987 resultados para DISPLACED GANGLION CELL


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PURPOSE: To introduce techniques for deriving a map that relates visual field locations to optic nerve head (ONH) sectors and to use the techniques to derive a map relating Medmont perimetric data to data from the Heidelberg Retinal Tomograph. METHODS: Spearman correlation coefficients were calculated relating each visual field location (Medmont M700) to rim area and volume measures for 10 degrees ONH sectors (HRT III software) for 57 participants: 34 with glaucoma, 18 with suspected glaucoma, and 5 with ocular hypertension. Correlations were constrained to be anatomically plausible with a computational model of the axon growth of retinal ganglion cells (Algorithm GROW). GROW generated a map relating field locations to sectors of the ONH. The sector with the maximum statistically significant (P < 0.05) correlation coefficient within 40 degrees of the angle predicted by GROW for each location was computed. Before correlation, both functional and structural data were normalized by either normative data or the fellow eye in each participant. RESULTS: The model of axon growth produced a 24-2 map that is qualitatively similar to existing maps derived from empiric data. When GROW was used in conjunction with normative data, 31% of field locations exhibited a statistically significant relationship. This significance increased to 67% (z-test, z = 4.84; P < 0.001) when both field and rim area data were normalized with the fellow eye. CONCLUSIONS: A computational model of axon growth and normalizing data by the fellow eye can assist in constructing an anatomically plausible map connecting visual field data and sectoral ONH data.

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Recently discovered intrinsically photosensitive melanopsin retinal ganglion cells contribute to the maintenance of pupil diameter, recovery and post-illumination components of the pupillary light reflex and provide the primary environmental light input to the suprachiasmatic nucleus for photoentrainment of the circadian rhythm. This review summarises recent progress in understanding intrinsically photosensitive ganglion cell histology and physiological properties in the context of their contribution to the pupillary and circadian functions and introduces a clinical framework for using the pupillary light reflex to evaluate inner retinal (intrinsically photosensitive melanopsin ganglion cell) and outer retinal (rod and cone photoreceptor) function in the detection of retinal eye disease.

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Intrinsically photosensitive retinal ganglion cells (ipRGCs) in the eye transmit the environmental light level, projecting to the suprachiasmatic nucleus (SCN) (Berson, Dunn & Takao, 2002; Hattar, Liao, Takao, Berson & Yau, 2002), the location of the circadian biological clock, and the olivary pretectal nucleus (OPN) of the pretectum, the start of the pupil reflex pathway (Hattar, Liao, Takao, Berson & Yau, 2002; Dacey, Liao, Peterson, Robinson, Smith, Pokorny, Yau & Gamlin, 2005). The SCN synchronizes the circadian rhythm, a cycle of biological processes coordinated to the solar day, and drives the sleep/wake cycle by controlling the release of melatonin from the pineal gland (Claustrat, Brun & Chazot, 2005). Encoded photic input from ipRGCs to the OPN also contributes to the pupil light reflex (PLR), the constriction and recovery of the pupil in response to light. IpRGCs control the post-illumination component of the PLR, the partial pupil constriction maintained for > 30 sec after a stimulus offset (Gamlin, McDougal, Pokorny, Smith, Yau & Dacey, 2007; Kankipati, Girkin & Gamlin, 2010; Markwell, Feigl & Zele, 2010). It is unknown if intrinsic ipRGC and cone-mediated inputs to ipRGCs show circadian variation in their photon-counting activity under constant illumination. If ipRGCs demonstrate circadian variation of the pupil response under constant illumination in vivo, when in vitro ipRGC activity does not (Weng, Wong & Berson, 2009), this would support central control of the ipRGC circadian activity. A preliminary experiment was conducted to determine the spectral sensitivity of the ipRGC post-illumination pupil response under the experimental conditions, confirming the successful isolation of the ipRGC response (Gamlin, et al., 2007) for the circadian experiment. In this main experiment, we demonstrate that ipRGC photon-counting activity has a circadian rhythm under constant experimental conditions, while direct rod and cone contributions to the PLR do not. Intrinsic ipRGC contributions to the post-illumination pupil response decreased 2:46 h prior to melatonin onset for our group model, with the peak ipRGC attenuation occurring 1:25 h after melatonin onset. Our results suggest a centrally controlled evening decrease in ipRGC activity, independent of environmental light, which is temporally synchronized (demonstrates a temporal phase-advanced relationship) to the SCN mediated release of melatonin. In the future the ipRGC post-illumination pupil response could be developed as a fast, non-invasive measure of circadian rhythm. This study establishes a basis for future investigation of cortical feedback mechanisms that modulate ipRGC activity.

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Purpose: IpRGCs mediate non-image forming functions including photoentrainment and the pupil light reflex (PLR). Temporal summation increases visual sensitivity and decreases temporal resolution for image forming vision, but the summation properties of nonimage forming vision are unknown. We investigated the temporal summation of inner (ipRGC) and outer (rod/cone) retinal inputs to the PLR. Method: The consensual PLR of the left eye was measured in six participants with normal vision using a Maxwellian view infrared pupillometer. Temporal summation was investigated using a double-pulse protocol (100 ms stimulus pairs; 0–1024 ms inter-stimulus interval, ISI) presented to the dilated fellow right eye (Tropicamide 1%). Stimulus lights (blue λmax = 460 nm; red λmax = 638 nm) biased activity to inneror outer retinal inputs to non-image forming vision. Temporal summation was measured suprathreshold (15.2 log photons.cm−2.s−1 at the cornea) and subthreshold (11.4 log photons.cm−2.s−1 at the cornea). Results: RM-ANOVAs showed the suprathreshold and subthreshold 6 second post illumination pupil response (PIPR: expressed as percentage baseline diameter) did not significantly vary for red or blue stimuli (p > .05). The PIPR for a subthreshold red 16 ms double-pulse control condition did not significantly differ with ISI (p > .05). The maximum constriction amplitude for red and blue 100 ms double- pulse stimuli did not significantly vary with ISI (p > .05). Conclusion: The non-significant changes in suprathreshold PIPR and subthreshold maximum pupil constriction indicate that inner retinal ipRGC inputs and outer retinal photoreceptor inputs to the PLR do not show temporal summation. The results suggest a fundamental difference between the temporal summation characteristics of image forming and non-image forming vision.

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Purpose Melanopsin-expressing retinal ganglion cells (mRGCs) have non-image forming functions including mediation of the pupil light reflex (PLR). There is limited knowledge about mRGC function in retinal disease. Initial retinal changes in age-related macular degeneration (AMD) occur in the paracentral region where mRGCs have their highest density, making them vulnerable during disease onset. In this cross-sectional clinical study, we measured the PLR to determine if mRGC function is altered in early stages of macular degeneration. Methods Pupil responses were measured in 8 early AMD patients (AREDS 2001 classification; mean age 72.6 ± 7.2 years, 5M, and 3F) and 12 healthy control participants (mean age 66.6 ± 6.1 years, 8M and 4F) using a custom-built Maxwellian-view pupillometer. Stimuli were 0.5 Hz sinewaves (10 s duration, 35.6° diameter) of short wavelength light (464nm, blue; retinal irradiance = 14.5 log quanta.cm-2.s-1) to produce high melanopsin excitation and of long wavelength light (638nm, red; retinal irradiance = 14.9 log quanta.cm-2.s-1), to bias activation to outer retina and provide a control. Baseline pupil diameter was determined during a 10 s pre-stimulus period. The post illumination pupil response (PIPR) was recorded for 40 s. The 6 s PIPR and maximum pupil constriction were expressed as percentage baseline (M ± SD). Results The blue PIPR was significantly less sustained (p<0.01) in the early AMD group (75.49 ± 7.88%) than the control group (58.28 ± 9.05%). The red PIPR was not significantly different (p>0.05) between the early AMD (84.79 ± 4.03%) and control groups (82.01 ± 5.86%). Maximum constriction amplitude in the early AMD group for blue (43.67 ± 6.35%) and red (48.64 ± 6.49%) stimuli were not significantly different to the control group for blue (39.94 ± 3.66%) and red (44.98 ± 3.15%) stimuli (p>0.05). Conclusions These results are suggestive of inner retinal mRGC deficits in early AMD. This non-invasive, objective measure of pupil responses may provide a new method for quantifying mRGC function and monitoring AMD progression.

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This article describes a nonlinear model of neural processing in the vertebrate retina, comprising model photoreceptors, model push-pull bipolar cells, and model ganglion cells. Previous analyses and simulations have shown that with a choice of parameters that mimics beta cells, the model exhibits X-like linear spatial summation (null response to contrast-reversed gratings) in spite of photoreceptor nonlinearities; on the other hand, a choice of parameters that mimics alpha cells leads to Y-like frequency doubling. This article extends the previous work by showing that the model can replicate qualitatively many of the original findings on X and Y cells with a fixed choice of parameters. The results generally support the hypothesis that X and Y cells can be seen as functional variants of a single neural circuit. The model also suggests that both depolarizing and hyperpolarizing bipolar cells converge onto both ON and OFF ganglion cell types. The push-pull connectivity enables ganglion cells to remain sensitive to deviations about the mean output level of nonlinear photoreceptors. These and other properties of the push-pull model are discussed in the general context of retinal processing of spatiotemporal luminance patterns.

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PURPOSE

To introduce techniques for deriving a map that relates visual field locations to optic nerve head (ONH) sectors and to use the techniques to derive a map relating Medmont perimetric data to data from the Heidelberg Retinal Tomograph.

METHODS
Spearman correlation coefficients were calculated relating each visual field location (Medmont M700) to rim area and volume measures for 10° ONH sectors (HRT III software) for 57 participants: 34 with glaucoma, 18 with suspected glaucoma, and 5 with ocular hypertension. Correlations were constrained to be anatomically plausible with a computational model of the axon growth of retinal ganglion cells (Algorithm GROW). GROW generated a map relating field locations to sectors of the ONH. The sector with the maximum statistically significant (P < 0.05) correlation coefficient within 40° of the angle predicted by GROW for each location was computed. Before correlation, both functional and structural data were normalized by either normative data or the fellow eye in each participant.

RESULTS
The model of axon growth produced a 24-2 map that is qualitatively similar to existing maps derived from empiric data. When GROW was used in conjunction with normative data, 31% of field locations exhibited a statistically significant relationship. This significance increased to 67% (z-test, z = 4.84; P < 0.001) when both field and rim area data were normalized with the fellow eye.

CONCLUSIONS
A computational model of axon growth and normalizing data by the fellow eye can assist in constructing an anatomically plausible map connecting visual field data and sectoral ONH data.

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The turtle retina has been extensively used for the study of chromatic processing mechanisms. Color opponency has been previously investigated with trichromatic paradigms, but behavioral studies show that the turtle has ail ultraviolet (UV) channel and a tetrachromatic visual system. Our laboratory has been working ill the characterization of neuronal responses in the retina of vertebrates using stimuli in the UV-visible range of the electromagnetic spectrum. In the present investigation, we recorded color-opponent responses from turtle amacrine and ganglion cells to UV and visible stimuli and extended our previous results that UV color-opponency is present at the level of the inner nuclear layer. We recorded from 181 neurons, 36 of which were spectrally opponent. Among these, there were 10 amacrine (5%), and 26 ganglion cells (15%). Morphological identification of color-opponent neurons was possible for two ganglion cell classes (G17 and G22) and two amacrine cell classes (A22 and A23b). There was a variety of cell response types and a potential for complex processing of chromatic stimuli, with intensity- and wavelength-dependent response components. Ten types of color opponency were found in ganglion cells and by adding previous results from our laboratory, 12 types of opponent responses have been found. The majority of the ganglion cells were R+UVBG- and RG+UVB-color-opponents but there were other less frequent types of chromatic opponency. This study confirms the participation of a UV channel in the processing of color opponency in the turtle inner retina and shows that the turtle visual system has the retinal mechanisms to allow many possible chromatic combinations.

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The mechanisms regulating retinal ganglion cell (RGC) development are crucial for retinogenesis and for the establishment of normal vision. However, these mechanisms are only vaguely understood. RGCs are the first neuronal lineage to segregate from pluripotent progenitors in the developing retina. As output neurons, RGCs display developmental features very distinct from those of the other retinal cell types. To better understand RGC development, we have previously constructed a gene regulatory network featuring a hierarchical cascade of transcription factors that ultimately controls the expression of downstream effector genes. This has revealed the existence of a Pou domain transcription factor, Pou4f2, that occupies a key node in the RGC gene regulatory network and that is essential for RGC differentiation. However, little is known about the genes that connect upstream regulatory genes, such as Pou4f2 with downstream effector genes responsible for RGC differentiation. The purpose of this study was to characterize the retinal function of eomesodermin (Eomes), a T-box transcription factor with previously unsuspected roles in retinogenesis. We show that Eomes is expressed in developing RGCs and is a mediator of Pou4f2 function. Pou4f2 directly regulates Eomes expression through a cis-regulatory element within a conserved retinal enhancer. Deleting Eomes in the developing retina causes defects reminiscent of those in Pou4f2(-/-) retinas. Moreover, myelin ensheathment in the optic nerves of Eomes(-/-) embryos is severely impaired, suggesting that Eomes regulates this process. We conclude that Eomes is a crucial regulator positioned immediately downstream of Pou4f2 and is required for RGC differentiation and optic nerve development.

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We describe experiments on behaving rats with electrodes implanted on the cornea, in the optic chiasm, and on the visual cortex; in addition, two red light-emitting diodes (LED) are permanently attached to the skull over the left eye. Recordings timelocked to the LED flashes reveal both the local events at each electrode site and the orderly transfer of visual information from retina to cortex. The major finding is that every stimulus, regardless of its luminance, duration, or the state of retinal light adaptation, elicits an optic nerve volley with a latency of about 10 ms and a duration of about 300 ms. This phenomenon has not been reported previously, so far as we are aware. We conclude that the retina, which originates from the forebrain of the developing embryo, behaves like a typical brain structure: it translates, within a few hundred milliseconds, the chemical information in each pattern of bleached photoreceptors into a corresponding pattern of ganglion cell neuronal information that leaves via the optic nerve. The attributes of each rat ganglion cell appear to include whether the retinal neuropile calls on it to leave after a stimulus and, if so when, within a 300-ms poststimulus epoch. The resulting retinal analysis of the scene, on arrival at the cortical level, is presumed to participate importantly in the creation of visual perceptual experiences.

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During retinogenesis, the Xenopus basic helix–loop–helix transcription factor Xath5 has been shown to promote a ganglion cell fate. In the developing mouse and chicken retinas, gene targeting and overexpression studies have demonstrated critical roles for the Brn3 POU domain transcription factor genes in the promotion of ganglion cell differentiation. However, the genetic relationship between Ath5 and Brn3 genes is unknown. To understand the genetic regulatory network(s) that controls retinal ganglion cell development, we analyzed the relationship between Ath5 and Brn3 genes by using a gain-of-function approach in the chicken embryo. We found that during retinogenesis, the chicken Ath5 gene (Cath5) is expressed in retinal progenitors and in differentiating ganglion cells but is absent in terminally differentiated ganglion cells. Forced expression of both Cath5 and the mouse Ath5 gene (Math5) in retinal progenitors activates the expression of cBrn3c following central-to-peripheral and temporal-to-nasal gradients. As a result, similar to the Xath5 protein, both Cath5 and Math5 proteins have the ability to promote the development of ganglion cells. Moreover, we found that forced expression of all three Brn3 genes also can stimulate the expression of cBrn3c. We further found that Ath5 and Brn3 proteins are capable of transactivating a Brn3b promoter. Thus, these data suggest that the expression of cBrn3c in the chicken and Brn3b in the mouse is initially activated by Ath5 factors in newly generated ganglion cells and later maintained by a feedback loop of Brn3 factors in the differentiated ganglion cells.

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Recordings were obtained from the visual system of rats as they cycled normally between waking (W), slow-wave sleep (SWS), and rapid eye movement (REM) sleep. Responses to flashes delivered by a light-emitting diode attached permanently to the skull were recorded through electrodes implanted on the cornea, in the chiasm, and on the cortex. The chiasm response reveals the temporal order in which the activated ganglion cell population exits the eyeball; as reported, this triphasic event is invariably short in latency (5–10 ms) and around 300 ms in duration, called the histogram. Here we describe the differences in the histograms recorded during W, SWS, and REM. SWS histograms are always larger than W histograms, and an REM histogram can resemble either. In other words, the optic nerve response to a given stimulus is labile; its configuration depends on whether the rat is asleep or awake. We link this physiological information with the anatomical fact that the brain dorsal raphe region, which is known to have a sleep regulatory role, sends fibers to the rat retina and receives fibers from it. At the cortical electrode, the visual cortical response amplitudes also vary, being largest during SWS. This well known phenomenon often is explained by changes taking place at the thalamic level. However, in the rat, the labile cortical response covaries with the labile optic nerve response, which suggests the cortical response enhancement during SWS is determined more by what happens in the retina than by what happens in the thalamus.