Development of spatiotemporal receptive fields of simple cells: I. Model formulation

1997 ◽  
Vol 77 (6) ◽  
pp. 453-461 ◽  
Author(s):  
S. Wimbauer ◽  
O.G. Wenisch ◽  
K.D. Miller ◽  
J.L. van Hemmen
Keyword(s):  
Receptive Fields ◽  
Model Formulation ◽  
Simple Cells ◽  
Spatiotemporal Receptive Fields

Development of spatiotemporal receptive fields of simple cells: II. Simulation and analysis

1997 ◽  
Vol 77 (6) ◽  
pp. 463 ◽  
Author(s):  
S. Wimbauer ◽  
O.G. Wenisch ◽  
J.L. van Hemmen ◽  
K.D. Miller
Keyword(s):  
Receptive Fields ◽  
Simple Cells ◽  
Spatiotemporal Receptive Fields

Directional selectivity and spatiotemporal structure of receptive fields of simple cells in cat striate cortex

1991 ◽  
Vol 66 (2) ◽  
pp. 505-529 ◽  
Author(s):  
R. C. Reid ◽  
R. E. Soodak ◽  
R. M. Shapley
Keyword(s):  
Time Course ◽  
Linear Prediction ◽  
Striate Cortex ◽  
Receptive Fields ◽  
Quantitative Measure ◽  
Direction Selectivity ◽  
Simple Cells ◽  
Preferred Direction ◽  
Orientation Contrast ◽  
Cat Striate Cortex

1. Simple cells in cat striate cortex were studied with a number of stimulation paradigms to explore the extent to which linear mechanisms determine direction selectivity. For each paradigm, our aim was to predict the selectivity for the direction of moving stimuli given only the responses to stationary stimuli. We have found that the prediction robustly determines the direction and magnitude of the preferred response but overestimates the nonpreferred response. 2. The main paradigm consisted of comparing the responses of simple cells to contrast reversal sinusoidal gratings with their responses to drifting gratings (of the same orientation, contrast, and spatial and temporal frequencies) in both directions of motion. Although it is known that simple cells display spatiotemporally inseparable responses to contrast reversal gratings, this spatiotemporal inseparability is demonstrated here to predict a certain amount of direction selectivity under the assumption that simple cells sum their inputs linearly. 3. The linear prediction of the directional index (DI), a quantitative measure of the degree of direction selectivity, was compared with the measured DI obtained from the responses to drifting gratings. The median value of the ratio of the two was 0.30, indicating that there is a significant nonlinear component to direction selectivity. 4. The absolute magnitudes of the responses to gratings moving in both directions of motion were compared with the linear predictions as well. Whereas the preferred direction response showed only a slight amount of facilitation compared with the linear prediction, there was a significant amount of nonlinear suppression in the nonpreferred direction. 5. Spatiotemporal inseparability was demonstrated also with stationary temporally modulated bars. The time course of response to these bars was different for different positions in the receptive field. The degree of spatiotemporal inseparability measured with sinusoidally modulated bars agreed quantitatively with that measured in experiments with stationary gratings. 6. A linear prediction of the responses to drifting luminance borders was compared with the actual responses. As with the grating experiments, the prediction was qualitatively accurate, giving the correct preferred direction but underestimating the magnitude of direction selectivity observed.(ABSTRACT TRUNCATED AT 400 WORDS)

Receptive-field characteristics of neurons in cat striate cortex: Changes with visual field eccentricity

1976 ◽  
Vol 39 (3) ◽  
pp. 512-533 ◽  
Author(s):  
J. R. Wilson ◽  
S. M. Sherman
Keyword(s):  
Visual Field ◽  
Receptive Field ◽  
Striate Cortex ◽  
Ocular Dominance ◽  
Receptive Fields ◽  
Direction Selectivity ◽  
Orientation Selectivity ◽  
Simple Cells ◽  
Complex Cells ◽  
Cat Striate Cortex

1. Receptive-field properties of 214 neurons from cat striate cortex were studied with particular emphasis on: a) classification, b) field size, c) orientation selectivity, d) direction selectivity, e) speed selectivity, and f) ocular dominance. We studied receptive fields located throughtout the visual field, including the monocular segment, to determine how receptivefield properties changed with eccentricity in the visual field.2. We classified 98 cells as "simple," 80 as "complex," 21 as "hypercomplex," and 15 in other categories. The proportion of complex cells relative to simple cells increased monotonically with receptive-field eccenticity.3. Direction selectivity and preferred orientation did not measurably change with eccentricity. Through most of the binocular segment, this was also true for ocular dominance; however, at the edge of the binocular segment, there were more fields dominated by the contralateral eye.4. Cells had larger receptive fields, less orientation selectivity, and higher preferred speeds with increasing eccentricity. However, these changes were considerably more pronounced for complex than for simple cells.5. These data suggest that simple and complex cells analyze different aspects of a visual stimulus, and we provide a hypothesis which suggests that simple cells analyze input typically from one (or a few) geniculate neurons, while complex cells receive input from a larger region of geniculate neurons. On average, this region is invariant with eccentricity and, due to a changing magnification factor, complex fields increase in size with eccentricity much more than do simple cells. For complex cells, computations of this geniculate region transformed to cortical space provide a cortical extent equal to the spread of pyramidal cell basal dendrites.

Binocular Combination of Contrast Signals by Striate Cortical Neurons in the Monkey

1997 ◽  
Vol 78 (1) ◽  
pp. 366-382 ◽  
Author(s):  
Earl L. Smith ◽  
Yuzo Chino ◽  
Jinren Ni ◽  
Han Cheng
Keyword(s):  
Cortical Neurons ◽  
Striate Cortex ◽  
Receptive Fields ◽  
Spatial Summation ◽  
Simple Cells ◽  
Complex Cells ◽  
Threshold Response ◽  
Binocular Interactions ◽  
Specific Complex ◽  
Left And Right

Smith, Earl L., III, Yuzo Chino, Jinren Ni, and Han Cheng. Binocular combination of contrast signals by striate cortical neurons in the monkey. J. Neurophysiol. 78: 366–382, 1997. With the use of microelectrode recording techniques, we investigated how the contrast signals from the two eyes are combined in individual cortical neurons in the striate cortex of anesthetized and paralyzed macaque monkeys. For a given neuron, the optimal spatial frequency, orientation, and direction of drift for sine wave grating stimuli were determined for each eye. The cell's disparity tuning characteristics were determined by measuring responses as a function of the relative interocular spatial phase of dichoptic stimuli that consisted of the optimal monocular gratings. Binocular contrast summation was then investigated by measuring contrast response functions for optimal dichoptic grating pairs that had left- to right-eye interocular contrast ratios that varied from 0.1 to 10. The goal was to determine the left- and right-eye contrast components required to produce a criterion threshold response. For all functional classes of cortical neurons and for both cooperative and antagonistic binocular interactions, there was a linear relationship between the left- and right-eye contrast components required to produce a threshold response. Thus, for example for cooperative binocular interactions, a reduction in contrast to one eye was counterbalanced by an equivalent increase in contrast to the other eye. These results showed that in simple cells and phase-specific complex cells, the contrast signals from the two eyes were linearly combined at the subunit level before nonlinear rectification. In non-phase-specific complex cells, the linear binocular convergence of contrast signals could have taken place either before or after the rectification process, but before spike generation. In addition, for simple cells, vector analysis of spatial summation showed that the inputs from the two eyes were also combined in a linear manner before nonlinear spike-generating mechanisms. Thus simple cells showed linear spatial summation not only within and between subregions in a given receptive field, but also between the left- and right-eye receptive fields. Overall, the results show that the effectiveness of a stimulus in producing a response reflects interocular differences in the relative balance of inputs to a given cell, however, the eye of origin of a light-evoked signal has no specific consequence.

Spatial properties of neurons in the monkey striate cortex

1987 ◽  
Vol 231 (1263) ◽  
pp. 251-288 ◽  
Keyword(s):  
Receptive Field ◽  
Contrast Sensitivity ◽  
Visual Processing ◽  
Striate Cortex ◽  
Receptive Fields ◽  
Spatial Filter ◽  
Cortical Cells ◽  
Simple Cells ◽  
Gabor Function ◽  
Difference Of Gaussians

Contrast sensitivity as a function of spatial frequency was determined for 138 neurons in the foveal region of primate striate cortex. The accuracy of three models in describing these functions was assessed by the method of least squares. Models based on difference-of-Gaussians (DOG) functions were shown to be superior to those based on the Gabor function or the second differential of a Gaussian. In the most general case of the DOG models, each subregion of a simple cell’s receptive field was constructed from a single DOG function. All the models are compatible with the classical observation that the receptive fields of simple cells are made up of spatially discrete ‘on’ and ‘off’ regions. Although the DOG-based models have more free parameters, they can account better for the variety of shapes of spatial contrast sensitivity functions observed in cortical cells and, unlike other models, they provide a detailed description of the organization of subregions of the receptive field that is consistent with the physiological constraints imposed by earlier stages in the visual pathway. Despite the fact that the DOG-based models have spatially discrete components, the resulting amplitude spectra in the frequency domain describe complex cells just as well as simple cells. The superiority of the DOG-based models as a primary spatial filter is discussed in relation to popular models of visual processing that use the Gabor function or the second differential of a Gaussian.

Spatiotemporal receptive fields: a dynamical model derived from cortical architectonics

1986 ◽  
Vol 226 (1245) ◽  
pp. 421-444 ◽  
Keyword(s):  
Cortical Neurons ◽  
Receptive Fields ◽  
Pyramidal Cells ◽  
Tuning Curves ◽  
Cell Responses ◽  
Intrinsic Connectivity ◽  
Output System ◽  
Spatiotemporal Receptive Fields ◽  
External Connections ◽  
Insight Into

We assume that the mammalian neocortex is built up out of some six layers which differ in their morphology and their external connections. Intrinsic connectivity is largely excitatory, leading to a considerable amount of positive feedback. The majority of cortical neurons can be divided into two main classes: the pyramidal cells, which are said to be excitatory, and local cells (most notably the non-spiny stellate cells), which are said to be inhibitory. The form of the dendritic and axonal arborizations of both groups is discussed in detail. This results in a simplified model of the cortex as a stack of six layers with mutual connections determined by the principles of fibre anatomy. This stack can be treated as a multi-input-multi-output system by means of the linear systems theory of homogeneous layers. The detailed equations for the simulation are derived in the Appendix. The results of the simulations show that the temporal and spatial behaviour of an excitation distribution cannot be treated separately. Further, they indicate specific processing in the different layers and some independence from details of wiring. Finally, the simulation results are applied to the theory of visual receptive fields. This yields some insight into the mechanisms possibly underlying hypercomplexity, putative nonlinearities, lateral inhibition, oscillating cell responses, and velocity-dependent tuning curves.

scholarly journals Spatial and Temporal Features of Synaptic to Discharge Receptive Field Transformation in Cat Area 17

2010 ◽  
Vol 103 (2) ◽  
pp. 677-697 ◽  
Author(s):  
Lionel G. Nowak ◽  
Maria V. Sanchez-Vives ◽  
David A. McCormick
Keyword(s):  
Spatial Frequency ◽  
Response Latency ◽  
Frequency Tuning ◽  
Receptive Fields ◽  
Width Ratio ◽  
Area 17 ◽  
Simple Cells ◽  
Complex Cells ◽  
Temporal Features ◽  
Simple And Complex Cells

The aim of the present study was to characterize the spatial and temporal features of synaptic and discharge receptive fields (RFs), and to quantify their relationships, in cat area 17. For this purpose, neurons were recorded intracellularly while high-frequency flashing bars were used to generate RFs maps for synaptic and spiking responses. Comparison of the maps shows that some features of the discharge RFs depended strongly on those of the synaptic RFs, whereas others were less dependent. Spiking RF duration depended poorly and spiking RF amplitude depended moderately on those of the underlying synaptic RFs. At the other extreme, the optimal spatial frequency and phase of the discharge RFs in simple cells were almost entirely inherited from those of the synaptic RFs. Subfield width, in both simple and complex cells, was less for spiking responses compared with synaptic responses, but synaptic to discharge width ratio was relatively variable from cell to cell. When considering the whole RF of simple cells, additional variability in width ratio resulted from the presence of additional synaptic subfields that remained subthreshold. Due to these additional, subthreshold subfields, spatial frequency tuning predicted from synaptic RFs appears sharper than that predicted from spiking RFs. Excitatory subfield overlap in spiking RFs was well predicted by subfield overlap at the synaptic level. When examined in different regions of the RF, latencies appeared to be quite variable, but this variability showed negligible dependence on distance from the RF center. Nevertheless, spiking response latency faithfully reflected synaptic response latency.

scholarly journals Substructure of Direction-Selective Receptive Fields in Macaque V1

2003 ◽  
Vol 89 (5) ◽  
pp. 2743-2759 ◽  
Author(s):  
Margaret S. Livingstone ◽  
Bevil R. Conway
Keyword(s):  
Receptive Fields ◽  
Direction Selectivity ◽  
Positive Interactions ◽  
Null Direction ◽  
Simple Cells ◽  
Complex Cells ◽  
Preferred Direction ◽  
Orientation Axis ◽  
Interaction Regions ◽  
Simple And Complex Cells

We used two-dimensional (2-D) sparse noise to map simultaneous and sequential two-spot interactions in simple and complex direction-selective cells in macaque V1. Sequential-interaction maps for both simple and complex cells showed preferred-direction facilitation and null-direction suppression for same-contrast stimulus sequences and the reverse for inverting-contrast sequences, although the magnitudes of the interactions were weaker for the simple cells. Contrast-sign selectivity in complex cells indicates that direction-selective interactions in these cells must occur in antecedent simple cells or in simple-cell-like dendritic compartments. Our maps suggest that direction selectivity, and on andoff segregation perpendicular to the orientation axis, can occur prior to receptive-field elongation along the orientation axis. 2-D interaction maps for some complex cells showed elongated alternating facilitatory and suppressive interactions as predicted if their inputs were orientation-selective simple cells. The negative interactions, however, were less elongated than the positive interactions, and there was an inflection at the origin in the positive interactions, so the interactions were chevron-shaped rather than band-like. Other complex cells showed only two round interaction regions, one negative and one positive. Several explanations for the map shapes are considered, including the possibility that directional interactions are generated directly from unoriented inputs.

scholarly journals Receptive Fields of Disparity-Tuned Simple Cells in Macaque V1

Neuron ◽  
2003 ◽  
Vol 38 (1) ◽  
pp. 103-114 ◽  
Author(s):  
Doris Y. Tsao ◽  
Bevil R. Conway ◽  
Margaret S. Livingstone
Keyword(s):  
Receptive Fields ◽  
Simple Cells
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