scholarly journals The relationship of receptive field properties to the dendritic shape of neurones in the cat striate cortex.

1984 ◽  
Vol 356 (1) ◽  
pp. 291-302 ◽  
Author(s):  
K A Martin ◽  
D Whitteridge
1986 ◽  
Vol 55 (6) ◽  
pp. 1136-1152 ◽  
Author(s):  
C. L. Baker ◽  
M. S. Cynader

Responses of direction-selective neurons in cat striate cortex (area 17) were studied with flashed-bar stimuli. Spatial parameters of interactions within the receptive field giving rise to direction selectivity and of receptive-field subunits were quantitatively determined for the same cells and correlated. A bar stimulus flashed sequentially at two nearby locations in the receptive field produced direction-selective behavior comparable with that elicited by continuously moving stimuli. Each cell exhibited a characteristic optimal spatial displacement, Dopt, for which responses in the presumed preferred and null directions were maximally distinct. In all cases, Dopt was much smaller than the receptive-field size. The spatial structure of receptive fields in simple cells was studied using single narrow-bar stimuli flashed at different locations in the receptive field. The resulting line-weighting function exhibited alternating regions of ON and OFF responses having a characteristic spatial period or wavelength, lambda. Spatial subunit structure in complex cells was determined by flashing two bars simultaneously in the receptive field. The response as a function of bar separation was again a wavelike function having a spatial wavelength, lambda. Values of the optimal displacement for direction selectivity, Dopt, showed a clear relationship with the spatial wavelength, lambda, for a given unit. Dopt was also correlated to a somewhat lesser degree with receptive-field size. Generally, the ratio of Dopt to lambda was approximately 1/10 to 1/4, in agreement with theoretical predictions by Marr and Poggio. Taken together with the findings of Movshon et al., these results indicate a systematic relationship between Dopt and the spatial frequency of a sinusoidal grating, which is optimal for that cell. Such a relationship is consistent with the results of human psychophysical experiments on apparent motion.


1976 ◽  
Vol 39 (3) ◽  
pp. 512-533 ◽  
Author(s):  
J. R. Wilson ◽  
S. M. Sherman

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.


1976 ◽  
Vol 104 (2) ◽  
pp. 197-219 ◽  
Author(s):  
C.E. Rocha-Miranda ◽  
R. Linden ◽  
E. Volchan ◽  
R. Lent ◽  
R.A. Bombardieri

1997 ◽  
Vol 14 (2) ◽  
pp. 293-309 ◽  
Author(s):  
D. J. Tolhurst ◽  
D. J. Heeger

AbstractIn almost every study of the linearity of spatiotemporal summation in simple cells of the cat's visual cortex, there have been systematic mismatches between the experimental observations and the predictions of the linear theory. These mismatches have generally been explained by supposing that the initial spatiotemporal summation stage is strictly linear, but that the following output stage of the simple cell is subject to some contrast-dependent nonlinearity. Two main models of the output nonlinearity have been proposed: the threshold model (e.g. Tolhurst & Dean, 1987) and the contrast-normalization model (e.g. Heeger, 1992a, b). In this paper, the two models are fitted rigorously to a variety of previously published neurophysiological data, in order to determine whether one model is a better explanation of the data. We reexamine data on the interaction between two bar stimuli presented in different parts of the receptive field; on the relationship between the receptive-field map and the inverse Fourier transform of the spatial-frequency tuning curve; on the dependence of response amplitude and phase on the spatial phase of stationary gratings; on the relationships between the responses to moving and modulated gratings; and on the suppressive action of gratings moving in a neuron's nonpreferred direction. In many situations, the predictions of the two models are similar, but the contrast-normalization model usually fits the data slightly better than the threshold model, and it is easier to apply the equations of the normalization model. More importantly, the normalization model is naturally able to account very well for the details and subtlety of the results in experiments where the total contrast energy of the stimuli changes; some of these phenomena are completely beyond the scope of the threshold model. Rigorous application of the models' equations has revealed some situations where neither model fits quite well enough, and we must suppose, therefore, that there are some subtle nonlinearities still to be characterized.


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