scholarly journals How Stimulus Statistics Affect The Receptive Fields of V1 Cells

2021 ◽  
Author(s):  
Ali Almasi ◽  
Shi Hai Sun ◽  
Molis Yunzab ◽  
Young Jun Jung ◽  
Hamish Meffin ◽  
...  
Keyword(s):  
Gaussian Noise ◽  
Visual Information ◽  
Receptive Fields ◽  
White Gaussian Noise ◽  
Natural Scenes ◽  
Linear Filters ◽  
Response Latencies ◽  
V1 Neurons ◽  
Neuronal Spike ◽  
Nonlinear Processing

AbstractWe studied the changes that neuronal RF models undergo when the statistics of the stimulus are changed from those of white Gaussian noise (WGN) to those of natural scenes (NS). Fitting the model to data estimates both a cascade of linear filters on the stimulus, as wells as the static nonlinearities that map the output of the filters to the neuronal spike rates. We found that cells respond differently to these two classes of stimuli, with mostly higher spike rates and shorter response latencies to NS than to WGN. The most striking finding was that NS resulted in RFs that had additional uncovered filters than did WGN. This finding was not an artefact of the higher spike rates but rather related to a change in coding. Our results reveal a greater extent of nonlinear processing in V1 neurons when stimulated using NS compared to WGN. Our findings indicate the existence of nonlinear mechanisms that endow V1 neurons with context-dependent transmission of visual information.

scholarly journals Spatiotemporal functional organization of excitatory synaptic inputs onto macaque V1 neurons

2019 ◽  
Author(s):  
Niansheng Ju ◽  
Yang Li ◽  
Fang Liu ◽  
Hongfei Jiang ◽  
Stephen L. Macknik ◽  
...  
Keyword(s):  
Visual Information ◽  
Spatial Organization ◽  
Functional Organization ◽  
Receptive Fields ◽  
Feature Space ◽  
Response Latencies ◽  
Synaptic Inputs ◽  
V1 Neurons ◽  
Basal Dendrites ◽  
Dendritic Branches

The integration of synaptic inputs onto dendrites provides the basis for computation within individual neurons. Whereas recent studies have begun to outline the spatial organization of synaptic inputs on individual neurons, the underlying principles related to the specific neural functions is not well known. Here we performed two-photon dendritic imaging with genetically-encoded glutamate sensor in awake monkeys, and successfully mapped the excitatory synaptic inputs on dendrites of individual V1 neurons with high spatial and temporal resolution. We found that although synaptic inputs on dendrites were functionally clustered by feature, they were highly scattered in multidimensional feature space, providing a potential substrate of local feature integration on dendritic branches. We also found that nearly all individual neurons received both abundant orientation-selective and color-selective inputs. Furthermore, we found apical dendrites received more diverse inputs than basal dendrites, with larger receptive fields, and relatively longer response latencies, suggesting a specific apical role in integrating feedback in visual information processing.

scholarly journals Laminar and Orientation-Dependent Characteristics of Spatial Nonlinearities: Implications for the Computational Architecture of Visual Cortex

2009 ◽  
Vol 102 (6) ◽  
pp. 3414-3432 ◽  
Author(s):  
Jonathan D. Victor ◽  
Ferenc Mechler ◽  
Ifije Ohiorhenuan ◽  
Anita M. Schmid ◽  
Keith P. Purpura
Keyword(s):  
Visual Cortex ◽  
Hermite Functions ◽  
Natural Scenes ◽  
Model Framework ◽  
Linear Filters ◽  
V1 Neurons ◽  
Mathematical Properties ◽  
Complex Stimuli ◽  
Highly Nonlinear ◽  
Neural Computations

A full understanding of the computations performed in primary visual cortex is an important yet elusive goal. Receptive field models consisting of cascades of linear filters and static nonlinearities may be adequate to account for responses to simple stimuli such as gratings and random checkerboards, but their predictions of responses to complex stimuli such as natural scenes are only approximately correct. It is unclear whether these discrepancies are limited to quantitative inaccuracies that reflect well-recognized mechanisms such as response normalization, gain controls, and cross-orientation suppression or, alternatively, imply additional qualitative features of the underlying computations. To address this question, we examined responses of V1 and V2 neurons in the monkey and area 17 neurons in the cat to two-dimensional Hermite functions (TDHs). TDHs are intermediate in complexity between traditional analytic stimuli and natural scenes and have mathematical properties that facilitate their use to test candidate models. By exploiting these properties, along with the laminar organization of V1, we identify qualitative aspects of neural computations beyond those anticipated from the above-cited model framework. Specifically, we find that V1 neurons receive signals from orientation-selective mechanisms that are highly nonlinear: they are sensitive to phase correlations, not just spatial frequency content. That is, the behavior of V1 neurons departs from that of linear–nonlinear cascades with standard modulatory mechanisms in a qualitative manner: even relatively simple stimuli evoke responses that imply complex spatial nonlinearities. The presence of these findings in the input layers suggests that these nonlinearities act in a feedback fashion.

Surround Suppression of V1 Neurons Mediates Orientation-Based Representation of High-Order Visual Features

2009 ◽  
Vol 101 (3) ◽  
pp. 1444-1462 ◽  
Author(s):  
Hiroki Tanaka ◽  
Izumi Ohzawa
Keyword(s):  
Visual Information ◽  
Receptive Fields ◽  
High Order ◽  
Visual Features ◽  
Surround Suppression ◽  
V1 Neurons ◽  
Spatial Frequencies ◽  
Wide Range ◽  
Novel Method ◽  
Optimal Values

Neurons with surround suppression have been implicated in processing high-order visual features such as contrast- or texture-defined boundaries and subjective contours. However, little is known regarding how these neurons encode high-order visual information in a systematic manner as a population. To address this issue, we have measured detailed spatial structures of classical center and suppressive surround regions of receptive fields of primary visual cortex (V1) neurons and examined how a population of such neurons allow encoding of various high-order features and shapes in visual scenes. Using a novel method to reconstruct structures, we found that the center and surround regions are often both elongated parallel to each other, reminiscent of on and off subregions of simple cells without surround suppression. These structures allow V1 neurons to extract high-order contours of various orientations and spatial frequencies, with a variety of optimal values across neurons. The results show that a wide range of orientations and widths of the high-order features are systematically represented by the population of V1 neurons with surround suppression.

scholarly journals The emergence of multiple retinal cell types through efficient coding of natural movies

2018 ◽  
Author(s):  
Samuel A. Ocko ◽  
Jack Lindsey ◽  
Surya Ganguli ◽  
Stephane Deny
Keyword(s):  
Visual Processing ◽  
Visual Information ◽  
Ganglion Cells ◽  
Receptive Fields ◽  
Cell Types ◽  
Retinal Cell ◽  
Retinal Eccentricity ◽  
Natural Scenes ◽  
Efficient Coding ◽  
Cell Densities

AbstractOne of the most striking aspects of early visual processing in the retina is the immediate parcellation of visual information into multiple parallel pathways, formed by different retinal ganglion cell types each tiling the entire visual field. Existing theories of efficient coding have been unable to account for the functional advantages of such cell-type diversity in encoding natural scenes. Here we go beyond previous theories to analyze how a simple linear retinal encoding model with different convolutional cell types efficiently encodes naturalistic spatiotemporal movies given a fixed firing rate budget. We find that optimizing the receptive fields and cell densities of two cell types makes them match the properties of the two main cell types in the primate retina, midget and parasol cells, in terms of spatial and temporal sensitivity, cell spacing, and their relative ratio. Moreover, our theory gives a precise account of how the ratio of midget to parasol cells decreases with retinal eccentricity. Also, we train a nonlinear encoding model with a rectifying nonlinearity to efficiently encode naturalistic movies, and again find emergent receptive fields resembling those of midget and parasol cells that are now further subdivided into ON and OFF types. Thus our work provides a theoretical justification, based on the efficient coding of natural movies, for the existence of the four most dominant cell types in the primate retina that together comprise 70% of all ganglion cells.

Background Changes Delay Information Represented in Macaque V1 Neurons

2005 ◽  
Vol 94 (6) ◽  
pp. 4314-4330 ◽  
Author(s):  
Xin Huang ◽  
Michael A. Paradiso
Keyword(s):  
Visual Field ◽  
Visual Information ◽  
Time Course ◽  
Receptive Fields ◽  
Saccadic Eye Movements ◽  
Initial Response ◽  
Temporal Changes ◽  
Background Condition ◽  
V1 Neurons ◽  
Static Background

In natural behavioral situations, saccadic eye movements not only introduce new stimuli into V1 receptive fields, they also cause changes in the background. We recorded in awake macaque V1 using a fixation paradigm and compared evoked activity to small stimuli when the background was either static or changing as with a saccade. When a stimulus was shown on a static background, as in most previous experiments, the initial response was orientation selective and contrast was inversely correlated with response latency. When a stimulus was introduced with a background change, V1 neurons showed a qualitatively different temporal response pattern in which information about stimulus orientation and contrast was delayed. The delay in the representation of visual information was found with three different types of background change—luminance increment, luminance decrement, and a pattern change with fixed mean luminance. We also found that with a background change, V1 off responses were suppressed and had a shorter time course compared with the static-background situation. Our results suggest that the distribution of temporal changes across the visual field plays a fundamental role in determining V1 responses. In the static-background condition, temporal change in the visual input occurs only in a small portion of the visual field. In the changing-background condition, and presumably in natural vision, temporal changes are widely distributed. Thus a delayed representation of visual information may be more representative of natural visual situations.

scholarly journals Effects of white Gaussian noise on dynamic balance in healthy young adults

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ziyou Zhou ◽  
Can Wu ◽  
Zhen Hu ◽  
Yujuan Chai ◽  
Kai Chen ◽  
...  
Keyword(s):  
Young Adults ◽  
Gaussian Noise ◽  
Center Of Pressure ◽  
Dynamic Balance ◽  
White Gaussian Noise ◽  
Fluctuation Analysis ◽  
Balance Performance ◽  
Short Term ◽  
Crossover Point ◽  
Short Time

AbstractIt has been known that short-time auditory stimulation can contribute to the improvement of the balancing ability of the human body. The present study aims to explore the effects of white Gaussian noise (WGN) of different intensities and frequencies on dynamic balance performance in healthy young adults. A total of 20 healthy young participants were asked to stand at a dynamic balance force platform, which swung along the x-axis with an amplitude of ± 4° and frequency of 1 Hz. Their center of pressure (COP) trajectories were recorded when they were stimulated by WGN of different intensities (block 1) and different frequencies (block 2). A traditional method and detrended fluctuation analysis (DFA) were used for data preprocessing. The authors found that only with 75–85 dB WGN, the COP parameters improved. WGN frequency did not affect the dynamic balance performance of all the participants. The DFA results indicated stimulation with 75 dB WGN enhanced the short-term index and reduced the crossover point. Stimulation with 500 Hz and 2500 Hz WGN significantly enhanced the short-term index. These results suggest that 75 dB WGN and 500 Hz and 2500 Hz WGN improved the participants’ dynamic balance performance. The results of this study indicate that a certain intensity of WGN is indispensable to achieve a remarkable improvement in dynamic balance. The DFA results suggest that WGN only affected the short-term persistence, indicating the potential of WGN being considered as an adjuvant therapy in low-speed rehabilitation training.

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