Synchronized retinal oscillations encode essential information for escape behavior in frogs

Synergy from silence in a combinatorial neural code

The manner in which groups of neurons represent events in the external world is a central question in neuroscience. Estimation of the information encoded by small groups of neurons has shown that in many neural systems, cells carry mildly redundant information. These measures average over all the activity patterns of a neural population. Here, we analyze the population code of the salamander and guinea pig retinas by quantifying the information conveyed by specific multicell activity patterns. Synchronous spikes, even though they are relatively rare and highly informative, convey less information than the sum of either spike alone, making them redundant coding symbols. Instead, patterns of spiking in one cell and silence in others, which are relatively common and often overlooked as special coding symbols, were found to be mostly synergistic. Our results reflect that the mild average redundancy between ganglion cells that was previously reported is actually the result of redundant and synergistic multicell patterns, whose contributions partially cancel each other when taking the average over all patterns. We further show that similar coding properties emerge in a generic model of neural responses, suggesting that this form of combinatorial coding, in which specific compound patterns carry synergistic or redundant information, may exist in other neural circuits.

Collision detection as a model for sensory-motor integration

Visually guided collision avoidance is critical for the survival of many animals. The execution of successful collision-avoidance behaviors requires accurate processing of approaching threats by the visual system and signaling of threat characteristics to motor circuits to execute appropriate motor programs in a timely manner. Consequently, visually guided collision avoidance offers an excellent model with which to study the neural mechanisms of sensory-motor integration in the context of a natural behavior. Neurons that selectively respond to approaching threats and brain areas processing them have been characterized across many species. In locusts in particular, the underlying sensory and motor processes have been analyzed in great detail: These animals possess an identified neuron, called the LGMD, that responds selectively to approaching threats and conveys that information through a second identified neuron, the DCMD, to motor centers, generating escape jumps. A combination of behavioral and in vivo electrophysiological experiments has unraveled many of the cellular and network mechanisms underlying this behavior.

Spikes with short inter-spike intervals in frog retinal ganglion cells are more correlated with their adjacent neurons' activities

Correlated firings among neurons have been extensively investigated; however, previous studies on retinal ganglion cell (RGC) population activities were mainly based on analyzing the correlated activities between the entire spike trains. In the present study, the correlation properties were explored based on burst-like activities and solitary spikes separately. The results indicate that: (1) burst-like activities were more correlated with other neurons' activities; (2) burst-like spikes correlated with their neighboring neurons represented a smaller receptive field than that of correlated solitary spikes. These results suggest that correlated burst-like spikes should be more efficient in signal transmission, and could encode more detailed spatial information.

Neuronal responses to looming objects in the superior colliculus of the cat

The superior colliculus (SC) in the mammalian mesencephalon is involved in avoidance or escape behaviors, but little is known about the response properties of collicular neurons to an object approaching on a collision course towards the animal. The present study identified two classes of looming-sensitive neurons, rho and eta cells, in the SC of the cat, but did not find any tau cell, which has been observed in the pigeon tectofugal pathway. The looming responses were characterized by distinct firing patterns, in which the neuronal discharge steadily increased as the object was approaching, and peaked approximately at the time of collision (rho cell) or some time earlier (eta cell). The response onset time of both rho and eta cells was linearly related to the square root of the diameter/velocity ratio of looming objects; whereas for eta cells, the response peak time was linearly related to the diameter/velocity ratio. The receptive fields of these collicular cells were composed of an excitatory center and a suppressive surround, but the occurrence and development of neuronal responses to looming stimuli were independent of the receptive-field organization. Although the cell number was relatively small in the deep layers of the SC, the proportion of looming-sensitive neurons was close to that in the superficial layers. These results suggest that a population of collicular cells is involved in signaling impending collision of a looming object with the animal and the neural mechanisms underlying the collision avoidance behaviors are to some extent conservative across species from insects to mammals.

Information loss associated with imperfect observation and mismatched decoding

We consider two types of causes leading to information loss when neural activities are passed and processed in the brain. One is responses of upstream neurons to stimuli being imperfectly observed by downstream neurons. The other is upstream neurons non-optimally decoding stimuli information contained in the activities of the downstream neurons. To investigate the importance of neural correlation in information processing in the brain, we specifically consider two situations. One is when neural responses are not simultaneously observed, i.e., neural correlation data is lost. This situation means that stimuli information is decoded without any specific assumption about neural correlations. The other is when stimuli information is decoded by a wrong statistical model where neural responses are assumed to be independent even when they are not. We provide the information geometric interpretation of these two types of information loss and clarify their relationship. We then concretely evaluate these types of information loss in some simple examples. Finally, we discuss use of these evaluations of information loss to elucidate the importance of correlation in neural information processing.

Multiplexing of motor information in the discharge of a collision detecting neuron during escape behaviors

Locusts possess an identified neuron, the descending contralateral movement detector (DCMD), conveying visual information about impending collision from the brain to thoracic motor centers. We built a telemetry system to simultaneously record, in freely behaving animals, the activity of the DCMD and of motoneurons involved in jump execution. Cocontraction of antagonistic leg muscles, a required preparatory phase, was triggered after the DCMD firing rate crossed a threshold. Thereafter, the number of DCMD spikes predicted precisely motoneuron activity and jump occurrence. Additionally, the time of DCMD peak firing rate predicted that of jump. Ablation experiments suggest that the DCMD, together with a nearly identical ipsilateral descending neuron, is responsible for the timely execution of the escape. Thus, three distinct features that are multiplexed in a single neuron's sensory response to impending collision-firing rate threshold, peak firing time, and spike count-probably control three distinct motor aspects of escape behaviors.

LFP spectral peaks in V1 cortex: network resonance and cortico-cortical feedback

This paper is about how cortical recurrent interactions in primary visual cortex (V1) together with feedback from extrastriate cortex can account for spectral peaks in the V1 local field potential (LFP). Recent studies showed that visual stimulation enhances the γ-band (25-90 Hz) of the LFP power spectrum in macaque V1. The height and location of the γ-band peak in the LFP spectrum were correlated with visual stimulus size. Extensive spatial summation, possibly mediated by feedback connections from extrastriate cortex and long-range horizontal connections in V1, must play a crucial role in the size dependence of the LFP. To analyze stimulus-effects on the LFP of V1 cortex, we propose a network model for the visual cortex that includes two populations of V1 neurons, excitatory and inhibitory, and also includes feedback to V1 from extrastriate cortex. The neural network model for V1 was a resonant system. The model's resonance frequency (ResF) was in the γ-band and varied up or down in frequency depending on cortical feedback. The model's ResF shifted downward with stimulus size, as in the real cortex, because increased size recruited more activity in extrastriate cortex and V1 thereby causing stronger feedback. The model needed to have strong local recurrent inhibition within V1 to obtain ResFs that agree with cortical data. Network resonance as a consequence of recurrent excitation and inhibition appears to be a likely explanation for γ-band peaks in the LFP power spectrum of the primary visual cortex.

Response properties and receptive field organization of collision-sensitive neurons in the optic tectum of bullfrog, Rana catesbeiana

OBJECTIVE

Many studies have reported that animals will display collision avoidance behavior when the size of retinal image of an object reaches a threshold. The present study aimed to investigate the neural correlates underlying the frog collision avoidance behavior.

METHODS

Different types of visual stimuli simulating the retinal image of an approaching or a recessing object were generated by a computer and presented to the right eye of frog. A multielectrode array was used to examine the activity of collision-sensitive neurons, and single electrode recordings were employed to quantify visual parameter(s) of the frog collision-sensitive neurons.

RESULTS

The multielectrode array revealed that 40 neurons in the optic tectum showed selective responsiveness to objects approaching on a direct collision course. The response profiles of these collision-sensitive neurons were similar to those of lobula giant movement detector (LGMD) in the locust or to those of neurons in the pigeon. However, the receptive field (RF) size of the frog neurons [(18.5+/-3.8) degrees, n=33)] was smaller than those of collision-sensitive neurons of the locust and the pigeon. Multielectrode recordings also showed that the collision-sensitive neurons were activated only when the focus of expansion of a looming retinal image was located within the center of its RF. There was a linear relationship between the parameter l/v (l denotes half-size of the object, v denotes approaching velocity) and time-to-collision (time difference between the peak of the neuronal activity and the predictive collision) in 16 collision-sensitive neurons. Theoretical consideration showed that the peak firing rate always occurred at a fixed delay of (60.1 +/- 39.5) ms (n=16) after the object had reached a constant angular size of (14.8 +/- 3.4) degrees (n=16) on the retina.

CONCLUSION

The results may help clarify the mechanisms underlying the collision avoidance behavior in bullfrog.

Collision-Sensitive Neurons in the Optic Tectum of the Bullfrog, Rana catesbeiana

In this study, we examined the neuronal correlates of frog collision avoidance behavior. Single unit recordings in the optic tectum showed that 11 neurons gave selective responses to objects approaching on a direct collision course. The collision-sensitive neurons exhibited extremely tight tuning for collision bound trajectories with mean half-width at half height values of 0.8 and 0.9° ( n = 4) for horizontal and vertical deviations, respectively. The response of frog collision-sensitive neurons can be fitted by a function that simply multiplies the size dependence of its response, e−αθ( t), by the image's instantaneous angular velocity θ′( t). Using fitting analysis, we showed that the peak firing rate always occurred after the approaching object had reached a constant visual angle of 24.2 ± 2.6° (mean ± SD; n = 8), regardless of the approaching velocity. Moreover, a linear relationship was demonstrated between parameters l/v ( l: object's half-size, v: approach velocity) and time-to-collision (time difference between peak neuronal activity and the predicted collision) in the 11 collision-sensitive neurons. In addition, linear regression analysis was used to show that peak firing rate always occurred after the object had reached a constant angular size of 21.1° on the retina. The angular thresholds revealed by both theoretical analyses were comparable and showed a good agreement with that revealed by our previous behavioral experiments. This strongly suggests that the collision-sensitive neurons of the frog comprise a threshold detector, which triggers collision avoidance behavior.

Enlarged gold-tipped silicon microprobe arrays and signal compensation for multi-site electroretinogram recordings in the isolated carp retina

In order to record multi-site electroretinogram (ERG) responses in isolated carp retinae, we utilized three-dimensional (3D), extracellular, 3.5-μm-diameter silicon (Si) probe arrays fabricated by the selective vapor-liquid-solid (VLS) growth method. Neural recordings with the Si microprobe exhibit low signal-to-noise (S/N) ratios of recorded responses due to the high-electrical-impedance characteristics of the small recording area at the probe tip. To increase the S/N ratio, we designed and fabricated enlarged gold (Au) tipped Si microprobes (10-μm-diameter Au tip and 3.5-μm-diameter probe body). In addition, we demonstrated that the signal attenuation and phase delay of ERG responses recorded via the Si probe can be compensated by the inverse filtering method. We conclude that the reduction of probe impedance and the compensation of recorded signals are useful approaches to obtain distortion-free recording of neural signals with high-impedance microelectrodes.

Dynamics of stimulus-evoked spike timing correlations in the cat lateral geniculate nucleus

Precisely synchronized neuronal activity has been commonly observed in the mammalian visual pathway. Spike timing correlations in the lateral geniculate nucleus (LGN) often take the form of phase synchronized oscillations in the high gamma frequency range. To study the relations between oscillatory activity, synchrony, and their time-dependent properties, we recorded activity from multiple single units in the cat LGN under stimulation by stationary spots of light. Autocorrelation analysis showed that approximately one third of the cells exhibited oscillatory firing with a mean frequency ∼80 Hz. Cross-correlation analysis showed that 30% of unit pairs showed significant synchronization, and 61% of these pairs consisted of synchronous oscillations. Cross-correlation analysis assumes that synchronous firing is stationary and maintained throughout the period of stimulation. We tested this assumption by applying unitary events analysis (UEA). We found that UEA was more sensitive to weak and transient synchrony than cross-correlation analysis and detected a higher incidence (49% of cell pairs) of significant synchrony (unitary events). In many unit pairs, the unitary events were optimally characterized at a bin width of 1 ms, indicating that neural synchrony has a high degree of temporal precision. We also found that approximately one half of the unit pairs showed nonstationary changes in synchrony that could not be predicted by the modulation of firing rates. Population statistics showed that the onset of synchrony between LGN cells occurred significantly later than that observed between retinal afferents and LGN cells. The synchrony detected among unit pairs recorded on separate tetrodes tended to be more transient and have a later onset than that observed between adjacent units. These findings show that stimulus-evoked synchronous activity within the LGN is often rhythmic, highly nonstationary, and modulated by endogenous processes that are not tightly correlated with firing rate.

Influence of GABAergic inhibition on concerted activity between the ganglion cells

In this study, the spike discharges of one subtype of bullfrog retinal ganglion cells (dimming detectors) in response to repetitive full field light-OFF stimuli were recorded using multi-electrode arrays. Two different types of concerted activity (precise synchronization and correlated activity) could be distinguished. The nearby cells with overlapped receptive field areas often fired in synchrony, whereas the correlated activity was mainly observed from remote cell pairs with separated receptive fields. After the bicuculline application, the strength of the synchronized activity was increased whereas that of the correlated activity was decreased. These results suggest that the activation of GABAA-receptor-mediated inhibitory pathways differentially modulates the concerted firing of the ganglion cells.

Exploring the function of neural oscillations in early sensory systems

Neuronal oscillations appear throughout the nervous system, in structures as diverse as the cerebral cortex, hippocampus, subcortical nuclei and sense organs. Whether neural rhythms contribute to normal function, are merely epiphenomena, or even interfere with physiological processing are topics of vigorous debate. Sensory pathways are ideal for investigation of oscillatory activity because their inputs can be defined. Thus, we will focus on sensory systems as we ask how neural oscillations arise and how they might encode information about the stimulus. We will highlight recent work in the early visual pathway that shows how oscillations can multiplex different types of signals to increase the amount of information that spike trains encode and transmit. Last, we will describe oscillation-based models of visual processing and explore how they might guide further research.

Mismatched decoding in the brain

"How is information decoded in the brain?" is one of the most difficult and important questions in neuroscience. We have developed a general framework for investigating to what extent the decoding process in the brain can be simplified. First, we hierarchically constructed simplified probabilistic models of neural responses that ignore more than Kth-order correlations using the maximum entropy principle. We then computed how much information is lost when information is decoded using these simplified probabilistic models (i.e., "mismatched decoders"). To evaluate the information obtained by mismatched decoders, we introduced an information theoretic quantity, I*, which was derived by extending the mutual information in terms of communication rate across a channel. We showed that I* provides consistent results with the minimum mean-square error as well as the mutual information, and demonstrated that a previously proposed measure quantifying the importance of correlations in decoding substantially deviates from I* when many cells are analyzed. We then applied this proposed framework to spike data for vertebrate retina using short natural scene movies of 100 ms duration as a set of stimuli and computing the information contained in neural activities. Although significant correlations were observed in population activities of ganglion cells, information loss was negligibly small even if all orders of correlation were ignored in decoding. We also found that, if we inappropriately assumed stationarity for long durations in the information analysis of dynamically changing stimuli, such as natural scene movies, correlations appear to carry a large proportion of total information regardless of their actual importance.

Eye smarter than scientists believed: neural computations in circuits of the retina

We rely on our visual system to cope with the vast barrage of incoming light patterns and to extract features from the scene that are relevant to our well-being. The necessary reduction of visual information already begins in the eye. In this review, we summarize recent progress in understanding the computations performed in the vertebrate retina and how they are implemented by the neural circuitry. A new picture emerges from these findings that helps resolve a vexing paradox between the retina's structure and function. Whereas the conventional wisdom treats the eye as a simple prefilter for visual images, it now appears that the retina solves a diverse set of specific tasks and provides the results explicitly to downstream brain areas.

Safety, efficacy, and quality control of a photoelectric dye-based retinal prosthesis (Okayama University-type retinal prosthesis) as a medical device

Patients with retinitis pigmentosa lose photoreceptor cells as a result of genetic abnormalities and hence become blind. Neurons such as bipolar cells and ganglion cells remain alive even in the retina of these patients, and ganglion cells send axons to the brain as the optic nerve. The basic concept of retinal prostheses is to replace dead photoreceptor cells with artificial devices to stimulate the remaining neurons with electric currents or potentials. Photodiode arrays and digital camera-type electrode arrays are the two main approaches for retinal prostheses to stimulate retinal neurons, but these arrays have the problems of poor biocompatibility, low sensitivity, and low output of electric currents, and hence have a requirement for external electric sources (batteries). To overcome these problems, we are developing photoelectric dye-based retinal prostheses that absorb light and convert photon energy to generate electric potentials. The prototype, using a photoelectric dye-coupled polyethylene film, could induce intracellular calcium elevation in photoreceptor-lacking embryonic retinal tissues and cultured retinal neurons. The subretinal implantation of the prototype in the eyes of Royal College of Surgeons (RCS) rats led to vision recovery as proved by a behavior test. The photoelectric dye that was chosen for the prototype did not exhibit any cytotoxicity. The surface potentials of the photoelectric dye-coupled film showed a rapid on-and-off response to illumination with a threshold for light intensity as measured by a Kelvin probe system. Photoelectric dye-based retinal prostheses are thin and soft, and therefore, a sheet of the film of large size, corresponding to a large visual field, could be inserted into the vitreous and then to the subretinal space through a small opening by rolling up the film. Clinical studies of photoelectric dye-based retinal prostheses in patients with retinitis pigmentosa who lose sight will be planned after the manufacturing control and the quality control had been established for the medical device.

Approach sensitivity in the retina processed by a multifunctional neural circuit

The detection of approaching objects, such as looming predators, is necessary for survival. Which neurons and circuits mediate this function? We combined genetic labeling of cell types, two-photon microscopy, electrophysiology and theoretical modeling to address this question. We identify an approach-sensitive ganglion cell type in the mouse retina, resolve elements of its afferent neural circuit, and describe how these confer approach sensitivity on the ganglion cell. The circuit's essential building block is a rapid inhibitory pathway: it selectively suppresses responses to non-approaching objects. This rapid inhibitory pathway, which includes AII amacrine cells connected to bipolar cells through electrical synapses, was previously described in the context of night-time vision. In the daytime conditions of our experiments, the same pathway conveys signals in the reverse direction. The dual use of a neural pathway in different physiological conditions illustrates the efficiency with which several functions can be accommodated in a single circuit.

The structure of large-scale synchronized firing in primate retina

Synchronized firing among neurons has been proposed to constitute an elementary aspect of the neural code in sensory and motor systems. However, it remains unclear how synchronized firing affects the large-scale patterns of activity and redundancy of visual signals in a complete population of neurons. We recorded simultaneously from hundreds of retinal ganglion cells in primate retina, and examined synchronized firing in completely sampled populations of approximately 50-100 ON-parasol cells, which form a major projection to the magnocellular layers of the lateral geniculate nucleus. Synchronized firing in pairs of cells was a subset of a much larger pattern of activity that exhibited local, isotropic spatial properties. However, a simple model based solely on interactions between adjacent cells reproduced 99% of the spatial structure and scale of synchronized firing. No more than 20% of the variability in firing of an individual cell was predictable from the activity of its neighbors. These results held both for spontaneous firing and in the presence of independent visual modulation of the firing of each cell. In sum, large-scale synchronized firing in the entire population of ON-parasol cells appears to reflect simple neighbor interactions, rather than a unique visual signal or a highly redundant coding scheme.

Retinal oscillations carry visual information to cortex

Thalamic relay cells fire action potentials that transmit information from retina to cortex. The amount of information that spike trains encode is usually estimated from the precision of spike timing with respect to the stimulus. Sensory input, however, is only one factor that influences neural activity. For example, intrinsic dynamics, such as oscillations of networks of neurons, also modulate firing pattern. Here, we asked if retinal oscillations might help to convey information to neurons downstream. Specifically, we made whole-cell recordings from relay cells to reveal retinal inputs (EPSPs) and thalamic outputs (spikes) and then analyzed these events with information theory. Our results show that thalamic spike trains operate as two multiplexed channels. One channel, which occupies a low frequency band (<30 Hz), is encoded by average firing rate with respect to the stimulus and carries information about local changes in the visual field over time. The other operates in the gamma frequency band (40–80 Hz) and is encoded by spike timing relative to retinal oscillations. At times, the second channel conveyed even more information than the first. Because retinal oscillations involve extensive networks of ganglion cells, it is likely that the second channel transmits information about global features of the visual scene.

Information transmission in oscillatory neural activity

Periodic neural activity not locked to the stimulus or to motor responses is usually ignored. Here, we present new tools for modeling and quantifying the information transmission based on periodic neural activity that occurs with quasi-random phase relative to the stimulus. We propose a model to reproduce characteristic features of oscillatory spike trains, such as histograms of inter-spike intervals and phase locking of spikes to an oscillatory influence. The proposed model is based on an inhomogeneous Gamma process governed by a density function that is a product of the usual stimulus-dependent rate and a quasi-periodic function. Further, we present an analysis method generalizing the direct method (Rieke et al. in Spikes: exploring the neural code. MIT Press, Cambridge, 1999; Brenner et al. in Neural Comput 12(7):1531-1552, 2000) to assess the information content in such data. We demonstrate these tools on recordings from relay cells in the lateral geniculate nucleus of the cat.

Synchronized firing in the retina

Synchronized firing in neural populations has been proposed to constitute an elementary aspect of the neural code, but a complete understanding of its origins and significance has been elusive. Synchronized firing has been extensively documented in retinal ganglion cells, the output neurons of the retina. However, differences in synchronized firing across species and cell types have led to varied conclusions about its mechanisms and role in visual signaling. Recent work on two identified cell populations in the primate retina, the ON-parasol and OFF-parasol cells, permits a more unified understanding. Intracellular recordings reveal that synchronized firing in these cell types arises primarily from common synaptic input to adjacent pairs of cells. Statistical analysis indicates that local pairwise interactions can explain the pattern of synchronized firing in the entire parasol cell population. Computational analysis reveals that the aggregate impact of synchronized firing on the visual signal is substantial. Thus, in the parasol cells, the origin and impact of synchronized firing on the neural code may be understood as locally shared input which influences the visual signals transmitted from eye to brain.

The maintained discharge of rat retinal ganglion cells

Action potentials were recorded from rat retinal ganglion cell fibers in the presence of a uniform field, and the maintained discharge pattern was characterized. Spike trains recorded under ketaminexylazine. The majority of cells had multimodal interval distributions, with the first peak in the range of 25.00.97). Both ON and OFF cells show serial correlations between adjacent interspike intervals, while ON cells also showed second-order correlations. Cells with multimodal interval distribution showed a strong peak at high frequencies in the power spectra in the range of 28.9-41.4 Hz. Oscillations were present under both anesthetic conditions and persisted in the dark at a slightly lower frequency, implying that the oscillations are generated independent of any light stimulus but can be modulated by light level. The oscillation frequency varied slightly between cells of the same type and in the same eye, suggesting that multiple oscillatory generating mechanisms exist within the retina. Cells with high-frequency oscillations were described well by an integrate-and-fire model with the input consisting of Gaussian noise plus a sinusoid where the phase was jittered randomly to account for the bandwidth present in the oscillations.

Homeostatically regulated synchronized oscillations induced by short-term tetrodotoxin treatment in cultured neuronal network

Homeostatic plasticity plays a critical role in the stability of neuronal activities. Here, with high-density hippocampal networks cultured on multi-electrode arrays (MEAs), the transformation of spontaneous neuronal firing patterns induced by 1microM tetrodotoxin was clarified. Once tetrodotoxin was washed out after a 4-h treatment, spontaneous activities rose significantly with spike rate increasing approximately three times, and synchronized burst oscillations appeared throughout the network, with the cross-correlation coefficient between the active sites rising from 0.06+/-0.03 to 0.27+/-0.05. The long-term recording showed that the oscillations lasted for more than 4h before the network recovered. These results suggest that short-term treatment by tetrodotoxin may induce the homeostatically enhanced neuronal excitability, and that the spontaneous synchronized oscillations should be an indicator of homeostatic plasticity in cultured neuronal network. Furthermore, the non-invasive and long-term recording with MEAs as a novel sensing system is identified to be appropriate for pharmacological investigations of neuronal plasticity at the network level.

Valuations for spike train prediction

The ultimate product of an electrophysiology experiment is often a decision on which biological hypothesis or model best explains the observed data. We outline a paradigm designed for comparison of different models, which we refer to as spike train prediction. A key ingredient of this paradigm is a prediction quality valuation that estimates how close a predicted conditional intensity function is to an actual observed spike train. Although a valuation based on log likelihood (L) is most natural, it has various complications in this context. We propose that a quadratic valuation (Q) can be used as an alternative to L. Q shares some important theoretical properties with L, including consistency, and the two valuations perform similarly on simulated and experimental data. Moreover, Q is more robust than L, and optimization with Q can dramatically improve computational efficiency. We illustrate the utility of Q for comparing models of peer prediction, where it can be computed directly from cross-correlograms. Although Q does not have a straightforward probabilistic interpretation, Q is essentially given by Euclidean distance.

High-throughput electrophysiology: an emerging paradigm for ion-channel screening and physiology

Ion channels represent highly attractive targets for drug discovery and are implicated in a diverse range of disorders, in particular in the central nervous and cardiovascular systems. Moreover, assessment of cardiac ion-channel activity of new chemical entities is now an integral component of drug discovery programmes to assess potential for cardiovascular side effects. Despite their attractiveness as drug discovery targets ion channels remain an under-exploited target class, which is in large part due to the labour-intensive and low-throughput nature of patch-clamp electrophysiology. This Review provides an update on the current state-of-the-art for the various automated electrophysiology platforms that are now available and critically evaluates their impact in terms of ion-channel screening, lead optimization and the assessment of cardiac ion-channel safety liability.

Expression of SPIG1 reveals development of a retinal ganglion cell subtype projecting to the medial terminal nucleus in the mouse

Visual information is transmitted to the brain by roughly a dozen distinct types of retinal ganglion cells (RGCs) defined by a characteristic morphology, physiology, and central projections. However, our understanding about how these parallel pathways develop is still in its infancy, because few molecular markers corresponding to individual RGC types are available. Previously, we reported a secretory protein, SPIG1 (clone name; D/Bsp120I #1), preferentially expressed in the dorsal region in the developing chick retina. Here, we generated knock-in mice to visualize SPIG1-expressing cells with green fluorescent protein. We found that the mouse retina is subdivided into two distinct domains for SPIG1 expression and SPIG1 effectively marks a unique subtype of the retinal ganglion cells during the neonatal period. SPIG1-positive RGCs in the dorsotemporal domain project to the dorsal lateral geniculate nucleus (dLGN), superior colliculus, and accessory optic system (AOS). In contrast, in the remaining region, here named the pan-ventronasal domain, SPIG1-positive cells form a regular mosaic and project exclusively to the medial terminal nucleus (MTN) of the AOS that mediates the optokinetic nystagmus as early as P1. Their dendrites costratify with ON cholinergic amacrine strata in the inner plexiform layer as early as P3. These findings suggest that these SPIG1-positive cells are the ON direction selective ganglion cells (DSGCs). Moreover, the MTN-projecting cells in the pan-ventronasal domain are apparently composed of two distinct but interdependent regular mosaics depending on the presence or absence of SPIG1, indicating that they comprise two functionally distinct subtypes of the ON DSGCs. The formation of the regular mosaic appears to be commenced at the end of the prenatal stage and completed through the peak period of the cell death at P6. SPIG1 will thus serve as a useful molecular marker for future studies on the development and function of ON DSGCs.

GABA(C) receptors in retina and brain

The expression of GABA(C) receptors has long been regarded as a specific property of bipolar cells in the inner retina where they control the information transfer from bipolar to retinal ganglion cells. A number of recent anatomical and physiological studies, however, have provided evidence that GABA(C) receptors are also expressed in many brain structures apart from the retina. The presence of GABA(C) receptors in many GABAergic neurons suggests that this receptor type may be involved in the regulation of local inhibition. This chapter focuses on the distribution of GABA(C) receptors and their possible function in various brain areas.

Synchronized firing among retinal ganglion cells signals motion reversal

We show that when a moving object suddenly reverses direction, there is a brief, synchronous burst of firing within a population of retinal ganglion cells. This burst can be driven by either the leading or trailing edge of the object. The latency is constant for movement at different speeds, objects of different size, and bright versus dark contrasts. The same ganglion cells that signal a motion reversal also respond to smooth motion. We show that the brain can build a pure reversal detector using only a linear filter that reads out synchrony from a group of ganglion cells. These results indicate that not only can the retina anticipate the location of a smoothly moving object, but that it can also signal violations in its own prediction. We show that the reversal response cannot be explained by models of the classical receptive field and suggest that nonlinear receptive field subunits may be responsible.

Contribution of the GABAergic pathway(s) to the correlated activities of chicken retinal ganglion cells

In the present study, the spatiotemporal pattern of chicken retinal ganglion cells' firing activity in response to full-field white light stimulation was investigated. Cross-correlation analysis showed that ganglion cells of sustained subtype fired in precise synchrony with their adjacent neurons of the same subtype (delay lag within 2 ms, narrow correlation). On the other hand, the activities of neighboring ganglion cells of transient subtype were correlated with distributed time lags (10-30 ms, medium correlation). Pharmacological studies demonstrated that the intensity of the medium correlations could be strengthened when exogenous GABA was applied and attenuated when GABA receptors were blocked by picrotoxin. Meanwhile, the GABAergic modulation on the narrow correlations was not consistent. These results suggest that, in the chicken retina, GABAergic pathway(s) are likely involved in the formation of medium correlations between ganglion cells. Neurons might fire at a lower rate but with higher level of synchronization to improve the efficiency of information transmission, with the mechanism involving the GABAergic inhibitory input.

The role of neuronal synchronization in selective attention

Attention selectively enhances the influence of neuronal responses conveying information about relevant sensory attributes. Accumulating evidence suggests that this selective neuronal modulation relies on rhythmic synchronization at local and long-range spatial scales: attention selectively synchronizes the rhythmic responses of those neurons that are tuned to the spatial and featural attributes of the attended sensory input. The strength of synchronization is thereby functionally related to perceptual accuracy and behavioural efficiency. Complementing this synchronization at a local level, attention has recently been demonstrated to regulate which locally synchronized neuronal groups phase-synchronize their rhythmic activity across long-range connections. These results point to a general computational role for selective synchronization in dynamically controlling which neurons communicate information about sensory inputs effectively.

Neuronal coherence during selective attentional processing and sensory-motor integration

Groups of neurons synchronize their activities during a variety of conditions, but whether this synchronization is functionally relevant has remained a matter of debate. Here, we survey recent findings showing that synchronization is dynamically modulated during cognitive processes. Based on this evidence, synchronization appears to reflect a general mechanism that renders interactions among selective subsets of neurons effective. We show that neuronal synchronization predicts which sensory input is processed and how efficient it is transmitted to postsynaptic target neurons during sensory-motor integration. Four lines of evidence are presented supporting the hypothesis that rhythmic neuronal synchronization, also called neuronal coherence, underlies effective and selective neuronal communication. (1) Findings from intracellular recordings strongly suggest that postsynaptic neurons are particularly sensitive to synaptic input that is synchronized in the gamma-frequency (30-90 Hz) range. (2) Neurophysiological studies in awake animals revealed enhanced rhythmic synchronization among neurons encoding task-relevant information. (3) The trial-by-trial variation in the precision of neuronal synchronization predicts part of the trial-by-trial variation in the speed of visuo-motor integration. (4) The planning and selection of specific movements can be predicted by the strength of coherent oscillations among local neuronal groups in frontal and parietal cortex. Thus, neuronal coherence appears as a neuronal substrate of an effective neuronal communication structure that dynamically links neurons into functional groups processing task-relevant information and selecting appropriate actions during attention and effective sensory-motor integration.

Network variability limits stimulus-evoked spike timing precision in retinal ganglion cells

Visual, auditory, somatosensory, and olfactory stimuli generate temporally precise patterns of action potentials (spikes). It is unclear, however, how the precision of spike generation relates to the pattern and variability of synaptic input elicited by physiological stimuli. We determined how synaptic conductances evoked by light stimuli that activate the rod bipolar pathway control spike generation in three identified types of mouse retinal ganglion cells (RGCs). The relative amplitude, timing, and impact of excitatory and inhibitory input differed dramatically between On and Off RGCs. Spikes evoked by repeated somatic injection of identical light-evoked synaptic conductances were more temporally precise than those evoked by light. However, the precision of spikes evoked by conductances that varied from trial to trial was similar to that of light-evoked spikes. Thus, the rod bipolar pathway modulates different RGCs via unique combinations of synaptic input, and RGC temporal variability reflects variability in the input this circuit provides.

Neural strategies for optimal processing of sensory signals

The electrosensory system is used for both spatial navigation tasks and communication. An electric organ generates a sinusoidal electric field and cutaneous electroreceptors respond to this field. Objects such as prey or rocks cause a local low-frequency modulation of the electric field; this cue is used by electric fish for navigation and prey capture. The interference of the electric fields of conspecifics produces beats, often with high frequencies, that are also sensed by the electroreceptors; furthermore, these electric fish can transiently modulate their electric discharge as a communication signal. Thus these fish must therefore detect a variety of low-intensity signals that differ greatly in their spatial extent, frequency, and duration. Behavioral studies suggest that they are highly adapted to these tasks. Experimental and theoretical analyses of the neural circuitry for the electrosense has demonstrated many commonalities with the more common senses, e.g., topographic mapping and receptive fields with On or Off centers and surround inhibition. The integration of computational and experimental analyses has demonstrated novel mechanisms that appear to optimize weak signal detection in the electrosense including: noise shaping by correlations within single spike trains, induction of oscillations by delayed feedback inhibition, the requirement for maps with differing receptive field sizes tuned for different stimulus parameters, and the role of non-plastic feedback for adaptive cancellation of redundant signals. It is likely that these mechanisms will also be operative in other sensory systems.

Dopaminergic modulation and rod contribution in the generation of oscillatory potentials in the tiger salamander retina

The roles of rod and cone input and of dopamine in the generation of oscillatory potentials were studied in tiger salamander retina. Under scotopic conditions, oscillations were elicited with a green, but not a red stimulus. With mesopic background illumination, both stimuli caused oscillations. Addition of quinpirole to a mesopic retina eliminated oscillations while SKF-38393 had no effect. Similarly, addition of sulpiride to a light-adapted retina elicited oscillatory activity, but SCH 22390 had no effect. These results suggest that oscillatory potentials are elicited through activation of the rod pathway and are modulated by dopamine through D2-receptors.

Global Electrosensory Oscillations Enhance Directional Responses of Midbrain Neurons inEigenmannia

Eigenmannia, a genus of weakly electric fish, exhibits a specialized behavior known as the jamming avoidance response (JAR). The JAR results in a categorical difference between Eigenmannia that are in groups of conspecifics and those that are alone. Fish in groups exhibit the JAR behavior and thereby experience ongoing, global synchronous 20- to 50-Hz electrosensory oscillations, whereas solitary fish do not. Although previous work has shown that these ongoing signals do not significantly degrade electrosensory behavior, these oscillations nevertheless elicit short-term synaptic depression in midbrain circuits. Because short-term synaptic depression can have profound effects on the transmission of information through synapses, we examined the differences in intracellularly recorded responses of midbrain neurons in awake, behaving fish to moving electrosensory images under electrosensory conditions that mimic solitary fish and fish in groups. In solitary conditions, moving objects elicited Gaussian or sinusoidal postsynaptic potentials (PSPs) that commonly exhibited preferential responses to a direction of motion. Surprisingly, when the same stimulus was presented in the presence of the global oscillations, directional selectivity was increased in all neurons tested. The magnitudes of the differences in PSP amplitude for preferred and nonpreferred directions were correlated with a measure of short-term synaptic depression in both conditions. The electrosensory consequences of the JAR appear to result in an enhancement of the representation of direction of motion in midbrain neurons. The data also support a role for short-term synaptic depression in the generation and modulation of directional responses.

See globally, spike locally: oscillations in a retinal model encode large visual features

We show that coherent oscillations among neighboring ganglion cells in a retinal model encode global topological properties, such as size, that cannot be deduced unambiguously from their local, time-averaged firing rates. Whereas ganglion cells may fire similar numbers of spikes in response to both small and large spots, only large spots evoke coherent high frequency oscillations, potentially allowing downstream neurons to infer global stimulus properties from their local afferents. To determine whether such information might be extracted over physiologically realistic spatial and temporal scales, we analyzed artificial spike trains whose oscillatory correlations were similar to those measured experimentally. Oscillatory power in the upper gamma band, extracted on single-trials from multi-unit spike trains, supported good to excellent size discrimination between small and large spots, with performance improving as the number of cells and/or duration of the analysis window was increased. By using Poisson distributed spikes to normalize the firing rate across stimulus conditions, we further found that coincidence detection, or synchrony, yielded substantially poorer performance on identical size discrimination tasks. To determine whether size encoding depended on contiguity independent of object shape, we examined the total oscillatory activity across the entire model retina in response to random binary images. As the ON-pixel probability crossed the percolation threshold, which marks the sudden emergence of large connected clusters, the total gamma-band activity exhibited a sharp transition, a phenomena that may be experimentally observable. Finally, a reanalysis of previously published oscillatory responses from cat ganglion cells revealed size encoding consistent with that predicted by the retinal model.

A Synchronization-Desynchronization Code for Natural Communication Signals

Synchronous spiking of neural populations is hypothesized to play important computational roles in forming neural assemblies and solving the binding problem. Although the opposite phenomenon of desynchronization is well known from EEG studies, it is largely neglected on the neuronal level. We here provide an example of in vivo recordings from weakly electric fish demonstrating that, depending on the social context, different types of natural communication signals elicit transient desynchronization as well as synchronization of the electroreceptor population without changing the mean firing rate. We conclude that, in general, both positive and negative changes in the degree of synchrony can be the relevant signals for neural information processing.

A high frequency resonance in the responses of retinal ganglion cells to rapidly modulated stimuli: a computer model

Brisk Y-type ganglion cells in the cat retina exhibit a high frequency resonance (HFR) in their responses to large, rapidly modulated stimuli. We used a computer model to test whether negative feedback mediated by axon-bearing amacrine cells onto ganglion cells could account for the experimentally observed properties of HFRs. Temporal modulation transfer functions (tMTFs) recorded from model ganglion cells exhibited HFR peaks whose amplitude, width, and locations were qualitatively consistent with experimental data. Moreover, the wide spatial distribution of axon-mediated feedback accounted for the observed increase in HFR amplitude with stimulus size. Model phase plots were qualitatively similar to those recorded from Y ganglion cells, including an anomalous phase advance that in our model coincided with the amplification of low-order harmonics that overlapped the HFR peak. When axon-mediated feedback in the model was directed primarily to bipolar cells, whose synaptic output was graded, or else when the model was replaced with a simple cascade of linear filters, it was possible to produce large HFR peaks but the region of anomalous phase advance was always eliminated, suggesting the critical involvement of strongly non-linear feedback loops. To investigate whether HFRs might contribute to visual processing, we simulated high frequency ocular tremor by rapidly modulating a naturalistic image. Visual signals riding on top of the imposed jitter conveyed an enhanced representation of large objects. We conclude that by amplifying responses to ocular tremor, HFRs may selectively enhance the processing of large image features.

GABA transporters regulate a standing GABAC receptor-mediated current at a retinal presynaptic terminal

At the axon terminal of goldfish retinal bipolar cells, GABA(C) receptors have been shown to mediate inhibitory reciprocal synaptic currents. Here, we demonstrate a novel standing GABAergic current mediated exclusively by GABA(C) receptors. Selective inhibition of GAT-1 GABA transporters on amacrine cells increases this tonic current and reveals a specific functional coupling between GAT-1 transporters and GABA(C) receptors. We propose that this GABA(C) receptor-mediated standing current serves to regulate synaptic gain by shunting depolarizing potentials that can produce Ca2+-dependent action potentials at the bipolar cell terminal. Furthermore, we find that the amount of GABA(C) receptor-mediated reciprocal feedback between bipolar cell terminals and amacrine cells is greatly increased when GAT-1 transporters are specifically blocked by NO-711 (1-[2-[[(diphenylmethylene)imino]oxy]ethyl]-1,2,5,6-tetrahydro-3-pyridinecarboxylic acid hydrochloride). The involvement of GAT-1 transporters in regulating this standing (or tonic) GABA(C) current implicates them in a novel role as major determinants of presynaptic excitability.