Spike Code Research Articles

The Effects of Ghrelin on Spike Activity of the Suprachiasmatic Nucleus Neurones of the Rat

In one of the most important non-photic mechanisms of the circadian biological clock synchronization with environmental geophysical 24 h rhythm, information on feeding schedule, composition and calorie content of food is used. Hormone ghrelin, a product of the neuroendocrine oxyntic cells of the gastric mucosa to be a signal molecule within this mechanism. In experiments on sagittal hypothalamic slices of male Wistar rats, the effects of 25 nM ghrelin on spike activity and parameters of spike information coding were investigated. Application of ghrelin induced an increase in spike frequency and a decrease in entropy of interspike interval distribution in 32.1% of the neurones recorded. In 29.6% of the cells, opposite responses in the form of a reduction of activity and an increase in the entropy of interspike interval distribution were observed. Parameters of spike activity of the reminder 38.3% neurones of the suprachiasmatic nucleus did not change. The observed responses of the entropy of interspike interval distribution indicate the appropriate changes in a degree of irregularity of interspike interval induced by ghrelin. Application of selective high-affinity antagonist of GHS-R1a receptor, JMV 2959 (100 nM) did not induce responses of the investigated parameters of spike activity but completely prevented changes of both, spike frequency and entropy of interspike interval distribution observed in the presence of ghrelin. The obtained data show that hormone ghrelin by a direct influence on the suprachiasmatic nucleus in vitro modulates the activity level and spike code of relatively numerous population of neurones of the nucleus, wherein the effects of ghrelin are implemented via GHS-R1a receptors. The results of the current study provide additional evidence in favour of the hypothesis on the involvement of ghrelin in mechanisms of non-photic entrainment of the circadian biological clock in accordance with severity of food motivation and level of metabolism.

Fields or firings? Comparing the spike code and the electromagnetic field hypothesis.

Where is consciousness? Neurobiological theories of consciousness look primarily to synaptic firing and "spike codes" as the physical substrate of consciousness, although the specific mechanisms of consciousness remain unknown. Synaptic firing results from electrochemical processes in neuron axons and dendrites. All neurons also produce electromagnetic (EM) fields due to various mechanisms, including the electric potential created by transmembrane ion flows, known as "local field potentials," but there are also more meso-scale and macro-scale EM fields present in the brain. The functional role of these EM fields has long been a source of debate. We suggest that these fields, in both their local and global forms, may be the primary seat of consciousness, working as a gestalt with synaptic firing and other aspects of neuroanatomy to produce the marvelous complexity of minds. We call this assertion the "electromagnetic field hypothesis." The neuroanatomy of the brain produces the local and global EM fields but these fields are not identical with the anatomy of the brain. These fields are produced by, but not identical with, the brain, in the same manner that twigs and leaves are produced by a tree's branches and trunk but are not the same as the branches and trunk. As such, the EM fields represent the more granular, both spatially and temporally, aspects of the brain's structure and functioning than the neuroanatomy of the brain. The brain's various EM fields seem to be more sensitive to small changes than the neuroanatomy of the brain. We discuss issues with the spike code approach as well as the various lines of evidence supporting our argument that the brain's EM fields may be the primary seat of consciousness. This evidence (which occupies most of the paper) suggests that oscillating neural EM fields may make firing in neural circuits oscillate, and these oscillating circuits may help unify and guide conscious cognition.

Electromagnetic-field theories of qualia: can they improve upon standard neuroscience?

How do brains create all our different colors, pains, and other conscious qualities? These various qualia are the most essential aspects of consciousness. Yet standard neuroscience (primarily based on synaptic information processing) has not found the synaptic-firing codes, sometimes described as the "spike code," to account for how these qualia arise and how they unite to form complex perceptions, emotions, et cetera. Nor is it clear how to get from these abstract codes to the qualia we experience. But electromagnetic field (versus synaptic) approaches to how qualia arise have been offered in recent years by Pockett, McFadden, Jones, Bond, Ward and Guevera, Keppler and Shani, Hunt and Schooler, et cetera. These EM-field approaches show promise in offering more viable accounts of qualia. Yet, until now, they have not been evaluated together. We review various EM field theories of qualia, highlight their strengths and weaknesses, and contrast these theories with standard neuroscience approaches.

The Effects of Insulin on Spike Activity of the Suprachiasmatic Nucleus Neurones and Functional State of Afferent Inputs from the Arcuate Nucleus in Rats

In experiments on the sagittal hypothalamic slices of male Wistar rats, the effects of 15 nM insulin on the level of spike activity, parameters of spike information coding by the suprachiasmatic nucleus neurones, and functional state of afferent inputs to the neurones from the arcuate nucleus were studied. Application of insulin induced a decrease in the frequency of action potential generation and an increase in the entropy of interspike interval distribution in 33.3% of neurones recorded; in 12% of cells, the responses of opposite direction were found; in the remaining 54.7% neurones, spike activity did not change. The responses of the entropy of interspike interval distribution suggest the related changes in a degree of interspike interval irregularity induced by insulin. To characterise afferent inputs to the suprachiasmatic nucleus neurones from the arcuate nucleus, electrophysiological technique of the construction and analysis of the peristimulus time histogram (PSTH) was used. Statistically significant responses to the stimulation of the arcuate nucleus were recorded in 24 of 38 neurones of the suprachiasmatic nucleus. In 6 of the neurones, the responses were in the form of a short-latency (20 ms) excitation, in 1 neurone in the form of a long-latency excitation, in 6 neurones in the form of a short-latency inhibition; in 11 neurones complex two- or three-phase responses in the form of different compositions of excitation and inhibition were observed. Application of 15 nM insulin induced a qualitative transformation of the responses (disappearing of the initial responses or emergence of new responses) in 5 neurones initially responded to stimulation, and in 1 neurone initially not responded to stimulation of the arcuate nucleus. Statistically significant changes in the latency or duration of the responses in the presence of insulin were not found. The results of the study suggest the ability of insulin to influence the activity level and the spike code of a respectively numerous population of neurones in the suprachiasmatic nucleus circadian oscillator as well as modulate the functional state of afferent inputs to the circadian oscillator from hypothalamic arcuate nucleus playing an important role in the control of appetite and metabolism.

GaAs a model system to study the role of electron–phonon coupling on ionization stimulated damage recovery

The latent ion tracks observed in various materials after swift heavy ion (SHI) irradiation is often explained in the framework of thermal spike model (TSM). Dominantly, SHIs deposit most of their energy via intense ionization leading to a very high density of localized electronic excitations. The energy transfer from electrons to lattice, within a time of electronic cooling ∼100 fs, is governed by the ‘electron-phonon coupling’ parameter g. In this work, GaAs is used as a model system for studying ionization-stimulated damage recovery. Controlled damage is introduced using 300 KeV Ar ion irradiation, followed by successive irradiation using 100 MeV Ag ions at ∼80 K by varying the fluence (ions cm−2). The TSM is utilized to explain the observed recovery. Using the previously published value of 1012 W cm−3 K−1 for GaAs, the existing thermal spike code resulted in melting and quick quenching within ∼10 ps, suggesting the formation of SHI-induced tracks. However, experimental observations do not support the formation of tracks in pristine GaAs. Multiple simulation runs, for different g values, predict that for no melting in GaAs, g should be 1.4 × 1012 W cm−3 K−1. Finally, the 3D version of the TSM is used to simulate the temperature profiles after an impact of SHI irradiation on an amorphous nano-zone embedded in a crystalline GaAs matrix. Simulations predict that the thermal spike in this zone is confined, indicating melt-flow at the crystalline-amorphous interface that can promote recovery. This lattice recovery is further supported by both RBS/C and TEM results.

Paradoxical Rules of Spike Train Decoding Revealed at the Sensitivity Limit of Vision

All sensory information is encoded in neural spike trains. It is unknown how the brain utilizes this neural code to drive behavior. Here, we unravel the decoding rules of the brain at the most elementary level by linking behavioral decisions to retinal output signals in a single-photon detection task. A transgenic mouse line allowed us to separate the two primary retinal outputs, ON and OFF pathways, carrying information about photon absorptions as increases and decreases in spiking, respectively. We measured the sensitivity limit of rods and the most sensitive ONand OFF ganglion cells and correlated these results with visually guided behavior using markerless head and eye tracking. We show that behavior relies only on the ON pathway even when the OFF pathway would allow higher sensitivity. Paradoxically, behavior does not rely on the spike code with maximal information but instead relies on a decoding strategy based on increases in spiking.

Extraction of acoustic features based on auditory spike code and its application to music genre classification

A new method of extracting acoustic features based on auditory spike code is proposed. An auditory spike code represents the acoustic activities created by the signal, similar to sound encoding of the human auditory system. In the proposed method, an auditory spike code of the signal is computed using a 64-band Gammatone filterbank as the kernel functions. Then, for each spectral band, the sum and non-zero counts of the auditory spike code are determined, and the features corresponding to the population and occurrence rate of the acoustic activities for each band are computed. In addition, the distribution of the acoustic activities on a time axis is analysed based on the histogram of time intervals between the adjacent acoustic activities, and the features for expressing temporal properties of the signal are extracted. The reconstruction accuracy of the auditory spike code is also measured as the features. Different from most conventional features obtained by complex statistical modelling or learning, the features by the proposed method can directly show specific acoustic characteristics contained in the signal. These features are applied to a music genre classification, and it is confirmed that they provide a performance comparable to state-of-the-art features.

Integrating a brain into a bat robot

The sophisticated biosonar systems of horseshoe bats have enabled these animals to navigate and pursue prey in complex environments. A conspicuous peripheral dynamics in which the animals' noseleaves and pinnae change during biosonar behaviors could play an important role in enabling these capabilities. It may be hypothesized that for the integration between peripheral dynamics and neural signal processing/estimation to be maximally effective, the periphery should be controlled by feedback from the output of the subsequent neural echo processing. In the way, the specifics of sensory information encoding in the periphery could be controlled based on the needs of the neural signal processing. As a first step towards such an integration in a biomimetic sonar head, a computational model for the inner ear and the auditory nerve's spike code has been integrated with a dynamic periphery that—like the computational models—mimics horseshoe bats. For each model stage, alternative versions with different levels of complexity have been implemented to test how module complexity and the values of the associated parameters affect the capacity of the echo representation to encode sensory information. These effects have been tested based on a large dataset of 220 000 echoes collected in natural forest environments.

Effects of Neuropeptide Y on Neuron Spike Activity in the Rat Suprachiasmatic Nucleus in Vitro

Experiments on sagittal hippocampus slices from male Wistar rats addressed the effects of 10 nM neuropeptide Y on the level of electrical activity in neurons in the suprachiasmatic nucleus and parameters of spike-based information encoding. Application of neuropeptide Y led to a decrease in the action potential generation frequency in 35 of the 81 neurons recorded; eight cells showed increases in this parameter, and the remaining 38 neurons showed no change in the level of spike activity. The decrease in the spike generation frequency in suprachiasmatic nucleus neurons was accompanied by increases in the entropy of the distribution of interspike intervals and the mutual information between adjacent interspike intervals, which is evidence for increases in the degree of irregularity in these intervals and the patterning of spike information in response to neuropeptide Y. These results demonstrate the ability of neuropeptide Y to modulate the activity level and affect the spike code in the relatively numerous population of neurons in the circadian oscillator of the suprachiasmatic nucleus.

Multiplexed coding by cerebellar Purkinje neurons.

Purkinje cells (PC), the sole output neurons of the cerebellar cortex, encode sensorimotor information, but how they do it remains a matter of debate. Here we show that PCs use a multiplexed spike code. Synchrony/spike time and firing rate encode different information in behaving monkeys during saccadic eye motion tasks. Using the local field potential (LFP) as a probe of local network activity, we found that infrequent pause spikes, which initiated or terminated intermittent pauses in simple spike trains, provide a temporally reliable signal for eye motion onset, with strong phase-coupling to the β/γ band LFP. Concurrently, regularly firing, non-pause spikes were weakly correlated with the LFP, but were crucial to linear encoding of eye movement kinematics by firing rate. Therefore, PC spike trains can simultaneously convey information necessary to achieve precision in both timing and continuous control of motion.

Spike Code Flow in Cultured Neuronal Networks.

We observed spike trains produced by one-shot electrical stimulation with 8 × 8 multielectrodes in cultured neuronal networks. Each electrode accepted spikes from several neurons. We extracted the short codes from spike trains and obtained a code spectrum with a nominal time accuracy of 1%. We then constructed code flow maps as movies of the electrode array to observe the code flow of “1101” and “1011,” which are typical pseudorandom sequence such as that we often encountered in a literature and our experiments. They seemed to flow from one electrode to the neighboring one and maintained their shape to some extent. To quantify the flow, we calculated the “maximum cross-correlations” among neighboring electrodes, to find the direction of maximum flow of the codes with lengths less than 8. Normalized maximum cross-correlations were almost constant irrespective of code. Furthermore, if the spike trains were shuffled in interval orders or in electrodes, they became significantly small. Thus, the analysis suggested that local codes of approximately constant shape propagated and conveyed information across the network. Hence, the codes can serve as visible and trackable marks of propagating spike waves as well as evaluating information flow in the neuronal network.

Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition.

During the last decade, Bayesian probability theory has emerged as a framework in cognitive science and neuroscience for describing perception, reasoning and learning of mammals. However, our understanding of how probabilistic computations could be organized in the brain, and how the observed connectivity structure of cortical microcircuits supports these calculations, is rudimentary at best. In this study, we investigate statistical inference and self-organized learning in a spatially extended spiking network model, that accommodates both local competitive and large-scale associative aspects of neural information processing, under a unified Bayesian account. Specifically, we show how the spiking dynamics of a recurrent network with lateral excitation and local inhibition in response to distributed spiking input, can be understood as sampling from a variational posterior distribution of a well-defined implicit probabilistic model. This interpretation further permits a rigorous analytical treatment of experience-dependent plasticity on the network level. Using machine learning theory, we derive update rules for neuron and synapse parameters which equate with Hebbian synaptic and homeostatic intrinsic plasticity rules in a neural implementation. In computer simulations, we demonstrate that the interplay of these plasticity rules leads to the emergence of probabilistic local experts that form distributed assemblies of similarly tuned cells communicating through lateral excitatory connections. The resulting sparse distributed spike code of a well-adapted network carries compressed information on salient input features combined with prior experience on correlations among them. Our theory predicts that the emergence of such efficient representations benefits from network architectures in which the range of local inhibition matches the spatial extent of pyramidal cells that share common afferent input.

Interactions between the spike code and the epigenetic code during information processing in the brain

In a recent paper in this journal (Smythies and Edelstein, 2012) we described an epigenetic code involved in neurocomputation. This was based on the following facts. Clinical observations from a number of sources had shown that the modality of a sensory neuron (i.e., whether it is a visual or an auditory neuron) is determined by the origin of its afferent fibers. This can be changed if the afferent source is rerouted, and involves radical rebuilding of the functional neuroanatomy of the postsynaptic neuron. At that time the nature of the transsynaptic mechanism that effected this change was unknown. Our hypothesis suggested that the mechanism consists of the epigenetic material that contains the code (whose elements are protein transcription factors, DNA fragments and various types of RNA, including microRNAs) transported from the pre- to the post-synaptic neuron by exosomes. These exosomes enter the postsynaptic cell and some are transported to its nuclear zone (Waldenstrom et al., 2012). Neurons possess at least one other neurocomputational system—the familiar spike code mediated by electrochemical events. The spike code is fast and uses small molecules such as glutamate and acetylcholine as its effective agents. The epigenetic code is slower and uses protein synthesis as its effective agent. This rebuilds the hardware so as to process different inputs most effectively. The question then arises “How do these two codes interact?” This is one subject of this present paper. We also consider a second question “How do subsections of the epigenetic code interact with each other?” We end by considering the functional role of a part of the epigenetic code—DNA fragments carried by exosomes. The first section relates what little is known of the interactions of microRNAs (major ingredients of the epigenetic code) with ion channels (major ingredients of the spike code) particularly in the nervous system.

Movement Related Statistics of Grid Cell Firing

Event Abstract Back to Event Movement Related Statistics of Grid Cell Firing Carleen Kluger1, 2*, Alexander Mathis1, 3, Martin Stemmler1, 3 and Andreas V. Herz1, 3 1 Ludwig-Maximilians-Universität München, Bernstein Center for Computational Neuroscience Munich, Germany 2 Ludwig-Maximilians-Universität München, Department of Physics, Germany 3 Ludwig-Maximilians-Universität München, Division of Neurobiology, Germany The spatially modulated firing of grid cells in the entorhinal cortex (EC) [Hafting et al, 2005] has revolutionized our understanding of how the rodent brain represents space. Whether or how grid cells manage to disambiguate spatial location, velocity, and path and movement history by their spike code remains an open question, however. Here we study the correlation between the statistics of grid cell spiking and movement, based on linear track data recorded in the lab of E. I. Moser. Every passage through a firing field yields a spike train. We clustered spike trains resulting from similar runs through space, ordering them according to parameters such as mean velocity or the net deviation from a straight-line path. Using a cost-based spike train metric, we computed the relative similarity of the spike trains and found strong correlations of the spike trains with the order parameters derived from the movement statistics. Extending the spike-train metric to include information about the local field potential (LFP) in the theta band (7-12 Hz), we map the spike trains onto the cylinder of time and phase (Fig. 1) before computing distances between spike trains. This transformation reveals the role of the LFP in shaping the temporal sequence of spikes, highlighting the importance of the theta rhythm in the EC. While spikes exhibit position-dependent locking to the LFP, the spike count for a run through the grid field is generally Poisson-distributed. In contrast, place cells in hippocampus have been shown to exhibit spike counts with even higher variance. In addition, the spatial tuning of grid fields is nearly Gaussian, as evidenced by comparing kernel density estimates of firing probability with Gaussian fits. The statistical properties of grid cell firing are thus well captured by a doubly stochastic process modulated by both position and LFP; such a statistical model can then be used to estimate the coding properties of grid cells, based either on the spike count or the spike timing. Fig 1: A new metric for the parallel analysis of LFP phase and spike timing for Grid Cells recorded on the linear track Figure 1 Keywords: computational neuroscience Conference: Bernstein Conference on Computational Neuroscience, Berlin, Germany, 27 Sep - 1 Oct, 2010. Presentation Type: Presentation Topic: Bernstein Conference on Computational Neuroscience Citation: Kluger C, Mathis A, Stemmler M and Herz AV (2010). Movement Related Statistics of Grid Cell Firing. Front. Comput. Neurosci. Conference Abstract: Bernstein Conference on Computational Neuroscience. doi: 10.3389/conf.fncom.2010.51.00134 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 24 Sep 2010; Published Online: 24 Sep 2010. * Correspondence: Ms. Carleen Kluger, Ludwig-Maximilians-Universität München, Bernstein Center for Computational Neuroscience Munich, Martinsried, Germany, carleen.kluger@physik.uni-muenchen.de Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Carleen Kluger Alexander Mathis Martin Stemmler Andreas V Herz Google Carleen Kluger Alexander Mathis Martin Stemmler Andreas V Herz Google Scholar Carleen Kluger Alexander Mathis Martin Stemmler Andreas V Herz PubMed Carleen Kluger Alexander Mathis Martin Stemmler Andreas V Herz Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Amplification of Transducer Gain by Angiotensin II-Mediated Enhancement of Cortical Actin Density in Osmosensory Neurons

Osmosensory neurons transduce osmotic signals into a neural spike code that commands behavioral and endocrine responses that mediate body fluid homeostasis. Although changes in osmoregulatory reflex gain are known to occur under physiological and pathological conditions, the basis for this modulation is unknown. Here, we show that angiotensin II amplifies osmosensory transduction by enhancing the proportional relationship between osmolality, receptor potential, and action potential firing in rat supraoptic nucleus neurons. This effect is mediated by a phospholipase C- and protein kinase C-dependent increase in cellular mechanosensitivity that is associated with a rapid increase in cortical actin filament density. Preventing this increase with cytochalasin D eliminated the enhancement of mechanosensitivity, whereas enhancing actin filament density with jasplakinolide potentiated mechanosensitivity and occluded the effects of angiotensin II. These results indicate that a receptor-mediated increase in cortical actin density can enhance osmosensitivity in acutely isolated supraoptic neurons.

Retinal ganglion cells in model organisms: development, function and disease

The vertebrate retina is the most peripheral part of the central nervous system. Light signals from the visual environment are captured by photoreceptors where they are converted to electrical signals, which then are processed by the excitatory and inhibitory pathways within the retinal network, and converted at the level of the retinal ganglion cells (RGCs) into spike trains. This culmination represents the synthesis of all signal processing in the retina. Within the spike code, which travels along ganglion cell axons (the optic nerve) to higher visual centres, is the essential information that is processed in the remaining visual system and is required for visual perception and behaviour. The normal development and physiological function of RGCs are fascinating research areas, in which significant progress has been made in recent years. In addition, diseases have been identified that have a primary effect on the ability of these relay neurons to function. This issue of The Journal of Physiology contains eight articles that highlight some of the recent findings and current thinking in these areas.

How ionic conductances shape firing

Event Abstract Back to Event How ionic conductances shape firing Susanne Schreiber1* 1 BCCN Berlin, Germany Although for bare spike generation only very few ionic conductances would be needed, neurons express a large variety of ion channels with diverse properties. It can hence be assumed that these conductances fulfil an important role in shaping neural responses. Here we present mechanisms by which ionic conductances can influence two temporal characteristics of the spike code: spike-timing reliability and specific firing patterns. In the first case, we show that a cell’s ion channel composition determines how spike-timing precision depends on the input frequency. In addition, ionic conductances can also modify the extent to which noise affects spike-timing precision. In the second case, we analyse how a resonance in the subthreshold membrane potential, which is known to result from specific ionic conductances with slow dynamics, leads to clustered firing patterns. To fully account for the observed clustered patterns in cells of the entorhinal cortex, however, also spike-induced currents have to be considered. Conference: Bernstein Symposium 2008, Munich, Germany, 8 Oct - 10 Oct, 2008. Presentation Type: Oral Presentation Topic: All Abstracts Citation: Schreiber S (2008). How ionic conductances shape firing. Front. Comput. Neurosci. Conference Abstract: Bernstein Symposium 2008. doi: 10.3389/conf.neuro.10.2008.01.018 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 12 Nov 2008; Published Online: 12 Nov 2008. * Correspondence: Susanne Schreiber, BCCN Berlin, 82152 Planegg-Martinsried, Germany, s.schreiber@biologie.hu-berlin.de Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Susanne Schreiber Google Susanne Schreiber Google Scholar Susanne Schreiber PubMed Susanne Schreiber Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Retinogeniculate Transmission in Wakefulness

Despite popular belief that the primary function of the thalamus is to "gate" sensory inputs by state, few studies have attempted to directly characterize the efficacy of such gating in the awake, behaving animal. I measured the efficacy of retinogeniculate transmission in the awake cat by taking advantage of the fact that many neurons in the lateral geniculate nucleus (LGN) are dominated by a single retinal input, and that this input produces a distinct event known as the S-potential. Retinal input failed to produce an LGN action potential half of the time. However, success or failure was powerfully tied to the recency of the S-potential. Short intervals tend to be successful and long intervals unsuccessful. For four of 12 neurons, the probability that a given S-potential could cause a spike exceeded 90% if that S-potential was preceded by an S-potential within the previous 10 ms (100 Hz). Whereas this temporal influence on efficacy has been demonstrated extensively in anesthetized animals, wakefulness is different in several ways. Overall efficacy is better in wakefulness than in anesthesia, the durations of facilitating effects are briefer in wakefulness, efficacy of long intervals is superior in wakefulness, and the temporal dependence can be briefly disrupted by altering background illumination. The last two observations may be particularly significant. Increased success at long intervals in wakefulness provides additional evidence that the spike code of the anesthetized animal is not the spike code of the awake animal. Altering retinogeniculate efficacy by altering visual conditions undermines the influence inter-S-potential interval might have in determining efficacy in the real world. Finally, S-potential amplitude, duration, and even slope are dynamic and systematic within wakefulness; providing further support that the S-potential is the extracellular signature of the retinal EPSP.

Efficient auditory coding

The auditory neural code must serve a wide range of auditory tasks that require great sensitivity in time and frequency and be effective over the diverse array of sounds present in natural acoustic environments. It has been suggested that sensory systems might have evolved highly efficient coding strategies to maximize the information conveyed to the brain while minimizing the required energy and neural resources. Here we show that, for natural sounds, the complete acoustic waveform can be represented efficiently with a nonlinear model based on a population spike code. In this model, idealized spikes encode the precise temporal positions and magnitudes of underlying acoustic features. We find that when the features are optimized for coding either natural sounds or speech, they show striking similarities to time-domain cochlear filter estimates, have a frequency-bandwidth dependence similar to that of auditory nerve fibres, and yield significantly greater coding efficiency than conventional signal representations. These results indicate that the auditory code might approach an information theoretic optimum and that the acoustic structure of speech might be adapted to the coding capacity of the mammalian auditory system.

Perceptual Consequences of Disrupted Auditory Nerve Activity

Perceptual consequences of disrupted auditory nerve activity were systematically studied in 21 subjects who had been clinically diagnosed with auditory neuropathy (AN), a recently defined disorder characterized by normal outer hair cell function but disrupted auditory nerve function. Neurological and electrophysical evidence suggests that disrupted auditory nerve activity is due to desynchronized or reduced neural activity or both. Psychophysical measures showed that the disrupted neural activity has minimal effects on intensity-related perception, such as loudness discrimination, pitch discrimination at high frequencies, and sound localization using interaural level differences. In contrast, the disrupted neural activity significantly impairs timing related perception, such as pitch discrimination at low frequencies, temporal integration, gap detection, temporal modulation detection, backward and forward masking, signal detection in noise, binaural beats, and sound localization using interaural time differences. These perceptual consequences are the opposite of what is typically observed in cochlear-impaired subjects who have impaired intensity perception but relatively normal temporal processing after taking their impaired intensity perception into account. These differences in perceptual consequences between auditory neuropathy and cochlear damage suggest the use of different neural codes in auditory perception: a suboptimal spike count code for intensity processing, a synchronized spike code for temporal processing, and a duplex code for frequency processing. We also proposed two underlying physiological models based on desynchronized and reduced discharge in the auditory nerve to successfully account for the observed neurological and behavioral data. These methods and measures cannot differentiate between these two AN models, but future studies using electric stimulation of the auditory nerve via a cochlear implant might. These results not only show the unique contribution of neural synchrony to sensory perception but also provide guidance for translational research in terms of better diagnosis and management of human communication disorders.