A unified neural network model of spatiotemporal processing in X and Y retinal ganglion cells

This article makes use of a push-pull shunting network, which was introduced in the companion article, to model certain properties of X and Y retinal ganglion cells. Input to the push-pull network is preprocessed by a nonlinear mechanism for temporal adaptation, which is ascribed here to photoreceptor dynamics. The complete circuit is used to show that a simple change in receptive field morphology within a single model equation can change the network's response characteristics to closely resemble those of either X or Y cells. Specifically, an increase in width of the receptive field center mechanism is sufficient to account for generation of on-off (Y-like) instead of null (X-like) responses to modulated gratings. In agreement with experimental data, the Y cell on-off response is independent of spatial phase. Also, the model accurately predicts that on-off responses can be observed in X cells for particular stimulus configurations. Taken together, the results show how the retina combines individually inadequate modules to efficiently handle the tasks required for accurate spatial and temporal visual information processing. The model is also able to clarify a number of controversial experimental findings on the nature of spatiotemporal visual processing in the retina.     

Receptive field mechanisms of cat X and Y retinal ganglion cells

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 first-order 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.     

A model of neural network for spatiotemporal pattern recognition

A model of neural network to recognize spatiotemporal patterns is presented. The network consists of two kinds of neural cells: P-cells and B-cells. A P-cell generates an impulse responding to more than one impulse and embodies two special functions: short term storage (STS) and heterosynaptic facilitation (HSF). A B-cell generates several impulses with high frequency as soon as it receives an impulse. In recognizing process, an impulse generated by a P-cell represents a recognition of stimulus pattern, and triggers the generation of impulses of a B-cell. Inhibitory impulses with high frequency generated by a B-cell reset the activities of all P-cells in the network.Two examples of spatiotemporal pattern recognition are presented. They are achieved by giving different values to the parameters of the network. In one example, the network recognizes both directional and non-directional patterns. The selectivities to directional and non-directional patterns are realized by only adjusting excitatory synaptic weights of P-cells. In the other example, the network recognizes time series of spatial patterns, where the lengths of the series are not necessarily the same and the transitional speeds of spatial patterns are not always the same. In both examples, the HSF signal controls the total activity of the network, which contributes to exact recognition and error recovery. In the latter example, it plays a role to trigger and execute the recognizing process. Finally, we discuss the correspondence between the model and physiological findings.     

Applications of minimum-order Wiener modeling to retinal ganglion cell spatiotemporal dynamics

In a previous paper (Marmarelis et al. 1986) we presented the concept of minimum-order Wiener (MOW) modeling of continuous-input/spike-output (CISO) systems. The associated MOW methodology aims at obtaining low-order Wiener models for CISO systems of practical interest. The assertion was made that many neurophysiological systems that fall in this class can be studied effectively by the use of this method. We have chosen a sensory system to demonstrate the efficacy of the method with actual experimental data. The response of retinal ganglion cells to spatiotemporal visual stimuli was studied with this approach and a second-order MOW model was obtained. The results appear to corroborate the adequacy of this model in terms of predicting the timing of the output spikes.     

The P2X7 receptor in retinal ganglion cells: A neuronal model of pressure-induced damage and protection by a shifting purinergic balance

Retinal ganglion cells process the visual signal and transmit it along their axons in the optic nerve to the brain. Molecular, immunohistochemical, and functional analyses indicate that the majority of retinal ganglion cells express the ionotropic P2X₇ receptor. Stimulation of the receptor can lead to a rise in intracellular calcium and cell death, although death does not involve the opening of a large diameter pore. Adenosine acting at A₃ receptors can attenuate the rise in calcium and death accompanying P2X₇ receptor activation, suggesting that dephosphorylation of ATP into adenosine is neuroprotective and that the balance of extracellular purines can influence neuronal survival. Increased intraocular pressure can lead to release of excessive extracellular ATP in the retina and damage ganglion cells by acting on P2X₇ receptors, implicating a role for the receptor in the loss of ganglion cell activity in glaucoma. In summary, the activation of P2X₇ receptors has both physiologic and pathophysiologic implications for ganglion cell function. These characteristics may also provide an insight into the contributions the P2X₇ receptor makes to neurons elsewhere.     

Ionic mechanisms underlying tonic and phasic firing behaviors in retinal ganglion cells: A model study

In the retina, the firing behaviors that ganglion cells exhibit when exposed to light stimuli are very important due to the significant roles they play in encoding the visual information. However, the detailed mechanisms, especially the intrinsic properties that generate and modulate these firing behaviors is not completely clear yet. In this study, 2 typical firing behaviors—i.e., tonic and phasic activities, which are widely observed in retinal ganglion cells (RGCs)—are investigated. A modified computational model was developed to explore the possible ionic mechanisms that underlie the generation of these 2 firing patterns. Computational results indicate that the generation of tonic and phasic activities may be attributed to the collective actions of 2 kinds of adaptation currents, i.e., an inactivating sodium current and a delayed-rectifier potassium current. The concentration of magnesium ions has crucial but differential effects in the modulation of tonic and phasic firings, when the model neuron is driven by N-methyl-D-aspartate (NMDA) -type synaptic input instead of constant current injections. The proposed model has robust features that account for the ionic mechanisms underlying the tonic and phasic firing behaviors, and it may also be used as a good candidate for modeling some other firing patterns in RGCs.     

Cellular basis for the response to second-order motion cues in Y retinal ganglion cells.

We perceive motion when presented with spatiotemporal changes in contrast (second-order cue). This requires linear signals to be rectified and then summed in temporal order to compute direction. Although both operations have been attributed to cortex, rectification might occur in retina, prior to the ganglion cell. Here we show that the Y ganglion cell does indeed respond to spatiotemporal contrast modulations of a second-order motion stimulus. Responses in an OFF ganglion cell are caused by an EPSP/IPSP sequence evoked from within the dendritic field; in ON cells inhibition is indirect. Inhibitory effects, which are blocked by tetrodotoxin, clamp the response near resting potential thus preventing saturation. Apparently the computation for second-order motion can be initiated by Y cells and completed by cortical cells that sum outputs of multiple Y cells in a directionally selective manner.     

A general model of stochastic neural processing

A model of neural processing is proposed which is able to incorporate a great deal of neurophysiological detail, including effects associated with the mechanics of postsynaptic summation and cell surface geometry and is capable of hardware realisation as a probabilistic random access memory (pRAM). The model is an extension of earlier work by the authors, which by operating at much shorter time scales (of the order of the lifetime of a quantum of neurotransmitter in the synaptic cleft) allows a greater amount of information to be retrieved from the simulated spike train. The mathematical framework for the model appears to be that of an extended Markov process (involving the firing histories of the N neurons); simulation work has yielded results in excellent agreement with theoretical predictions. The extended neural model is expected to be particularly applicable in situations where timing constraints are of special importance (such as the auditory cortex) or where firing thresholds are high, as in the case for the granule and pyramidal cells of the hippocampus.     

A unified hypothesis on the lineage of neural stem cells

For many years, it was assumed that neurons and glia in the central nervous system were produced from two distinct precursor pools that diverged early during embryonic development. This theory was partially based on the idea that neurogenesis and gliogenesis occurred during different periods of development, and that neurogenesis ceased perinatally. However, there is now abundant evidence that neural stem cells persist in the adult brain and support ongoing neurogenesis in restricted regions of the central nervous system. Surprisingly, these stem cells have the characteristics of fully differentiated glia. Neuroepithelial stem cells in the embryonic neural tube do not show glial characteristics, raising questions about the putative lineage from embryonic to adult stem cells. In the developing brain, radial glia have long been known to produce cortical astrocytes, but recent data indicate that radial glia might also divide asymmetrically to produce cortical neurons. Here we review these new developments and propose that the stem cells in the central nervous system are contained within the neuroepithelial --> radial glia --> astrocyte lineage.     

The distribution of the intervals between neural impulses in the maintained discharges of retinal ganglion cells

Simulated neural impulse trains were generated by a digital realization of the integrate-and-fire model. The variability in these impulse trains had as its origin a random noise of specified distribution. Three different distributions were used: the normal (Gaussian) distribution (no skew, normokurtic), a first-order gamma distribution (positive skew, leptokurtic), and a uniform distribution (no skew, platykurtic). Despite these differences in the distribution of the variability, the distributions of the intervals between impulses were nearly indistinguishable. These inter-impulse distributions were better fit with a hyperbolic gamma distribution than a hyperbolic normal distribution, although one might expect a better approximation for normally distributed inverse intervals. Consideration of why the inter-impulse distribution is independent of the distribution of the causative noise suggests two putative interval distributions that do not depend on the assumed noise distribution: the log normal distribution, which is predicated on the assumption that long intervals occur with the joint probability of small input values, and the random walk equation, which is the diffusion equation applied to a random walk model of the impulse generating process. Either of these equations provides a more satisfactory fit to the simulated impulse trains than the hyperbolic normal or hyperbolic gamma distributions. These equations also provide better fits to impulse trains derived from the maintained discharges of ganglion cells in the retinae of cats or goldfish. It is noted that both equations are free from the constraint that the coefficient of variation (CV) have a maximum of unity. The concluding discussion argues against the random walk equation because it embodies a constraint that is not valid, and because it implies specific parameters that may be spurious.     

Electrical activity of rat retinal ganglion cells

The electrical activity of rat retinal ganglion cells is described. It was found that most such cells generate tonic discharges, while cells that demonstrate a phasic type of activity are less numerous. Neirofiziologiya/Neurophysiology, Vol. 39, Nos. 4/5, pp. 382–384, July–October, 2007.     

Asymmetrical dendritic fields of retinal ganglion cells

By use of Golgi chrome—silver impregnation, studies were made of the dendritic branchings of feline and frog ganglion cells. It was shown that besides the known varieties of ganglion cells there were asymmetrical neurones whose dendrites lay all to one side. Essential differences distinguished these ganglion cells in the cat from those in the frog, differences depending upon the architectonics of the inner plexiform layer, which is broad and subdivided into layers in the frog, and narrow in the cat. We discuss the possible role of neurones with a unilateral arrangement of dendrites in relation to know electrophysiological data on retinal detectors and the receptive fields of ganglion cells.Brain Institute, Academy of Medical Sciences of the USSR, Moscow. Translated from Neirofiziologiya, Vol. 3, No. 3, pp. 301–307, May–June, 1971.     

Dark rearing alters the normal development of spatiotemporal response properties but not of contrast detection threshold in mouse retinal ganglion cells

The mouse visual system is immature when the eyes open two weeks after birth. As in other mammals, some of the maturation that occurs in the subsequent weeks is known to depend on visual experience. Development of the retina, which as the first stage of vision provides the visual information to the brain, also depends on light‐driven activity for proper development but has been less well studied than visual cortical development. The critical properties for retinal encoding of images include detection of contrast and responsiveness to the broad range of temporal stimulus frequencies present in natural stimuli. Here we show that contrast detection threshold and temporal frequency response characteristics of ON and OFF retinal ganglion cells (RGCs), which are poor at eye opening, subsequently undergo maturation, improving RGC performance. Further, we find that depriving mice of visual experience from before birth by rearing them in the dark causes ON and OFF RGCs to have smaller receptive field centers but does not affect their contrast detection threshold development. The modest developmental increase in temporal frequency responsiveness of RGCs in mice reared on a normal light cycle was inhibited by dark rearing only in ON but not OFF RGCs. Thus, these RGC response characteristics are in many ways unaffected by the experience‐dependent changes to synaptic and spontaneous activity known to occur in the mouse retina in the two weeks after eye opening, but specific differences are apparent in the ON vs. OFF RGC populations. © 2014 Wiley Periodicals, Inc. Develop Neurobiol 74: 692–706, 2014     

Apoptosis in adult retinal ganglion cells after axotomy

Lesions to the mature mammalian central nervous system cause irreversible degeneration, in which neurons have been previously thought to be passive victims. In this study, axon-lesioned adult rat nerons are shown instead to actively degrade themselves through the process of apoptosis: a programmed type of cell death in which the cellular apparatus is actively involved in the degradation process. To investigate whether retinal ganglion cells of an adult mammal follow an apoptotic type of death when their axons are severed, DNA breaks in nuclei were labeled in situ, using a method that specifically incorporates biotinylated deoxynucleotides by exogenous terminal deoxynucleotidyl transferase on the 3′-OH ends of DNA. The active nature of the death mechanism was demonstrated by the reduction in biotin-labeled nuclei after administering the protein synthesis inhibitor cycloheximide. Our results suggest that retinal ganglion cells of the adult rat die through apoptosis when axotomized. This raises new possibilities in the treatment of CNS injuries, by the potential interruptibility of a program for neuronal death. 1994 John Wiley & Sons, Inc.     

Photoreceptor adaptation in intrinsically photosensitive retinal ganglion cells

A rare type of mammalian retinal ganglion cell (RGC) expresses the photopigment melanopsin and is a photoreceptor. These intrinsically photosensitive RGCs (ipRGCs) drive circadian-clock resetting, pupillary constriction, and other non-image-forming photic responses. Both the light responses of ipRGCs and the behaviors they drive are remarkably sustained, raising the possibility that, unlike rods and cones, ipRGCs do not adjust their sensitivity according to lighting conditions ("adaptation"). We found, to the contrary, that ipRGC sensitivity is plastic, strongly influenced by lighting history. When exposed to a constant, bright background, the background-evoked response decayed, and responses to superimposed flashes grew in amplitude, indicating light adaptation. After extinction of a light-adapting background, sensitivity recovered progressively in darkness, indicating dark adaptation. Because these adjustments in sensitivity persisted when synapses were blocked, they constitute "photoreceptor adaptation" rather than "network adaptation." Implications for the mechanisms generating various non-image-forming visual responses are discussed.     

A dynamic model of the neural network, which reproduces the signal of the ganglion cells

A functional model of the neural network was proposed, which reproduces the signal of a ganglion cell during the formation of receptive fields with the antagonistic center and the periphery.