ON/OFF domains shape receptive field structure in mouse visual cortex

Contrast gain control is a reparameterization of a population response curve

Neurons in primary visual cortex (area V1) adapt in different degrees to the average contrast of the environment, suggesting that the representation of visual stimuli may interact with the state of cortical gain control in complex ways. To investigate this possibility, we measured and analyzed the responses of neural populations to visual stimuli as a function of contrast in different environments, each characterized by a unique distribution of contrast. Our findings reveal that, for a given stimulus, the population response can be described by a vector functionr ( g e c ) , where the gaing e is a decreasing function of the mean contrast of the environment. Thus, gain control can be viewed as a reparameterization of a population response curve, which is invariant across environments. Different stimuli are mapped to distinct curves, all originating from a common origin, corresponding to a zero-contrast response. Altogether, our findings provide a straightforward, geometric interpretation of contrast gain control at the population level and show that changes in gain are well coordinated among members of a neural population.

Persistent spiking activity in neuromorphic circuits incorporating post-inhibitory rebound excitation

Objective. This study introduces a novel approach for integrating the post-inhibitory rebound excitation (PIRE) phenomenon into a neuronal circuit. Excitatory and inhibitory synapses are designed to establish a connection between two hardware neurons, effectively forming a network. The model demonstrates the occurrence of PIRE under strong inhibitory input. Emphasizing the significance of incorporating PIRE in neuromorphic circuits, the study showcases generation of persistent activity within cyclic and recurrent spiking neuronal networks.Approach. The neuronal and synaptic circuits are designed and simulated in Cadence Virtuoso using TSMC 180 nm technology. The operating mechanism of the PIRE phenomenon integrated into a hardware neuron is discussed. The proposed circuit encompasses several parameters for effectively controlling multiple electrophysiological features of a neuron.Main results. The neuronal circuit has been tuned to match the response of a biological neuron. The efficiency of this circuit is evaluated by computing the average power dissipation and energy consumption per spike through simulation. The sustained firing of neural spikes is observed till 1.7 s using the two neuronal networks.Significance. Persistent activity has significant implications for various cognitive functions such as working memory, decision-making, and attention. Therefore, hardware implementation of these functions will require our PIRE-integrated model. Energy-efficient neuromorphic systems are useful in many artificial intelligence applications, including human-machine interaction, IoT devices, autonomous systems, and brain-computer interfaces.

Visual neurons recognize complex image transformations

Natural visual scenes are dominated by sequences of transforming images. Spatial visual information is thought to be processed by detection of elemental stimulus features which are recomposed into scenes. How image information is integrated over time is unclear. We explored visual information encoding in the optic tectum. Unbiased stimulus presentation shows that the majority of tectal neurons recognize image sequences. This is achieved by temporally dynamic response properties, which encode complex image transitions over several hundred milliseconds. Calcium imaging reveals that neurons that encode spatiotemporal image sequences fire in spike sequences that predict a logical diagram of spatiotemporal information processing. Furthermore, the temporal scale of visual information is tuned by experience. This study indicates how neurons recognize dynamic visual scenes that transform over time.

Self-organization of modular activity in immature cortical networks

During development, cortical activity is organized into distributed modular patterns that are a precursor of the mature columnar functional architecture. Theoretically, such structured neural activity can emerge dynamically from local synaptic interactions through a recurrent network with effective local excitation with lateral inhibition (LE/LI) connectivity. Utilizing simultaneous widefield calcium imaging and optogenetics in juvenile ferret cortex prior to eye opening, we directly test several critical predictions of an LE/LI mechanism. We show that cortical networks transform uniform stimulations into diverse modular patterns exhibiting a characteristic spatial wavelength. Moreover, patterned optogenetic stimulation matching this wavelength selectively biases evoked activity patterns, while stimulation with varying wavelengths transforms activity towards this characteristic wavelength, revealing a dynamic compromise between input drive and the network's intrinsic tendency to organize activity. Furthermore, the structure of early spontaneous cortical activity - which is reflected in the developing representations of visual orientation - strongly overlaps that of uniform opto-evoked activity, suggesting a common underlying mechanism as a basis for the formation of orderly columnar maps underlying sensory representations in the brain.

Stimulus-dependent differences in cortical versus subcortical contributions to visual detection in mice

The primary visual cortex (V1) and the superior colliculus (SC) both occupy stations early in the processing of visual information. They have long been thought to perform distinct functions, with the V1 supporting the perception of visual features and the SC regulating orienting to visual inputs. However, growing evidence suggests that the SC supports the perception of many of the same visual features traditionally associated with the V1. To distinguish V1 and SC contributions to visual processing, it is critical to determine whether both areas causally contribute to the detection of specific visual stimuli. Here, mice reported changes in visual contrast or luminance near their perceptual threshold while white noise patterns of optogenetic stimulation were delivered to V1 or SC inhibitory neurons. We then performed a reverse correlation analysis on the optogenetic stimuli to estimate a neuronal-behavioral kernel (NBK), a moment-to-moment estimate of the impact of V1 or SC inhibition on stimulus detection. We show that the earliest moments of stimulus-evoked activity in the SC are critical for the detection of both luminance and contrast changes. Strikingly, there was a robust stimulus-aligned modulation in the V1 contrast-detection NBK but no sign of a comparable modulation for luminance detection. The data suggest that behavioral detection of visual contrast depends on both V1 and SC spiking, whereas mice preferentially use SC activity to detect changes in luminance. Electrophysiological recordings showed that neurons in both the SC and V1 responded strongly to both visual stimulus types, while the reverse correlation analysis reveals when these neuronal signals actually contribute to visually guided behaviors.

Temporal weighting of cortical and subcortical spikes reveals stimulus dependent differences in their contributions to behavior

The primary visual cortex (V1) and the superior colliculus (SC) both occupy stations early in the processing of visual information. They have long been thought to perform distinct functions, with V1 supporting perception of visual features and the SC regulating orienting to visual inputs. However, growing evidence suggests that the SC supports perception of many of the same visual features traditionally associated with V1. To distinguish V1 and SC contributions to visual processing, it is critical to determine whether both areas causally contribute to perception of specific visual stimuli. Here, mice reported changes in visual contrast or luminance near perceptual threshold while we presented white noise patterns of optogenetic stimulation to V1 or SC inhibitory neurons. We then performed a reverse correlation analysis on the optogenetic stimuli to estimate a neuronal-behavioral kernel (NBK), a moment-to-moment estimate of the impact of V1 or SC inhibition on stimulus detection. We show that the earliest moments of stimulus-evoked activity in SC are critical for detection of both luminance or contrast changes. Strikingly, there was a robust stimulus-aligned modulation in the V1 contrast-detection NBK, but no sign of a comparable modulation for luminance detection. The data suggest that perception of visual contrast depends on both V1 and SC spiking, whereas mice preferentially use SC activity to detect changes in luminance. Electrophysiological recordings showed that neurons in both SC and V1 responded strongly to both visual stimulus types, while the reverse correlation analysis reveals when these neuronal signals actually contribute to visually-guided behaviors.

Dynamic Recruitment of the Feedforward and Recurrent Mechanism for Black-White Asymmetry in the Primary Visual Cortex

Black and white information is asymmetrically distributed in natural scenes, evokes asymmetric neuronal responses, and causes asymmetric perceptions. Recognizing the universality and essentiality of black-white asymmetry in visual information processing, the neural substrates for black-white asymmetry remain unclear. To disentangle the role of the feedforward and recurrent mechanisms in the generation of cortical black-white asymmetry, we recorded the V1 laminar responses and LGN responses of anesthetized cats of both sexes. In a cortical column, we found that black-white asymmetry starts at the input layer and becomes more pronounced in the output layer. We also found distinct dynamics of black-white asymmetry between the output layer and the input layer. Specifically, black responses dominate in all layers after stimulus onset. After stimulus offset, black and white responses are balanced in the input layer, but black responses still dominate in the output layer. Compared with that in the input layer, the rebound response in the output layer is significantly suppressed. The relative suppression strength evoked by white stimuli is notably stronger and depends on the location within the ON-OFF cortical map. A model with delayed and polarity-selective cortical suppression explains black-white asymmetry in the output layer, within which prominent recurrent connections are identified by Granger causality analysis. In addition to black-white asymmetry in response strength, the interlaminar differences in spatial receptive field varied dynamically. Our findings suggest that the feedforward and recurrent mechanisms are dynamically recruited for the generation of black-white asymmetry in V1.SIGNIFICANCE STATEMENT Black-white asymmetry is universal and essential in visual information processing, yet the neural substrates for cortical black-white asymmetry remain unknown. Leveraging V1 laminar recordings, we provided the first laminar pattern of black-white asymmetry in cat V1 and found distinct dynamics of black-white asymmetry between the output layer and the input layer. Comparing black-white asymmetry across three visual hierarchies, the LGN, V1 input layer, and V1 output layer, we demonstrated that the feedforward and recurrent mechanisms are dynamically recruited for the generation of cortical black-white asymmetry. Our findings not only enhance our understanding of laminar processing within a cortical column but also elucidate how feedforward connections and recurrent connections interact to shape neuronal response properties.

High-resolution structural and functional retinal imaging in the awake behaving mouse

The laboratory mouse has provided tremendous insight to the underpinnings of mammalian central nervous system physiology. In recent years, it has become possible to image single neurons, glia and vascular cells in vivo by using head-fixed preparations combined with cranial windows to study local networks of activity in the living brain. Such approaches have also succeeded without the use of general anesthesia providing insights to the natural behaviors of the central nervous system. However, the same has not yet been developed for the eye, which is constantly in motion. Here we characterize a novel head-fixed preparation that enables high-resolution adaptive optics retinal imaging at the single-cell level in awake-behaving mice. We reveal three new functional attributes of the normal eye that are overlooked by anesthesia: 1) High-frequency, low-amplitude eye motion of the mouse that is only present in the awake state 2) Single-cell blood flow in the mouse retina is reduced under anesthesia and 3) Mouse retinae thicken in response to ketamine/xylazine anesthesia. Here we show key benefits of the awake-behaving preparation that enables study of retinal physiology without anesthesia to study the normal retinal physiology in the mouse.

The brain-inspired decoder for natural visual image reconstruction

The visual system provides a valuable model for studying the working mechanisms of sensory processing and high-level consciousness. A significant challenge in this field is the reconstruction of images from decoded neural activity, which could not only test the accuracy of our understanding of the visual system but also provide a practical tool for solving real-world problems. Although recent advances in deep learning have improved the decoding of neural spike trains, little attention has been paid to the underlying mechanisms of the visual system. To address this issue, we propose a deep learning neural network architecture that incorporates the biological properties of the visual system, such as receptive fields, to reconstruct visual images from spike trains. Our model outperforms current models and has been evaluated on different datasets from both retinal ganglion cells (RGCs) and the primary visual cortex (V1) neural spikes. Our model demonstrated the great potential of brain-inspired algorithms to solve a challenge that our brain solves.

Thalamocortical boutons cluster by ON/OFF responses in mouse primary visual cortex

In higher mammals, the thalamic afferents to primary visual cortex cluster according to their responses to increases (ON) or decreases (OFF) in luminance. This feature of thalamocortical wiring is thought to create columnar, ON/OFF domains in V1. We have recently shown that mice also have ON/OFF cortical domains, but the organization of their thalamic afferents remains unknown. Here we measured the visual responses of thalamocortical boutons with two-photon imaging and found that they also cluster in space according to ON/OFF responses. Moreover, fluctuations in the relative density of ON/OFF boutons mirror fluctuations in the relative density of ON/OFF receptive field positions on the visual field. These findings indicate a segregation of ON/OFF signals already present in the thalamic input. We propose that ON/OFF clustering may reflect the spatial distribution of ON/OFF responses in retinal ganglion cell mosaics.NEW & NOTEWORTHY Neurons in primary visual cortex cluster into ON and OFF domains, which have been shown to be linked to the organization of receptive fields and cortical maps. Here we show that in the mouse such clustering is already present in the geniculate input, suggesting that the cortical architecture may be shaped by the representation of ON/OFF signals in the thalamus and the retina.

ON and OFF Signaling Pathways in the Retina and the Visual System

Visual processing starts at the retina of the eye, and signals are then transferred primarily to the visual cortex and the tectum. In the retina, multiple neural networks encode different aspects of visual input, such as color and motion. Subsequently, multiple neural streams in parallel convey unique aspects of visual information to cortical and subcortical regions. Bipolar cells, which are the second order neurons of the retina, separate visual signals evoked by light and dark contrasts and encode them to ON and OFF pathways, respectively. The interplay between ON and OFF neural signals is the foundation for visual processing for object contrast which underlies higher order stimulus processing. ON and OFF pathways have been classically thought to signal in a mirror-symmetric manner. However, while these two pathways contribute synergistically to visual perception in some instances, they have pronounced asymmetries suggesting independent operation in other cases. In this review, we summarize the role of the ON-OFF dichotomy in visual signaling, aiming to contribute to the understanding of visual recognition.