The sensitivity of rod- and cone-driven responses was studied in the isolated frog retina during the period of rapid dark adaptation following a conditioning flash which bleached a negligible amount of visual pigment. Following a conditioning flash, cone-driven b-wave responses were first enhanced and then depressed. The time courses of the enhancement and subsequent depression of cone-drive responses varies greatly with the intensity and wavelength of the conditioning flash, but were identical when the conditioning' flashes were matched for equal excitation of 502 nm rods. These changes in cone-driven response sensitivity were correlated with the desensitization and recovery of rods following the conditioning flash. When signal transmission from rods to second-order cells was interrupted by the addition of L-glutamate, the conditioning flash did not produce the above-described enhancement and subsequent depression of long-wavelength receptor potential responses. The suppression of cone-driven response therefore appears to be due to a synaptically mediated influence from 502 nm rods which is maximal when the rods are in the dark-adapted state, with little or no contribution from 433 nm rods, and no involvement of the pigment epithelium.

A method for constructing nonlinear models for light adaptation in the retina is introduced. The components of the models are linear filters and static (instantaneous) nonlinear elements configured in a feedback arrangement. The signals in the models are combined through algebraic addition or multiplication. We apply the method to model light adaptation measured in turtle horizontal cells. Given a particular wiring diagram for the components, the functional forms of the static nonlinearities and frequency responses of the linear filters are determined by constraining the model to give temporal frequency responses (linear regime behavior) consistent with a family of linear feedback models which has been shown to provide a good description of adaptation in these cells. Two particular models, quite different in structure, are presented. Each model responds to perturbations around a mean light level as a feedback circuit in which the gain (strength) of feedback is adjusted to be proportional to the mean light level, but neither model has a separate pathway for measuring the mean light level. Thus, each of these nonlinear models embeds an entire family of linear models parametric in mean light level. Harmonic distortion in the responses of these models to sinusoidal input is found to be qualitatively consistent with physiological data. An alternative class of nonlinear models in which feedback gain is set by a separate slow pathway which tracks the mean light level is ruled out on the basis of its incorrect steady-state input-output behavior. The methods presented can be used to develop specific physical models for light adaptation based on the chemical kinetics of phototransduction or on nonlinear neural feedback. The relevance of the nonlinear models and construction techniques to modeling phototransduction is discussed.

Monoclonal antibodies directed against nicotinic acetylcholine receptors (nAChRs) were used to identify and characterize cholinoceptive neurons in the chick retina. Two monoclonal antibodies (mAbs), mAb 210 and mAb 270, stained many neurons in both the inner nuclear layer (INL) and ganglion cell layer (GCL). A class of large labeled cells in the inner INL were positioned at the INL/IPL (inner plexiform layer) border and resembled displaced ganglion cells (DGCs). Their identity was confirmed with injections of rhodamine-labeled microspheres into the ventral tectum and nucleus of the basal optic root (nBOR). Four days after the injection, large nAChR-positive neurons in the inner INL were labeled with beads. The distribution of these cells matched that reported for DGCs in the chicken and pigeon (Reiner et al., 1979; Fite et al., 1981). Many smaller cells in the INL also exhibited nAChR immunoreactivity. These cells were not retrogradely labeled after bead injections into retinal recipient areas. Their processes entered the IPL where they arborized in a band comprised of the inner leaflet of lamina 1 and all of lamina 2. In some instances, a process continued inward to lamina 4. These neurons were tentatively identified as amacrine cells because of their position and branching pattern.

Approximately 12–18% of the cells in the GCL exhibited nAChR immunoreactivity. Many of these cells could be classified as ganglion cells as their axons were also labeled following exposure to nAChR antibodies. Their distribution mirrored that of all ganglion cells with a higher density of cells in the central retina than in the periphery (Ehrlich, 1981). A “double label” technique was used to compare the distribution of nAChR-positive neurons with that of the choline acetyltransferase-positive (ChAT), cholinergic neurons in the chick retina. The two antigens were visualized with two different fluorophores: FITC and RITC. We were unable to find any cells in either the INL or GCL that exhibited both ChAT- and nAChR-like immunoreactivity. The nAChR-positive cells and the ChAT-positive cells both arborized in two bands within the IPL. The patterns were in perfect register in the inner IPL (lamina 4). But, in the outer IPL, the nAChR-positive dendrites were observed in the inner leaflet of lamina 1 and in all of lamina 2 while the ChAT-positive dendrites did not extend into the innermost portion of lamina 2.

We have examined the soma size, number, and distribution of cholinergic amacrine cells in the retinas of albino and pigmented rats and of Siamese and common cats, using an antibody against choline acetyl transferase (ChAT). In the pigmented strains of rat and cat, ChAT-immunoreactive (ChAT-IR) somata were located in both the inner part of the inner nuclear layer (INL) and ganglion cell layer (GCL), and their processes spread in distinct strata of the inner plexiform layer (IPL). The diameters of the somata in the INL and GCL did not differ significantly at any retinal location. Furthermore, soma diameter did not vary with eccentricity, except at the area centralis of the common cat, where ChAT-IR somata in both layers were relatively smaller. In both species, ChAT-IR somata in the GCL outnumbered those in the INL at all retinal locations. Both populations of cells tended to concentrate at the area of peak ganglion cell density and along the visual streak. Additionally, areas of relatively high density extended superiorly from the area of peak density. The same features of morphology and distribution were identifiable in the hypopigmented strains of rat and cat, but the numbers of ChAT-IR cells were consistently higher.

A new form of receptive field map, the response-component map, was developed to identify points within a receptive field that produce similar response patterns. The fields were probed with discretely flashed small spots of light. The magnitudes of the responses to stimulus onset and to stimulus offset elicited at each point were represented on the map by a vector radiating from the position representing the location of that point. Thus, response-component maps preserve the spatial distributions of responsivity and temporal nonlinearities. Points with similar response patterns were identified from a scatterplot in which the response at each spatial position was located in a plane representing the angles of the response-component vectors. Points with similar response characteristics that were also spatially contiguous were considered as a distinct response subregion within the receptive field.

Barely 10% of the receptive fields of goldfish ganglion cells mapped with this technique proved as simple as the traditional concentric field described for retinal cells. In at least 17% of the cases, the field showed three concentric rings, with a very small “inner center” within the center of the field. In at least 50% of the cases, response subregions of different type lay side by side, rather than in a concentric configuration. Some subregions could be differentiated by the relative strengths of the responses to onset and offset of the stimulus spot, supporting the hypothesis that a push-pull system generates ganglion cell responses. Subregions were evident in successive mappings of the same cell, demonstrating they are not due to the vagaries of individual responses. They probably represent the spatial domains (or their intersections) of individual interneurons distal to the retinal ganglion cells. It is possible that position within the receptive field may be coded by the temporal pattern of the responses.

A serial-lesion technique was used to investigate interactions in visual processing between telencephalic components of the pigeon visual system. Pigeons were trained to discriminate pairs of stimuli that differed in color, intensity or pattern. After mastering the discrimination tasks, they were assigned to one of three groups. The first group (WI-EII) received lesions of the visual Wulst and were retested. After the discrimination tasks were again mastered, a second set of lesions was made, this time in the ectostriatum. The birds were tested once again after the second surgery. The second group (EI-WII), underwent the same sequence of events except that the order of the lesions was reversed. In the third group (E + W), lesions of both the visual Wulst and ectostriatum were made in a single operation, followed by retesting. The performance after the first lesion of the subjects in each of the two-stage lesion groups was typical of performance after such lesions; i.e. the birds with visual-Wulst lesions showed little or no impairment on any of the tasks, whereas the pigeons with ectostriatum lesions showed considerable deficits in intensity and pattern discrimination, which diminished after prolonged retraining. In contrast, the pigeons in the one-stage group (E + W) showed profound deficits that appeared to be permanent. The performance after the second operation of the WI-EII group was the same as that of pigeons with lesions of ectostriatum alone; i.e. destruction of ectostriatum first or second resulted in the same duration of impairment. The performance of the EI-WII group after its visual Wulst lesion, however, was similar to that observed in the E + W group. The results are interpreted as a reflection of parallel processing within the avian visual system; i.e. the presence of an intact tectofugal pathway may mask the effects of thalamofugal pathway interruption.

The orientation selectivity, ocular dominance, and binocular disparity tuning of 272 cells in areas 17 and 18 of barbiturate-anesthetized, paralyzed cats were studied with automated, quantitative techniques. Disparity was varied along the axis orthogonal to each cell's best orientation. Binocular correspondence was established by means of a reference electrode positioned at the boundary of lamina A and Al in the area centralis representation of the lateral geniculate nucleus. Measures were derived that expressed each cell's disparity sensitivity and best disparity and the shape and slope of its tuning curve. Cells were found that corresponded to categories described by previous authors (“disparity-insensitive,” “tuned excitatory,” “near,” and “far” cells), but many others had intermediate response patterns, or patterns that were difficult to categorize. Quantitative analysis suggested that the various types belong to a continuum.

No relationship could be established between a cell's best orientation and its ocular dominance or any aspect of its disparity tuning. There was no relationship between a cell's ocular dominance and its sensitivity to disparity. Ocular dominance and best disparity were related. As reported by others, cells with best disparities close to zero (the fixation plane) tended to have balanced ocularity, while cells with best disparities in the near or far range had a broad distribution of ocular dominance. Among cells with receptive fields near the vertical meridian, those preferring far disparities tended to be dominated by the contralateral eye, and those preferring near disparities by the ipsilateral eye. It is suggested that this relationship follows from the geometry of near and far images and the pattern of decussation in the visual pathway. There was a significant grouping of cells with similar best disparities along tangential electrode tracks. We believe that this grouping is due to the columnar organization for ocular dominance and the relationship between ocular dominance and best disparity. No evidence was found for a columnar segregation of disparity-sensitive and disparity-insensitive cells.

The existence in cat cortex of linearly operating simple cells with relative spatial-frequency bandwidths of between 0.5 and 1 octave is confirmed.