Synchronized retinal oscillations encode essential information for escape behavior in frogs

The mechanism of human color vision and potential implanted devices for artificial color vision

Vision plays a major role in perceiving external stimuli and information in our daily lives. The neural mechanism of color vision is complicated, involving the co-ordinated functions of a variety of cells, such as retinal cells and lateral geniculate nucleus cells, as well as multiple levels of the visual cortex. In this work, we reviewed the history of experimental and theoretical studies on this issue, from the fundamental functions of the individual cells of the visual system to the coding in the transmission of neural signals and sophisticated brain processes at different levels. We discuss various hypotheses, models, and theories related to the color vision mechanism and present some suggestions for developing novel implanted devices that may help restore color vision in visually impaired people or introduce artificial color vision to those who need it.

Doppler detection triggers instantaneous escape behavior in scanning bats

Animals must instantaneously escape from predators for survival, which requires quick detection of approaching threats. Although the neural mechanisms underlying the perception of looming objects have been extensively studied in the visual system, little is known about their auditory counterparts. Echolocating bats use their auditory senses to perceive not only the soundscape, but also the physical environment through active sensing. Although object movement induces both echo delay changes and Doppler shifts, the actual information required to perceive movement has been unclear. Herein, we addressed this question by playing back phantom echoes mimicking an approaching target to horseshoe bats and found that they relied only on Doppler shifts. This suggests that the bats do not perceive object motion in the spatiotemporal dimension (i.e., positional variation), as in vision, but rather take advantage of acoustic sensing by directly detecting velocity, thereby enabling them to respond instantaneously to approaching threats.

IRIS: Integrated Retinal Functionality in Image Sensors

Neuromorphic image sensors draw inspiration from the biological retina to implement visual computations in electronic hardware. Gain control in phototransduction and temporal differentiation at the first retinal synapse inspired the first generation of neuromorphic sensors, but processing in downstream retinal circuits, much of which has been discovered in the past decade, has not been implemented in image sensor technology. We present a technology-circuit co-design solution that implements two motion computations-object motion sensitivity and looming detection-at the retina's output that could have wide applications for vision-based decision-making in dynamic environments. Our simulations on Globalfoundries 22 nm technology node show that the proposed retina-inspired circuits can be fabricated on image sensing platforms in existing semiconductor foundries by taking advantage of the recent advances in semiconductor chip stacking technology. Integrated Retinal Functionality in Image Sensors (IRIS) technology could drive advances in machine vision applications that demand energy-efficient and low-bandwidth real-time decision-making.

On the Functional Role of Gamma Synchronization in the Retinogeniculate System of the Cat

Fast gamma oscillations, generated within the retina, and transmitted to the cortex via the lateral geniculate nucleus (LGN), are thought to carry information about stimulus size and continuity. This hypothesis relies mainly on studies conducted under anesthesia and the extent to which it holds under more naturalistic conditions remains unclear. Using multielectrode recordings of spiking activity in the retina and the LGN of both male and female cats, we show that visually driven gamma oscillations are absent for awake states and are highly dependent on halothane (or isoflurane). Under ketamine, responses were nonoscillatory, as in the awake condition. Response entrainment to the monitor refresh was commonly observed up to 120 Hz and was superseded by the gamma oscillatory responses induced by halothane. Given that retinal gamma oscillations are contingent on halothane anesthesia and absent in the awake cat, such oscillations should be considered artifactual, thus playing no functional role in vision.SIGNIFICANCE STATEMENT Gamma rhythms have been proposed to be a robust encoding mechanism critical for visual processing. In the retinogeniculate system of the cat, many studies have shown gamma oscillations associated with responses to static stimuli. Here, we extend these observations to dynamic stimuli. An unexpected finding was that retinal gamma responses strongly depend on halothane concentration levels and are absent in the awake cat. These results weaken the notion that gamma in the retina is relevant for vision. Notably, retinal gamma shares many of the properties of cortical gamma. In this respect, oscillations induced by halothane in the retina may serve as a valuable preparation, although artificial, for studying oscillatory dynamics.

Neural synchrony in cortical networks: mechanisms and implications for neural information processing and coding

Synchronization of neuronal discharges on the millisecond scale has long been recognized as a prevalent and functionally important attribute of neural activity. In this article, I review classical concepts and corresponding evidence of the mechanisms that govern the synchronization of distributed discharges in cortical networks and relate those mechanisms to their possible roles in coding and cognitive functions. To accommodate the need for a selective, directed synchronization of cells, I propose that synchronous firing of distributed neurons is a natural consequence of spike-timing-dependent plasticity (STDP) that associates cells repetitively receiving temporally coherent input: the “synchrony through synaptic plasticity” hypothesis. Neurons that are excited by a repeated sequence of synaptic inputs may learn to selectively respond to the onset of this sequence through synaptic plasticity. Multiple neurons receiving coherent input could thus actively synchronize their firing by learning to selectively respond at corresponding temporal positions. The hypothesis makes several predictions: first, the position of the cells in the network, as well as the source of their input signals, would be irrelevant as long as their input signals arrive simultaneously; second, repeating discharge patterns should get compressed until all or some part of the signals are synchronized; and third, this compression should be accompanied by a sparsening of signals. In this way, selective groups of cells could emerge that would respond to some recurring event with synchronous firing. Such a learned response pattern could further be modulated by synchronous network oscillations that provide a dynamic, flexible context for the synaptic integration of distributed signals. I conclude by suggesting experimental approaches to further test this new hypothesis.

Information synergy in the anticipatory dynamics of a retina

Anticipation is the phenomenon in which the response of a system is predictive of the stimulation. The encoding of stochastic light intensity (x) into spikes is investigated in an experiment with retinas from bullfrogs to understand the mechanism of anticipation of a retina. Partial information decomposition of the mutual information between the spike rates and the joint state {x,x[over ̇]} is found to be consistent with the encoding by the linear combination of x and x[over ̇] where x[over ̇] is the rate of change of x. This spike rate encoding form indicates that a retina is capable of anticipation based on the synergistic information generation between x and x[over ̇]. Our results suggest that illusions such as the anticipation studied here during retinal perception can originate from the recombination of information extracted in the retinal network.

Deficiency of the neurodevelopmental disorder-associated gene Cyfip2 alters the retinal ganglion cell properties and visual acuity

Intellectual disability (ID) is a neurodevelopmental disorder affecting approximately 0.5–3% of the population in the developed world. Individuals with ID exhibit deficits in intelligence, impaired adaptive behavior and often visual impairments. Cytoplasmic fragile X mental retardation 1 (FMR1)-interacting protein 2 (CYFIP2) is an interacting partner of the FMR protein, whose loss results in fragile X syndrome, the most common inherited cause of ID. Recently, CYFIP2 variants have been found in patients with early-onset epileptic encephalopathy, developmental delay and ID. Such individuals often exhibit visual impairments; however, the underlying mechanism is poorly understood. In the present study, we investigated the role of Cyfip2 in retinal and visual functions by generating and analyzing Cyfip2 conditional knockout (CKO) mice. While we found no major differences in the layer structures and cell compositions between the control and Cyfip2 CKO retinas, a subset of genes associated with the transporter and channel activities was differentially expressed in Cyfip2 CKO retinas than in the controls. Multi-electrode array recordings showed more sustained and stronger responses to positive flashes of the ON ganglion cells in the Cyfip2 CKO retina than in the controls, although electroretinogram analysis revealed that Cyfip2 deficiency unaffected the photoreceptor and ON bipolar cell functions. Furthermore, analysis of initial and late phase optokinetic responses demonstrated that Cyfip2 deficiency impaired the visual function at the organismal level. Together, our results shed light on the molecular mechanism underlying the visual impairments observed in individuals with CYFIP2 variants and, more generally, in patients with neurodevelopmental disorders, including ID.

Spatially displaced excitation contributes to the encoding of interrupted motion by a retinal direction-selective circuit

Spatially distributed excitation and inhibition collectively shape a visual neuron's receptive field (RF) properties. In the direction-selective circuit of the mammalian retina, the role of strong null-direction inhibition of On-Off direction-selective ganglion cells (On-Off DSGCs) on their direction selectivity is well-studied. However, how excitatory inputs influence the On-Off DSGC's visual response is underexplored. Here, we report that On-Off DSGCs have a spatially displaced glutamatergic receptive field along their horizontal preferred-null motion axes. This displaced receptive field contributes to DSGC null-direction spiking during interrupted motion trajectories. Theoretical analyses indicate that population responses during interrupted motion may help populations of On-Off DSGCs signal the spatial location of moving objects in complex, naturalistic visual environments. Our study highlights that the direction-selective circuit exploits separate sets of mechanisms under different stimulus conditions, and these mechanisms may help encode multiple visual features.

A Measure of Concurrent Neural Firing Activity Based on Mutual Information

Multiple methods have been developed in an attempt to quantify stimulus-induced neural coordination and to understand internal coordination of neuronal responses by examining the synchronization phenomena in neural discharge patterns. In this work we propose a novel approach to estimate the degree of concomitant firing between two neural units, based on a modified form of mutual information (MI) applied to a two-state representation of the firing activity. The binary profile of each single unit unfolds its discharge activity in time by decomposition into the state of neural quiescence/low activity and state of moderate firing/bursting. Then, the MI computed between the two binary streams is normalized by their minimum entropy and is taken as positive or negative depending on the prevalence of identical or opposite concomitant states. The resulting measure, denoted as Concurrent Firing Index based on MI (CFI_MI), relies on a single input parameter and is otherwise assumption-free and symmetric. Exhaustive validation was carried out through controlled experiments in three simulation scenarios, showing that CFI_MI is independent on firing rate and recording duration, and is sensitive to correlated and anti-correlated firing patterns. Its ability to detect non-correlated activity was assessed using ad-hoc surrogate data. Moreover, the evaluation of CFI_MI on experimental recordings of spiking activity in retinal ganglion cells brought insights into the changes of neural synchrony over time. The proposed measure offers a novel perspective on the estimation of neural synchrony, providing information on the co-occurrence of firing states in the two analyzed trains over longer temporal scales compared to existing measures.

OFF-transient alpha RGCs mediate looming triggered innate defensive response

Animals respond to visual threats, such as a looming object, with innate defensive behaviors. Here, we report that a specific type of retinal ganglion cell (RGC), the OFF-transient alpha RGC, is critical for the detection of looming objects. We identified Kcnip2 as its molecular marker. The activity of the Kcnip2-expressing RGCs encodes the size of the looming object. Ablation or suppression of these RGCs abolished or severely impaired the escape and freezing behaviors of mice in response to a looming object, while activation of their somas in the retina, or their axon terminals in the superior colliculus, triggered immediate escape behavior. Our results link the activity of a single type of RGC to visually triggered innate defensive behaviors and underscore that ethologically significant visual information is encoded by a labeled line strategy as early as in the retina.

Anticipation and negative group delay in a retina

The mechanism of negative group delay (NGD) is used to understand the anticipatory capability of a retina. Experiments with retinas from bullfrogs are performed to compare with the predictions of the NGD model. In particular, whole field stochastic stimulations with various autocorrelation times are used to probe anticipatory responses from the retina. We find that the NGD model can reproduce essential features of experimental observations characterized by the cross correlations between the stimulation and the retinal responses. Experiments with dark light pulse stimulations further support the NGD mechanism, with the retina producing time-advanced pulse responses. However, no time-advanced pulse responses are produced by bright pulses. Counterintuitively, the NGD model shows that it is the delay in the system which gives rise to anticipation because of the negative feedback adaptation mechanism.

A frog's eye view: Foundational revelations and future promises

From the mid-19th century until the 1980's, frogs and toads provided important research models for many fundamental questions in visual neuroscience. In the present century, they have been largely neglected. Yet they are animals with highly developed vision, a complex retina built on the basic vertebrate plan, an accessible brain, and an experimentally useful behavioural repertoire. They also offer a rich diversity of species and life histories on a reasonably restricted physiological and evolutionary background. We suggest that important insights may be gained from revisiting classical questions in anurans with state-of-the-art methods. At the input to the system, this especially concerns the molecular evolution of visual pigments and photoreceptors, at the output, the relation between retinal signals, brain processing and behavioural decision-making.

A single retinal circuit model for multiple computations

Vision is dependent on extracting intricate features of the visual information from the outside world, and complex visual computations begin to take place as soon as at the retinal level. In multiple studies on salamander retinas, the responses of a subtype of retinal ganglion cells, i.e., fast/biphasic-OFF ganglion cells, have been shown to be able to realize multiple functions, such as the segregation of a moving object from its background, motion anticipation, and rapid encoding of the spatial features of a new visual scene. For each of these visual functions, modeling approaches using extended linear-nonlinear cascade models suggest specific preceding retinal circuitries merging onto fast/biphasic-OFF ganglion cells. However, whether multiple visual functions can be accommodated together in a certain retinal circuitry and how specific mechanisms for each visual function interact with each other have not been investigated. Here, we propose a physiologically consistent, detailed computational model of the retinal circuit based on the spatiotemporal dynamics and connections of each class of retinal neurons to implement object motion sensitivity, motion anticipation, and rapid coding in the same circuit. Simulations suggest that multiple computations can be accommodated together, thereby implying that the fast/biphasic-OFF ganglion cell has potential to output a train of spikes carrying multiple pieces of information on distinct features of the visual stimuli.

Rapid depth perception in hunting archerfish. II. An analysis of potential cues

Based on the initial movement of falling prey, hunting archerfish select a C-start that turns them right to where their prey is going to land and lends the speed to arrive simultaneously with prey. Our companion study suggested that the information sampled in less than 100 ms also includes the initial height of falling prey. Here, we examine which cues the fish might be using to gauge height so quickly. First, we show that binocular cues are not required: C-starts that either could or could not have used binocular information were equally fast and precise. Next, we explored whether the fish were using simplifying assumptions about the absolute size of their prey or its distance from a structured background. However, experiments with unexpected changes from the standard conditions failed to cause any errors. We then tested the hypothesis that the fish might infer depth from accommodation or from cues related to blurring in the image of their falling prey. However, the fish also determined the height of 'fake flies' correctly, even though their image could never be focused and their combined size and degree of blurring should have misled the fish. Our findings are not compatible with the view that archerfish use a flexible combination of cues. They also do not support the view that height is gauged relative to structures in the vicinity of starting prey. We suggest that these fish use an elaborate analysis of looming to rapidly gauge initial height.

Gamma and infra-slow oscillations shape neuronal firing in the rat subcortical visual system

KEY POINTS

Neuronal oscillations observed in sensory systems are physiological carriers of information about stimulus features. Rhythm in the infra-slow range, originating from the retina, was previously found in the firing of subcortical visual system nuclei involved in both image and non-image forming functions. The present study shows that the firing of neurons in the lateral geniculate nucleus is also governed by gamma oscillation (∼35 Hz) time-locked to high phase of infra-slow rhythm that codes the intensity of transient light stimulation. We show that both physiological rhythms are synchronized within and between ipsilateral nuclei of the subcortical visual system and are dependent on retinal activity. The present study shows that neurophysiological oscillations characterized by various frequencies not only coexist in the subcortical visual system, but also are subjected to complex interference and synchronization processes.

ABSTRACT

The physiological function of rhythmic firing in the neuronal networks of sensory systems has been linked with information coding. Also, neuronal oscillations in different frequency bands often change as a signature of brain state or sensory processing. Infra-slow oscillation (ISO) in the neuronal firing dependent on the retinal network has been described previously in the structures of the subcortical visual system. In the present study, we show for the first time that firing of ISO neurons in the lateral geniculate nucleus is also characterized by a harmonic discharge pattern (i.e. action potentials are separated by the intervals governed by fundamental frequency in the gamma range: ∼35 Hz). A similar phenomenon was recently described in the suprachiasmatic nuclei of the hypothalamus: the master biological clock. We found that both gamma and ISO rhythms were synchronized within and between ipsilateral nuclei of the subcortical visual system and were dependent on the retinal activity of the contralateral eye. These oscillatory patterns were differentially influenced by transient and prolonged light stimulation with respect to both frequency change direction and sustainability. The results of the present study show that the firing pattern of neurons in the subcortical visual system is shaped by oscillations from infra-slow and gamma frequency bands that are plausibly generated by the retinal network. Additionally, the results demonstrate that both rhythms are not a distinctive feature of image or non-image forming visual systems but, instead, they comprise two channels carrying distinctive properties of photic information.

[Electrophysiological Analysis of Retinal Oscillation in Normal and Degenerated Retina]

　The vertebrate retina is one of the most sophisticated parts of the nervous system. It comprises five classes of neurons and one glial type cell. During development, but prior to a vertebrate's eyes opening, retinal circuits are refined by endogenous neural activity. Characteristic patterns of activity, including oscillatory activity, occur in the normal retina, whereas distinctive alternative patterns occur in abnormal retinas. In this paper, we first describe the electrophysiological and spike sorting methods used to study retinal oscillations. Next, we describe the mechanisms and functions of oscillation in the normal retina. Finally, we characterize the distinctive oscillations and abnormal spontaneous activities in the degenerative retina.

Dynamic Information Encoding With Dynamic Synapses in Neural Adaptation

Adaptation refers to the general phenomenon that the neural system dynamically adjusts its response property according to the statistics of external inputs. In response to an invariant stimulation, neuronal firing rates first increase dramatically and then decrease gradually to a low level close to the background activity. This prompts a question: during the adaptation, how does the neural system encode the repeated stimulation with attenuated firing rates? It has been suggested that the neural system may employ a dynamical encoding strategy during the adaptation, the information of stimulus is mainly encoded by the strong independent spiking of neurons at the early stage of the adaptation; while the weak but synchronized activity of neurons encodes the stimulus information at the later stage of the adaptation. The previous study demonstrated that short-term facilitation (STF) of electrical synapses, which increases the synchronization between neurons, can provide a mechanism to realize dynamical encoding. In the present study, we further explore whether short-term plasticity (STP) of chemical synapses, an interaction form more common than electrical synapse in the cortex, can support dynamical encoding. We build a large-size network with chemical synapses between neurons. Notably, facilitation of chemical synapses only enhances pair-wise correlations between neurons mildly, but its effect on increasing synchronization of the network can be significant, and hence it can serve as a mechanism to convey the stimulus information. To read-out the stimulus information, we consider that a downstream neuron receives balanced excitatory and inhibitory inputs from the network, so that the downstream neuron only responds to synchronized firings of the network. Therefore, the response of the downstream neuron indicates the presence of the repeated stimulation. Overall, our study demonstrates that STP of chemical synapse can serve as a mechanism to realize dynamical neural encoding. We believe that our study shed lights on the mechanism underlying the efficient neural information processing via adaptation.

The morphological characterization of orientation-biased displaced large-field ganglion cells in the central part of goldfish retina

The vertebrate retina has about 30 subtypes of ganglion cells. Each ganglion cell receives synaptic inputs from specific types of bipolar and amacrine cells ramifying at the same depth of the inner plexiform layer (IPL), each of which is thought to process a specific aspect of visual information. Here, we identified one type of displaced ganglion cell in the goldfish retina which had a large and elongated dendritic field. As a population, all of these ganglion cells were oriented in the horizontal axis and perpendicular to the dorsal-ventral axis of the goldfish eye in the central part of retina. This ganglion cell has previously been classified as Type 1.2. However, the circuit elements which synapse with this ganglion cell are not yet characterized. We found that this displaced ganglion cell was directly tracer-coupled only with homologous ganglion cells at sites containing Cx35/36 puncta. We further illustrated that the processes of dopaminergic neurons often terminated next to intersections between processes of ganglion cells, close to where dopamine D1 receptors were localized. Finally, we showed that Mb1 ON bipolar cells had ribbon synapses in the axonal processes passing through the IPL and made ectopic synapses with this displaced ganglion cell that stratified into stratum 1 of the IPL. These results suggest that the displaced ganglion cell may synapse with both Mb1 cells using ectopic ribbon synapses and OFF cone bipolar cells with regular ribbon synapses in the IPL to function in both scotopic and photopic light conditions.

Progress in automating patch clamp cellular physiology

Patch clamp electrophysiology has transformed research in the life sciences over the last few decades. Since their inception, automatic patch clamp platforms have evolved considerably, demonstrating the capability to address both voltage- and ligand-gated channels, and showing the potential to play a pivotal role in drug discovery and biomedical research. Unfortunately, the cell suspension assays to which early systems were limited cannot recreate biologically relevant cellular environments, or capture higher order aspects of synaptic physiology and network dynamics. In vivo patch clamp electrophysiology has the potential to yield more biologically complex information and be especially useful in reverse engineering the molecular and cellular mechanisms of single-cell and network neuronal computation, while capturing important aspects of human disease mechanisms and possible therapeutic strategies. Unfortunately, it is a difficult procedure with a steep learning curve, which has restricted dissemination of the technique. Luckily, in vivo patch clamp electrophysiology seems particularly amenable to robotic automation. In this review, we document the development of automated patch clamp technology, from early systems based on multi-well plates through to automated planar-array platforms, and modern robotic platforms capable of performing two-photon targeted whole-cell electrophysiological recordings in vivo.

Three Small-Receptive-Field Ganglion Cells in the Mouse Retina Are Distinctly Tuned to Size, Speed, and Object Motion

Retinal ganglion cells (RGCs) are frequently divided into functional types by their ability to extract and relay specific features from a visual scene, such as the capacity to discern local or global motion, direction of motion, stimulus orientation, contrast or uniformity, or the presence of large or small objects. Here we introduce three previously uncharacterized, nondirection-selective ON-OFF RGC types that represent a distinct set of feature detectors in the mouse retina. The three high-definition (HD) RGCs possess small receptive-field centers and strong surround suppression. They respond selectively to objects of specific sizes, speeds, and types of motion. We present comprehensive morphological characterization of the HD RGCs and physiological recordings of their light responses, receptive-field size and structure, and synaptic mechanisms of surround suppression. We also explore the similarities and differences between the HD RGCs and a well characterized RGC with a comparably small receptive field, the local edge detector, in response to moving objects and textures. We model populations of each RGC type to study how they differ in their performance tracking a moving object. These results, besides introducing three new RGC types that together constitute a substantial fraction of mouse RGCs, provide insights into the role of different circuits in shaping RGC receptive fields and establish a foundation for continued study of the mechanisms of surround suppression and the neural basis of motion detection.

SIGNIFICANCE STATEMENT

The output cells of the retina, retinal ganglion cells (RGCs), are a diverse group of ∼40 distinct neuron types that are often assigned "feature detection" profiles based on the specific aspects of the visual scene to which they respond. Here we describe, for the first time, morphological and physiological characterization of three new RGC types in the mouse retina, substantially augmenting our understanding of feature selectivity. Experiments and modeling show that while these three "high-definition" RGCs share certain receptive-field properties, they also have distinct tuning to the size, speed, and type of motion on the retina, enabling them to occupy different niches in stimulus space.

Characterization of Predictive Behavior of a Retina by Mutual Information

Probing a bullfrog retina with spatially uniform light pulses of correlated stochastic intervals, we calculate the mutual information between the spiking output at the ganglion cells measured with multi-electrode array (MEA) and the interval of the stimulus at a time shift later. The time-integrated information from the output about the future stimulus is maximized when the mean interval of the stimulus is within the dynamic range of the well-established anticipative phenomena of omitted-stimulus responses for the retina. The peak position of the mutual information as a function of the time shift is typically negative considering the processing delay of the retina. However, the peak position can become positive for long enough correlation time of the stimulus when the pulse intervals are generated by a Hidden Markovian model (HMM). This is indicative of a predictive behavior of the retina which is possible only when the hidden variable of the HMM can be recovered from the history of the stimulus for a prediction of its future. We verify that stochastic intervals of the same mean, variance, and correlation time do not result in the same predictive behavior of the retina when they are generated by an Ornstein-Uhlenbeck (OU) process, which is strictly Markovian.

Action ability modulates time-to-collision judgments

Time-to-collision (TTC) underestimation has been interpreted as an adaptive response that allows observers to have more time to engage in a defensive behaviour. This bias seems, therefore, strongly linked to action preparation. There is evidence that the observer’s physical fitness modulates the underestimation effect so that people who need more time to react (i.e. those with less physical fitness) show a stronger underestimation effect. Here we investigated whether this bias is influenced by the momentary action capability of the observers. In the first experiment, participants estimated the time-to-collision of threatening or non-threatening stimuli while being mildly immobilized (with a chin rest) or while standing freely. Having reduced the possibility of movement led participants to show more underestimation of the approaching stimuli. However, this effect was not stronger for threatening relative to non-threatening stimuli. The effect of the action capability found in the first experiment could be interpreted as an expansion of peripersonal space (PPS). In the second experiment, we thus investigated the generality of this effect using an established paradigm to measure the size of peripersonal space. Participants bisected lines from different distances while in the chin rest or standing freely. The results replicated the classic left-to-right gradient in lateral spatial attention with increasing viewing distance, but no effect of immobilization was found. The manipulation of the momentary action capability of the observers influenced the participants’ performance in the TTC task but not in the line bisection task. These results are discussed in relation to the different functions of PPS.

Rapid and coordinated processing of global motion images by local clusters of retinal ganglion cells

Even when the body is stationary, the whole retinal image is always in motion by fixational eye movements and saccades that move the eye between fixation points. Accumulating evidence indicates that the brain is equipped with specific mechanisms for compensating for the global motion induced by these eye movements. However, it is not yet fully understood how the retina processes global motion images during eye movements. Here we show that global motion images evoke novel coordinated firing in retinal ganglion cells (GCs). We simultaneously recorded the firing of GCs in the goldfish isolated retina using a multi-electrode array, and classified each GC based on the temporal profile of its receptive field (RF). A moving target that accompanied the global motion (simulating a saccade following a period of fixational eye movements) modulated the RF properties and evoked synchronized and correlated firing among local clusters of the specific GCs. Our findings provide a novel concept for retinal information processing during eye movements.

Emergence of Selectivity to Looming Stimuli in a Spiking Network Model of the Optic Tectum

The neural circuits in the optic tectum of Xenopus tadpoles are selectively responsive to looming visual stimuli that resemble objects approaching the animal at a collision trajectory. This selectivity is required for adaptive collision avoidance behavior in this species, but its underlying mechanisms are not known. In particular, it is still unclear how the balance between the recurrent spontaneous network activity and the newly arriving sensory flow is set in this structure, and to what degree this balance is important for collision detection. Also, despite the clear indication for the presence of strong recurrent excitation and spontaneous activity, the exact topology of recurrent feedback circuits in the tectum remains elusive. In this study we take advantage of recently published detailed cell-level data from tadpole tectum to build an informed computational model of it, and investigate whether dynamic activation in excitatory recurrent retinotopic networks may on its own underlie collision detection. We consider several possible recurrent connectivity configurations and compare their performance for collision detection under different levels of spontaneous neural activity. We show that even in the absence of inhibition, a retinotopic network of quickly inactivating spiking neurons is naturally selective for looming stimuli, but this selectivity is not robust to neuronal noise, and is sensitive to the balance between direct and recurrent inputs. We also describe how homeostatic modulation of intrinsic properties of individual tectal cells can change selectivity thresholds in this network, and qualitatively verify our predictions in a behavioral experiment in freely swimming tadpoles.

The oscillation-like activity in bullfrog ON-OFF retinal ganglion cell

Oscillatory activity of retinal ganglion cell (RGC) has been observed in various species. It was reported such oscillatory activity is raised within large neural network and involved in retinal information coding. In the present research, we found an oscillation-like activity in ON-OFF RGC of bullfrog retina, and studied the mechanisms underlying the ON and OFF activities respectively. Pharmacological experiments revealed that the oscillation-like activity patterns in both ON and OFF pathways were abolished by GABA receptor antagonists, indicating GABAergic inhibition is essential for generating them. At the meantime, such activities in the ON and OFF pathways showed different responses to several other applied drugs. The oscillation-like pattern in the OFF pathway was abolished by glycine receptor antagonist or gap junction blocker, whereas that in the ON pathway was not affected. Furthermore, the blockade of the ON pathway by metabotropic glutamate receptor agonist led to suppression of the oscillation-like pattern in the OFF pathway. These results suggest that the ON pathway has modulatory effect on the oscillation-like activity in the OFF pathway. Therefore, the mechanisms underlying the oscillation-like activities in the ON and OFF pathways are different: the oscillation-like activity in the ON pathway is likely caused by GABAergic amacrine cell network, while that in the OFF pathway needs the contributions of GABAergic and glycinergic amacrine cell network, as well as gap junction connections.

Contribution of Nav1.8 sodium channels to retinal function

We examined the contribution of the sodium channel isoform Na_v1.8 to retinal function using the specific blocker A803467. We found that A803467 has little influence on the electroretinogram (ERG) a- and b-waves, but significantly reduces the oscillatory potentials (OPs) to 40-60% of their original amplitude, with significant changes in implicit time in the rod-driven range. To date, only two cell types were found in mouse to express Na_v1.8; the starburst amacrine cells (SBACs), and a subtype of retinal ganglion cells (RGCs). When we recorded light responses from ganglion cells using a multielectrode array we found significant and opposing changes in two physiological groups of RGCs. ON-sustained cells showed significant decreases while transient ON-OFF cells showed significant increases. The effects on ON-OFF transient cells but not ON-sustained cells disappeared in the presence of an inhibitory cocktail. We have previously shown that RGCs have only a minor contribution to the OPs (Smith et al., 2014), therefore suggesting that SBACs might be a significant contributor to this ERG component. Targeting SBACs with the cholinergic neurotoxin ethylcholine mustard aziridinium (AF64A) caused a reduction in the amplitude of the OPs similar to A803467. Our results, both using the ERG and MEA recordings from RGCs, suggest that Na_v1.8 plays a role in modulating specific aspects of the retinal physiology and that SBACs are a fundamental cellular contributor to the OPs in mice, a clear demonstration of the dichotomy between ERG b-wave and OPs.

Neural correlations enable invariant coding and perception of natural stimuli in weakly electric fish

Neural representations of behaviorally relevant stimulus features displaying invariance with respect to different contexts are essential for perception. However, the mechanisms mediating their emergence and subsequent refinement remain poorly understood in general. Here, we demonstrate that correlated neural activity allows for the emergence of an invariant representation of natural communication stimuli that is further refined across successive stages of processing in the weakly electric fish Apteronotus leptorhynchus. Importantly, different patterns of input resulting from the same natural communication stimulus occurring in different contexts all gave rise to similar behavioral responses. Our results thus reveal how a generic neural circuit performs an elegant computation that mediates the emergence and refinement of an invariant neural representation of natural stimuli that most likely constitutes a neural correlate of perception.

DOI:http://dx.doi.org/10.7554/eLife.12993.001

We can effortlessly recognize an object – a car, for example – in many different contexts such as when seen from behind, under different lighting levels or even from different viewpoints. This phenomenon is known as perceptual invariance: objects are correctly recognized, despite variations in exactly what is seen (or otherwise sensed). However, it is still not clear how the brain processes perceptual information to recognize the same object under a wide variety of contexts.

Some fish, such as the brown ghost knifefish, produce a weak electric signal that they can alter to communicate with other members of their species. A communication call may be produced in a variety of contexts that alter which aspects of the signal nearby fish detect. Despite this, fish tend to respond to a given communication call in the same way regardless of its context; this suggests that these fish also have perceptual invariance.

The communication calls of weakly electric fish can be easily mimicked in a laboratory and produce reliable behavioral responses, which makes these fish a good model for understanding how perceptual invariance might be coded in the brain. Therefore, Metzen et al. recorded the activity of the receptor neurons that first respond to communication calls in weakly electric fish. The results revealed that a given communication signal made the firing patterns of all receptor neurons in the fish’s brain more similar to each other, regardless of the signal’s context. This occurs despite the changes in context causing single receptor neurons to respond in different ways. At each stage of the process by which information is transmitted from the receptor neurons to neurons deeper in the brain, the similarity in the neurons’ firing patterns is refined, thereby giving rise to perceptual invariance.

While perceptual invariance to a given object in different contexts is desirable, it is also important to be able to distinguish between different objects. This implies that neurons should respond similarly to stimuli associated with the same object and differently to stimuli associated with different objects. Further studies are now needed to confirm whether this is the case.

DOI:http://dx.doi.org/10.7554/eLife.12993.002

Aberrant Activity in Degenerated Retinas Revealed by Electrical Imaging

In this review, I present and discuss the current understanding of aberrant electrical activity found in the ganglion cell layer (GCL) of rod-degenerated (rd) mouse retinas. The reported electrophysiological properties revealed by electrical imaging using high-density microelectrode arrays can be subdivided between spiking activity originating from retinal ganglion cells (RGCs) and local field potentials (LFPs) reflecting strong trans-membrane currents within the GCL. RGCs in rd retinas show increased and rhythmic spiking compared to age-matched wild-type retinas. Fundamental spiking frequencies range from 5 to 15 Hz in various mouse models. The rhythmic RGC spiking is driven by a presynaptic network comprising AII amacrine and bipolar cells. In the healthy retina this rhythm-generating circuit is inhibited by photoreceptor input. A unique physiological feature of rd retinas is rhythmic LFP manifested as spatially-restricted low-frequency (5-15 Hz) voltage changes. Their spatiotemporal characterization revealed propagation and correlation with RGC spiking. LFPs rely on gap-junctional coupling and are shaped by glycinergic and by GABAergic transmission. The aberrant RGC spiking and LFPs provide a simple readout of the functionality of the remaining retinal circuitry which can be used in the development of improved vision restoration strategies.

Dorsal raphe nucleus projecting retinal ganglion cells: Why Y cells?

Retinal ganglion Y (alpha) cells are found in retinas ranging from frogs to mice to primates. The highly conserved nature of the large, fast conducting retinal Y cell is a testament to its fundamental task, although precisely what this task is remained ill-defined. The recent discovery that Y-alpha retinal ganglion cells send axon collaterals to the serotonergic dorsal raphe nucleus (DRN) in addition to the lateral geniculate nucleus (LGN), medial interlaminar nucleus (MIN), pretectum and the superior colliculus (SC) has offered new insights into the important survival tasks performed by these cells with highly branched axons. We propose that in addition to its role in visual perception, the Y-alpha retinal ganglion cell provides concurrent signals via axon collaterals to the DRN, the major source of serotonergic afferents to the forebrain, to dramatically inhibit 5-HT activity during orientation or alerting/escape responses, which dis-facilitates ongoing tonic motor activity while dis-inhibiting sensory information processing throughout the visual system. The new data provide a fresh view of these evolutionarily old retinal ganglion cells.

Pharmacological study of direction selectivity in the archer fish retina

Direction selective cells have been found in the retina, the first level of the visual system, in mammals and recently also in the archer fish. These cells are involved in a variety of fast neural computation processes, from the control of eye movements to the detection of prey by the archer fish. The standard model for this mechanism in mammalian retina is well understood and is based on the asymmetry of inhibitory and excitatory inputs to the retinal ganglion cells. However, it remains unclear whether the mechanism that underlies direction selectivity is similar across animal classes. This study reports a pharmacological investigation designed to elucidate the mechanism that underlies motion detection in the archer fish retina. Direction selectivity in the retina was characterized under the influence of specific channel blockers that are known to be present in the different types of neurons of the retina. The results show that the direction-selective mechanism in the archer fish retina is modified only when the inhibitory channels of GABA and Glycine are manipulated. This suggests that the mechanism of direction selectivity in the archer fish retina is fundamentally different from the mechanism of direction selectivity in the mammalian retina.

A Visual Pathway for Looming-Evoked Escape in Larval Zebrafish

Avoiding the strike of an approaching predator requires rapid visual detection of a looming object, followed by a directed escape maneuver. While looming-sensitive neurons have been discovered in various animal species, the relative importance of stimulus features that are extracted by the visual system is still unclear. Furthermore, the neural mechanisms that compute object approach are largely unknown. We found that a virtual looming stimulus, i.e., a dark expanding disk on a bright background, reliably evoked rapid escape movements. Related stimuli, such as dimming, receding, or bright looming objects, were substantially less effective, and angular size was a critical determinant of escape initiation. Two-photon calcium imaging in retinal ganglion cell (RGC) axons revealed three retinorecipient areas that responded robustly to looming stimuli. One of these areas, the optic tectum, is innervated by a subset of RGC axons that respond selectively to looming stimuli. Laser-induced lesions of the tectal neuropil impaired the behavior. Our findings demonstrate a visually mediated escape behavior in zebrafish larvae exposed to objects approaching on a collision course. This response is sensitive to spatiotemporal parameters of the looming stimulus. Our data indicate that a subset of RGC axons within the tectum responds selectively to features of looming stimuli and that this input is necessary for visually evoked escape.

Coding of envelopes by correlated but not single-neuron activity requires neural variability

Understanding how the brain processes sensory information is often complicated by the fact that neurons exhibit trial-to-trial variability in their responses to stimuli. Indeed, the role of variability in sensory coding is still highly debated. Here, we examined how variability influences neural responses to naturalistic stimuli consisting of a fast time-varying waveform (i.e., carrier or first order) whose amplitude (i.e., envelope or second order) varies more slowly. Recordings were made from fish electrosensory and monkey vestibular sensory neurons. In both systems, we show that correlated but not single-neuron activity can provide detailed information about second-order stimulus features. Using a simple mathematical model, we made the strong prediction that such correlation-based coding of envelopes requires neural variability. Strikingly, the performance of correlated activity at predicting the envelope was similarly optimally tuned to a nonzero level of variability in both systems, thereby confirming this prediction. Finally, we show that second-order sensory information can only be decoded if one takes into account joint statistics when combining neural activities. Our results thus show that correlated but not single-neural activity can transmit information about the envelope, that such transmission requires neural variability, and that this information can be decoded. We suggest that envelope coding by correlated activity is a general feature of sensory processing that will be found across species and systems.

The neural circuit mechanisms underlying the retinal response to motion reversal

To make up for delays in visual processing, retinal circuitry effectively predicts that a moving object will continue moving in a straight line, allowing retinal ganglion cells to anticipate the object's position. However, a sudden reversal of motion triggers a synchronous burst of firing from a large group of ganglion cells, possibly signaling a violation of the retina's motion prediction. To investigate the neural circuitry underlying this response, we used a combination of multielectrode array and whole-cell patch recordings to measure the responses of individual retinal ganglion cells in the tiger salamander to reversing stimuli. We found that different populations of ganglion cells were responsible for responding to the reversal of different kinds of objects, such as bright versus dark objects. Using pharmacology and designed stimuli, we concluded that ON and OFF bipolar cells both contributed to the reversal response, but that amacrine cells had, at best, a minor role. This allowed us to formulate an adaptive cascade model (ACM), similar to the one previously used to describe ganglion cell responses to motion onset. By incorporating the ON pathway into the ACM, we were able to reproduce the time-varying firing rate of fast OFF ganglion cells for all experimentally tested stimuli. Analysis of the ACM demonstrates that bipolar cell gain control is primarily responsible for generating the synchronized retinal response, as individual bipolar cells require a constant time delay before recovering from gain control.

Population activity changes during a trial-to-trial adaptation of bullfrog retinal ganglion cells

A 'trial-to-trial adaptation' of bullfrog retinal ganglion cells in response to a repetitive light stimulus was investigated in the present study. Using the multielectrode recording technique, we studied the trial-to-trial adaptive properties of ganglion cells and explored the activity of population neurons during this adaptation process. It was found that the ganglion cells adapted with different degrees: their firing rates were decreased in different extents from early-adaptation to late-adaptation stage, and this was accompanied by a decrease in cross-correlation strength. In addition, adaptation behavior was different for ON-response and OFF-response, which implied that the mechanism of the trial-to-trial adaptation might involve bipolar cells and/or their synapses with other neurons and the stronger adaptation in the ganglion cells' OFF-responses might reflect the requirement to avoid possible saturation in the OFF circuit.

Excitation and inhibition in recurrent networks mediate collision avoidance in Xenopus tadpoles

Information processing in the vertebrate brain is thought to be mediated through distributed neural networks, but it is still unclear how sensory stimuli are encoded and detected by these networks, and what role synaptic inhibition plays in this process. Here we used a collision avoidance behavior in Xenopus tadpoles as a model for stimulus discrimination and recognition. We showed that the visual system of the tadpole is selective for behaviorally relevant looming stimuli, and that the detection of these stimuli first occurs in the optic tectum. By comparing visually guided behavior, optic nerve recordings, excitatory and inhibitory synaptic currents, and the spike output of tectal neurons, we showed that collision detection in the tadpole relies on the emergent properties of distributed recurrent networks within the tectum. We found that synaptic inhibition was temporally correlated with excitation, and did not actively sculpt stimulus selectivity, but rather it regulated the amount of integration between direct inputs from the retina and recurrent inputs from the tectum. Both pharmacological suppression and enhancement of synaptic inhibition disrupted emergent selectivity for looming stimuli. Taken together these findings suggested that, by regulating the amount of network activity, inhibition plays a critical role in maintaining selective sensitivity to behaviorally-relevant visual stimuli.

Effects of dopamine on response properties of ON-OFF RGCs in encoding stimulus durations

Single retinal ganglion cell's (RGCs) response properties, such as spike count and response latency, are known to encode some features of visual stimuli. On the other hand, neuronal response can be modulated by dopamine (DA), an important endogenous neuromodulator in the retina. In the present study, we investigated the effects of DA on the spike count and the response latency of bullfrog ON-OFF RGCs during exposure to different stimulus durations. We found that neuronal spike count and response latency were both changed with stimulus durations, and exogenous DA (10 μM) obviously attenuated the stimulus-duration-dependent response latency change. Information analysis showed that the information about light ON duration was mainly carried by the OFF response and vice versa, and the stimulation information was carried by both spike count and response latency. However, during DA application, the information carried by the response latency was greatly decreased, which suggests that dopaminergic pathway is involved in modulating the role of response latency in encoding the information about stimulus durations.

Functions of gamma-band synchronization in cognition: from single circuits to functional diversity across cortical and subcortical systems

Gamma-band activity (30-90 Hz) and the synchronization of neural activity in the gamma-frequency range have been observed in different cortical and subcortical structures and have been associated with different cognitive functions. However, it is still unknown whether gamma-band synchronization subserves a single universal function or a diversity of functions across the full spectrum of cognitive processes. Here, we address this question reviewing the mechanisms of gamma-band oscillation generation and the functions associated with gamma-band activity across several cortical and subcortical structures. Additionally, we raise a plausible explanation of why gamma rhythms are found so ubiquitously across brain structures. Gamma band activity originates from the interplay between inhibition and excitation. We stress that gamma oscillations, associated with this interplay, originate from basic functional motifs that conferred advantages for low-level system processing and multiple cognitive functions throughout evolution. We illustrate the multifunctionality of gamma-band activity by considering its role in neural systems for perception, selective attention, memory, motivation and behavioral control. We conclude that gamma-band oscillations support multiple cognitive processes, rather than a single one, which, however, can be traced back to a limited set of circuit motifs which are found universally across species and brain structures.

Response dynamics of bullfrog ON-OFF RGCs to different stimulus durations

Stimulus duration is an important feature of visual stimulation. In the present study, response properties of bullfrog ON-OFF retinal ganglion cells (RGCs) in exposure to different visual stimulus durations were studied. By using a multi-electrode recording system, spike discharges from ON-OFF RGCs were simultaneously recorded, and the cells' ON and OFF responses were analyzed. It was found that the ON response characteristics, including response latency, spike count, as well as correlated activity and relative latency between pair-wise cells, were modulated by different light OFF intervals, while the OFF response characteristics were modulated by different light ON durations. Stimulus information carried by the ON and OFF responses was then analyzed, and it was found that information about different light ON durations was more carried by transient OFF response, whereas information about different light OFF intervals were more carried by transient ON response. Meanwhile, more than 80 % information about stimulus durations was carried by firing rate. These results suggest that ON-OFF RGCs are sensitive to different stimulus durations, and they can efficiently encode the information about visual stimulus duration by firing rate.

Shifted encoding strategy in retinal luminance adaptation: from firing rate to neural correlation

Neuronal responses to prolonged stimulation attenuate over time. Here, we ask a fundamental question: is adaptation a simple process for the neural system during which sustained input is ignored, or is it actually part of a strategy for the neural system to adjust its encoding properties dynamically? After simultaneously recording the activities of a group of bullfrog's retinal ganglion cells (dimming detectors) in response to sustained dimming stimulation, we applied a combination of information analysis approaches to explore the time-dependent nature of information encoding during the adaptation. We found that at the early stage of the adaptation, the stimulus information was mainly encoded in firing rates, whereas at the late stage of the adaptation, it was more encoded in neural correlations. Such a transition in encoding properties is not a simple consequence of the attenuation of neuronal firing rates, but rather involves an active change in the neural correlation strengths, suggesting that it is a strategy adopted by the neural system for functional purposes. Our results reveal that in encoding a prolonged stimulation, the neural system may utilize concerted, but less active, firings of neurons to encode information.

A linear model for characterization of synchronization frequencies of neural networks

The synchronization frequency of neural networks and its dynamics have important roles in deciphering the working mechanisms of the brain. It has been widely recognized that the properties of functional network synchronization and its dynamics are jointly determined by network topology, network connection strength, i.e., the connection strength of different edges in the network, and external input signals, among other factors. However, mathematical and computational characterization of the relationships between network synchronization frequency and these three important factors are still lacking. This paper presents a novel computational simulation framework to quantitatively characterize the relationships between neural network synchronization frequency and network attributes and input signals. Specifically, we constructed a series of neural networks including simulated small-world networks, real functional working memory network derived from functional magnetic resonance imaging, and real large-scale structural brain networks derived from diffusion tensor imaging, and performed synchronization simulations on these networks via the Izhikevich neuron spiking model. Our experiments demonstrate that both of the network synchronization strength and synchronization frequency change according to the combination of input signal frequency and network self-synchronization frequency. In particular, our extensive experiments show that the network synchronization frequency can be represented via a linear combination of the network self-synchronization frequency and the input signal frequency. This finding could be attributed to an intrinsically-preserved principle in different types of neural systems, offering novel insights into the working mechanism of neural systems.

Gap junctions are essential for generating the correlated spike activity of neighboring retinal ganglion cells

Neurons throughout the brain show spike activity that is temporally correlated to that expressed by their neighbors, yet the generating mechanism(s) remains unclear. In the retina, ganglion cells (GCs) show robust, concerted spiking that shapes the information transmitted to central targets. Here we report the synaptic circuits responsible for generating the different types of concerted spiking of GC neighbors in the mouse retina. The most precise concerted spiking was generated by reciprocal electrical coupling of GC neighbors via gap junctions, whereas indirect electrical coupling to a common cohort of amacrine cells generated the correlated activity with medium precision. In contrast, the correlated spiking with the lowest temporal precision was produced by shared synaptic inputs carrying photoreceptor noise. Overall, our results demonstrate that different synaptic circuits generate the discrete types of GC correlated activity. Moreover, our findings expand our understanding of the roles of gap junctions in the retina, showing that they are essential for generating all forms of concerted GC activity transmitted to central brain targets.

Luminance and contrast in visual perception of time to collision

Many animals avoid dark, approaching objects seen against a lighter background but show no or weaker reactions to stimuli with inverted contrast. We investigated whether human observers would respond differently to such stimuli in terms of estimated time-to-arrival. We varied luminances of an approaching, light or dark disk and a plain, grey background, and for several conditions, continuously adjusted calibrations so as to keep contrast and/or overall lightness constant. Since no effects were found, we conclude that humans are able to discard luminance and contrast for the task at hand. Generally, however, performance was affected by different, consecutive regimes of feedback: Initially, without feedback, observers responded inconsistently and much too late; they improved after correct feedback, and in a third block of trials with pseudo-random feedback, they responded increasingly early without reverting to the initial level of uncertainty. We discuss our findings with regard to implications for neural mechanisms, put them in the context of evolutionary considerations, and propose continuative animal behavioral studies.

Alert response to motion onset in the retina

Previous studies have shown that motion onset is very effective at capturing attention and is more salient than smooth motion. Here, we find that this salience ranking is present already in the firing rate of retinal ganglion cells. By stimulating the retina with a bar that appears, stays still, and then starts moving, we demonstrate that a subset of salamander retinal ganglion cells, fast OFF cells, responds significantly more strongly to motion onset than to smooth motion. We refer to this phenomenon as an alert response to motion onset. We develop a computational model that predicts the time-varying firing rate of ganglion cells responding to the appearance, onset, and smooth motion of a bar. This model, termed the adaptive cascade model, consists of a ganglion cell that receives input from a layer of bipolar cells, represented by individual rectified subunits. Additionally, both the bipolar and ganglion cells have separate contrast gain control mechanisms. This model captured the responses to our different motion stimuli over a wide range of contrasts, speeds, and locations. The alert response to motion onset, together with its computational model, introduces a new mechanism of sophisticated motion processing that occurs early in the visual system.

Gap junctional coupling in the vertebrate retina: variations on one theme?

Gap junctions connect cells in the bodies of all multicellular organisms, forming either homologous or heterologous (i.e. established between identical or different cell types, respectively) cell-to-cell contacts by utilizing identical (homotypic) or different (heterotypic) connexin protein subunits. Gap junctions in the nervous system serve electrical signaling between neurons, thus they are also called electrical synapses. Such electrical synapses are particularly abundant in the vertebrate retina where they are specialized to form links between neurons as well as glial cells. In this article, we summarize recent findings on retinal cell-to-cell coupling in different vertebrates and identify general features in the light of the evergrowing body of data. In particular, we describe and discuss tracer coupling patterns, connexin proteins, junctional conductances and modulatory processes. This multispecies comparison serves to point out that most features are remarkably conserved across the vertebrate classes, including (i) the cell types connected via electrical synapses; (ii) the connexin makeup and the conductance of each cell-to-cell contact; (iii) the probable function of each gap junction in retinal circuitry; (iv) the fact that gap junctions underlie both electrical and/or tracer coupling between glial cells. These pan-vertebrate features thus demonstrate that retinal gap junctions have changed little during the over 500 million years of vertebrate evolution. Therefore, the fundamental architecture of electrically coupled retinal circuits seems as old as the retina itself, indicating that gap junctions deeply incorporated in retinal wiring from the very beginning of the eye formation of vertebrates. In addition to hard wiring provided by fast synaptic transmitter-releasing neurons and soft wiring contributed by peptidergic, aminergic and purinergic systems, electrical coupling may serve as the 'skeleton' of lateral processing, enabling important functions such as signal averaging and synchronization.

20Hz membrane potential oscillations are driven by synaptic inputs in collision-detecting neurons in the frog optic tectum

Although the firing patterns of collision-detecting neurons have been described in detail in several species, the mechanisms generating responses in these neurons to visual objects on a collision course remain largely unknown. This is partly due to the limited number of intracellular recordings from such neurons, particularly in vertebrate species. By employing patch recordings in a novel integrated frog eye-tectum preparation we tested the hypothesis that OFF retinal ganglion cells were driving the responses to visual objects on a collision course in the frog optic tectum neurons. We found that the majority (22/26) of neurons in layer 6 responding to visual stimuli fitted the definition of η class collision-detectors: they readily responded to a looming stimulus imitating collision but not a receding stimulus (spike count difference ∼10 times) and the spike firing rate peaked after the stimulus visual angle reached a threshold value of ∼20-45°. In the majority of these neurons (15/22) a slow frequency oscillation (f=∼20Hz) of the neuronal membrane potential could be detected in the responses to a simulated collision stimulus, as well as to turning off the lights. Since OFF retinal ganglion cells could produce such oscillations, our observations are in agreement with the hypothesis that 'collision' responses in the frog optic tectum neurons are driven by synaptic inputs from OFF retinal ganglion cells.

Closed-loop measurements of iso-response stimuli reveal dynamic nonlinear stimulus integration in the retina

Neurons often integrate information from multiple parallel signaling streams. How a neuron combines these inputs largely determines its computational role in signal processing. Experimental assessment of neuronal signal integration, however, is often confounded by cell-intrinsic nonlinear processes that arise after signal integration has taken place. To overcome this problem and determine how ganglion cells in the salamander retina integrate visual contrast over space, we used automated online analysis of recorded spike trains and closed-loop control of the visual stimuli to identify different stimulus patterns that give the same neuronal response. These iso-response stimuli revealed a threshold-quadratic transformation as a fundamental nonlinearity within the receptive field center. Moreover, for a subset of ganglion cells, the method revealed an additional dynamic nonlinearity that renders these cells particularly sensitive to spatially homogeneous stimuli. This function is shown to arise from a local inhibition-mediated dynamic gain control mechanism.

Archer fish fast hunting maneuver may be guided by directionally selective retinal ganglion cells

Archer fish are known for their unique hunting method, where one fish in a group shoots down an insect with a jet of water while all the other fish are observing the prey's motion. To reap its reward, the archer fish must reach the prey before its competitors. This requires fast computation of the direction of motion of the prey, which enables the fish to initiate a turn towards the prey with an accuracy of 99%, at about 100 ms after the prey is shot. We explored the hypothesis that direction-selective retinal ganglion cells may underlie this rapid processing. We quantified the degree of directional selectivity of ganglion cells in the archer fish retina. The cells could be categorized into three groups: sharply (5%), broadly (37%) and non-tuned (58%) directionally selective cells. To relate the electrophysiological data to the behavioral results we studied a computational model and estimated the time required to accumulate sufficient directional information to match the decision accuracy of the fish. The computational model is based on two direction-selective populations that race against each other until one reaches the threshold and drives the decision. We found that this competition model can account for the observed response time at the required accuracy. Thus, our results are consistent with the hypothesis that the fast response behavior of the archer fish relies on retinal identification of movement direction.

Gamma oscillations are generated locally in an attention-related midbrain network

Gamma-band (25-140 Hz) oscillations are a hallmark of sensory processing in the forebrain. The optic tectum (OT), a midbrain structure implicated in sensorimotor processing and attention, also exhibits gamma oscillations. However, the origin and mechanisms of these oscillations remain unknown. We discovered that in acute slices of the avian OT, persistent (>100 ms) epochs of large amplitude gamma oscillations can be evoked that closely resemble those recorded in vivo. We found that cholinergic, glutamatergic, and GABAergic mechanisms differentially regulate the structure of the oscillations at various timescales. These persistent oscillations originate in the multisensory layers of the OT and are broadcast to visual layers via the cholinergic nucleus Ipc, providing a potential mechanism for enhancing the processing of visual information within the OT. The finding that the midbrain contains an intrinsic gamma-generating circuit suggests that the OT could use its own oscillatory code to route signals to forebrain networks.

State-space analysis of time-varying higher-order spike correlation for multiple neural spike train data

Precise spike coordination between the spiking activities of multiple neurons is suggested as an indication of coordinated network activity in active cell assemblies. Spike correlation analysis aims to identify such cooperative network activity by detecting excess spike synchrony in simultaneously recorded multiple neural spike sequences. Cooperative activity is expected to organize dynamically during behavior and cognition; therefore currently available analysis techniques must be extended to enable the estimation of multiple time-varying spike interactions between neurons simultaneously. In particular, new methods must take advantage of the simultaneous observations of multiple neurons by addressing their higher-order dependencies, which cannot be revealed by pairwise analyses alone. In this paper, we develop a method for estimating time-varying spike interactions by means of a state-space analysis. Discretized parallel spike sequences are modeled as multi-variate binary processes using a log-linear model that provides a well-defined measure of higher-order spike correlation in an information geometry framework. We construct a recursive Bayesian filter/smoother for the extraction of spike interaction parameters. This method can simultaneously estimate the dynamic pairwise spike interactions of multiple single neurons, thereby extending the Ising/spin-glass model analysis of multiple neural spike train data to a nonstationary analysis. Furthermore, the method can estimate dynamic higher-order spike interactions. To validate the inclusion of the higher-order terms in the model, we construct an approximation method to assess the goodness-of-fit to spike data. In addition, we formulate a test method for the presence of higher-order spike correlation even in nonstationary spike data, e.g., data from awake behaving animals. The utility of the proposed methods is tested using simulated spike data with known underlying correlation dynamics. Finally, we apply the methods to neural spike data simultaneously recorded from the motor cortex of an awake monkey and demonstrate that the higher-order spike correlation organizes dynamically in relation to a behavioral demand.

Nearly half a century ago, the Canadian psychologist D. O. Hebb postulated the formation of assemblies of tightly connected cells in cortical recurrent networks because of changes in synaptic weight (Hebb's learning rule) by repetitive sensory stimulation of the network. Consequently, the activation of such an assembly for processing sensory or behavioral information is likely to be expressed by precisely coordinated spiking activities of the participating neurons. However, the available analysis techniques for multiple parallel neural spike data do not allow us to reveal the detailed structure of transiently active assemblies as indicated by their dynamical pairwise and higher-order spike correlations. Here, we construct a state-space model of dynamic spike interactions, and present a recursive Bayesian method that makes it possible to trace multiple neurons exhibiting such precisely coordinated spiking activities in a time-varying manner. We also formulate a hypothesis test of the underlying dynamic spike correlation, which enables us to detect the assemblies activated in association with behavioral events. Therefore, the proposed method can serve as a useful tool to test Hebb's cell assembly hypothesis.