Retinal Output Research Articles

Do chromatic responses in V1 match retinal output or perceptual performance?

Do chromatic responses in V1 match retinal output or perceptual performance?

Ruling out and ruling in neural codes

The subject of neural coding has generated much heated debate. A key issue is whether the nervous system uses coarse or fine coding strategies. Each has different advantages and disadvantages and, therefore, different implications for how the brain computes. For example, the advantage to coarse coding is that it's robust to fluctuations in spike arrival times. Downstream neurons don't have to keep track of the details of the spike trains. The disadvantage, though, is that individual cells can't carry much information, so downstream neurons have to pool signals across cells and/or across time to obtain enough information to represent the sensory world and guide behavior. In contrast, the advantage to fine coding is that individual cells can carry a great deal of information; however, downstream neurons have to resolve spike train structure. Here we address the question of what the neural code can and can't be, using the retinal output cells as the model system. We recorded from essentially all the retinal output cells an animal uses to solve a task, evaluated the cells‘ spike trains for as long as the animal evaluates them, and used optimal, i.e., Bayesian, decoding. This approach makes it possible to obtain an upper bound on the performance of codes and thus eliminate those that are not viable. Our results show that coarse coding strategies are insufficient; finer, more information-rich codes are necessary.

Visual hyperacuity despite fixational eye movements: a network model

Event Abstract Back to Event Visual hyperacuity despite fixational eye movements: a network model Ofer Mazor1*, Yoram Burak2 and Markus Meister2 1 Harvard University, United States 2 Harvard University, Center for Brain Science, United States The retina transmits a representation of the visual environment to the brain. Recent studies have focused on the many forms of information processing that occur within the retina. Yet much less is known about how the brain interprets the raw retinal output. Here we address this question by focusing on a visual acuity task with well-characterized behavioral performance. Human observers can resolve the separation of two parallel lines with a precision many times finer than the sampling resolution of the retina (Vernier hyperacuity). This occurs in the presence of constant involuntary body and eye movements that scan the visual image over the retina with a random trajectory. The image drifts faster than the output cells of the retina (retinal ganglion cells, RGCs) can respond, yet the visual system can extract high resolution stimulus information, in this case the line separation, from the RGC population response. What must the brain do to extract this information? Using a multi-electrode array, we measured the activity of a population of mouse RGCs in response to the presentation of two parallel lines. The effects of fixational movements were simulated by drifting the pair of lines, in unison, across the retina. We also simulated ganglion cell spike trains from the human eye, based on published response models from the primate retina. We then explored strategies for estimating the line separation from the RGC population response. An optimal decoder should treat the drift trajectory as a hidden variable to be estimated along with the stimulus. This approach results in a complex decoding algorithm with large memory requirements - an unlikely computation to attribute to the brain. As an alternative, we introduce a simpler decoding algorithm that does not track the drift trajectory but can still estimate the stimulus with high accuracy. This simplified decoder uses successive time windows of the RGC response to make independent estimates of stimulus likelihood that are accumulated to form a final estimate. We found that this scheme performs the Vernier task almost as well as a comparable decoder that does track the drift trajectory. Furthermore, its precision matches human performance: The algorithm can estimate line separation to less than one quarter of one RGC receptive field for presentations lasting only 100-200 ms. Finally, we propose a simple two-layer neural network, composed of coincidence detectors and temporal integrators, that implements this computation. We show that the network performs well when the implementation details - number of cells, connectivity, timescale of coincidence detection - are consistent with the known properties of visual cortex. Thus, by closely examining the output of the retina under natural conditions, we can make quantitative proposals about cortical processing that underlies human visual performance. Conference: Computational and Systems Neuroscience 2010, Salt Lake City, UT, United States, 25 Feb - 2 Mar, 2010. Presentation Type: Poster Presentation Topic: Poster session I Citation: Mazor O, Burak Y and Meister M (2010). Visual hyperacuity despite fixational eye movements: a network model. Front. Neurosci. Conference Abstract: Computational and Systems Neuroscience 2010. doi: 10.3389/conf.fnins.2010.03.00111 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 22 Feb 2010; Published Online: 22 Feb 2010. * Correspondence: Ofer Mazor, Harvard University, Paris, United States, omazor@fas.harvard.edu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Ofer Mazor Yoram Burak Markus Meister Google Ofer Mazor Yoram Burak Markus Meister Google Scholar Ofer Mazor Yoram Burak Markus Meister PubMed Ofer Mazor Yoram Burak Markus Meister Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Extreme synergy: Spatiotemporal correlations enable rapid image reconstruction from computer-generated spike trains

Over the brief time intervals available for processing retinal output, the number of spikes generated by individual ganglion cells can be quite variable. Here, two examples of extreme synergy are used to illustrate how realistic long-range spatiotemporal correlations can greatly improve the quality of retinal images reconstructed from computer-generated spike trains that are 25-400 ms in duration, approximately the time between saccadic eye movements. Firing probabilities were specified both explicitly: using time-varying waveforms consistent with stimulus-evoked oscillations measured experimentally, and implicitly: by superimposing realistic fixational eye movements on a biophysical model of primate outer retina. Synergistic encoding was investigated across arrays of model neurons up to 32 x 32 in extent, containing over 1 million pairwise correlations. The difficulty of estimating pairwise, spatiotemporal correlations on single trials from only a few events was overcome by using oscillatory, local multiunit activity to weight contributions from all spike pairs. Stimuli were reconstructed using either an independent rate code or the first principal component of the single-trial, pairwise correlation matrix. Spatiotemporal correlations mediated dramatic improvements in signal/noise without eliminating fine spatial detail, demonstrating how extreme synergy can support rapid image reconstruction using far fewer spikes than required by an independent rate code.

Interneuron Circuits Tune Inhibition in Retinal Bipolar Cells

While connections between inhibitory interneurons are common circuit elements, it has been difficult to define their signal processing roles because of the inability to activate these circuits using natural stimuli. We overcame this limitation by studying connections between inhibitory amacrine cells in the retina. These interneurons form spatially extensive inhibitory networks that shape signaling between bipolar cell relay neurons to ganglion cell output neurons. We investigated how amacrine cell networks modulate these retinal signals by selectively activating the networks with spatially defined light stimuli. The roles of amacrine cell networks were assessed by recording their inhibitory synaptic outputs in bipolar cells that suppress bipolar cell output to ganglion cells. When the amacrine cell network was activated by large light stimuli, the inhibitory connections between amacrine cells unexpectedly depressed bipolar cell inhibition. Bipolar cell inhibition elicited by smaller light stimuli or electrically activated feedback inhibition was not suppressed because these stimuli did not activate the connections between amacrine cells. Thus the activation of amacrine cell circuits with large light stimuli can shape the spatial sensitivity of the retina by limiting the spatial extent of bipolar cell inhibition. Because inner retinal inhibition contributes to ganglion cell surround inhibition, in part, by controlling input from bipolar cells, these connections may refine the spatial properties of the retinal output. This functional role of interneuron connections may be repeated throughout the CNS.

Crossover inhibition in the retina: circuitry that compensates for nonlinear rectifying synaptic transmission

In the mammalian retina, complementary ON and OFF visual streams are formed at the bipolar cell dendrites, then carried to amacrine and ganglion cells via nonlinear excitatory synapses from bipolar cells. Bipolar, amacrine and ganglion cells also receive a nonlinear inhibitory input from amacrine cells. The most common form of such inhibition crosses over from the opposite visual stream: Amacrine cells carry ON inhibition to the OFF cells and carry OFF inhibition to the ON cells (”crossover inhibition”). Although these synapses are predominantly nonlinear, linear signal processing is required for computing many properties of the visual world such as average intensity across a receptive field. Linear signaling is also necessary for maintaining the distinction between brightness and contrast. It has long been known that a subset of retinal outputs provide exactly this sort of linear representation of the world; we show here that rectifying (nonlinear) synaptic currents, when combined thorough crossover inhibition can generate this linear signaling. Using simple mathematical models we show that for a large set of cases, repeated rounds of synaptic rectification without crossover inhibition can destroy information carried by those synapses. A similar circuit motif is employed in the electronics industry to compensate for transistor nonlinearities in analog circuits.

Ruling out and ruling in neural codes

The subject of neural coding has generated much debate. A key issue is whether the nervous system uses coarse or fine coding. Each has different strengths and weaknesses and, therefore, different implications for how the brain computes. For example, the strength of coarse coding is that it is robust to fluctuations in spike arrival times; downstream neurons do not have to keep track of the details of the spike train. The weakness, though, is that individual cells cannot carry much information, so downstream neurons have to pool signals across cells and/or time to obtain enough information to represent the sensory world and guide behavior. In contrast, with fine coding, individual cells can carry much more information, but downstream neurons have to resolve spike train structure to obtain it. Here, we set up a strategy to determine which codes are viable, and we apply it to the retina as a model system. We recorded from all the retinal output cells an animal uses to solve a task, evaluated the cells' spike trains for as long as the animal evaluates them, and used optimal, i.e., Bayesian, decoding. This approach makes it possible to obtain an upper bound on the performance of codes and thus eliminate those that are insufficient, that is, those that cannot account for behavioral performance. Our results show that standard coarse coding (spike count coding) is insufficient; finer, more information-rich codes are necessary.

Melanopsin Phototransduction: Great Excitement over a Poor Catch

A small subset of retinal output cells express the photopigment melanopsin, rendering them intrinsically light-sensitive. Recent work quantifies, for the first time, fundamental properties of their light response.

Non-visually evoked activity of isthmo-optic neurons in awake, head-unrestrained quail

Changes in the internal state of the brain may modulate retinal function. In birds, most neurons in the isthmo-optic (IO) nucleus project their axons topographically into the contralateral retina, and activity in IO neurons enhances visual responses of retinal ganglion cells in the target retinal region. To elucidate the significance of this pathway, we recorded spikes of IO neurons in four awake Japanese quail using an implanted electrode assembly while recording unrestrained head movements. The IO neurons fired passively in response to visual stimuli in receptive fields and non-visually without visual stimuli or eye-head movements. Non-visually evoked activity was observed in the middle of eye-head fixation, as well as at about 200 ms before the onset of head saccades. Intensity of activity before onset of head saccades depended on the direction of motion of subsequent head saccades. Local retinal output may be enhanced by centrifugal signals before gaze shifts.

Functional Stability of Retinal Ganglion Cells after Degeneration-Induced Changes in Synaptic Input

Glutamate released from photoreceptors controls the activity and output of parallel pathways in the retina. When photoreceptors die because of degenerative diseases, surviving retinal networks are left without their major source of input, but little is known about how photoreceptor loss affects ongoing synaptic activity and retinal output. Here, we use patch-clamp recording and two-photon microscopy to investigate morphological and physiological properties of identified types of ON and OFF retinal ganglion cells (RGCs) in the adult (36-210 d old) retinal degeneration rd-1/rd-1 mouse. We find that strong rhythmic synaptic input drives ongoing oscillatory spike activity in both ON and OFF RGCs at a fundamental "beating" frequency of approximately 10 Hz. Despite this aberrant activity, ON and OFF cells maintain their characteristic dendritic stratification, intrinsic firing properties, including rebound firing in OFF cells, balance of synaptic excitation and inhibition, and dendritic calcium signaling. Thus, RGCs are inherently stable during degeneration-induced retinal activity.

Melanopsin cells are the principal conduits for rod–cone input to non-image-forming vision

Rod and cone photoreceptors detect light and relay this information through a multisynaptic pathway to the brain by means of retinal ganglion cells (RGCs). These retinal outputs support not only pattern vision but also non-image-forming (NIF) functions, which include circadian photoentrainment and pupillary light reflex (PLR). In mammals, NIF functions are mediated by rods, cones and the melanopsin-containing intrinsically photosensitive retinal ganglion cells (ipRGCs). Rod-cone photoreceptors and ipRGCs are complementary in signalling light intensity for NIF functions. The ipRGCs, in addition to being directly photosensitive, also receive synaptic input from rod-cone networks. To determine how the ipRGCs relay rod-cone light information for both image-forming and non-image-forming functions, we genetically ablated ipRGCs in mice. Here we show that animals lacking ipRGCs retain pattern vision but have deficits in both PLR and circadian photoentrainment that are more extensive than those observed in melanopsin knockouts. The defects in PLR and photoentrainment resemble those observed in animals that lack phototransduction in all three photoreceptor classes. These results indicate that light signals for irradiance detection are dissociated from pattern vision at the retinal ganglion cell level, and animals that cannot detect light for NIF functions are still capable of image formation.

The ON–OFF dichotomy in visual processing: From receptors to perception

Vision scientists long ago pointed to black and white as separate sensations and saw confirmation in the fact that in the absence of light, one perceives the visual field as gray against which the negative after-image of a bright light appeared blacker. The first recordings from optic nerve fibers in vertebrates revealed ON and OFF signals, later associated with separate streams, arising already at the synapse between receptors and bipolar cells. These can be identified anatomically and physiologically and remain distinct all the way to the lateral geniculate nucleus, whose fibers form the input to the primary visual cortex. The dichotomy has been probed by electroretinography and analyzed by means of pharmacological agents and dysfunction due to genetic causes. The bi- rather than a unidirectional nature of the retinal output has advantages in allowing small signals to remain prominent over a greater dynamic range. The two streams innervate cortical neurons in a push-pull manner, generating receptive fields with spatial sensitivity profiles featuring ON and OFF subregions. Manifestations of the dichotomy appear in a variety of simple visual discriminations where there are often profound threshold differences in patterns with same polarity as compared with mixed contrast-polarity components. But even at levels in which the spatial, contrast and color attributes have already been securely established and black and white elements participate equally, a categorical difference between blackness and whiteness of a percept persists. It is an opponency, akin to the ones in the color domain, derived from the original ON and OFF signals and subsequently bound with the other attributes to yield a feature's unitary percept.

Presynaptic inhibition differentially shapes transmission in distinct circuits in the mouse retina

Diverse retinal outputs are mediated by ganglion cells that receive excitatory input from distinct classes of bipolar cells (BCs). These classes of BCs separate visual signals into rod, ON and OFF cone pathways. Although BC signalling is a major determinant of the ganglion cell-mediated retinal output, it is not fully understood how light-evoked, presynaptic inhibition from amacrine cell inputs shapes BC outputs. To determine whether differences in presynaptic inhibition uniquely modulate BC synaptic output to specific ganglion cells, we assessed the inhibitory contributions of GABA(A), GABA(C) and glycine receptors across the BC pathways. Here we show that different proportions of GABA(A) and GABA(C) receptor-mediated inhibition determined the kinetics of GABAergic presynaptic inhibition across different BC classes. Large, slow GABA(C) and small, fast GABA(A) receptor-mediated inputs to rod BCs prolonged light-evoked inhibitory postsynaptic currents (L-IPSCs), while smaller GABA(C) and larger GABA(A) receptor-mediated contributions produced briefer L-IPSCs in ON and OFF cone BCs. Glycinergic inhibition also varied across BC class. In the rod-dominant conditions studied here, slow glycinergic inputs dominated L-IPSCs in OFF cone BCs, attributable to inputs from the rod pathway via AII amacrine cells, while rod and ON cone BCs received little and no glycinergic input, respectively. As these large glycinergic inputs come from rod signalling pathways, in cone-dominant conditions L-IPSCs in OFF cone bipolar cells will probably be dominated by GABA(A) receptor-mediated input. Thus, unique presynaptic receptor combinations mediate distinct forms of inhibition to selectively modulate BC outputs, enhancing the distinctions among parallel retinal signals.

Vesicular Glutamate Transporter 1 Is Required for Photoreceptor Synaptic Signaling But Not For Intrinsic Visual Functions

Glutamatergic neurotransmission requires vesicular glutamate transporters (VGLUTs) to sequester glutamate into synaptic vesicles. Generally, VGLUT1 and VGLUT2 isoforms show complementary expression in the CNS and retina. However, little is known about whether isoform-specific expression serves distinct pathways and physiological functions. Here, by examining visual functions in VGLUT1-null mice, we demonstrate that visual signaling from photoreceptors to retinal output neurons requires VGLUT1. However, photoentrainment and pupillary light responses are preserved. We provide evidence that melanopsin-containing, intrinsically photosensitive retinal ganglion cells (RGCs), signaling via VGLUT2 pathways, support these non-image-forming functions. We conclude that VGLUT1 is essential for transmitting visual signals from photoreceptors to second- and third-order neurons, but VGLUT1 is not necessary for intrinsic visual functions. Furthermore, melanopsin and VGLUT2 expression in a subset of RGCs immediately after birth strongly supports the idea that intrinsic vision can function well before rod- and cone-mediated signaling has matured.

Physics of psychophysics: optimal dynamic range of critical excitable networks

A recurrent idea in the study of complex systems is that optimal information processing is to be found near phase transitions [1-3]. However, this heuristic hypothesis has few (if any) concrete realizations where a standard and biologically relevant quantity is optimized at criticality. Here we give a clear example of such phenomenon: a network of excitable elements has its sensitivity and dynamic range maximized at the critical point of a nonequilibrium phase transition. Our results are compatible with the essential role of gap junctions in olfactory glomeruli and retinal ganglion cell output. Synchronization and global oscillations also emerge from the network dynamics. We propose that the main functional role of electrical coupling is to provide an enhancement of dynamic range, therefore allowing the coding of information spanning several orders of magnitude. The mechanism provides a microscopic neural basis for psychophysical laws.

Performance of ultra-high-density microelectrode arrays

Imaging the electrical output activity of biological cells is important to gain an understanding of how cell networks process information. This has implications for the understanding of brain processing, such as that performed by the retina in encoding the visual scene. The performance and electrical quality of a state-of-the-art high-density 519-microelectrode array, that recorded simultaneously from hundreds of live retinal output cells (ganglion cells) is reported on. The fabrication process for these devices has been optimised and their electrical characteristics examined. The electrode arrays typically exhibit an impedance of ∼200 kΩ at 1 kHz and the RMS noise of the whole recording system is 7 μV with a signal to noise ratio of 20:1. With a view to direct stimulation of retinal ganglion cells, a low impedance Z=300 kΩ iridium oxide interface capable of delivering large currents Q cap=4 mC/cm 2 to cells was also developed.

Effects of fixational eye movements on retinal ganglion cell responses: a modelling study

Visual response properties of retinal ganglion cells (GCs), the retinal output neurons, are shaped by numerous processes and interactions within the retina. In particular, amacrine cells are known to form microcircuits that affect GC responses in specific ways. So far, relatively little is known about the influence of retinal processing on GC responses under naturalistic viewing conditions, in particular in the presence of fixational eye movements. Here we used a detailed model of the mammalian retina to investigate possible effects of fixational eye movements on retinal GC activity. Populations of linear, sustained (parvocellular, PC) and nonlinear, transient (magnocellular, MC) GCs were simulated during fixation of a star-shaped stimulus, and two distinct effects were found: (1) a fading of complete wedges of the star and (2) an apparent splitting of stimulus lines. Both effects only occur in MC-cells, and an analysis shows that fading is caused by an expression of the aperture problem in retinal GCs, and the splitting effect by spatiotemporal nonlinearities in the MC-cell receptive field. These effects strongly resemble perceived instabilities during fixation of the same stimulus, and we propose that these illusions may have a retinal origin. We further suggest that in this case two parallel retinal streams send conflicting, rather than complementary, information to the higher visual system, which here leads to a dominant influence of the MC pathway. Similar situations may be common during natural vision, since retinal processing involves numerous nonlinearities.

A Survey of Architecture and Function of the Primary Visual Cortex (V1)

The largest visual area, known as the primary visual cortex or V1, has greatly contributed to the current understanding of mammalian and human visual pathways and their role in visual perception. The initial discovery of orientation-sensitive neurons in V1, arranged according to a retinotopic mapping, suggested an analogy to its function as a low-level feature analyser. Subsequent discoveries of phase, spatial frequency, color, ocular origin, and direction-of-motion-sensitive neurons, arranged into overlapping maps, further lent support to the view that it performs a rich decomposition, similar to signal processing transforms, of the retinal output. Like the other cortical areas, V1 has a laminar organization with specialization for input from the relayed retinal afferents, output to the higher visual areas, and the segregation of the magno (motion) and parvo (form) pathways. Spatially lateral connections that exist between neurons of similar and varying properties have also been proposed to give rise to a computation of a bottom-up saliency map in V1. We provide a review of the selectivity of neurons in V1, laminar specialization and analogies to signal processing techniques, a model of V1 saliency computation, and higher-area feedback that may mediate perception.

Independence of luminance and contrast in natural scenes and in the early visual system

The early visual system is endowed with adaptive mechanisms that rapidly adjust gain and integration time based on the local luminance (mean intensity) and contrast (standard deviation of intensity relative to the mean). Here we show that these mechanisms are matched to the statistics of the environment. First, we measured the joint distribution of luminance and contrast in patches selected from natural images and found that luminance and contrast were statistically independent of each other. This independence did not hold for artificial images with matched spectral characteristics. Second, we characterized the effects of the adaptive mechanisms in lateral geniculate nucleus (LGN), the direct recipient of retinal outputs. We found that luminance gain control had the same effect at all contrasts and that contrast gain control had the same effect at all mean luminances. Thus, the adaptive mechanisms for luminance and contrast operate independently, reflecting the very independence encountered in natural images.

Disruption and Recovery of Patterned Retinal Activity in the Absence of Acetylcholine

Many developing neural circuits generate synchronized bursting activity among neighboring neurons, a pattern thought to be important for sculpting precise neural connectivity. Network output remains relatively constant as the cellular and synaptic components of these immature circuits change during development, suggesting the presence of homeostatic mechanisms. In the retina, spontaneous waves of activity are present even before chemical synapse formation, needing gap junctions to propagate. However, as synaptogenesis proceeds, retinal waves become dependent on cholinergic neurotransmission, no longer requiring gap junctions. Later still in development, waves are driven by glutamatergic rather than cholinergic synapses. Here, we asked how retinal activity evolves in the absence of cholinergic transmission by using a conditional mutant in which the gene encoding choline acetyltransferase (ChAT), the sole synthetic enzyme for acetylcholine (ACh), was deleted from large retinal regions. ChAT-negative regions lacked retinal waves for the first few days after birth, but by postnatal day 5 (P5), ACh-independent waves propagated across these regions. Pharmacological analysis of the waves in ChAT knock-out regions revealed a requirement for gap junctions but not glutamate, suggesting that patterned activity may have emerged via restoration of previous gap-junctional networks. Similarly, in P5 wild-type retinas, spontaneous activity recovered after a few hours in nicotinic receptor antagonists, often as local patches of coactive cells but not waves. The rapid recovery of rhythmic spontaneous activity in the presence of cholinergic antagonists and the eventual emergence of waves in ChAT knock-out regions suggest that homeostatic mechanisms regulate retinal output during development.