Ординатура / Офтальмология / Английские материалы / The Retina and its Disorders_Besharse, Bok_2011

S M Wu, Baylor College of Medicine, Houston, TX, USA

ã 2010 Elsevier Ltd. All rights reserved.

Glossary

Center-surround antagonistic receptive field (CSARF) – A receptive field of a visual neuron whose light response to light falling on the center region is of the opposite polarity (or spike increment/decrement) to the response to light falling on the surrounding regions of the cell’s receptive field.

Depolarizing (ON-center) bipolar cell (DBC) – A bipolar cell exhibiting a depolarizing

voltage response to light falling on the center region of its receptive field and a hyperpolarizing voltage response to light on its receptive field surround region.

Distal and proximal retina – In a retinal cross section, the distal retina refers to the photoreceptor side of the retina and the proximal retina refers to the ganglion cell side.

Feedback synapse – A synapse made from a higher-order neuron to a lower-order neuron, such as synapses made from horizontal cells to cones and from amacrine cells to bipolar cell axon terminals.

Hyperpolarizing (OFF-center) bipolar cell (HBC) – A bipolar cell exhibiting a hyperpolarizing

voltage response to light falling on the center region of its receptive field and a depolarizing voltage response to light on its receptive field surround region.

Metabotropic glutamate receptor 6 (mGluR6) – A metabotropic glutamate receptor

coupled with a second-messenger cascade found in DBC dendrites. It results in closure of cation channels in DBCs when bound with glutamate or its agonist L-2-amino-4-phosphonobutyrate (LAP4). Rod bipolar cell – A bipolar cell whose light-evoked cation current is mediated primarily by rod synaptic inputs. In mammals, only rod DBCs have been identified.

Bipolar cells (BCs) are second-order neurons in the retina whose somas are located in the distal half of the inner nuclear layer (INL) (except for the displaced BCs found in some species whose somas are located in the outer nuclear layer (ONL)). BC dendrites branch in the outer plexiform layer (OPL) and make synaptic contacts with rod spherules, cone pedicles, and horizontal cell (HC) dendrites. Each BC bears an axon projecting to

the inner plexiform layer (IPL) with terminals ramifying in different patterns at different sublaminae of the IPL. Based on their rod/cone contacts and axon terminal ramification patterns, BCs have been classified morphologically into several types. In mammals, one type of rod BC and 9 to 10 types of cone BCs have been identified (Figure 1). In fish, small BCs make synaptic contacts exclusively with cones and large BCs make contacts with both rods and cones, and in turtle, 11 morphological types of BCs have been found, with some contacting only cones and others contacting only rods. BCs in amphibian retinas contact both rods and cones, but some are clearly rod dominated where others are cone dominated.

BCs are the first neurons along the visual pathway that exhibit the center-surround antagonistic receptive field (CSARF) organization, the basic code for spatial information processing in the visual system. Light falling directly on the BC receptive field center region elicits voltage responses of the opposite polarity to the responses elicited by light falling on the surrounding regions of the BC’s receptive field. BCs may be ON center with OFF surrounds (named ON-center BCs or depolarizing BCs (DBCs)), or OFF center with ON surrounds (named OFF-center BCs or hyperpolarizing BCs (HBCs)). The center input of BCs is mediated by rod and cone photoreceptors, which make chemical synapses on BC dendrites. BC receptive field centers are often found to be larger than their dendritic fields, suggesting that these cells may be electrically coupled. The surround input to BCs is mediated by interneurons that carry signals laterally from the surround region to the central region of the BCs’ receptive field. These interneurons include HCs in the outer retina and amacrine cells (ACs) in the inner retina. HCs mediate BC surround responses through HC–cone–BC feedback synaptic pathways and/or HC–BC feed-forward (electrical or chemical) synapses, whereas ACs mediate BC surrounds through chemical synapses made on BC axon terminals in the IPL.

By using the whole-cell or microelectrode recording techniques in conjunction with fluorescent dye filling method, it has been shown that light response characteristics of various types of BCs are closely correlated with their axon terminal morphology. For example, it has been found in many species that axon terminals of DBCs ramify in the proximal half (sublamina B) of the IPL, whereas those of the HBCs ramify in the distal half (sublamina A) of the IPL. Axon terminals of rod BCs in mammalian retinas end near the proximal margin of the IPL, and axon terminals of cone BCs ramify in more central regions of the IPL. This agrees with the patterns of BC axon terminal stratification

in the salamander: axon terminals of rod-dominated BCs ramify at the two margins of the IPL, whereas those of cone-dominated BCs ramify at central regions of the IPL. Additionally, despite the anatomical finding that mammalian rod and cone BCs make segregated synaptic contacts with rods and cones, it has been recently shown that some mammalian BCs exhibit mixed rod/cone responses similar to most BCs in lower vertebrates. Furthermore, although rod HBCs were not identified by earlier mammalian anatomical studies, recent physiological evidence suggests that they may exist at least in some mammals.

Based on studies of BC physiological properties in various species, it is reasonable to propose that vertebrate retinas have six major functional types of BCs: the rod (or rod dominated), cone (or cone dominated), and mixed (rod/cone) depolarizing and hyperpolarizing BCs (DBCR,

DBCC, DBCM, HBCR, HBCC, and HBCM). Each carries a characteristic set of light response attributes and projects them to the inner retina through axons that terminate at segregated regions (strata) of the IPL. Such stratum-by- stratum projection of light response attributes is exemplified by a large-scale voltage-clamp study of the salamander BC responses and morphology. This study reveals several rules for the function–morphology relationships of retinal BCs:

(1) Cells with axon terminals in strata 1–5 (sublamina A) are HBCs (with outward light-evoked cation currents (DIC)) and those in strata 6–10 (sublamina B) are DBCs (with inward DIC). This agrees with the sublamina A/B rule observed in many vertebrate species (see, e.g., Figure 1, in which the IPL is divided into five sublaminae instead of 10). (2) Cells with axon terminals in strata 1, 2, and 10 are rod dominated, those in strata 4–8 are cone dominated, and

those in strata 3 and 9 exhibit mixed rod/cone dominance.

(3)Light-evoked DIC at light onset in rod-dominated HBCs and DBCs are sustained, that of the cone-dominated HBCs exhibit a smaller sustained outward current followed by a transient inward current at the light offset, and that of the cone-dominated DBCs exhibit a sustained inward current followed by a small transient off outward current.

(4)DICl (light-evoked chloride currents) in rod-dominated BCs are sustained ON currents, whereas those in cone-

dominated BCs are transient ON–OFF currents. DICl in all BCs are outward, and thus they are synergistic to DIC in HBCs and antagonistic to DIC in DBCs. (5) BCs with axon terminals stratified in multiple strata exhibit combined light

response properties of the narrowly monostratified cells in the same strata. (6) BCs with pyramidally branching or globular axons exhibit light response properties very similar to those of narrowly monostratified cells whose axon terminals stratified in the same stratum as the axon terminal endings of the pyramidally branching or globular cells.

In addition to projecting signals to various strata of the IPL, where ACs and ganglion cells (GCs) gather their inputs, BCs with various light response attributes have different CSARF organizations. Figure 2 shows the morphology, patterns of dye coupling, light responses, CSARF properties, and membrane resistance changes associated with the center and surround voltage responses of the six functional types of BCs (HBCR, HBCM, HBCC, DBCC, DBCM, and DBCR) in the tiger salamander retina. These results suggest that the center and surround responses of various types of BCs in the retina are mediated by heterogeneous synaptic circuitry. The BC receptive field center diameters (RFCDs) vary with the relative rod/cone input: RFCD is larger in DBCs with stronger cone input, and it is larger in HBCs with stronger rod input. RFCD also correlates with the degree of dye coupling: BCs with larger RFCD are more strongly dye coupled with neighboring cells of the same type, suggesting that BC–BC coupling significantly contributes to the BC receptive field center.

BC center inputs are mediated by glutamatergic synapses. In darkness, glutamate is released from rod and cone photoreceptors, and it closes cation channels in DBCs and opens cation channels in HBCs. Postsynaptic responses of DBCs are mediated by metabotropic (metabotropic glutamate receptor 6 (mGluR6), L-2-amino-4- phosphonobutyrate (L-AP4)-sensitive) receptors coupled with a second-messenger cascade. In fish, the cone-to-DBC synaptic signal is mediated by a glutamate-activated chloride current that is suppressed by light and thus results in a membrane depolarization. Postsynaptic responses of HBCs are mediated by ionotropic receptors, and recent studies have shown that different subtypes of ionotropic glutamate receptors may be used by different types of HBCs in mediating rod/cone and transient/sustained signals.

Membrane resistance measurements in Figure 2(e) demonstrate that the center responses of all HBCs are

associated with a resistance increase and the center responses of all DBCs are accompanied with a resistance decrease. This is consistent with the notion that glutamate released from rods and cones in darkness opens a-amino- 3-hydroxyl-5-methyl-4-isoxazole-propionate (AMPA)/ kainate receptor-mediated cation channels in HBCs and closes mGluR6-receptor-mediated cation channels in DBCs. Center light stimuli hyperpolarize rods and cones, suppress glutamate release, and result in a resistance increase (close ion channels) in HBCs and a resistance decrease (open ion channels) in DBCs.

Figure 3 is a schematic representation of the possible and unlikely synaptic pathways underlying surround inputs of various types of BCs, based on the surround response polarity and accompanying resistance changes shown in Figure 2. These results suggest that the HC–cone–BC feedback synapses may contribute to the surround responses of all six types of BCs. The negative HC–cone feedback synapses (pathway I) partially turn off the center responses by depolarizing the cones, as the membrane resistance changes associated with surround responses of all BCs are opposite to the resistance changes associated with center responses (Figure 2(e)).

Although all BCs share a common surround response pathway (the HC–cone–BC feedback pathway), various types of BCs use different HC and AC synaptic inputs to mediate their surround responses. It is unlikely, for example, that HBC surround responses are directly mediated by chemical synaptic inputs from hyperpolarizing lateral neurons, such as HCs and ACOFFs, because of resistance change mismatch, and thus HBCs may only receive surround inputs from HC–cone–HBC and ACON–HBC synapses. On the other hand, resistance analysis suggests that DBC surround responses can be mediated by HC–cone–DBC, HC–DBC and ACOFF–DBC chemical synapses, but not the ACON–DBC synapses. Moreover, dye coupling (Figure 2(a)) results indicate that DBCCs receive additional surround inputs from wide-field HCs through electrical synapses. Despite the heterogeneity, it is interesting to point out that an ON/OFF crossover inhibition rule applies here: cells with OFF (hyperpolarizing) responses (HCs and ACOFFs) mediate surround inhibitory inputs to ON cells (DBCs); and cells with ON (depolarizing) responses (ACONs) mediate surround inhibitory inputs to OFF cells (HBCs). ON/OFF crossover inhibition from ACs to GCs have been reported in the salamander and mammalian retinas, and the data shown in Figures 2 and 3 suggest that it may be a general rule for lateral inhibition in the visual system.

HCs mediate BC surround responses through the feedback synaptic pathway (HC!cone!BC) and/or the feed-forward synapses (HC!BC). Three synaptic mechanisms have been proposed for the HC feedback actions on cones. The first is that HCs release an inhibitory neurotransmitter (gamma aminobutyric acid (GABA) in several

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species) in darkness that opens chloride channels in cones, and surround light hyperpolarizes the HCs, suppresses feedback transmitter release, depolarizes the cones, depolarizes the HBCs, and hyperpolarizes the DBCs. The second mechanism is that surround light hyperpolarizes HCs, resulting in an outward current through hemichannels in their dendrites near the cones, charging the cone membrane and modulating calcium currents in cones, increasing their calcium-dependent glutamate release which depolarizes

the HBCs and hyperpolarizes the DBCs. The third mechanism is that surround-induced HC hyperpolarization elevates the pH in the HC–cone synaptic cleft, leading to an increase of calcium current in cones and a higher rate of glutamate release which depolarizes the HBCs and hyperpolarizes the DBCs. It is possible that different species under different conditions favor different feedback synaptic mechanisms, and/or different types of HC–cone synapses in the same animal may use one or more of

these three HC–cone feedback mechanisms. This idea is supported by a recent study demonstrating that the responses of salamander GCs to dim surround stimuli are sensitive to GABA blockers and those to bright surround stimuli are sensitive to carbenoxolone, a gap-junction/ hemichannel blocker.

The HC–BC feed-forward pathway requires a signpreserving HC–DBC synapse and a sign-inverting HC– HBC synapse. Studies from salamander retina suggest that HC!DBC feed-forward synapses may be functional. However, application of GABA on BC dendrites in Co2þ Ringer’s does not elicit any response, indicating that if feed-forward synapses are chemical, the neurotransmitter is not GABA. Histochemical evidence suggests that only about 50–60% of the HCs in the salamander retina are GABAergic, and the identity of neurotransmitter(s) in the rest of the HCs is unknown (but unlikely to be glycine). As illustrated in the salamander (Figure 2(a)) and the rabbit retinas, subpopulations of BCs are dye coupled with HCs, raising the possibility that HC–BC electrical coupling may be involved in mediating the HC–BC feedforward synapses for DBC surround responses.

The AC–BC contribution to BC surround responses are mediated by GABAergic or glycinergic synapses. GABA receptors on ACs and GCs are largely GABAA, and those on BC axon terminals are largely GABAC. Glycine receptors have been localized in ACs, GCs, BC dendrites, and BC axon terminals. These receptors localized in the IPL are postsynaptic to glycinergic ACs, while those in the OPL are postsynaptic to glycinergic interplexiform cells. In the Xenopus retina, GABA suppresses the surround responses of the DBCs, but only slightly reduces the surround of the HBCs, and glycine suppresses the surround responses of both DBCs and HBCs. In the tiger salamander, one study shows that GABA reduces the surround responses of a subpopulation of HBCs, but another report reveals that application of picrotoxin and strychnine does not affect the surround responses of either DBCs or HBCs. Recent studies in the primate retina indicate that the HC feedback signal to cones as well as to the surround responses of GCs are not sensitive to GABAergic or glycinergic agents, but sensitive to carbenoxolone, suggesting that the surround responses in GCs are mainly mediated by HC actions on BCs in the outer retina, not by GABAergic or glycinergic AC actions in the inner retina. The reasons for these different GABA/ glycine actions on surround responses are unclear. As illustrated in Figures 2 and 3, surround responses of different functional types of BCs in the salamander retina are mediated by different combinations of synaptic circuitries: HC!cone (GABA/hemichannel/proton) !BC, HC!BC

(chemical/gap junction) and AC!BC (GABA/glycine). It is conceivable that the surround responses of different BCs/GCs from different animals under different conditions are mediated by different combinations of surround synaptic pathways, and thus they are sensitive to different synaptic blockers. The wide variation of synaptic circuitries underlying surround responses of various functional types of BCs allows for flexibility in function-specific modulation of BC/GC receptive fields. Hence different features of spatial and contrast information, such as rod/cone and ON/OFF signals, can be differentially modulated by different lighting and adaptation conditions.

Acknowledgements

This work was supported by grants from NIH (EY 04446), NIH Vision Core (EY 02520), the Retina Research Foundation (Houston), and the Research to Prevent Blindness, Inc.

Further Reading

Boycott, B. and Wassle, H. (1999). Parallel processing in the mammalian retina: The Proctor lecture. Investigative Ophthalmology and Visual Science 40: 1313–1327.

Dowling, J. E. (1987). The Retina, an Approachable Part of the Brain. Cambridge, MA: Harvard University Press.

Ghosh, K. K., Bujan, S., Haverkamp, S., Feigenspan, A., and Wassle, H. (2004). Types of bipolar cells in the mouse retina. Journal of Comparative Neurology 469: 70–82.

Kamermans, M. and Fahrenfort, I. (2004). Ephaptic interactions within a chemical synapse: Hemichannel-mediated ephaptic inhibition in the retina. Current Opinion in Neurobiology 14: 531–541.

Kolb, H., Ripps, H., and Wu, S. M. (2001). Concepts and challenges in retinal biology: A tribute to John E. Dowling. Progress in Brain Research 131: 23–29.

Pang, J. J., Gao, F., and Wu, S. M. (2004). Stratum-by-stratum projection of light response attributes by retinal bipolar cells of Ambystoma. Journal of Physiology 558: 249–262.

Sterling, P. and Demb, J. B. (2004). Retina. In: Sherpherd, G. M. (ed.)

The Synaptic Organization of the Brain, 5th edn., pp. 217–269. Oxford: Oxford University Press.

Wu, S. M. (1992). Feedback connections and operation of outer plexiform layer of the retina. Current Opinion in Neurobiology 2(4): 462–468.

Wu, S. M. (1994). Synaptic transmission in the outer retina. Annual Review of Physiology 56: 141–168.

Wu, S. M. (2003). Intracellular light responses and synaptic organization of the vertebrate retina. In: Kaufman, P. L. and Mosby, A. A. (eds.) Adler’s Physiology of the Eye, ch. 15, pp. 422–438. St. Louis, MO: Elsevier.

Wu, S. M. (2009). Bipolar cells. In: Squire, L., Albright, T., Bloom, F., Gage, F., and Spitzer, N. (eds.) Encyclopedia of Neuroscience, vol. 8, pp. 181–186.

Zhang, A. J. and Wu, S. M. (2009). Receptive fields of retinal bipolar cells are mediated by heterogeneous synaptic circuitry. Journal of Neuroscience 29(3): 789–797.

Glossary

Adaptation – The change in response properties of a neuron, which enhance the ability to encode the immediate environment.

Contrast – The percent deviation in light intensity from the mean intensity (as defined over some period of time and region of visual angle).

Filter – The concept of a neuron’s receptive field as a tuning function that is matched to certain spatial or temporal frequencies.

Receptive field – The area of space and period of recent time over which changes in light input can modulate the response of a neuron.

Threshold – The lowest contrast level of a spatiotemporal pattern where a neuron can respond to the stimulus reliably (physiology) or where an observer can perceive the stimulus reliably (psychophysics).

Contrast Processing and Adaptation

Humans can see and behave across a wide range of lighting conditions. For example, one can navigate through the woods on a starry night, where each rod photoreceptor absorbs a photon only about once per minute; and yet one can also navigate across the beach on a cloudless day, where cone photoreceptors absorb thousands of photons per second. The mean luminance between these extreme examples can differ by 100-million-fold. This wide range of intensities poses a computational problem for the retina, because a ganglion cell can fire only about 20 action potentials (spikes) in the 100 ms integration time of a postsynaptic neuron. Thus, the ganglion cell must continually adjust its sensitivity so that the wide range of light levels ( 8 log units) can be encoded with the narrow range of output signals ( 1–2 log units).

To deal with the mismatch between input and output, the retina adjusts its sensitivity depending on the mean intensity; and through mechanisms of light adaptation. These mechanisms are varied, and they include: the switch between rod photoreceptors (for night vision) and cone photoreceptors (for day vision); intrinsic properties of each receptor type that alter sensitivity depending on mean intensity; and postreceptoral mechanisms

within the retinal circuitry. The apparent purpose of light adaptation is to adjust the ganglion cell’s response to report, not the absolute intensity, but rather the contrast, or the percentage deviations from the mean intensity.

The contrast of a visual stimulus is a more robust property than the absolute intensity. To illustrate this point, consider a simple example, where an observer gazes at a bird on a background of leaves. Assume that the bird reflects 50% more light toward the observer’s eye compared to the leaves (and ignore color in this example). Now imagine that the light reflected to the eye is reduced either by the observer’s action (i.e., putting on a pair of sun glasses) or by a change in the light source reflecting off the objects (i.e., a cloud passes overhead, obscuring the sunlight). In either case, the light reflected into the eye is reduced 10-fold or more. However the relative reflectance is unchanged: the bird still reflects 50% more light than the leaves. Hence, it follows that the retina (and most of the visual system) is designed to encode contrast or the relative reflectance of objects within the same scene: the relative reflectance of objects represents a stable property of natural scenes, whereas absolute reflectance does not. Physiological measurements of retinal ganglion cells confirm this idea, showing that responses to a given contrast level are relatively constant over several orders of mean light level.

The Spatial Receptive Field

A ganglion cell calculates contrast over a specific retinal region known as its spatial receptive field. There are approximately 20 different types of ganglion cells whose axons form the optic nerve. These types encode different aspects of visual information, and some are highly selective for features such as wavelength of light or the direction of moving objects. Here, the focus is on the several types of ganglion cell that have a relatively conventional receptive field that can be described with an excitatory center region and an inhibitory surround region.

A ganglion cell’s excitatory center corresponds to the retinal region aligned with its dendritic tree. Thus, the photoreceptors within the span of the ganglion cell’s dendritic tree would all contribute to driving the excitatory center region. These photoreceptors synapse onto both ONand OFF-types of bipolar cell, which express distinct glutamate receptors at their dendrites (metabotropic or

ionotropic, respectively) and therefore have opposite responses to light: ON-type cells are excited by light increments, whereas OFF-type cells are excited by light decrements. Most ganglion cell types collect synapses from either ON-type bipolar cells or OFF-type bipolar cells and then inherit the ONor OFF-center property from these presynaptic bipolar cells.

A ganglion cell’s inhibitory surround corresponds to the retinal region that extends beyond the dendritic tree. Thus, an OFF-center cell that is excited by light decrements over the tree is inhibited by light decrements over the surround region, beyond the tree. The center and surround combine to report the relative contrast over space. The center is commonly stronger than the surround, so that a large object covering both the center and surround will drive a center response (e.g., a large bright object will provide some excitation to an ONcenter cell). For some cell types (e.g., the X/beta-type ganglion cell of the cat or the midget/parvocellularprojecting ganglion cell of the monkey), the center and surround combine in an approximately linear fashion. Thus, the response to center plus surround stimulation can be predicted reasonably well by summing the separate responses to center and surround measured individually. For other cell types (e.g., the Y/alpha-type of the cat) there is a nonlinear combination of center and surround regions. For these nonlinear receptive fields, the presynaptic bipolar cells may be described by relatively linear receptive fields; the major nonlinearity of the ganglion cell receptive field may arise at the level of the synaptic output of the bipolar cells as they converge onto the ganglion cell. In general, a ganglion cell’s excitatory

center is driven by the presynaptic bipolar cells, whereas the surround arises at two levels: the horizontal cells in the outer retina and the amacrine cells in the inner retina.

The Temporal Receptive Field

In addition to the two-dimensional spatial component, a ganglion cell’s receptive field also has a temporal component. In many cases, ganglion cell responses can be described with a temporal filter that represents the best stimulus for driving a response. Thus, if the time course of the stimulus contrast over the past 250 ms matches the filter, the response will be maximal. Ganglion cell firing rates can increase above the baseline rate much more than they can decrease below the baseline rate. In extreme cases, some ganglion cell types have essentially no background rate. Thus, a substantial nonlinearity in the ganglion cell’s response is the threshold for firing action potentials (also known as rectification). The temporal filter concept must thus be combined with the concept of an output nonlinearity to predict a cell’s response to a contrast modulation presented over time (Figure 1). A common method for modeling such responses is the linear–nonlinear model. The temporal filter can be measured by presenting a randomly flickering stimulus (commonly called white noise). For example, a spot over the receptive field center could have its intensity modulated over time. The response in the ganglion cell’s firing rate could then be correlated with the stimulus to generate the filter. A separate step is used to relate the filtered output (a linear prediction of the temporal response) to

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Receptive Field Properties Explain

Contrast Sensitivity Functions

For cell types with linear receptive fields, the contrast sensitivity function can be explained by the receptive field properties described over space or time. For example, Figure 2(a) shows a temporal filter and its relationship to sinusoidal modulation of luminance of different temporal frequencies. The biphasic filter is best matched to the 6-Hz frequency and would thus predict a strong response to this frequency. At the lower frequency (1 Hz), the two phases of the filter are stimulated simultaneously and would therefore cancel to some extent; at the high frequency (12 Hz), the two phases of the filter are not stimulated strongly by the modulations and would thus, likewise, yield suboptimal responses. The response as a function of temporal frequency is plotted as the solid line in Figure 2(b). This line represents the cell’s temporal tuning function (or temporal contrast sensitivity function).

The same concept of filtering can be applied to the spatial domain (Figure 2(c2) shows a one-dimensional cut through a circular center–surround receptive field). In this case, sinusoidal modulation of light (over space;

described in cycles per degree of visual angle) is presented to a center–surround receptive field. The center–surround filter best matches the 8 cycles deg–1 stimulus, whereas lower or higher frequencies are suboptimal. The tuning function (solid line in Figure 2(c3)) describes the spatial contrast sensitivity function.

Temporal and spatial contrast sensitivity functions can also be used to describe threshold measurements in human psychophysical experiments. In this case, the spatial or temporal filter is that of the entire visual system. A human is presented with brief stimuli of various spatial or temporal frequency contrast modulation and a threshold is determined (i.e., the lowest contrast at which the pattern can be reliably discriminated from the mean luminance). The perceptual contrast sensitivity function resembles the sensitivity functions of individual ganglion cells, at least superficially. It is difficult to determine how perceptual and neural sensitivity functions are related to one another, because perception depends on the output of many different types of ganglion cell as well as further processing at later stages in the brain.

Disrupting Specific Retinal Pathways

Alters Perceptual Contrast Sensitivity in

Selective Ways

The retinal ganglion cell axons exit the eye and travel to several different nuclei in the brain, including targets in the brainstem, midbrain, and thalamus. The pathway for

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conscious vision is believed to arise from the retinal projection to the thalamus, where relay cells then project retinal signals to the visual cortex. About a dozen or more different types of ganglion cell project to the lateral geniculate nucleus of the thalamus (LGN); and LGN relay cells provide a major input to primary visual cortex.

In primates, the LGN is organized into six prominent layers. The top four parvocellular (P) layers contain small cell bodies (ON and OFF midget/P cells), whereas the bottom two magnocellular (M) layers contain large cell bodies (ON and OFF parasol/M cells). Both P and M layers are separated by the eye where the ganglion cells originate; thus there are two P layers and one M layer that each receives input from the contralateral eye, whereas the other layers each receives input from the ipsilateral eye. The ON and OFF M and P cells thus account for four of the 13 types that project to the LGN. The other nine ganglion cell types apparently project to relay cells that either reside in the layers between the M and P layers (the intercalated layers) or intermingle with the M and P cell bodies. These pathways are referred to collectively as koniocellular (K) cells.

To understand the role of the different ganglion cell types in perceptual contrast sensitivity, the M or P layers of the LGN were lesioned. We now understand that these lesion experiments were not entirely selective; the lesions to the P layers, for example, must have also affected some of the other (less numerous) K pathway ganglion cell types that project to the dorsal region of the LGN. Nevertheless, the M and P cells are the most numerous cell types that project to the LGN, and lesions to either the M or P layers yielded distinct deficits on contrast sensitivity measurements. Thus, these deficits are probably explained in large part by the lesions of either M or P cell types.

Lesions to the M layers reduced the monkey’s sensitivity for high temporal frequency and low spatial frequency stimuli, whereas lesions to the P layers reduced sensitivity for low-temporal-frequency and high-spatial-frequency stimuli. Thus, the different ends of the monkey’s contrast sensitivity function depended most heavily on distinct ganglion cell classes in the retina. There are two clear conclusions from these studies: there was no single cell type that could explain perceptual sensitivity for all possible patterns; and specific spatial or temporal domains of perceptual sensitivity depended most heavily on particular cell types.

Physical Limits to Contrast Sensitivity

Under optimal conditions, humans can detect small spots with contrasts of 1–3%. The most sensitive ganglion cell

types can also detect small spots with contrasts of 1–3%. Thus, there may be certain conditions where perceptual thresholds are driven by a small number of ganglion cells and there may be relatively little information lost between the retina and the brain. However, there is a loss between the contrast threshold that could (theoretically) be computed at the level of photon absorptions by the photoreceptors and the threshold measured in the ganglion cell. Recent computational analysis suggests that, under certain conditions, this loss may be a factor of 10–20.

The ability to detect contrast depends on the statistics of photon arrival and the statistical properties of various cellular processes. Photon arrival follows Poisson statistics, where the mean and the variance are equal. For example, consider a case where a ganglion cell integrates signals over 20 photoreceptors across the retina and over a 100-ms integration time and where the mean rate of photoisomerizations (i.e., absorbed photons) is 50 isomerizations (R*) per photoreceptor per second (i.e., 5 R*/ photoreceptor/integration time). In this case, the mean R* rate over the spatial/temporal integration (20 100 5) is 10 000 and the variance (across multiple trials) would be the same. Thus, the SD (or noise level) would be the square root or 100 R*. The signal-to-noise ratio (mean/ SD per integration time) would then be 10 000/100 = 100. Therefore, the cell in question would have difficulty detecting a difference of less than 1/100 (i.e., SD/mean) or 1% deviation from the mean level (i.e., 1% contrast). The contrast threshold would be worse (i.e., higher) when the mean luminance is lower, the number of integrated photoreceptors is fewer or the temporal integration time decreases.

Similar limitations on contrast sensitivity must arise within the neural circuit of the retina. For example, the release of neurotransmitter at retinal synapses probably obeys Poisson statistics similar to the case of photon arrival. Thus, the ability of the synapses to transfer information at low contrast depends on the release rates at these synapses and the number of synapses that are integrated by a given neuron. For example, the threshold of a cell would be best (i.e., lowest) in the presence of high release rates and a large number of integrated synapses (i.e., high degree of synaptic convergence within the circuitry). Thus, several physiological factors will place neural limits on the contrast threshold of retinal ganglion cells.

See also: Information Processing: Ganglion Cells; Morphology of Interneurons: Amacrine Cells; Morphology of Interneurons: Horizontal Cells; Phototransduction: Adaptation in Cones; Phototransduction: Adaptation in Rods; Phototransduction: Phototransduction in Cones; Phototransduction: Phototransduction in Rods; Retinal Pigment Epithelium: Cytokine Modulation of Epithelial Physiology.