A theory of direction selectivity for macaque primary visual cortex

Neuronal composition of processing modules in human V1: laminar density for neuronal and non-neuronal populations and a comparison with macaque

The neuronal composition of homologous brain regions in different primates is important for understanding their processing capacities. Primary visual cortex (V1) has been widely studied in different members of the catarrhines. Neuronal density is considered to be central in defining the structure-function relationship. In human, there are large variations in the reported neuronal density from prior studies. We found the neuronal density in human V1 was 79,000 neurons/mm3, which is 35% of the neuronal density previously determined in macaque V1. Laminar density was proportionally similar between human and macaque. In V1, the ocular dominance column (ODC) contains the circuits for the emergence of orientation preference and spatial processing of a point image in many mammalian species. Analysis of the total neurons in an ODC and of the full number of neurons in macular vision (the central 15°) indicates that humans have 1.3× more neurons than macaques even though the density of neurons in macaque is 3× the density in human V1. We propose that the number of neurons in a functional processing unit rather than the number of neurons under a mm2 of cortex is more appropriate for cortical comparisons across species.

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.

Motion perception based on ON/OFF channels: A survey

Motion perception is an essential ability for animals and artificially intelligent systems interacting effectively, safely with surrounding objects and environments. Biological visual systems, that have naturally evolved over hundreds-million years, are quite efficient and robust for motion perception, whereas artificial vision systems are far from such capability. This paper argues that the gap can be significantly reduced by formulation of ON/OFF channels in motion perception models encoding luminance increment (ON) and decrement (OFF) responses within receptive field, separately. Such signal-bifurcating structure has been found in neural systems of many animal species articulating early motion is split and processed in segregated pathways. However, the corresponding biological substrates, and the necessity for artificial vision systems have never been elucidated together, leaving concerns on uniqueness and advantages of ON/OFF channels upon building dynamic vision systems to address real world challenges. This paper highlights the importance of ON/OFF channels in motion perception through surveying current progress covering both neuroscience and computationally modelling works with applications. Compared to related literature, this paper for the first time provides insights into implementation of different selectivity to directional motion of looming, translating, and small-sized target movement based on ON/OFF channels in keeping with soundness and robustness of biological principles. Existing challenges and future trends of such bio-plausible computational structure for visual perception in connection with hotspots of machine learning, advanced vision sensors like event-driven camera finally are discussed.

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.

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

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