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H M Sakai

Publications and source records attributed to H M Sakai.

At least 19 recordsLinked to original sources
PubMed1997

Processing of color- and noncolor-coded signals in the gourami retina. I. Horizontal cells.

There are two types of horizontal cells, the luminosity and the chromaticity cells, in the retina of the kissing gourami, Helostoma rudolfi. Luminosity cells occupy the outermost layer proximal to the receptor terminals, whereas chromaticity cells form a layer proximal to the layer of luminosity cells. Neither type of cell has axons. Responses were evoked by light from red and green light-emitting diodes. The two stimuli were modulated either by a pulsatile or a white-noise signal. The luminosity cell always produced a hyperpolarizing response. The chromaticity cell produced a hyperpolarizing response when stimulated by only one color. However, in the presence of a steady or modulated green input, a red stimulus produced a depolarizing response. Such chromaticity cells were similar to the (spectral) biphasic chromaticity horizontal cells observed in other retinae. The depolarizing phase of the red response was produced by the balance of intensity of the two inputs, red and green. We used white-noise methodology to identify the dynamics of the horizontal cell's modulation response by taking advantage of the fact that a Wiener kernel is a measure of a cell's incremental sensitivity, which includes its response dynamics. Under all conditions, a steady state modulation response by both luminosity and chromaticity cells always was related linearly to the input modulation. The average mean square error (MSE) of the model predicted by the first-order kernel was approximately 8% for both luminosity (n = 116) and chromaticity (n = 23) cells. In some cases, the MSE was a few percent even when the peak-to-peak response amplitude was nearly 30 mV. The ratio of inputs from red and green cones to both types of horizontal cells was variable; the major input for luminosity cells came from red cones, whereas the major input for chromaticity cells came from green cones. First-order kernels generated by the major input were robust in terms of waveform in the sense that the waveform remained unchanged whether or not there was a steady or modulated illumination by the opposing color. The results reported here do not address the question of the neural circuitry that generates horizontal cell responses, in particular, the depolarizing response. However, whatever that circuitry might be, the high degree of linearity of the modulation response by both types of cell under various stimulus conditions imposes restrictions on the performance of any proposed model as well as on mechanisms that underlie the generation of the horizontal cell response.

Animals↗
PubMed1997

Processing of color- and noncolor-coded signals in the gourami retina. II. Amacrine cells.

The same set of stimuli and analytic methods that was used to study the dynamics of horizontal cells () was applied to a study of the response dynamics and signal processing in amacrine cells in the retina of the kissing gourami, Helostoma rudolfi. The retina contains two major classes of amacrine cells that could be identified from their morphology: C and N amacrine cells. C amacrine cells had a two-layered dendritic field, whereas N cells had a monolayered dendritic field. Both types of amacrine cell were tracer-coupled but coupling was more extensive in the N amacrine cells. Responses from C amacrine cells lacked a DC component and had a small linear component that was <10% in terms of mean square error (MSE); the second-order component often accounted for >50% of the modulation response. The C amacrine cells did not show any characteristic color coding under any stimulus condition. Most responses of N cells to a pulsatile stimulus consisted of a series of depolarizing transient potentials and steady illumination did not generate any DC potential in these cells. The response to a white-noise modulated input was composed of well-defined first- and second-order components and, possibly, higher-order components. The response evoked by a red or green white-noise-modulated stimulus given alone was not color coded. Modulated red illumination in the presence of a green illumination elicited a color-coded response from >70% of N amacrine cells. Color information was carried not only by the polarity but also by the dynamics of the first-order component. No convincing evidence was obtained to indicate that the second-order component might be involved in color processing. Some N amacrine cells produced a well-defined (second-order) interaction kernel to show that the temporal sequence of red and green stimuli was a parameter to be considered. In a complex cell such as an amacrine cell, responses evoked by a pulsatile stimulus given in darkness and by modulation of a mean luminance could be very different in terms of their characteristics. It was not always possible to predict the response evoked by one stimulus from observing the cell's response to another stimulus. This is because, in N cells, a flash-evoked (nonsteady state) response is composed largely of nonlinear components whereas a modulation (steady state) response is composed of linear as well as nonlinear components.

Animals↗
PubMed1997

Processing of color- and noncolor-coded signals in the gourami retina. III. Ganglion cells.

The dynamics of intracellular responses from ganglion cells, as well as that of spike discharges, were studied with the stimulus regimens and analytic procedures identical to those used to study the dynamics of the responses from horizontal and amacrine cells (,). The stimuli used were large fields of red and green light given as a pulsatile input or modulation about a mean luminance by a white-noise signal. Spike discharges evoked by a white-noise stimulus were analyzed in exactly the same manner as that used for analysis of analog responses. The canonical nature of kernels allowed us to correlate the first- and second-order components in a spike train with those of the intracellular responses from horizontal, amacrine, and ganglion cells. Both red and green stimuli given alone in darkness produced noncolor-coded responses from all ganglion cells. In the case of some cells, steady red illumination changed the polarity or waveform of the response to green light. Color-coded ganglions responded only to simultaneous color contrast. Nonlinearities recovered from intracellular responses, and spike discharges were similar to those found in responses from amacrine cells and were of two types, one characteristic of the C amacrine cells and the other characteristic of the N amacrine cells. The first-order kernels of most ganglion cells could be divided into two basic types, biphasic and triphasic. The combination of kernels of these two basic types with different polarities can produce a wide range of responses. Addition of two types of second-order nonlinearity could render color coding in this relatively simple retina as an extremely complex process. Color information appeared to be represented by the polarity, as well as the waveform, of the first-order kernel. The response dynamics is a means of transmission of color-coded information. Second-order components carry information about changes around a mean luminance regardless of the color of an input. Some spike discharges produced a well-defined cross-kernel between red and green inputs to show that a particular time sequence of red and green stimuli was detected by the retinal neuron network. The similarity between signatures of second-order kernels for both amacrine and ganglion cells indicates that signals undergo a minimal transformation in the temporal domain when they are transmitted from amacrine to ganglion cells and then transformed into a spike train. Under our experimental conditions, a single spike train carried simultaneously information about red and green inputs, as well as about linear and nonlinear components. In addition, the spike train also carries a cross-talk component. A spike train is a carrier of multiple signals. Conversely, many types of information in a stimulus are independently encoded into a spike train.

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PubMed1997

Complexity and frequency hierarchies in the catfish retina.

The intricate connectivity and interactions between neurons in the vertebrate retina have made their individual roles in signal processing very difficult to elucidate. We have used a recently developed mathematical tool, fast orthogonal search (FOS), to probe the catfish outer (distal) and inner (proximal) retina, and study the signal processing within. Through FOS, a given waveform can be decomposed into a parsimonious sinusoidal series containing the most significant constituent frequencies. In particular, we examined the light-evoked first-order Wiener kernels of horizontal cells and on-bipolar cells, and on-off, off- and on-amacrine and ganglion cells. Here we report a hierarchy (correlation coefficient up to 0.86) in preferred frequency and complexity of response corresponding to the retina's structural hierarchy. In addition, clear differences between on-, on-off and off-cell functional characteristics were detected. For example, the kernel waveform for the on-amacrine cell was found to be more complex and to have a higher preferred frequency than that for the off-amacrine cell. Indeed FOS analysis revealed that both off- (sustained) amacrine and off-ganglion cells exhibit significantly less complexity in their waveforms for signal processing of light input than do the corresponding on- and on-off cells. This shows a clear breakdown in symmetry between on- and off-pathways, and suggests that connections to off-cells may provide fewer or a smaller variety of inputs than those to on- and on-off cells. Many of our new findings can be appreciated by assuming an underlying cascade structure for the retinal information processing. The FOS findings in particular support the following previously advanced hypothesis: the transition in nonlinear processing from on-off amacrine to on- off-amacrine cells is due to high-pass linear filtering. Furthermore, our results indicate that the high-pass filtering is more sharply differentiating for the on-amacrine than for the off-amacrine cell.

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PubMed1995

Response dynamics and receptive-field organization of catfish ganglion cells.

Responses from catfish retinal ganglion cells were evoked by a spot or an annulus of light and were analyzed by a procedure identical to the one used previously to study catfish amacrine cells (Sakai H. M., and K.-I. Naka, 1992. Journal of Neurophysiology. 67:430-442.). In two-input white-noise experiments, a response evoked by simultaneous stimulation of the center and surround was decomposed into the components generated by the center and surround through a process of cross-correlation. The center and surround responses were also decomposed into their linear and nonlinear components so that the response dynamics of the linear and nonlinear components could be measured. We found that the concentric organization of the receptive field was determined by linear components, i.e., the first-order kernels generated by the center and surround were of opposite polarity. Both the center and surround generated second-order kernels with similar signatures, i.e., the second-order components formed a monotonic receptive field. The peak response time of the first- and second-order kernels from the surround was longer by approximately 20 ms than that of the center. Except for the DC potential present in the intracellular responses, almost identical first- and second-order kernels for the center and surround were obtained from both the intracellular response and spike discharges. Thus, information on concentric organization of a receptive field is translated into spike discharges with little loss of information. A train of spike discharges carries, simultaneously, at least four kinds of information: two linear and two nonlinear components, which originate in the receptive field center and the surround. A spike train is not a simple signaling device but is a carrier of complex and multiple signals. Victor, J. D., and R. M. Shapley (1979. Journal of General Physiology. 74:671-687.) discovered similarly that, in the cat retina, static second-order nonlinearity is encoded into spike trains. Results obtained in this study support the thesis that signals generated by the preganglionic cells are translated into spike discharges without major modification and that those signals can be recovered from the spike trains (Sakuranaga, M., Y. Ando, and K.-I. Naka. 1987. Journal of General Physiology. 90:229-259.; Korenberg, M. J., H. M. Sakai, and K.-I. Naka. 1989. Journal of Neurophysiology. 61:1110-1120.). Current injection studies have shown that such signal transmission is possible (Sakai, H. M., and K.-I. Naka, 1988a. Journal of Neurophysiology. 60:1549-1567.; 1990. Journal of Neurophysiology. 63:105-119.).

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PubMed1995

Contrast gain control in the lower vertebrate retinas.

Control of contrast sensitivity was studied in two kinds of retina, that of the channel catfish and that of the kissing gourami. The former preparation is dominantly monochromatic and the latter is bichromatic. Various stimuli were used, namely a large field of light, a spot-annulus configuration and two overlapping stimuli of red and green. Recordings were made from horizontal, amacrine, and ganglion cells and the results were analyzed by means of Wiener's theory, in which the kernels are the contrast (incremental) sensitivity. Modulation responses from horizontal cells are linear, in that the waveform and amplitude of the first-order kernels are independent of the depth of modulation. In the N (sustained) amacrine and ganglion cells, contrast sensitivity was low for a large modulation input and was high for a small modulation input, providing an example of contrast gain control. In most of the cells, the contrast gain control did not affect the dynamics of the response because the waveform of the first-order kernels remained unchanged when the contrast sensitivity increased more than fivefold. The signature of the second-order kernels also remained unchanged over a wide range of modulation. The increase in the contrast sensitivity for the second-order component, as defined by the amplitude of the kernels, was much larger than for the first-order component. This observation suggests that the contrast gain control proceeded the generation of the second-order nonlinearity. An analysis of a cascade of the Wiener type shows that the control of contrast sensitivity in the proximal retinal cells could be modeled by assuming the presence of a simple (static) saturation nonlinearity. Such a nonlinearity must exist somewhere between the horizontal cells and the amacrine cells. The functional implications of the contrast gain control are as follows: (a) neurons in the proximal retina exhibit greater sensitivity to input of lower contrast; (b) saturation of a neuronal response can be prevented because of the lower sensitivity for an input with large contrast, and (c) over a large range of modulation depths, the amplitude of the response remains approximately constant.

Algorithms↗
PubMed1992

Response dynamics and receptive-field organization of catfish amacrine cells.

1. We have applied Wiener analysis to a study of response dynamics of N (sustained) and C (transient) amacrine cells. Stimuli were a spot and an annulus of light, the luminance of which was modulated by two independent white-noise signals. First- and second-order Wiener kernels were computed for each spot and annulus input. The analysis allowed us to separate a modulation response into its linear and nonlinear components, and into responses generated by a receptive-field center and its surround. 2. Organization of the receptive field of N amacrine cells consists of both linear and nonlinear components. The receptive field of linear components was center-surround concentric and opposite in polarity, whereas that of second-order nonlinear components was monotonic. 3. In NA (center-depolarizing) amacrine cells, the membrane DC potentials brought about by the mean luminance of a white-noise spot or a steady spot were depolarizations, whereas those brought about by the mean luminance of a white-noise annulus or a steady annulus were hyperpolarizations. In NB (center-hyperpolarizing) amacrine cells, this relationship was reversed. If both receptive-field center and surround were stimulated by a spot and annulus, membrane DC potentials became close to the dark level and the amplitude of modulation responses became larger. 4. The linear responses of a receptive-field center of an N amacrine cell, measured in terms of the first-order Wiener kernel, were facilitated if the surround was stimulated simultaneously. The amplitude of the kernel became larger, and its peak response time became shorter. The same facilitation occurred in the linear responses of a receptive-field surround if the center was stimulated simultaneously. 5. The second-order nonlinear responses were not usually generated in N amacrine cells if the stimulus was either a white-noise spot or a white-noise annulus alone. Significant second-order nonlinearity appeared if the other region of the receptive field was also stimulated. 6. Membrane DC potentials of C amacrine cells remained at the dark level with either a white-noise spot or a white-noise annulus. The cell responded only to modulations. 7. The major characteristics of center and surround responses of C amacrine cells could be approximated by second-order Wiener kernels of the same structure. The receptive field of second-order nonlinear components of C amacrine cells was monotonic.(ABSTRACT TRUNCATED AT 400 WORDS)

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PubMed1990

Dissection of the neuron network in the catfish inner retina. IV. Bidirectional interactions between amacrine and ganglion cells.

1. We have functionally dissected the neuron network in the catfish inner retina by means of current injection. Simultaneous intracellular recordings were made from two neighboring neurons with the use of two separate electrodes. Extrinsic current was injected into one neuron, and the resulting intracellular responses were recorded from the other neuron. The test signals included 1) a single-frequency sinusoid, 2) a depolarizing or a hyperpolarizing current pulse, and 3) white-noise modulated current from which Wiener kernels were computed by an input-output cross-correlation process. 2. Extrinsic current injected into an ON amacrine (NA) cell evoked responses from a neighboring ON ganglion (GA) cell. Conversely, current injected into a GA cell elicited responses from a neighboring NA cell. Similar results were obtained for the transmission between OFF amacrine (NB) and OFF ganglion (GB) cells. Neural filters for the forward and backward transmissions between amacrine and ganglion cells of the same response polarity were low-pass, constant gain with a cutoff frequency of 40-50 Hz. The gain measured by current-amplitude relationships was comparable for the forward (N----G) and backward (G----N) transmission. 3. Similar bidirectional signal transmission was found between amacrine cells and between ganglion cells of the same response polarity. Neural filters for such transmission were also low-pass, constant gain with a cutoff frequency of 40-50 Hz. 4. Because a large portion of the current-evoked response was predicted by the first-order kernel, transmission between cells of the same response polarity was approximately linear. The current-evoked first-order kernels were brief and impulse-like compared with the light-evoked first-order kernels. 5. We conclude that ON and OFF amacrine and ganglion cells form two ON- and OFF-cell clusters in which cells are extensively and bidirectionally interconnected, enhancing the response in each cluster.

Animals↗
PubMed1990

Dissection of the neuron network in the catfish inner retina. V. Interactions between NA and NB amacrine cells.

1. Simultaneous intracellular recordings were made from two neighboring N amacrine cells, one an ON amacrine (NA) cell and the other an OFF amacrine (NB) cell. Extrinsic current was injected into one amacrine cell, and the resulting intracellular responses were recorded from the other amacrine cell. Test signals included 1) a single-frequency sinusoid, 2) a depolarizing or hyperpolarizing pulse, or 3) a white-noise modulated current. In some cell pairs, membrane noise was measured in the dark as well as under a steady background illumination. 2. Current pulses injected into a NA cell evoked a damped oscillation from a NB cell. The first-order kernel derived by cross-correlating the white-noise current injected into a NA cell against the evoked response from a NB cell was a large depolarization followed by a damped oscillation. The frequency of oscillations varied slightly from pair to pair but averaged 35 Hz. 3. Current pulses injected into a NB cell evoked a sign-inverting response (hyperpolarization) of very small amplitude from a NA cell. Similarly, the first-order kernel was a hyperpolarization of very small amplitude. 4. The power spectrum of the membrane noise recorded from NA and NB cells in the dark or during steady illumination often showed a peak at 35 Hz. Such membrane noise synchronizes synergistically among NA cells and among NB cells in the dark. In addition, the membrane fluctuations seen in NA and NB cells in the dark were out of phase. 5. Transmission between NA and NB cells was largely accounted for by a linear component; however, a very small but significant second- and third-order nonlinearity was also generated. 6. These results show that the interactions occurring between amacrine cells of opposite response polarity are much more complex than those between cells of the same response polarity and that the neural circuitry in the inner retina actively controls interactions between ON and OFF channels in the dark as well as in the presence of light stimuli.

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PubMed1989

Dissection of the neuron network in the catfish inner retina. III. Interpretation of spike kernels.

1. Three independent sets of evidence have been obtained to show that similar first- and second-order light-evoked kernels are computed for the ganglion cell when the system output is taken to be either the spike train (discrete signal) or the postsynaptic potential (analog signal). In this paper we show that the similarity of postsynaptic potential (PSP) kernels and spike kernels is readily explained by assuming an underlying cascade structure for the neural information processing. The cascade structure enables spike kernels to be mathematically related very simply to the process of generating the postsynaptic potentials of ganglion cells. 2. Mathematical analysis of the cascade structure also suggests why spike kernels appear to differ slightly from PSP kernels. The relation between the two sets of kernels predicted from our analysis is substantiated here by experiment and reveals an interconnection between several of the signals measured. 3. Our experimental results, in particular, suggest that the neuronal circuitry leading from the light stimulus to the generation of ganglion cell spike discharges can be represented as follows: either a Wiener (LN) or a dynamic linear-static nonlinear-dynamic linear (LNL) structure is followed by a highly nonlinear process [static or brief-memory Hammerstein static-nonlinear dynamic-linear (NL) structure] of spike generation. Cross-correlation between the analog input and spike output enables identification of these structures.

Action Potentials↗
PubMed1988

Generation and transformation of second-order nonlinearity in catfish retina.

A large part of the response from catfish retinal neurons evoked by a white-noise modulated light stimulus is reconstructed by the linear and the second-order nonlinear components, which shows that the first- and second-order kernels represent the major response characteristics. In catfish retina, amacrine cells are classified as type-C and type-N cells. Type-C cells produce a stable and stereotyped second-order kernel that can be reproduced by squaring an underdamped first-order kernel. This is a linear filter followed by a static nonlinearity and is modeled by a cascade of the Wiener structure. A second-order kernel from the other class of amacrine cells, type-N cells, is reproduced by a simple linear filtering of type-C cell response. This is a static nonlinearity sandwiched between two linear filters and is modelled by a cascade of the Korenberg structure. These findings may greatly simplify future attempts to reconstruct retinal circuitry and may give some insight into the process of complex signal processing in the inner part of the vertebrate retina.

Animals↗
PubMed1988

White-noise analysis in visual neuroscience.

In 1827, plant biologist Robert Brown discovered what is known as Brownian motion, a class of chaos. Formal derivative of Brownian motion is Gaussian white-noise. In 1938, Norbert Wiener proposed to use the Gaussian white-noise as an input probe to identify a system by a series of orthogonal functionals known as the Wiener G-functionals. White-noise analysis is uniquely suited for studying the response dynamics of retinal neurons because (1) white-noise light stimulus is a modulation around a mean luminance, as are the natural photic inputs, and it is a highly efficient input; and (2) the analysis defines the response dynamics and can be extended to spike trains, the final output of the retina. Demonstrated here are typical examples and results from applications of white-noise analysis to a visual system.

Action Potentials↗
PubMed1988

Dissection of the neuron network in the catfish inner retina. I. Transmission to ganglion cells.

1. To characterize the signal transmission from amacrine to ganglion cells, and to identify the filter that transforms amacrine-cell responses into ganglion-cell spike discharges, an extrinsic current, either sinusoidally or white-noise modulated, was injected into an amacrine cell and the resulting extracellular spike discharges were recorded from a neighboring ganglion cell. For the sinusoidal inputs, PST (poststimulus time) histograms were produced; for the white-noise inputs, first- and second-order Wiener kernels were computed by a cross-correlation process. 2. Extrinsic current injected either into a type-N (sustained) amacrine cell or a type-C (transient) amacrine cell modulated the spike discharges of nearby ganglion cells, whether of the "ON," "ON-OFF" or "OFF" types. We identified two modes of signal transmission, fast (probably monosynaptic) and slow (probably polysynaptic) transmission. Signal transmission from amacrine to ganglion cells of the same response polarity i.e., from type-NA (depolarizing, sustained) amacrine to ON-ganglion cell and from-NB (hyperpolarizing, sustained) amacrine to OFF-ganglion cell, was either fast or slow. Similarly, the signal transmission from type-C to either ON- or OFF-ganglion cells was either fast or slow. 3. The signal transmission from amacrine to ganglion cell of the opposite response polarity, i.e., from type-NA to OFF-ganglion cell and from type-NB to ON-ganglion cell, was always slow. 4. Fast transmission from type-N amacrine to a ganglion cell of the same polarity, or from type-C to either ON- or OFF-ganglion cells was always sign-noninverting. The transfer function was lowpass, with a cutoff frequency of 30 Hz. 5. Slow transmission from any type of amacrine cell (either type-NA, -NB or -C) to ON-ganglion cells was always sign inverting, whereas from any amacrine to OFF-ganglion cells was always sign-noninverting. The transfer function for the slow transmission was narrow bandpass, with a cutoff frequency of 30-40 Hz.

Action Potentials↗
PubMed1988

Dissection of the neuron network in the catfish inner retina. II. Interactions between ganglion cells.

1. To characterize signal interactions between ganglion cells, extrinsic current, either sinusoidally or white-noise modulated, was injected into a ganglion cell and the resulting extracellular spike discharges were recorded from a neighboring ganglion cell. 2. Current injected into an ON-ganglion (GA) cell modulated the spike discharges of a neighboring ON-ganglion cell (GA). Similarly, a current injected into an OFF-ganglion (GB) cell modulated the spike discharges of a neighboring OFF-ganglion (GB) cell. The signal transmission between ganglion cells of the same response polarity was fast and sign-noninverting. The transfer function was lowpass with a cutoff frequency of 30 Hz. The efficacy of the transmission was comparable to that from bipolar or amacrine to ganglion cells of the same polarity. 3. Current injected into an ON-ganglion (GA) cell modulated the spike discharges of a neighboring OFF-ganglion (GB) cell; the signal transmission was slow and sign-noninverting. Correspondingly, current injected into an OFF-ganglion (GB) cell modulated the spike discharges of a neighboring ON-ganglion (GA) cell; transmission was slow and sign-inverting. 4. A brief electrical stimulation of the optic nerve activated a single antidromic ganglion cell spike at threshold. With suprathreshold stimulation, multiple spikes appeared, which probably were activated orthodromically. Changes in membrane potential of ganglion and amacrine cells induced by optic nerve stimulation usually lasted 50-80 ms, with an initial depolarization followed by hyperpolarization. We interpret such long-lasting responses to be mediated by reciprocal circuits that include amacrine, bipolar, and ganglion cells. 5. Together with the observations made by Sakai and Naka, we conclude that virtually almost all amacrine, bipolar, and ganglion cells are functionally interconnected; direct and fast connections are established among ON-cells and similarly among OFF-cells, and complex, indirect connections are established between ON- and OFF-cells.

Animals↗
PubMed1987

Signal transmission in the catfish retina. IV. Transmission to ganglion cells.

1. To characterize the temporal dynamic responses of ganglion cells and to define the possible inputs giving rise to their responses in catfish retina, we recorded the ganglion cell responses evoked by 1) a step of light presented in the dark, 2) an incremental and decremental step from a background illumination, and 3) a white-noise modulated light. 2. For comparison, we recorded the responses of preganglionic cells evoked by the same set of stimuli as used for the ganglion cells. Type-C cells produced on-off transient depolarizations to step stimuli, whether presented in the dark or an illuminated background. Type-N amacrine cells produced complex transient responses to incremental and decremental steps, whereas their step-evoked responses in the dark were sustained polarizations. Bipolar cells produced sustained responses to all step stimuli. 3. Ganglion cells were classified into three types, based on their responses evoked by incremental and decremental steps of light. One class of ganglion cells produced responses similar to those of type-C cells, the second class produced responses similar to those of type-N cells, and the third class resembled bipolar cell responses, although spike discharges accompanied the ganglion cell responses. 4. The analysis of the first-order kernels indicates that the temporal properties of linear dynamic responses are established at the level of bipolar cells and encoded into spike trains of ganglion cells without a major transformation. 5. The second-order nonlinearity appeared at the amacrine cell level. Type-C and type-N cells produced a second-order kernel characteristic of each cell type. The second-order kernels produced in ganglion cells were similar to those produced either by type-C or type-N cells. 6. We conclude that bipolar cells are the major source of linear components of ganglion cell responses and that type-C and type-N amacrine cells are the major source of the nonlinear responses. These linear and second-order nonlinear signals were encoded into spike trains by ganglion cells without a major transformation of the temporal response properties.

Animals↗
PubMed1987

Signal transmission in the catfish retina. V. Sensitivity and circuit.

1. We analyzed the light-evoked responses of retinal neurons by means of a white-noise technique. Horizontal and bipolar cells produced a modulation response that was linearly related to a modulation of the mean luminance of a large field of light. The first-order kernels were capable of reproducing the cells' modulation response with a fair degree of accuracy. The amplitude as well as the waveform of the kernels changed with the change in the mean luminance. This is a parametric change and is a form of field adaptation. As the time constant of the parametric change was much longer than that of the modulation response (memory), neurons were assumed to be at a dynamic steady state at a given mean luminance. 2. With the presence of a steady annular illumination, the first-order kernel derived from stimulation with a small spot of light became faster in peak response time and larger in amplitude. For horizontal-cell somas and bipolar cells, the surround also linearized their modulation response. This surround enhancement has been seen in all the cone-driven retinal cells except the receptor and horizontal cell axon, in which a steady surround decreased the amplitude of the spot-evoked kernel but shortened the peak response time. 3. A change in the modulation depth did not affect either the amplitude or the wave-form of the first-order kernels from the horizontal and bipolar cells. In the amacrine and ganglion cells, on the other hand, the amplitude of kernels was related inversely to the depth of modulation. These cells were more sensitive to the modulation of a small modulation depth. 4. A static nonlinearity appeared when signals were transmitted to the amacrine cells. The nonlinearity was first produced in the type-C amacrine cells by a process, which could be modeled by squaring the bipolar cell response. A gamut of more complex second-order nonlinearities found in type-N amacrine cells could be modeled by a band-pass filtering of the type-C cell response. Linear components in the bipolar cells and nonlinear components in the amacrine cells are encoded into spike trains in the ganglion cells. Thus, under our simple stimulus regimen, the ganglion cells transformed the results of the preganglionic signal processing into a spike train without much modification. 5. We propose a tentative diagram of the signal flow in the cone-driven catfish retinal neurons based on this and previous studies.(ABSTRACT TRUNCATED AT 400 WORDS)

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PubMed1986

Synaptic organization of the cone horizontal cells in the catfish retina.

Horizontal cells of the vertebrate retina are known to contribute to the formation of the receptive field surrounds of photoreceptor and bipolar cells. However, few synapses have been described anatomically that might mediate these interactions. We have observed in the catfish retina that cone horizontal cell perikarya and dendrites make conventional chemical synapses onto photoreceptor terminal telodendria and onto bipolar cell dendrites, while horizontal cell axon terminals make chemical synapses onto the perikarya and processes of amacrine cells. The synapses are characterized by clusters of round vesicles aggregated close to the site of contact, as well as by electron-dense material associated with both pre- and postsynaptic membranes. The three kinds of synapses observed anatomically correspond to the synaptic pathways involving cone horizontal cells that have been suggested by the physiology of these cells.

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