LGN. Retrograde tracer-labelled cells and anterograde tracer-labelled axon terminals merged seamlessly from IPulCL into LGN K layers. These results support continuity between LGN K layers and IPulCL, providing an anatomical basis for functional congruity of this region of the dorsal thalamic matrix and calling into question the traditional segregation between LGN and the inferior pulvinar nucleus.

Binocular summation in marmoset lateral geniculate nucleus.

In primates and carnivores, the main laminae of the dorsal lateral geniculate nucleus (LGN) receive monocular excitatory input in an eye-alternating fashion. There is also evidence that nondominant eye stimulation can reduce responses to dominant eye stimulation and that a subset of LGN cells in the koniocellular (K) layers receives convergent binocular excitatory input from both eyes. What is not known is how the two eye inputs summate in the K layers of LGN. Here, we aimed to answer this question by making extracellular array electrode recordings targeted to K layers in the marmoset (Callithrix jacchus) LGN, as visual stimuli (flashed 200 ms temporal square-wave pulses or drifting gratings) were presented to each eye independently or to both eyes simultaneously. We found that when the flashed stimulus was presented to both eyes, compared to the dominant eye, the peak firing rate of most cells (61%, 14/23) was reduced. The remainder showed response facilitation (17%) or partial summation (22%). A greater degree of facilitation was seen when the total number of spikes across the stimulus time window (200 ms) rather than peak firing rates was measured. A similar pattern of results was seen for contrast-varying gratings and for small numbers of parvocellular (n = 12) and magnocellular (n = 3) cells recorded. Our findings show that binocular summation in the marmoset LGN is weak and predominantly sublinear in nature.

Cell-Type-Specific Thalamocortical Inputs Constrain Direction Map Formation in Visual Cortex

Finding the relationship between individual cognitive functions and cell-type-specific neuronal circuits is acentral topic in neuroscience. In cats, the lateral geniculate nucleus (LGN) contains several cell types carrying spatially and temporally precise visual information. Whereas LGN cell types lack selectivity for motion direction, neurons in the primary visual cortex (area 17) exhibit sharp direction selectivity. Whether and how such de novo formation of direction selectivity depends on LGN cell types remains unknown. Here, we addressed this question using invivo two-photon calcium imaging in cat area 17, which consists of two compartments receiving different combinations of inputs from the LGN cell types. The direction map in area 17 showed unique fragmented organization and was present only in small and distributed cortical domains. Moreover, direction-selective domains preferentially localized in specific compartments receiving Y and W inputs carrying low spatial frequency visual information, indicating that cell-type-specific thalamocortical projections constrain the formation of direction selectivity.

Single-cell transcriptomics of the developing lateral geniculate nucleus reveals insights into circuit assembly and refinement

Coordinated changes in gene expression underlie the early patterning and cell-type specification of the central nervous system. However, much less is known about how such changes contribute to later stages of circuit assembly and refinement. In this study, we employ single-cell RNA sequencing to develop a detailed, whole-transcriptome resource of gene expression across four time points in the developing dorsal lateral geniculate nucleus (LGN), a visual structure in the brain that undergoes a well-characterized program of postnatal circuit development. This approach identifies markers defining the major LGN cell types, including excitatory relay neurons, oligodendrocytes, astrocytes, microglia, and endothelial cells. Most cell types exhibit significant transcriptional changes across development, dynamically expressing genes involved in distinct processes including retinotopic mapping, synaptogenesis, myelination, and synaptic refinement. Our data suggest that genes associated with synapse and circuit development are expressed in a larger proportion of nonneuronal cell types than previously appreciated. Furthermore, we used this single-cell expression atlas to identify the Prkcd-Cre mouse line as a tool for selective manipulation of relay neurons during a late stage of sensory-driven synaptic refinement. This transcriptomic resource provides a cellular map of gene expression across several cell types of the LGN, and offers insight into the molecular mechanisms of circuit development in the postnatal brain.