Receptive-field maps of correlated discharge between pairs of neurons in the cat's visual cortex

1994 ◽  
Vol 71 (1) ◽  
pp. 330-346 ◽  
Author(s):  
G. M. Ghose ◽  
I. Ohzawa ◽  
R. D. Freeman
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Correlation Analysis ◽  
Random Sequence ◽  
Receptive Fields ◽  
Simple Cell ◽  
Reverse Correlation ◽  
Sinusoidal Gratings ◽  
Reverse Correlation Analysis ◽  
Correlation Procedure

1. To investigate the functional significance of temporally correlated discharge between nearby cells in the visual cortex, we obtained receptive-field maps of correlated discharge for 68 cell pairs in kittens and cats. Discharge from cell pairs was measured by a single extracellular electrode. A reverse correlation procedure was used to relate neural discharge to particular stimuli within a random sequence of briefly flashed bright and dark bars. Bicellular receptive fields (BRFs) were mapped by applying reverse correlation to approximately synchronous discharge from two cells. Unicellular receptive fields (URFs) were simultaneously mapped by separately applying reverse correlation to the discharge of each cell. 2. The receptive fields of the two neurons within each pair were initially studied by varying the orientation and spatial frequency of drifting sinusoidal gratings. After these tests a random sequence of appropriately oriented bars was used to evoke discharge suitable for reverse correlation analysis. For most cell pairs, the temporal pattern or strength of correlated discharge produced by such stimulation is different from that observed with stimulation by sinusoidal gratings. This indicates that visually evoked correlated discharge between nearby cells is stimulus dependent. 3. BRFs were classified according to their pattern of spatial sensitivity into three groups that roughly correspond to the single-cell receptive-field types of the lateral geniculate nucleus (LGN; center-surround) and visual cortex (simple and complex). These classifications were compared with the receptive-field types of the single cells within each pair. LGN-type and simple-type BRFs were only seen for pairs in which at least one of the cells was simple. Conversely, complex-type BRFs were only seen for pairs in which at least one of the cells was complex. 4. Because the reverse correlation procedure can be used to characterize the spatiotemporal receptive-field structure of simple cells, we were able to compare both the spatial and temporal properties associated with the URFs and BRFs of simple cell pairs. The spatiotemporal structure of the BRF of a simple-cell pair can largely be predicted on the basis of the two URFs. Although this prediction suggests the possibility that BRFs are stimulus artifacts, a shuffle procedure, in which multiple repetitions of random sequences were presented, verifies the neural origin of BRFs. BRFs emerge from specific neural pathways and are not simply a consequence of unicellular response preferences. 5. Five measures were derived from the reverse correlation analysis of simple-cell receptive fields: width, duration, optimal spatial and temporal frequency, and optimal velocity.(ABSTRACT TRUNCATED AT 400 WORDS)

scholarly journals Replicating Receptive Fields of Simple and Complex Cells in Primary Visual Cortex in a Neuronal Network Model with Temporal and Population Sparseness and Reliability

2012 ◽  
Vol 24 (10) ◽  
pp. 2700-2725 ◽  
Author(s):  
Takuma Tanaka ◽  
Toshio Aoyagi ◽  
Takeshi Kaneko
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Primary Visual Cortex ◽  
Receptive Fields ◽  
Learning Rule ◽  
Simple Cell ◽  
Complex Cells ◽  
Receptive Field Properties ◽  
Output Neurons ◽  
Simple And Complex Cells

We propose a new principle for replicating receptive field properties of neurons in the primary visual cortex. We derive a learning rule for a feedforward network, which maintains a low firing rate for the output neurons (resulting in temporal sparseness) and allows only a small subset of the neurons in the network to fire at any given time (resulting in population sparseness). Our learning rule also sets the firing rates of the output neurons at each time step to near-maximum or near-minimum levels, resulting in neuronal reliability. The learning rule is simple enough to be written in spatially and temporally local forms. After the learning stage is performed using input image patches of natural scenes, output neurons in the model network are found to exhibit simple-cell-like receptive field properties. When the output of these simple-cell-like neurons are input to another model layer using the same learning rule, the second-layer output neurons after learning become less sensitive to the phase of gratings than the simple-cell-like input neurons. In particular, some of the second-layer output neurons become completely phase invariant, owing to the convergence of the connections from first-layer neurons with similar orientation selectivity to second-layer neurons in the model network. We examine the parameter dependencies of the receptive field properties of the model neurons after learning and discuss their biological implications. We also show that the localized learning rule is consistent with experimental results concerning neuronal plasticity and can replicate the receptive fields of simple and complex cells.

Spatial and temporal analysis by neurons in the representation of the central visual field in the cat's lateral suprasylvian visual cortex

1990 ◽  
Vol 5 (5) ◽  
pp. 463-468 ◽  
Author(s):  
Martin S. Gizzi ◽  
Ephraim Katz ◽  
J. Anthony Movshon
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Temporal Frequency ◽  
Visual Fields ◽  
Receptive Fields ◽  
Visual Signals ◽  
Field Size ◽  
Spatial Frequencies ◽  
Sinusoidal Gratings ◽  
Areas 17 And 18

AbstractWe studied quantitatively the receptive-field properties of 74 units recorded from the representation of the central visual fields in the cat's lateral suprasylvian (LS) visual cortex. In agreement with previous workers, we found that LS receptive fields tended to be large and to lack discernible spatial structure. They resembled the complex receptive fields of areas 17 and 18 in their general organization. We examined the responses of these neurons to moving optimally oriented sinusoidal gratings that varied in spatial and temporal frequency of drift. Most LS neurons were selective for the spatial frequency of sinusoidal gratings; 7% responded to all spatial frequencies below a cutoff value. In agreement with previous reports, the optimal spatial frequencies for LS neurons covered a wider range than is seen in either area 17 or 18 alone (0.05–1 cycle/deg), but are certainly included in the range covered by both these afferent areas. Individual neurons in LS responded to a range of spatial frequencies broader than is typical for neurons in areas 17 and 18. The effect of varying the drift rate of otherwise optimal gratings was similar in LS to that reported for areas 17 and 18. Most neurons were optimally responsive to drift rates between 0.5 and 4 Hz, and resolved frequencies as high as 10–30 Hz. A few neurons had optima higher than 6 Hz and resolved frequencies in excess of 30 Hz. We conclude that the receptive fields of LS neurons reflect rather closely the properties of their afferents from areas 17 and 18. Apart from the increased incidence of directional selectivity in LS and the increase in receptive-field size seen there, we find no evidence for a significant reorganization of visual signals.

Ferrier lecture - Functional architecture of macaque monkey visual cortex

1977 ◽  
Vol 198 (1130) ◽  
pp. 1-59 ◽  
Keyword(s):  
Visual Cortex ◽  
Visual Field ◽  
Receptive Field ◽  
Striate Cortex ◽  
Single Cells ◽  
Ocular Dominance ◽  
Receptive Fields ◽  
Macaque Monkey ◽  
Area 17 ◽  
Orientation Specificity

Of the many possible functions of the macaque monkey primary visual cortex (striate cortex, area 17) two are now fairly well understood. First, the incoming information from the lateral geniculate bodies is rearranged so that most cells in the striate cortex respond to specifically oriented line segments, and, second, information originating from the two eyes converges upon single cells. The rearrangement and convergence do not take place immediately, however: in layer IVc, where the bulk of the afferents terminate, virtually all cells have fields with circular symmetry and are strictly monocular, driven from the left eye or from the right, but not both; at subsequent stages, in layers above and below IVc, most cells show orientation specificity, and about half are binocular. In a binocular cell the receptive fields in the two eyes are on corresponding regions in the two retinas and are identical in structure, but one eye is usually more effective than the other in influencing the cell; all shades of ocular dominance are seen. These two functions are strongly reflected in the architecture of the cortex, in that cells with common physiological properties are grouped together in vertically organized systems of columns. In an ocular dominance column all cells respond preferentially to the same eye. By four independent anatomical methods it has been shown that these columns have the form of vertically disposed alternating left-eye and right-eye slabs, which in horizontal section form alternating stripes about 400 μm thick, with occasional bifurcations and blind endings. Cells of like orientation specificity are known from physiological recordings to be similarly grouped in much narrower vertical sheeet-like aggregations, stacked in orderly sequences so that on traversing the cortex tangentially one normally encounters a succession of small shifts in orientation, clockwise or counterclockwise; a 1 mm traverse is usually accompanied by one or several full rotations through 180°, broken at times by reversals in direction of rotation and occasionally by large abrupt shifts. A full complement of columns, of either type, left-plus-right eye or a complete 180° sequence, is termed a hypercolumn. Columns (and hence hypercolumns) have roughly the same width throughout the binocular part of the cortex. The two independent systems of hypercolumns are engrafted upon the well known topographic representation of the visual field. The receptive fields mapped in a vertical penetration through cortex show a scatter in position roughly equal to the average size of the fields themselves, and the area thus covered, the aggregate receptive field, increases with distance from the fovea. A parallel increase is seen in reciprocal magnification (the number of degrees of visual field corresponding to 1 mm of cortex). Over most or all of the striate cortex a movement of 1-2 mm, traversing several hypercolumns, is accompanied by a movement through the visual field about equal in size to the local aggregate receptive field. Thus any 1-2 mm block of cortex contains roughly the machinery needed to subserve an aggregate receptive field. In the cortex the fall-off in detail with which the visual field is analysed, as one moves out from the foveal area, is accompanied not by a reduction in thickness of layers, as is found in the retina, but by a reduction in the area of cortex (and hence the number of columnar units) devoted to a given amount of visual field: unlike the retina, the striate cortex is virtually uniform morphologically but varies in magnification. In most respects the above description fits the newborn monkey just as well as the adult, suggesting that area 17 is largely genetically programmed. The ocular dominance columns, however, are not fully developed at birth, since the geniculate terminals belonging to one eye occupy layer IVc throughout its length, segregating out into separate columns only after about the first 6 weeks, whether or not the animal has visual experience. If one eye is sutured closed during this early period the columns belonging to that eye become shrunken and their companions correspondingly expanded. This would seem to be at least in part the result of interference with normal maturation, though sprouting and retraction of axon terminals are not excluded.

Corticogeniculate neurons, corticotectal neurons, and suspected interneurons in visual cortex of awake rabbits: receptive-field properties, axonal properties, and effects of EEG arousal

1987 ◽  
Vol 57 (4) ◽  
pp. 977-1001 ◽  
Author(s):  
H. A. Swadlow ◽  
T. G. Weyand
Keyword(s):  
Electrical Stimulation ◽  
Visual Cortex ◽  
Receptive Field ◽  
Receptive Fields ◽  
Spontaneous Firing ◽  
Visual Responses ◽  
Firing Rates ◽  
Axonal Conduction ◽  
Conduction Velocities ◽  
Stimulation Of

The intrinsic stability of the rabbit eye was exploited to enable receptive-field analysis of antidromically identified corticotectal (CT) neurons (n = 101) and corticogeniculate (CG) neurons (n = 124) in visual area I of awake rabbits. Eye position was monitored to within 1/5 degrees. We also studied the receptive-field properties of neurons synaptically activated via electrical stimulation of the dorsal lateral geniculate nucleus (LGNd). Whereas most CT neurons had either complex (59%) or motion/uniform (15%) receptive fields, we also found CT neurons with simple (9%) and concentric (4%) receptive fields. Most complex CT cells were broadly tuned to both stimulus orientation and velocity, but only 41% of these cells were directionally selective. We could elicit no visual responses from 6% of CT cells, and these cells had significantly lower conduction velocities than visually responsive CT cells. The median spontaneous firing rates for all classes of CT neurons were 4-8 spikes/s. CG neurons had primarily simple (60%) and concentric (9%) receptive fields, and none of these cells had complex receptive fields. CG simple cells were more narrowly tuned to both stimulus orientation and velocity than were complex CT cells, and most (85%) were directionally selective. Axonal conduction velocities of CG neurons (mean = 1.2 m/s) were much lower than those of CT neurons (mean = 6.4 m/s), and CG neurons that were visually unresponsive (23%) had lower axonal conduction velocities than did visually responsive CG neurons. Some visually unresponsive CG neurons (14%) responded with saccadic eye movements. The median spontaneous firing rates for all classes of CG neurons were less than 1 spike/s. All neurons synaptically activated via LGNd stimulation at latencies of less than 2.0 ms had receptive fields that were not orientation selective (89% motion/uniform, 11% concentric), whereas most cells with orientation-selective receptive fields had considerably longer synaptic latencies. Most short-latency motion/uniform neurons responded to electrical stimulation of the LGNd (and visual area II) with a high-frequency burst (500-900 Hz) of three or more spikes. Action potentials of these neurons were of short duration, thresholds of synaptic activation were low, and spontaneous firing rates were the highest seen in rabbit visual cortex. These properties are similar to those reported for interneurons in several regions in mammalian central nervous system. Nonvisual sensory stimuli that resulted in electroencephalographic arousal (hippocampal theta activity) had a profound effect on the visual responses of many visual cortical neurons.(ABSTRACT TRUNCATED AT 400 WORDS)

The Joint Development of Orientation and Ocular Dominance: Role of Constraints

1997 ◽  
Vol 9 (5) ◽  
pp. 959-970 ◽  
Author(s):  
Christian Piepenbrock ◽  
Helge Ritter ◽  
Klaus Obermayer
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Ocular Dominance ◽  
Receptive Fields ◽  
Simple Cell ◽  
Orientation Preference ◽  
Joint Development ◽  
Independent Work ◽  
Insight Into

Correlation-based learning (CBL) has been suggested as the mechanism that underlies the development of simple-cell receptive fields in the primary visual cortex of cats, including orientation preference (OR) and ocular dominance (OD) (Linsker, 1986; Miller, Keller, & Stryker, 1989). CBL has been applied successfully to the development of OR and OD individually (Miller, Keller, & Stryker, 1989; Miller, 1994; Miyashita & Tanaka, 1991; Erwin, Obermayer, & Schulten, 1995), but the conditions for their joint development have not been studied (but see Erwin & Miller, 1995, for independent work on the same question) in contrast to competitive Hebbian models (Obermayer, Blasdel, & Schulten, 1992). In this article, we provide insight into why this has been the case: OR and OD decouple in symmetric CBL models, and a joint development of OR and OD is possible only in a parameter regime that depends on nonlinear mechanisms.

Internal Spatial Organization of Receptive Fields of Complex Cells in the Early Visual Cortex

2007 ◽  
Vol 98 (3) ◽  
pp. 1194-1212 ◽  
Author(s):  
Kota S. Sasaki ◽  
Izumi Ohzawa
Keyword(s):  
Visual Cortex ◽  
Minimal Model ◽  
Spatial Organization ◽  
Receptive Fields ◽  
Simple Cell ◽  
Complex Cell ◽  
Linear Filters ◽  
Simple Cells ◽  
Complex Cells ◽  
Early Visual Cortex

The receptive fields of complex cells in the early visual cortex are economically modeled by combining outputs of a quadrature pair of linear filters. For actual complex cells, such a minimal model may be insufficient because many more simple cells are thought to make up a complex cell receptive field. To examine the minimalist model physiologically, we analyzed spatial relationships between the internal structure (subunits) and the overall receptive fields of individual complex cells by a two-stimulus interaction technique. The receptive fields of complex cells are more circular and only slightly larger than their subunits in size. In addition, complex cell subunits occupy spatial extents similar to those of simple cell receptive fields. Therefore in these respects, the minimalist schema is a fair approximation to actual complex cells. However, there are violations against the minimal model. Simple cell receptive fields have significantly fewer subregions than complex cell subunits and, in general, simple cell receptive fields are elongated more horizontally than vertically. This bias is absent in complex cell subunits and receptive fields. Thus simple cells cannot be equated to individual complex cell subunits and spatial pooling of simple cells may occur anisotropically to constitute a complex cell subunit. Moreover, when linear filters for complex cell subunits are examined separately for bright and dark responses, there are significant imbalances and position displacements between them. This suggests that actual complex cell receptive fields are constructed by a richer combination of linear filters than proposed by the minimalist model.

Receptive-field properties of neurons in different laminae of visual cortex of the cat

1978 ◽  
Vol 41 (4) ◽  
pp. 948-962 ◽  
Author(s):  
A. G. Leventhal ◽  
H. V. Hirsch
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Striate Cortex ◽  
Visual Stimulation ◽  
Receptive Fields ◽  
Spontaneous Discharge ◽  
C Cells ◽  
Receptive Field Properties ◽  
Discharge Rates ◽  
Y Cells

1. Receptive-field properties of neurons in the different layers of the visual cortex of normal adult cats were analyzed quantitatively. Neurons were classified into one of two groups: 1) S-cells, which have discrete on- and/or off-regions in their receptive fields and possess inhibitory side bands; 2) C-cells, which do not have discrete on- and off-regions in their receptive fields but display an on-off response to flashing stimuli. Neurons of this type rarely display side-band inhibition. 2. As a group, S-cells display lower relative degrees of binocularity and are more selective for stimulus orientation than C-cells. In addition, within a given lamina the S-cells have smaller receptive fields, lower cutoff velocities, lower peak responses to visual stimulation, and lower spontaneous activity than do the C-cells. 3. S-cells in all layers of the cortex display similar orientation sensitivities, mean spontaneous discharge rates, peak response to visual stimulation, and degrees of binocularity. 4. Many of the receptive-field properties of cortical cells vary with laminar location. Receptive-field sizes and cutoff velocities of S-cells and of C-cells are greater in layers V and VI than in layers II-IV. For S-cells, preferred velocities are also greater in layers V and VI than in layers II-IV. Furthermore, C-cells in layers V and VI display high mean spontaneous discharge rates, weak orientation preferences, high relative degrees of binocularity, and higher peak responses to visual stimulation when compared to C-cells in layers II and III. 5. The receptive-field properties of cells in layers V-VI of the striate cortex suggest that most neurons that have their somata in these laminae receive afferents from LGNd Y-cells. Hence, our results suggest that afferents from LGNd Y-cells may play a major part in the cortical control of subcortical visual functions.

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