Dynamics of Spatial Resolution of Single Units in the Lateral Geniculate Nucleus of Cat During Brief Visual Stimulation (original) (raw)
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Experimental Brain Research, 1988
The spatial frequency tuning curves of neurones of area 18 depend upon the velocity of the visual stimulus. The higher the velocity the lower the spatial frequencies to which the cell is tuned. Since in area 17 the size of the cell receptive field is inversely related with the optimal spatial frequency to which the cell responds, we have investigated whether the shift of the optimal spatial frequency with the velocity corresponds to a "change" in the receptive field size. We recorded extracellularly from neurones in area 18; for each cell we selected two gratings, one of high spatial frequency drifting at low velocity and another of low spatial frequency drifting at high velocity to which the cell gave comparable responses. The results show that the masking of the cells receptive field which abolishes the response to the high frequency low velocity grating does not prevent the cell from responding to the low frequency high velocity grating. We conclude that the size of the receptive field of neurones in area 18 depends upon the characteristics (spatial frequency and velocity) of the visual stimulus.
Spatial and temporal features of synaptic to discharge receptive field transformation in cat area 17
Journal of …, 2010
LG, Sanchez-Vives MV, McCormick DA. Spatial and temporal features of synaptic to discharge receptive field transformation in cat area 17. . 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. Girard P, Hupé JM, Bullier J. Feedforward and feedback connections between areas V1 and V2 of the monkey have similar rapid conduction velocities. J Neurophysiol 85: 1328 -1331, 2001. Glezer VD, Tsherbach TA, Gauselman VE, Bondarko VM. Spatio-temporal organization of receptive fields of the cat striate cortex. The receptive fields as the grating filters. Biol Cybern 43: 35-49, 1982. Gonzalez-Burgos G, Barrionuevo G, Lewis DA. Horizontal synaptic connections in monkey prefrontal cortex: an in vitro electrophysiological study. Cereb Cortex 10: 82-92, 2000. Haider B, Duque A, Hasenstaub AR, Yu Y, McCormick DA. Enhancement of visual responsiveness by spontaneous local network activity in vivo. J Neurophysiol 97: 4186 -4202, 2007. Hawken MJ, Parker AJ. Spatial properties of neurons in the monkey striate cortex. Proc R Soc Lond B Biol Sci 231: 251-288, 1987. Heggelund P. Receptive field organization of simple cells in cat striate cortex. Exp Brain Res 42: 89 -98, 1981a. Heggelund P. Receptive field organization of complex cells in cat striate cortex. Exp Brain Res 42: 99 -107, 1981b. Heggelund P. Quantitative study of the discharge fields of single cells in cat striate cortex. J Physiol 373: 277-292, 1986. Heggelund P, Moors J. Orientation selectivity and the spatial distribution of enhancement and suppression in receptive fields of cat striate cortex cells. Exp Brain Res 52: 235-247, 1983. Hetherington PA, Swindale NV. Receptive field and orientation scatter studied by tetrode recordings in cat area 17. Vis Neurosci 16: 637-652, 1999. Hirsch JA, Alonso JM, Reid RC, Martinez LM. Synaptic integration in striate cortical simple cells. J Neurosci 18: 9517-9528, 1998. of chromatic linear motion detectors in macaque V1. J Vis 5: 525-533, 2005. Horwitz GD, Chichilnisky EJ, Albright TD. Cone inputs to simple and complex cells in V1 of awake macaque. J Neurophysiol 97: 3070 -3081, 2007. Hubel DH, Wiesel TN. Receptive fields of single neurones in the cat's striate cortex. J Physiol 148: 574 -591, 1959. Hubel DH, Wiesel TN. Receptive fields, binocular interaction and functional architecture in the cat's visual cortex. J Physiol 160: 106 -154, 1962. Humphrey AL, Saul AB. Strobe rearing reduces direction selectivity in area 17 by altering spatiotemporal receptive-field structure. J Neurophysiol 80: 2991-3004, 1998. Ikeda H, Wright MJ. Retinotopic distribution, visual latency and orientation tuning of "sustained" and "transient" cortical neurones in area 17 of the cat's visual cortex. Exp Brain Res 22: 385-398, 1975. Jancke D, Chavane F, Naaman S, Grinvald A. Imaging cortical correlates of illusion in early visual cortex. Nature 428: 423-426, 2004. Jones JP, Palmer LA. The two-dimensional spatial structure of simple receptive fields in cat striate cortex. J Neurophysiol 58: 1187-1211, 1987a. Jones JP, Palmer LA. An evaluation of the two-dimensional Gabor filter model of simple receptive fields in cat striate cortex. J Neurophysiol 58: 1233-1258, 1987b. Kennedy H, Salin P, Bullier J, Horsburgh G. Topography of developing thalamic and cortical pathways in the visual system of the cat. J Comp Neurol 348: 298 -319, 1994. Kisvarday ZF, Toth E, Rausch M, Eysel UT. Orientation-specific relationship between populations of excitatory and inhibitory connections in the visual cortex of the cat. Cereb Cortex 7: 605-618, 1997. Kitano M, Niiyama K, Kasamatsu T, Sutter EE, Norcia AM. Retinotopic and nonretinotopic field potentials in cat visual cortex. Vis Neurosci 11: 953-977, 1994. Komatsu Y, Nakajima S, Toyama K, Fetz EE. Intracortical connectivity revealed by spike-triggered averaging in slice preparations of cat visual cortex. Brain Res 442: 359 -362, 1988. SYNAPTIC TO DISCHARGE RF TRANSFORMATION
PLoS ONE, 2011
Visual processing in the brain seems to provide fast but coarse information before information about fine details. Such dynamics occur also in single neurons at several levels of the visual system. In the dorsal lateral geniculate nucleus (LGN), neurons have a receptive field (RF) with antagonistic center-surround organization, and temporal changes in centersurround organization are generally assumed to be due to a time-lag of the surround activity relative to center activity. Spatial resolution may be measured as the inverse of center size, and in LGN neurons RF-center width changes during static stimulation with durations in the range of normal fixation periods (250-500 ms) between saccadic eye-movements. The RFcenter is initially large, but rapidly shrinks during the first ,100 ms to a rather sustained size. We studied such dynamics in anesthetized cats during presentation (250 ms) of static spots centered on the RF with main focus on the transition from the first transient and highly dynamic component to the second more sustained component. The results suggest that the two components depend on different neuronal mechanisms that operate in parallel and with partial temporal overlap rather than on a continuously changing center-surround balance. Results from mathematical modeling further supported this conclusion. We found that existing models for the spatiotemporal RF of LGN neurons failed to account for our experimental results. The modeling demonstrated that a new model, in which the response is given by a sum of an early transient component and a partially overlapping sustained component, adequately accounts for our experimental data.
Receptive field mechanisms of cat X and Y retinal ganglion cells
The Journal of General Physiology, 1979
A B S T R A C: T We investigated receptive field properties of cat retinal ganglion cells with visual stimuli which were sinusoidal spatial gratings amplitude modulated in time by a sum of sinusoids. Neural responses were analyzed into the Fourier components at the input frequencies and the components at sum and difference frequencies. The first-order frequency response of X cells had a marked spatial phase and spatial frequency dependence which could be explained in terms of linear interactions between center and surround mechanisms in the receptive field. The second-order frequency response of X cells was much smaller than the first-order frequency response at all spatial frequencies. The spatial phase and spatial frequency dependence of the first-order frequency response in Y cells in some ways resembled that of X cells. However, the Y firstorder response declined to zero at a much lower spatial frequency than in X cells. Furthermore, the second-order frequency response was larger in Y cells; the second-order frequency components became the dominant part of the response for patterns of high spatial frequency. This implies that the receptive field center and surround mechanisms are physiologically quite different in Y cells from those in X cells, and that the Y cells also receive excitatory drive from an additional nonlinear receptive field mechanism.
Spatiotemporal frequency responses of cat retinal ganglion cells
The Journal of General Physiology, 1987
Spatiotemporal frequency responses were measured at different levels of light adaptation for cat X and Y retinal ganglion cells. Stationary sinusoidal luminance gratings whose contrast was modulated sinusoidally in time or drifting gratings were used as stimuli . Under photopic illumination, when the spatial frequency was held constant at or above its optimum value, an X cell's responsivity was essentially constant as the temporal frequency was changed from 1 .5 to 30 Hz. At lower temporal frequencies, responsivity rolled off gradually, and at higher ones it rolled off rapidly. In contrast, when the spatial frequency was held constant at a low value, an X cell's responsivity increased continuously with temporal frequency from a very low value at 0.1 Hz to substantial values at temporal frequencies higher than 30 Hz, from which responsivity rolled off again . Thus, 0 cycles -deg' became the optimal spatial frequency above 30 Hz. For Y cells under photopic illumination, the spatiotemporal interaction was even more complex. When the spatial frequency was held constant at or above its optimal value, the temporal frequency range over which responsivity was constant was shorter than that of X cells . At lower spatial frequencies, this range was not appreciably different . As for X cells, 0 cycles deg ' was the optimal spatial frequency above 30 Hz . Temporal resolution (defined as the high temporal frequency at which responsivity had fallen to 10 impulses -s') for a uniform field was^-95 Hz for X cells and^-120 Hz for Y cells under photopic illumination . Temporal resolution was lower at lower adaptation levels. The results were interpreted in terms of a Gaussian centersurround model . For X cells, the surround and center strengths were nearly equal at low and moderate temporal frequencies, but the surround strength exceeded the center strength above 30 Hz . Thus, the response to a spatially uniform stimulus at high temporal frequencies was dominated by the surround. In addition, at temporal frequencies above 30 Hz, the center radius increased .
Suppression at High Spatial Frequencies in the Lateral Geniculate Nucleus of the Cat
Journal of Neurophysiology, 2007
The spatial weighting functions of both retinal and lateral geniculate nucleus (LGN) X-cell receptive fields have been viewed as the difference of two Gaussians (DOG). We focus on a particular shortcoming of the DOG model, that is, suppression of responses of LGN cells at spatial frequencies above those to which the classical receptive field surround is responsive. By simultaneously recording one of the retinal ganglion cell (RGC) inputs (S-potentials) to an LGN cell, we find that half of this suppression at high spatial frequencies arises from the retinal input and that suppression in LGN cells is greater than that in RGCs, regardless of spatial frequency. We also inactivated the ipsilateral visual cortex and show that one quarter of the suppression at high spatial frequencies arises from corticothalamic feedback. We show that this suppression at high spatial frequencies is colocalized with the classical surround, is not dependent on the relative orientation of the center and surro...
The Journal of Physiology
1. Cat retinal ganglion cells may be subdivided into sustained and transient response-types by the application of a battery of simple tests based on responses to standing contrast, fine grating patterns, size and speed of contrasting targets, and on the presence or absence of the periphery effect. The classification is equivalent to the ;X'/;Y' (linear/nonlinear) subdivision of Enroth-Cugell & Robson which is thus confirmed and extended.2. The sustained/transient classification applied to both on-centre and off-centre cells.3. Lateral geniculate neurones may be similarly classified by the same tests. Occasional concentrically organized cells had a mixture of sustained and transient properties.4. A technique for simultaneous recording from a geniculate neurone and one or more retinal ganglion cells providing its excitatory input showed that the connexions were specific with respect to the sustained/transient classification as well as the on-centre/off-centre classification. M...
The receptive field of the primate P retinal ganglion cell, I: Linear dynamics
Visual Neuroscience, 1997
The ganglion cells of the primate retina include two major anatomical and functional classes: P cells which project to the four parvocellular layers of the lateral geniculate nucleus (LGN), and M cells which project to the two magnocellular layers. The characteristics of the P-cell receptive field are central to understanding early form and color vision processing . In this and in the following paper, P-cell dynamics are systematically analyzed in terms of linear and nonlinear response properties. Stimuli that favor either the center or the surround of the receptive field were produced on a CRT and modulated with a broadband signal composed of multiple m-sequences (Benardete et al., 1992ft;. The first-order responses were calculated and analyzed in this paper (part I). The findings are: (1) The first-order responses of the center and surround depend linearly on contrast.
Vision Research, 1969
An electrophysiological study of 28 neurons in the lateral geniculate nucleus of the cat found 20 of the neurons had receptive fields in both eyes, with an excitatory receptive field in the dominant eye, and in the other eye, a weak excitatory receptive field for 4 neurons and a weak inhibitory receptive field for 16 neurons. The non-dominant eye receptive fields were revealed using repeated visual stimulation with a light bar that swept over the receptive field and averaging to generate histograms of neuron firing in relation to the visual stimuli.