Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Collinear facilitation is independent of receptive-field expansion at low contrast.

ABSTRACT: Modulation of single-cell responses by compound stimuli (target plus flankers) extending outside the cell's receptive field (RF) may represent an early neural mechanism for encoding objects in visual space, enhancing their perceptual saliency. The spatial extent of contextual modulation is wide. The size of the RF is known to be dynamically variable. It has been suggested that RF expansion when target contrast decreases is the real cause of effects attributed to modulation by flankers. This is not the case. We directly compared, in the same cells, the extent of RF size changes when stimulus contrast decreased with that revealed by systematically changing the target-and-collinear-flankers separation. We found that RF expansion at low contrast was not universal, and that the spatial extent of RF expansion, when it existed, was smaller than that of collinear flanker modulation. We conclude that the two processes in striate cortex work independently from each other.

SUBMITTER: Kasamatsu T

PROVIDER: S-EPMC3252032 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Collinear facilitation is independent of receptive-field expansion at low contrast.

Kasamatsu Takuji T Miller Rich R Zhu Zhao Z Chang Michael M Ishida Yoshiyuki Y

Experimental brain research 20091104 3

Modulation of single-cell responses by compound stimuli (target plus flankers) extending outside the cell's receptive field (RF) may represent an early neural mechanism for encoding objects in visual space, enhancing their perceptual saliency. The spatial extent of contextual modulation is wide. The size of the RF is known to be dynamically variable. It has been suggested that RF expansion when target contrast decreases is the real cause of effects attributed to modulation by flankers. This is n ...[more]

PMID: 19888567

Similar Datasets

Perisaccadic Receptive Field Expansion in the Lateral Intraparietal Area.

Project description:Humans and monkeys have access to an accurate representation of visual space despite a constantly moving eye. One mechanism by which the brain accomplishes this is by remapping visual receptive fields around the time of a saccade. In this process a neuron can be excited by a probe stimulus in the current receptive field, and also simultaneously by a probe stimulus in the location that will be brought into the neuron's receptive field by the saccade (the future receptive field), even before saccade begins. Here we show that perisaccadic neuronal excitability is not limited to the current and future receptive fields but encompasses the entire region of visual space across which the current receptive field will be swept by the saccade. A computational model shows that this receptive field expansion is consistent with the propagation of a wave of activity across the cerebral cortex as saccade planning and remapping proceed.

| S-EPMC7035788 | biostudies-literature

Receptive field center-surround interactions mediate context-dependent spatial contrast encoding in the retina.

Project description:Antagonistic receptive field surrounds are a near-universal property of early sensory processing. A key assumption in many models for retinal ganglion cell encoding is that receptive field surrounds are added only to the fully formed center signal. But anatomical and functional observations indicate that surrounds are added before the summation of signals across receptive field subunits that creates the center. Here, we show that this receptive field architecture has an important consequence for spatial contrast encoding in the macaque monkey retina: the surround can control sensitivity to fine spatial structure by changing the way the center integrates visual information over space. The impact of the surround is particularly prominent when center and surround signals are correlated, as they are in natural stimuli. This effect of the surround differs substantially from classic center-surround models and raises the possibility that the surround plays unappreciated roles in shaping ganglion cell sensitivity to natural inputs.

| S-EPMC6185113 | biostudies-literature

A retinal circuit for the suppressed-by-contrast receptive field of a polyaxonal amacrine cell.

Project description:Amacrine cells are a diverse population of interneurons in the retina that play a critical role in extracting complex features of the visual world and shaping the receptive fields of retinal output neurons (ganglion cells). While much of the computational power of amacrine cells is believed to arise from the immense mutual interactions among amacrine cells themselves, the intricate circuitry and functions of amacrine-amacrine interactions are poorly understood in general. Here we report a specific interamacrine pathway from a small-field, glutamate-glycine dual-transmitter amacrine cell (vGluT3) to a wide-field polyaxonal amacrine cell (PAS4/5). Distal tips of vGluT3 cell dendrites made selective glycinergic (but not glutamatergic) synapses onto PAS4/5 dendrites to provide a center-inhibitory, surround-disinhibitory drive that helps PAS4/5 cells build a suppressed-by-contrast (sbc) receptive field, which is a unique and fundamental trigger feature previously found only in a small population of ganglion cells. The finding of this trigger feature in a circuit upstream to ganglion cells suggests that the sbc form of visual computation occurs more widely in the retina than previously believed and shapes visual processing in multiple downstream circuits in multiple ways. We also identified two different subpopulations of PAS4/5 cells based on their differential connectivity with vGluT3 cells and their distinct receptive-field and luminance-encoding characteristics. Moreover, our results revealed a form of crosstalk between small-field and large-field amacrine cell circuits, which provides a mechanism for feature-specific local (<150 µm) control of global (>1 mm) retinal activity.

| S-EPMC7196907 | biostudies-literature

Bayesian population receptive field modelling.

Project description:We introduce a probabilistic (Bayesian) framework and associated software toolbox for mapping population receptive fields (pRFs) based on fMRI data. This generic approach is intended to work with stimuli of any dimension and is demonstrated and validated in the context of 2D retinotopic mapping. The framework enables the experimenter to specify generative (encoding) models of fMRI timeseries, in which experimental stimuli enter a pRF model of neural activity, which in turns drives a nonlinear model of neurovascular coupling and Blood Oxygenation Level Dependent (BOLD) response. The neuronal and haemodynamic parameters are estimated together on a voxel-by-voxel or region-of-interest basis using a Bayesian estimation algorithm (variational Laplace). This offers several novel contributions to receptive field modelling. The variance/covariance of parameters are estimated, enabling receptive fields to be plotted while properly representing uncertainty about pRF size and location. Variability in the haemodynamic response across the brain is accounted for. Furthermore, the framework introduces formal hypothesis testing to pRF analysis, enabling competing models to be evaluated based on their log model evidence (approximated by the variational free energy), which represents the optimal tradeoff between accuracy and complexity. Using simulations and empirical data, we found that parameters typically used to represent pRF size and neuronal scaling are strongly correlated, which is taken into account by the Bayesian methods we describe when making inferences. We used the framework to compare the evidence for six variants of pRF model using 7 T functional MRI data and we found a circular Difference of Gaussians (DoG) model to be the best explanation for our data overall. We hope this framework will prove useful for mapping stimulus spaces with any number of dimensions onto the anatomy of the brain.

| S-EPMC7417811 | biostudies-literature

Cortical Synchrony as a Mechanism of Collinear Facilitation and Suppression in Early Visual Cortex.

Project description:Stimulus-induced oscillations and synchrony among neuronal populations in visual cortex are well-established phenomena. Their functional role in cognition are, however, not well-understood. Recent studies have suggested that neural synchrony may underlie perceptual grouping as stimulus-frequency relationships and stimulus-dependent lateral connectivity profiles can determine the success or failure of synchronization among neuronal groups encoding different stimulus elements. We suggest that the same mechanism accounts for collinear facilitation and suppression effects where the detectability of a target Gabor stimulus is improved or diminished by the presence of collinear flanking Gabor stimuli. We propose a model of oscillators which represent three neuronal populations in visual cortex with distinct receptive fields reflecting the target and two flankers, respectively, and whose connectivity is determined by the collinearity of the presented Gabor stimuli. Our model simulations confirm that neuronal synchrony can indeed explain known collinear facilitation and suppression effects for attended and unattended stimuli.

| S-EPMC8358273 | biostudies-literature

Receptive field inference with localized priors.

Project description:The linear receptive field describes a mapping from sensory stimuli to a one-dimensional variable governing a neuron's spike response. However, traditional receptive field estimators such as the spike-triggered average converge slowly and often require large amounts of data. Bayesian methods seek to overcome this problem by biasing estimates towards solutions that are more likely a priori, typically those with small, smooth, or sparse coefficients. Here we introduce a novel Bayesian receptive field estimator designed to incorporate locality, a powerful form of prior information about receptive field structure. The key to our approach is a hierarchical receptive field model that flexibly adapts to localized structure in both spacetime and spatiotemporal frequency, using an inference method known as empirical Bayes. We refer to our method as automatic locality determination (ALD), and show that it can accurately recover various types of smooth, sparse, and localized receptive fields. We apply ALD to neural data from retinal ganglion cells and V1 simple cells, and find it achieves error rates several times lower than standard estimators. Thus, estimates of comparable accuracy can be achieved with substantially less data. Finally, we introduce a computationally efficient Markov Chain Monte Carlo (MCMC) algorithm for fully Bayesian inference under the ALD prior, yielding accurate Bayesian confidence intervals for small or noisy datasets.

| S-EPMC3203052 | biostudies-literature

Intersession reliability of population receptive field estimates.

Project description:Population receptive field (pRF) analysis is a popular method to infer spatial selectivity of voxels in visual cortex. However, it remains largely untested how stable pRF estimates are over time. Here we measured the intersession reliability of pRF parameter estimates for the central visual field and near periphery, using a combined wedge and ring stimulus containing natural images. Sixteen healthy human participants completed two scanning sessions separated by 10-114 days. Individual participants showed very similar visual field maps for V1-V4 on both sessions. Intersession reliability for eccentricity and polar angle estimates was close to ceiling for most visual field maps (r>.8 for V1-3). PRF size and cortical magnification (CMF) estimates showed strong but lower overall intersession reliability (r≈.4-.6). Group level results for pRF size and CMF were highly similar between sessions. Additional control experiments confirmed that reliability does not depend on the carrier stimulus used and that reliability for pRF size and CMF is high for sessions acquired on the same day (r>.6). Our results demonstrate that pRF mapping is highly reliable across sessions.

| S-EPMC5139984 | biostudies-literature

Efficient Receptive Field Tiling in Primate V1.

Project description:The primary visual cortex (V1) encodes a diverse set of visual features, including orientation, ocular dominance (OD), and spatial frequency (SF), whose joint organization must be precisely structured to optimize coverage within the retinotopic map. Prior experiments have only identified efficient coverage based on orthogonal maps. Here we used two-photon calcium imaging to reveal an alternative arrangement for OD and SF maps in macaque V1; their gradients run parallel but with unique spatial periods, whereby low-SF regions coincide with monocular regions. Next we mapped receptive fields and found surprisingly precise micro-retinotopy that yields a smaller point-image and requires more efficient inter-map geometry, thus underscoring the significance of map relationships. While smooth retinotopy is constraining, studies suggest that it improves both wiring economy and the V1 population code read downstream. Altogether, these data indicate that connectivity within V1 is finely tuned and precise at the level of individual neurons.

| S-EPMC5384649 | biostudies-literature

The spatial structure of a nonlinear receptive field.

Project description:Understanding a sensory system implies the ability to predict responses to a variety of inputs from a common model. In the retina, this includes predicting how the integration of signals across visual space shapes the outputs of retinal ganglion cells. Existing models of this process generalize poorly to predict responses to new stimuli. This failure arises in part from properties of the ganglion cell response that are not well captured by standard receptive-field mapping techniques: nonlinear spatial integration and fine-scale heterogeneities in spatial sampling. Here we characterize a ganglion cell's spatial receptive field using a mechanistic model based on measurements of the physiological properties and connectivity of only the primary excitatory circuitry of the retina. The resulting simplified circuit model successfully predicts ganglion-cell responses to a variety of spatial patterns and thus provides a direct correspondence between circuit connectivity and retinal output.

| S-EPMC3517818 | biostudies-literature

Topological Receptive Field Model for Human Retinotopic Mapping

Project description:The mapping between visual inputs on the retina and neuronal activations in the visual cortex, i.e., retinotopic map, is an essential topic in vision science and neuroscience. Human retinotopic maps can be revealed by analyzing the functional magnetic resonance imaging (fMRI) signal responses to designed visual stimuli in vivo. Neurophysiology studies summarized that visual areas are topological (i.e., nearby neurons have receptive fields at nearby locations in the image). However, conventional fMRI-based analyses frequently generate non-topological results because they process fMRI signals on a voxel-wise basis, without considering the neighbor relations on the surface. Here we propose a topological receptive field (tRF) model which imposes the topological condition when decoding retinotopic fMRI signals. More specifically, we parametrized the cortical surface to a unit disk, characterized the topological condition by tRF, and employed an efficient scheme to solve the tRF model. We tested our framework on both synthetic and human fMRI data. Experimental results showed that the tRF model could remove the topological violations, improve model explaining power, and generate biologically plausible retinotopic maps. The proposed framework is general and can be applied to other sensory maps.

| S-EPMC8570543 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data