Retinal Lateral Inhibition Provides the Biological Basis of Long-Range Spatial Induction

Determination of the Time-frequency Features for Impulse Components in EEG Signals

Accurately identifying the timing and frequency characteristics of impulse components in EEG signals is essential but limited by the Heisenberg uncertainty principle. Inspired by the visual system's ability to identify objects and their locations, we propose a new method that integrates a visual system model with wavelet analysis to calculate both time and frequency features of local impulses in EEG signals. We develop a mathematical model based on invariant pattern recognition by the visual system, combined with wavelet analysis using Krawtchouk functions as the mother wavelet. Our method precisely identifies the localization and frequency characteristics of the impulse components in EEG signals. Tested on task-related EEG data, it accurately detected blink components (0.5 to 1 Hz) and separated muscle artifacts (16 Hz). It also identified muscle response durations (298 ms) within the 1 to 31 Hz range in emotional reaction studies, offering insights into both individual and typical emotional responses. We further illustrated how the new method circumvents the uncertainty principle in low-frequency wavelet analysis. Unlike classical wavelet analysis, our method provides spectral characteristics of EEG impulses invariant to time shifts, improving the identification and classification of EEG components.

Activation and depression of neural and hemodynamic responses induced by the intracortical microstimulation and visual stimulation in the mouse visual cortex

Objective. Intracortical microstimulation (ICMS) can be an effective method for restoring sensory perception in contemporary brain-machine interfaces. However, the mechanisms underlying better control of neuronal responses remain poorly understood, as well as the relationship between neuronal activity and other concomitant phenomena occurring around the stimulation site.Approach. Different microstimulation frequencies were investigatedin vivoon Thy1-GCaMP6s mice using widefield and two-photon imaging to evaluate the evoked excitatory neural responses across multiple spatial scales as well as the induced hemodynamic responses. Specifically, we quantified stimulation-induced neuronal activation and depression in the mouse visual cortex and measured hemodynamic oxyhemoglobin and deoxyhemoglobin signals using mesoscopic-scale widefield imaging.Main results. Our calcium imaging findings revealed a preference for lower-frequency stimulation in driving stronger neuronal activation. A depressive response following the neural activation preferred a slightly higher frequency stimulation compared to the activation. Hemodynamic signals exhibited a comparable spatial spread to neural calcium signals. Oxyhemoglobin concentration around the stimulation site remained elevated during the post-activation (depression) period. Somatic and neuropil calcium responses measured by two-photon microscopy showed similar dependence on stimulation parameters, although the magnitudes measured in soma was greater than in neuropil. Furthermore, higher-frequency stimulation induced a more pronounced activation in soma compared to neuropil, while depression was predominantly induced in soma irrespective of stimulation frequencies.Significance. These results suggest that the mechanism underlying depression differs from activation, requiring ample oxygen supply, and affecting neurons. Our findings provide a novel understanding of evoked excitatory neuronal activity induced by ICMS and offer insights into neuro-devices that utilize both activation and depression phenomena to achieve desired neural responses.

Modulation of motor surround inhibition during motor tasks

Surround inhibition (SI) in the motor system is important in individuation of actions, but is sometimes difficult to demonstrate. It has also not been evaluated in real life tasks. In this study, we use real life tasks and a new method where excitability of the surround muscle is assessed with respect to its current activity level rather than when it is at rest. Motor evoked potential (MEP) amplitudes were measured in the abductor digiti minimi (ADM) muscle while participants performed several motor tasks: "writing" on paper, "holding a pen" precisely and, "holding a water bottle" against gravity. These MEPs were compared to ADM MEPs amplitudes measured during a fifth finger abduction (ADM being the center muscle). SI was also measured in the traditional way, by comparing ADM MEPs during an index finger flexion and at rest. For the "writing" and "holding a pen" tasks, but not the "holding bottle" task, the MEP amplitudes were significantly smaller when compared to MEP amplitudes when the ADM was the center muscle with the same level of activation. The ADM MEP amplitudes were not different between rest and during index finger flexion. The new method employed here shows, that motor SI can be measured during tonic movements. The findings also show motor SI during two real-life motor tasks: "writing" and "holding a pen". The lack of modulation of MEP amplitude during "holding bottle" task seems to indicate that SI is action specific rather than muscle specific.

Activation and depression of neural and hemodynamic responses induced by the intracortical microstimulation and visual stimulation in the mouse visual cortex

Objective . Intracortical microstimulation can be an effective method for restoring sensory perception in contemporary brain-machine interfaces. However, the mechanisms underlying better control of neuronal responses remain poorly understood, as well as the relationship between neuronal activity and other concomitant phenomena occurring around the stimulation site. Approach . Different microstimulation frequencies were investigated in vivo on Thy1-GCaMP6s mice using widefield and two-photon imaging to evaluate the evoked excitatory neural responses across multiple spatial scales as well as the induced hemodynamic responses. Specifically, we quantified stimulation-induced neuronal activation and depression in the mouse visual cortex and measured hemodynamic oxyhemoglobin and deoxyhemoglobin signals using mesoscopic-scale widefield imaging. Main results . Our calcium imaging findings revealed a preference for lower-frequency stimulation in driving stronger neuronal activation. A depressive response following the neural activation preferred a slightly higher frequency stimulation compared to the activation. Hemodynamic signals exhibited a comparable spatial spread to neural calcium signals. Oxyhemoglobin concentration around the stimulation site remained elevated during the post-activation (depression) period. Somatic and neuropil calcium responses measured by two-photon microscopy showed similar dependence on stimulation parameters, although the magnitudes measured in soma was greater than in neuropil. Furthermore, higher-frequency stimulation induced a more pronounced activation in soma compared to neuropil, while depression was predominantly induced in soma irrespective of stimulation frequencies. Significance . These results suggest that the mechanism underlying depression differs from activation, requiring ample oxygen supply, and affecting neurons. Our findings provide a novel understanding of evoked excitatory neuronal activity induced by intracortical microstimulation and offer insights into neuro-devices that utilize both activation and depression phenomena to achieve desired neural responses.

Orgasm and Related Disorders Depend on Neural Inhibition Combined With Neural Excitation

INTRODUCTION

Prevalent models of sexual desire, arousal and orgasm postulate that they result from an excitatory process, whereas disorders of sexual desire, arousal and orgasm result from an inhibitory process based on psychosocial, pharmacological, medical, and other factors. But neuronal excitation and active neuronal inhibition normally interact at variable intensities, concurrently and continuously. We propose herein that in conjunction with neuronal excitation, neuronal inhibition enables the generation of the intense, non-aversive pleasure of orgasm. When this interaction breaks down, pathology can result, as in disorders of sexual desire, arousal, and orgasm, and in anhedonia and pain. For perspective, we review some fundamental behavioral and (neuro-) physiological functions of neuronal excitation and inhibition in normal and pathological processes.

OBJECTIVES

To review evidence that the variable balance between neuronal excitation and active neuronal inhibition at different intensities can account for orgasm and its disorders.

METHODS

We selected studies from searches on PubMed, Google Scholar, Dialnet, and SciELO for terms including orgasm, neuronal development, Wallerian degeneration, prenatal stress, parental behavior, sensorimotor, neuronal excitation, neuronal inhibition, sensory deprivation, anhedonia, orgasmic disorder, hypoactive sexual desire disorder, persistent genital arousal disorder, sexual pain.

RESULTS

We provide evidence that the intensity of neuronal inhibition dynamically covaries concurrently with the intensity of neuronal excitation. Differences in these relative intensities can facilitate the understanding of orgasm and disorders of orgasm.

CONCLUSION

Neuronal excitation and neuronal inhibition are normal, continuously active processes of the nervous system that are necessary for survival of neurons and the organism. The ability of genital sensory stimulation to induce concurrent neuronal inhibition enables the stimulation to attain the pleasurable, non-aversive, high intensity of excitation characteristic of orgasm. Excessive or deficient levels of neuronal inhibition relative to neuronal excitation may account for disorders of sexual desire, arousal and orgasm.

Aversive Conditioning of Spatial Position Sharpens Neural Population-Level Tuning in Visual Cortex and Selectively Alters Alpha-Band Activity

Processing capabilities for many low-level visual features are experientially malleable, aiding sighted organisms in adapting to dynamic environments. Explicit instructions to attend a specific visual field location influence retinotopic visuocortical activity, amplifying responses to stimuli appearing at cued spatial positions. It remains undetermined both how such prioritization affects surrounding nonprioritized locations, and if a given retinotopic spatial position can attain enhanced cortical representation through experience rather than instruction. The current report examined visuocortical response changes as human observers (N = 51, 19 male) learned, through differential classical conditioning, to associate specific screen locations with aversive outcomes. Using dense-array EEG and pupillometry, we tested the preregistered hypotheses of either sharpening or generalization around an aversively associated location following a single conditioning session. Competing hypotheses tested whether mean response changes would take the form of a Gaussian (generalization) or difference-of-Gaussian (sharpening) distribution over spatial positions, peaking at the viewing location paired with a noxious noise. Occipital 15 Hz steady-state visual evoked potential responses were selectively heightened when viewing aversively paired locations and displayed a nonlinear, difference-of-Gaussian profile across neighboring locations, consistent with suppressive surround modulation of nonprioritized positions. Measures of alpha-band (8-12 Hz) activity were differentially altered in anterior versus posterior locations, while pupil diameter exhibited selectively heightened responses to noise-paired locations but did not evince differences across the nonpaired locations. These results indicate that visuocortical spatial representations are sharpened in response to location-specific aversive conditioning, while top-down influences indexed by alpha-power reduction exhibit posterior generalization and anterior sharpening.SIGNIFICANCE STATEMENT It is increasingly recognized that early visual cortex is not a static processor of physical features, but is instead constantly shaped by perceptual experience. It remains unclear, however, to what extent the cortical representation of many fundamental features, including visual field location, is malleable by experience. Using EEG and an aversive classical conditioning paradigm, we observed sharpening of visuocortical responses to stimuli appearing at aversively associated locations along with location-selective facilitation of response systems indexed by pupil diameter and EEG alpha power. These findings highlight the experience-dependent flexibility of retinotopic spatial representations in visual cortex, opening avenues toward novel treatment targets in disorders of attention and spatial cognition.

Matching visual induction effects on screens of different size

In the film industry, the same movie is expected to be watched on displays of vastly different sizes, from cinema screens to mobile phones. But visual induction, the perceptual phenomenon by which the appearance of a scene region is affected by its surroundings, will be different for the same image shown on two displays of different dimensions. This phenomenon presents a practical challenge for the preservation of the artistic intentions of filmmakers, because it can lead to shifts in image appearance between viewing destinations. In this work, we show that a neural field model based on the efficient representation principle is able to predict induction effects and how, by regularizing its associated energy functional, the model is still able to represent induction but is now invertible. From this finding, we propose a method to preprocess an image in a screen-size dependent way so that its perception, in terms of visual induction, may remain constant across displays of different size. The potential of the method is demonstrated through psychophysical experiments on synthetic images and qualitative examples on natural images.

Vision Models for Wide Color Gamut Imaging in Cinema

Gamut mapping is the problem of transforming the colors of image or video content so as to fully exploit the color palette of the display device where the content will be shown, while preserving the artistic intent of the original content's creator. In particular, in the cinema industry, the rapid advancement in display technologies has created a pressing need to develop automatic and fast gamut mapping algorithms. In this article, we propose a novel framework that is based on vision science models, performs both gamut reduction and gamut extension, is of low computational complexity, produces results that are free from artifacts and outperforms state-of-the-art methods according to psychophysical tests. Our experiments also highlight the limitations of existing objective metrics for the gamut mapping problem.

A Neural Network Model With Gap Junction for Topological Detection

Visual information processing in the brain goes from global to local. A large volume of experimental studies has suggested that among global features, the brain perceives the topological information of an image first. Here, we propose a neural network model to elucidate the underlying computational mechanism. The model consists of two parts. The first part is a neural network in which neurons are coupled through gap junctions, mimicking the neural circuit formed by alpha ganglion cells in the retina. Gap junction plays a key role in the model, which, on one hand, facilitates the synchronized firing of a neuron group covering a connected region of an image, and on the other hand, staggers the firing moments of different neuron groups covering disconnected regions of the image. These two properties endow the network with the capacity of detecting the connectivity and closure of images. The second part of the model is a read-out neuron, which reads out the topological information that has been converted into the number of synchronized firings in the retina network. Our model provides a simple yet effective mechanism for the neural system to detect the topological information of images in ultra-speed.

Evidence for the intrinsically nonlinear nature of receptive fields in vision

The responses of visual neurons, as well as visual perception phenomena in general, are highly nonlinear functions of the visual input, while most vision models are grounded on the notion of a linear receptive field (RF). The linear RF has a number of inherent problems: it changes with the input, it presupposes a set of basis functions for the visual system, and it conflicts with recent studies on dendritic computations. Here we propose to model the RF in a nonlinear manner, introducing the intrinsically nonlinear receptive field (INRF). Apart from being more physiologically plausible and embodying the efficient representation principle, the INRF has a key property of wide-ranging implications: for several vision science phenomena where a linear RF must vary with the input in order to predict responses, the INRF can remain constant under different stimuli. We also prove that Artificial Neural Networks with INRF modules instead of linear filters have a remarkably improved performance and better emulate basic human perception. Our results suggest a change of paradigm for vision science as well as for artificial intelligence.

Cortical Interactions between Prosthetic and Natural Vision

Outer retinal degenerative diseases, such as retinitis pigmentosa (RP) and age-related macular degeneration (AMD), are among the leading causes of incurable blindness in the Western world [1]. Retinal prostheses have been shown to restore some useful vision by electrically stimulating the remaining retinal neurons [2]. In contrast to inherited retinal degenerative diseases (e.g., RP), typically leading to a complete loss of the visual field, in AMD patients the disease is localized to the macula, leaving the peripheral vision intact. Implanting a retinal prosthesis in the central macula in AMD patients [3, 4] leads to an intriguing situation where the patient's central retina is stimulated electrically, whereas the peripheral healthy retina responds to natural light stimulation. An important question is whether the visual cortex responds to these two concurrent stimuli similarly to the interaction between two adjacent natural light stimuli projected onto healthy retina. Here, we investigated the cortical interactions between prosthetic and natural vision based on visually evoked potentials (VEPs) recorded in rats implanted with photovoltaic subretinal implants. Using this model, where prosthetic and natural vision information are combined in the visual cortex, we observed striking similarities in the interactions of natural and prosthetic vision, including similar effect of background illumination, linear summation of non-patterned stimuli, and lateral inhibition with spatial patterns [5], which increased with target contrast. These results support the idea of combined prosthetic and natural vision in restoration of sight for AMD patients.

An adaptive scale Gaussian filter to explain White's illusion from the viewpoint of lightness assimilation for a large range of variation in spatial frequency of the grating and aspect ratio of the targets

The variation between the actual and perceived lightness of a stimulus has strong dependency on its background, a phenomena commonly known as lightness induction in the literature of visual neuroscience and psychology. For instance, a gray patch may perceptually appear to be darker in a background while it looks brighter when the background is reversed. In the literature it is further reported that such variation can take place in two possible ways. In case of stimulus like the Simultaneous Brightness Contrast (SBC), the apparent lightness changes in the direction opposite to that of the background lightness, a phenomenon often referred to as lightness contrast, while in the others like neon colour spreading or checkerboard illusion it occurs opposite to that, and known as lightness assimilation. The White's illusion is a typical one which according to many, does not completely conform to any of these two processes. This paper presents the result of quantification of the perceptual strength of the White's illusion as a function of the width of the background square grating as well as the length of the gray patch. A linear filter model is further proposed to simulate the possible neurophysiological phenomena responsible for this particular visual experience. The model assumes that for the White's illusion, where the edges are strong and quite a few, i.e., the spectrum is rich in high frequency components, the inhibitory surround in the classical Difference-of-Gaussians (DoG) filter gets suppressed, and the filter essentially reduces to an adaptive scale Gaussian kernel that brings about lightness assimilation. The linear filter model with a Gaussian kernel is used to simulate the White's illusion phenomena with wide variation of spatial frequency of the background grating as well as the length of the gray patch. The appropriateness of the model is presented through simulation results, which are highly tuned to the present as well as earlier psychometric results.