Sensitivity of auditory cortical neurons to locations of signals and competing noise sources.

The present study examined cortical parallels to psychophysical signal detection and sound localization in the presence of background noise. The activity of single units or of small clusters of units was recorded in cortical area A2 of chloralose-anesthetized cats. Signals were 80-ms click trains that varied in location in the horizontal plane around the animal. Maskers were continuous broadband noises. In the focal masker condition, a single masker source was tested at various azimuths. In the diffuse masker condition, uncorrelated noise was presented from two speakers at +/-90 degrees lateral to the animal. For about 2/3 of units ("type A"), the presence of the masker generally reduced neural sensitivity to signals, and the effects of the masker depended on the relative locations of signal and masker sources. For the remaining 1/3 of units ("type B"), the masker reduced spike rates at low signal levels but often augmented spike rates at higher signal levels. Increases in spike rates of type B units were most common for signal sources in front of the ear contralateral to the recording site but tended to be independent of masker source location. For type A units, masker effects could be modeled as a shift toward higher levels of spike-rate- and spike-latency-versus-level functions. For a focal masker, the shift size decreased with increasing separation of signal and masker. That result resembled psychophysical spatial unmasking, i.e., improved signal detection by spatial separation of the signal from the noise source. For the diffuse masker condition, the shift size generally was constant across signal locations. For type A units, we examined the effects of maskers on cortical signaling of sound-source location, using an artificial-neural-network (ANN) algorithm. First, an ANN was trained to estimate the signal location in the quiet condition by recognizing the spike patterns of single units. Then we tested ANN responses for spike patterns recorded under various masker conditions. Addition of a masker generally altered spike patterns and disrupted ANN identification of signal location. That disruption was smaller, however, for signal and masker configurations in which the masker did not severely reduce units' spike rates. That result compared well with the psychophysical observation that listeners maintain good localization performance as long as signals are clearly audible.     

Information content of auditory cortical responses to time-varying acoustic stimuli

The present study explores the issue of cortical coding by spike count and timing using statistical and information theoretic methods. We have shown in previous studies that neurons in the auditory cortex of awake primates have an abundance of sustained discharges that could represent time-varying signals by temporal discharge patterns or mean firing rates. In particular, we found that a subpopulation of neurons can encode rapidly occurring sounds, such as a click train, with discharges that are not synchronized to individual stimulus events, suggesting a temporal-to-rate transformation. We investigated whether there were stimulus-specific temporal patterns embedded in these seemingly random spike times. Furthermore, we quantitatively analyzed the precision of spike timing at stimulus onset and during ongoing acoustic stimulation. The main findings are the following. 1) Temporal and rate codes may operate at separate stimulus domains or encode the same stimulus domain in parallel via different neuronal populations. 2) Spike timing was crucial to encode stimulus periodicity in "synchronized" neurons. 3) "Nonsynchronized" neurons showed little stimulus-specific spike timing information in their responses to time-varying signals. Such responses therefore represent processed (instead of preserved) information in the auditory cortex. And 4) spike timing on the occurrence of acoustic events was more precise at the first event than at successive ones and more precise with sparsely distributed events (longer time intervals between events) than with densely packed events. These results indicate that auditory cortical neurons mark sparse acoustic events (or onsets) with precise spike timing and transform rapidly occurring acoustic events into firing rate-based representations.     

Spatial sensitivity in field PAF of cat auditory cortex

We compared the spatial tuning properties of neurons in two fields [primary auditory cortex (A1) and posterior auditory field (PAF)] of cat auditory cortex. Broadband noise bursts of 80-ms duration were presented from loudspeakers throughout 360 degrees in the horizontal plane (azimuth) or 260 degrees in the vertical median plane (elevation). Sound levels varied from 20 to 40 dB above units' thresholds. We recorded neural spike activity simultaneously from 16 sites in field PAF and/or A1 of alpha-chloralose-anesthetized cats. We assessed spatial sensitivity by examining the dependence of spike count and response latency on stimulus location. In addition, we used an artificial neural network (ANN) to assess the information about stimulus location carried by spike patterns of single units and of ensembles of 2-32 units. The results indicate increased spatial sensitivity, more uniform distributions of preferred locations, and greater tolerance to changes in stimulus intensity among PAF units relative to A1 units. Compared to A1 units, PAF units responded at significantly longer latencies, and latencies varied more strongly with stimulus location. ANN analysis revealed significantly greater information transmission by spike patterns of PAF than A1 units, primarily reflecting the information transmitted by latency variation in PAF. Finally, information rates grew more rapidly with the number of units included in neural ensembles for PAF than A1. The latter finding suggests more accurate population coding of space in PAF, made possible by a more diverse population of neural response types.     

Spatiotemporally graded NMDA spike/plateau potentials in basal dendrites of neocortical pyramidal neurons

Glutamatergic inputs clustered over approximately 20-40 microm can elicit local N-methyl-D-aspartate (NMDA) spike/plateau potentials in terminal dendrites of cortical pyramidal neurons, inspiring the notion that a single terminal dendrite can function as a decision-making computational subunit. A typical terminal basal dendrite is approximately 100-200 microm long: could it function as multiple decision-making subunits? We test this by sequential focal stimulation of multiple sites along terminal basal dendrites of layer 5 pyramidal neurons in rat somatosensory cortical brain slices, using iontophoresis or uncaging of brief glutamate pulses. There was an approximately sevenfold spatial gradient in average spike/plateau amplitude measured at the soma, from approximately 3 mV for distal inputs to approximately 23 mV for proximal inputs. Spike/plateaus were NMDA receptor (NMDAR) conductance-dominated at all locations. Large Ca(2+) transients accompanied spike/plateaus over a approximately 10- to 40-microm zone around the input site; smaller Ca(2+) transients extended approximately uniformly to the dendritic tip. Spike/plateau duration grew with increasing glutamate and depolarization; high Ca(2+) zone size grew with spike/plateau duration. The minimum high Ca(2+) zone half-width (just above NMDA spike threshold) increased from distal (approximately 10 microm) to proximal locations (approximately 25 microm), as did the NMDA spike glutamate threshold. Depolarization reduced glutamate thresholds. Simulations exploring multi-site interactions based on this demonstrate that if appropriately timed and localized inputs occur in vivo, a single basal dendrite could correspond to a cascade of multiple co-operating dynamic decision-making subunits able to retain information for hundreds of milliseconds, with increasing influence on neural output from distal to proximal. Dendritic NMDA spike/plateaus are thus well-suited to support graded persistent firing.     

Influence of ionic conductances on spike timing reliability of cortical neurons for suprathreshold rhythmic inputs

Spike timing reliability of neuronal responses depends on the frequency content of the input. We investigate how intrinsic properties of cortical neurons affect spike timing reliability in response to rhythmic inputs of suprathreshold mean. Analyzing reliability of conductance-based cortical model neurons on the basis of a correlation measure, we show two aspects of how ionic conductances influence spike timing reliability. First, they set the preferred frequency for spike timing reliability, which in accordance with the resonance effect of spike timing reliability is well approximated by the firing rate of a neuron in response to the DC component in the input. We demonstrate that a slow potassium current can modulate the spike timing frequency preference over a broad range of frequencies. This result is confirmed experimentally by dynamic-clamp recordings from rat prefrontal cortical neurons in vitro. Second, we provide evidence that ionic conductances also influence spike timing beyond changes in preferred frequency. Cells with the same DC firing rate exhibit more reliable spike timing at the preferred frequency and its harmonics if the slow potassium current is larger and its kinetics are faster, whereas a larger persistent sodium current impairs reliability. We predict that potassium channels are an efficient target for neuromodulators that can tune spike timing reliability to a given rhythmic input.     

Sensitivity of auditory cortical neurons to the locations of leading and lagging sounds

We recorded unit activity in the auditory cortex (fields A1, A2, and PAF) of anesthetized cats while presenting paired clicks with variable locations and interstimulus delays (ISDs). In human listeners, such sounds elicit the precedence effect, in which localization of the lagging sound is impaired at ISDs less, similar10 ms. In the present study, neurons typically responded to the leading stimulus with a brief burst of spikes, followed by suppression lasting 100-200 ms. At an ISD of 20 ms, at which listeners report a distinct lagging sound, only 12% of units showed discrete lagging responses. Long-lasting suppression was found in all sampled cortical fields, for all leading and lagging locations, and at all sound levels. Recordings from awake cats confirmed this long-lasting suppression in the absence of anesthesia, although recovery from suppression was faster in the awake state. Despite the lack of discrete lagging responses at delays of 1-20 ms, the spike patterns of 40% of units varied systematically with ISD, suggesting that many neurons represent lagging sounds implicitly in their temporal firing patterns rather than explicitly in discrete responses. We estimated the amount of location-related information transmitted by spike patterns at delays of 1-16 ms under conditions in which we varied only the leading location or only the lagging location. Consistent with human psychophysical results, transmission of information about the leading location was high at all ISDs. Unlike listeners, however, transmission of information about the lagging location remained low, even at ISDs of 12-16 ms.     

Object perception in natural scenes: encoding by inferior temporal cortex simultaneously recorded neurons

The firing of inferior temporal cortex neurons is tuned to objects and faces, and in a complex scene, their receptive fields are reduced to become similar to the size of an object being fixated. These two properties may underlie how objects in scenes are encoded. An alternative hypothesis suggests that visual perception requires the binding of features of the visual target through spike synchrony in a neuronal assembly. To examine possible contributions of firing synchrony of inferior temporal neurons, we made simultaneous recordings of the activity of several neurons while macaques performed a visual discrimination task. The stimuli were presented in either plain or complex backgrounds. The encoding of information of neurons was analyzed using a decoding algorithm. Ninety-four percent to 99% of the total information was available in the firing rate spike counts, and the contribution of spike timing calculated as stimulus-dependent synchronization (SDS) added only 1-6% of information to the total that was independent of the spike counts in the complex background. Similar results were obtained in the plain background. The quantitatively small contribution of spike timing to the overall information available in spike patterns suggests that information encoding about which stimulus was shown by inferior temporal neurons is achieved mainly by rate coding. Furthermore, it was shown that there was little redundancy (6%) between the information provided by the spike counts of the simultaneously recorded neurons, making spike counts an efficient population code with a high encoding capacity.     

Information transmission and detection thresholds in the vestibular nuclei: single neurons vs. population encoding

Understanding how sensory neurons transmit information about relevant stimuli remains a major goal in neuroscience. Of particular relevance are the roles of neural variability and spike timing in neural coding. Peripheral vestibular afferents display differential variability that is correlated with the importance of spike timing; regular afferents display little variability and use a timing code to transmit information about sensory input. Irregular afferents, conversely, display greater variability and instead use a rate code. We studied how central neurons within the vestibular nuclei integrate information from both afferent classes by recording from a group of neurons termed vestibular only (VO) that are known to make contributions to vestibulospinal reflexes and project to higher-order centers. We found that, although individual central neurons had sensitivities that were greater than or equal to those of individual afferents, they transmitted less information. In addition, their velocity detection thresholds were significantly greater than those of individual afferents. This is because VO neurons display greater variability, which is detrimental to information transmission and signal detection. Combining activities from multiple VO neurons increased information transmission. However, the information rates were still much lower than those of equivalent afferent populations. Furthermore, combining responses from multiple VO neurons led to lower velocity detection threshold values approaching those measured from behavior (～ 2.5 vs. 0.5-1°/s). Our results suggest that the detailed time course of vestibular stimuli encoded by afferents is not transmitted by VO neurons. Instead, they suggest that higher vestibular pathways must integrate information from central vestibular neuron populations to give rise to behaviorally observed detection thresholds.     

Spike timing in CA3 pyramidal cells during behavior: implications for synaptic transmission

Spike timing is thought to be an important mechanism for transmitting information in the CNS. Recent studies have emphasized millisecond precision in spike timing to allow temporal summation of rapid synaptic signals. However, spike timing over slower time scales could also be important, through mechanisms including activity-dependent synaptic plasticity or temporal summation of slow postsynaptic potentials (PSPs) such as those mediated by kainate receptors. To determine the extent to which these slower mechanisms contribute to information processing, it is first necessary to understand the properties of behaviorally relevant spike timing over this slow time scale. In this study, we examine the activity of CA3 pyramidal cells during the performance of a complex behavioral task in rats. Sustained firing rates vary over a wide range, and the firing rate of a cell is poorly correlated with the behavioral cues to which the cell responds. Nonrandom interactions between successive spikes can last for several seconds, but the nonrandom distribution of interspike intervals (ISIs) can account for the majority of nonrandom multi-spike patterns. During a stimulus, cellular responses are temporally complex, causing a shift in spike timing that favors intermediate ISIs over short and long ISIs. Response discrimination between related stimuli occurs through changes in both response time-course and response intensity. Precise synchrony between cells is limited, but loosely correlated firing between cells is common. This study indicates that spike timing is regulated over long time scales and suggests that slow synaptic mechanisms could play a substantial role in information processing in the CNS.     

Auditory discrimination of amplitude modulations based on metric distances of spike trains

Sound envelope cues play a crucial role for the recognition and discrimination of communication signals in diverse taxa, such as vertebrates and arthropods. Using a classification based on metric similarities of spike trains we investigate how well amplitude modulations (AMs) of sound signals can be distinguished at three levels of the locust's auditory pathway: receptors and local and ascending neurons. The spike train metric has the advantage of providing information about the necessary evaluation time window and about the optimal temporal resolution of processing, thereby yielding clues to possible coding principles. It further allows one to disentangle the respective contributions of spike count and spike timing to the fidelity of discrimination. These results are compared with the traditional paradigm using modulation transfer functions. Spike trains of receptors and two primary-like local interneurons enable an excellent discrimination of different AM frequencies, up to about 150 Hz. In these neurons discriminability depends almost completely on the timing of spikes, which must be evaluated with a temporal resolution of <5 ms. Even short spike-train segments of 150 ms, equivalent to five to eight spikes, suffice for a high (70%) discrimination performance. For the third level of processing, the ascending interneurons, the overall discrimination accuracy is reduced. Spike count differences become more important for the discrimination whereas the exact timing of spikes contributes less. This shift in temporal resolution does not primarily depend on the investigated stimulus space. Rather it appears to reflect a transformation of how amplitude modulations are represented at more central stages of processing.     

EEG oscillations at 600 Hz are macroscopic markers for cortical spike bursts

The human electroencephalogram (EEG) is generated predominantly by synchronised cortical excitatory postsynaptic potentials oscillating at frequencies <100 Hz. Unusually, EEG responses to electrical nerve stimulation contain brief bursts of high-frequency (600 Hz) wavelets. Here we show, in awake monkeys, that a subset of primary somatosensory cortex single units consistently fires both bursts and single spikes phase-locked to EEG wavelets. Spike bursts were also evoked by tactile stimuli, proving that this is a natural response mode. EEG wavelets at 600 Hz may therefore permit non-invasive assessment of population spike timing in human cortex.     

Spike-timing precision underlies the coding efficiency of auditory receptor neurons

Sensory systems must translate incoming signals quickly and reliably so that an animal can act successfully in its environment. Even at the level of receptor neurons, however, functional aspects of the sensory encoding process are not yet fully understood. Specifically, this concerns the question how stimulus features and neural response characteristics lead to an efficient transmission of sensory information. To address this issue, we have recorded and analyzed spike trains from grasshopper auditory receptors, while systematically varying the stimulus statistics. The stimulus variations profoundly influenced the efficiency of neural encoding. This influence was largely attributable to the presence of specific stimulus features that triggered remarkably precise spikes whose trial-to-trial timing variability was as low as 0.15 ms--one order of magnitude shorter than typical stimulus time scales. Precise spikes decreased the noise entropy of the spike trains, thereby increasing the rate of information transmission. In contrast, the total spike train entropy, which quantifies the variety of different spike train patterns, hardly changed when stimulus conditions were altered, as long as the neural firing rate remained the same. This finding shows that stimulus distributions that were transmitted with high information rates did not invoke additional response patterns, but instead displayed exceptional temporal precision in their neural representation. The acoustic stimuli that led to the highest information rates and smallest spike-time jitter feature pronounced sound-pressure deflections lasting for 2-3 ms. These upstrokes are reminiscent of salient structures found in natural grasshopper communication signals, suggesting that precise spikes selectively encode particularly important aspects of the natural stimulus environment.     

Action potential timing precision in dorsal cochlear nucleus pyramidal cells

Many studies of the dorsal cochlear nucleus (DCN) have focused on the representation of acoustic stimuli in terms of average firing rate. However, recent studies have emphasized the role of spike timing in information encoding. We sought to ascertain whether DCN pyramidal cells might employ similar strategies and to what extent intrinsic excitability regulates spike timing. Gaussian distributed low-pass noise current was injected into pyramidal cells in a brain slice preparation. The shuffled autocorrelation-based analysis was used to compute a correlation index of spike times across trials. The noise causes the cells to fire with temporal precision (SD congruent with 1-2 ms) and high reproducibility. Increasing the coefficient of variation of the noise improved the reproducibility of the spike trains, whereas increasing the firing rate of the neuron decreased the neurons' ability to respond with predictable patterns of spikes. Simulated inhibitory postsynaptic potentials superimposed on the noise stimulus enhanced spike timing for >300 ms, although the enhancement was greatest during the first 100 ms. We also found that populations of pyramidal neurons respond to the same noise stimuli with correlated spike trains, suggesting that ensembles of neurons in the DCN receiving shared input can fire with similar timing. These results support the hypothesis that spike timing can be an important aspect of information coding in the DCN.     

A role for short-term synaptic facilitation and depression in the processing of intensity information in the auditory brain stem

The nature of the synaptic connection from the auditory nerve onto the cochlear nucleus neurons has a profound impact on how sound information is transmitted. Short-term synaptic plasticity, by dynamically modulating synaptic strength, filters information contained in the firing patterns. In the sound-localization circuits of the brain stem, the synapses of the timing pathway are characterized by strong short-term depression. We investigated the short-term synaptic plasticity of the inputs to the bird's cochlear nucleus angularis (NA), which encodes intensity information, by using chick embryonic brain slices and trains of electrical stimulation. These excitatory inputs expressed a mixture of short-term facilitation and depression, unlike those in the timing nuclei that only depressed. Facilitation and depression at NA synapses were balanced such that postsynaptic response amplitude was often maintained throughout the train at high firing rates (>100 Hz). The steady-state input rate relationship of the balanced synapses linearly conveyed rate information and therefore transmits intensity information encoded as a rate code in the nerve. A quantitative model of synaptic transmission could account for the plasticity by including facilitation of release (with a time constant of approximately 40 ms), and a two-step recovery from depression (with one slow time constant of approximately 8 s, and one fast time constant of approximately 20 ms). A simulation using the model fit to NA synapses and auditory nerve spike trains from recordings in vivo confirmed that these synapses can convey intensity information contained in natural train inputs.     

Spike timing-dependent plasticity: from synapse to perception

Information in the nervous system may be carried by both the rate and timing of neuronal spikes. Recent findings of spike timing-dependent plasticity (STDP) have fueled the interest in the potential roles of spike timing in processing and storage of information in neural circuits. Induction of long-term potentiation (LTP) and long-term depression (LTD) in a variety of in vitro and in vivo systems has been shown to depend on the temporal order of pre- and postsynaptic spiking. Spike timing-dependent modification of neuronal excitability and dendritic integration was also observed. Such STDP at the synaptic and cellular level is likely to play important roles in activity-induced functional changes in neuronal receptive fields and human perception.     

Excess synchrony in motor cortical neurons provides redundant direction information with that from coarse temporal measures

Previous studies have shown that measures of fine temporal correlation, such as synchronous spikes, across responses of motor cortical neurons carries more directional information than that predicted from statistically independent neurons. It is also known, however, that the coarse temporal measures of responses, such as spike count, are not independent. We therefore examined whether the information carried by coincident firing was related to that of coarsely defined spike counts and their correlation. Synchronous spikes were counted in the responses from 94 pairs of simultaneously recorded neurons in primary motor cortex (MI) while monkeys performed arm movement tasks. Direct measurement of the movement-related information indicated that the coincident spikes (1- to 5-ms precision) carry approximately 10% of the information carried by a code of the two spike counts. Inclusion of the numbers of synchronous spikes did not add information to that available from the spike counts and their coarse temporal correlation. To assess the significance of the numbers of coincident spikes, we extended the stochastic spike count matched (SCM) model to include correlations between spike counts of the individual neural responses and slow temporal dependencies within neural responses (approximately 30 Hz bandwidth). The extended SCM model underestimated the numbers of synchronous spikes. Therefore as with previous studies, we found that there were more synchronous spikes in the neural data than could be accounted for by this stochastic model. However, the SCM model accounts for most (R(2) = 0.93 +/- 0.05, mean +/- SE) of the differences in the observed number of synchronous spikes to different directions of arm movement, indicating that synchronous spiking is directly related to spike counts and their broad correlation. Further, this model supports the information theoretic analysis that the synchronous spikes do not provide directional information beyond that available from the firing rates of the same pool of directionally tuned MI neurons. These results show that detection of precisely timed spike patterns above chance levels does not imply that those spike patterns carry information unavailable from coarser population codes but leaves open the possibility that excess synchrony carries other forms of information or serves other roles in cortical information processing not studied here.     

A learning rule for the emergence of stable dynamics and timing in recurrent networks

Neural dynamics within recurrent cortical networks is an important component of neural processing. However, the learning rules that allow networks composed of hundreds or thousands of recurrently connected neurons to develop stable dynamical states are poorly understood. Here I use a neural network model to examine the emergence of stable dynamical states within recurrent networks. I describe a learning rule that can account both for the development of stable dynamics and guide networks to states that have been observed experimentally, specifically, states that instantiate a sparse code for time. Across trials, each neuron fires during a specific time window; by connecting the neurons to a hypothetical set of output units, it is possible to generate arbitrary spatial-temporal output patterns. Intertrial jitter of the spike time of a given neuron increases as a direct function of the delay at which it fires. These results establish a learning rule by which cortical networks can potentially process temporal information in a self-organizing manner, in the absence of specialized timing mechanisms.     

Temporal encoding of two-dimensional patterns by single units in primate inferior temporal cortex. III. Information theoretic analysis

Ablation and single-unit studies in primates have shown that inferior temporal (IT) cortex is important for pattern discrimination. The first paper in this series suggested that single units in IT cortex of alert monkeys respond to a set of two-dimensional patterns with complex temporal modulation of their spike trains. The second paper quantified the waveform of the modulated responses of IT neurons with principal components and demonstrated that the coefficients of two to four of the principal components were stimulus dependent. Although the coefficients of the principal components are uncorrelated, it is possible that they are not statistically independent. That is, several coefficients could be determined by the same feature of the stimulus, and thus could be conveying the same information. The final part of this study examined this issue by comparing the amount of information about the stimulus that can be conveyed by two codes: a temporal waveform code derived from the coefficients of the first three principal components and a mean rate code derived from the spike count. We considered the neuron to be an information channel conveying messages about stimulus parameters. Previous applications of information theory to neurophysiology have dealt either with the theoretical capacity of neuronal channels or the temporal distribution of information within the spike train. This previous work usually used a general binary code to represent the spike train of a neuron's response. Such a general approach yields no indication of the nature of the neuron's intrinsic coding scheme because it depends only on the timing of spikes in the response. In particular, it is independent of any statistical properties of the responses. Our approach uses the principal components of the response waveform to derive a code for representing information about the stimuli. We regard this code as an indication of the neuron's intrinsic coding scheme, because it is based on the statistical properties of the neuronal responses. We measured how much information about the stimulus was present in the neuron's responses. This transmitted information was calculated for codes based on either the spike count or on the first three principal components of the response waveform. The information transmitted by each of the first three principal components was largely independent of that transmitted by the others. It was found that the average amount of information transmitted by the principal components was about twice as large as that transmitted by the spike count.(ABSTRACT TRUNCATED AT 400 WORDS)     

Synaptic transmission of chaotic spike trains between primary afferent fiber and spinal dorsal horn neuron in the rat

Primary sensory neurons can generate irregular burst firings in which the existence of significant deterministic behaviors of chaotic dynamics has been proved with nonlinear time series analysis. But how well the deterministic characteristics and neural information of presynaptic chaotic spike trains were transmitted into postsynaptic spike trains is still an open question. Here we investigated the synaptic transmission of chaotic spike trains between primary Adelta afferent fiber and spinal dorsal horn neuron. Two kinds of basic stimulus unit, brief burst and single pulse, were employed by us to comprise chaotic stimulus trains. For time series analysis, we defined "events" as the longest sequences of spikes with all interspike intervals less than or equal to a certain threshold and extracted the interevent intervals (IEIs) from spike trains. Return map analysis of the IEI series showed that the main temporal structure of chaotic input trains could be detected in postsynaptic output trains, especially under brief-burst stimulation. Using correlation dimension and nonlinear prediction methods, we found that synaptic transmission could influence the nonlinear characteristics of chaotic trains, such as fractal dimension and short-term predictability, with greater influence made under single-pulse stimulation. By calculating the mutual information between input and output trains, we found the information carried by presynaptic spike trains could not be completely transmitted at primary afferent synapses, and that brief bursts could more reliably transmit the information carried by chaotic input trains across synapses. These results indicate that although unreliability exists during synaptic transmission, the main deterministic characteristics of chaotic burst trains can be transmitted across primary afferent synapses. Moreover, brief bursts that come from the periphery can more reliably transmit neural information between primary afferent fibers and spinal dorsal horn neurons.     

Auditory cortical images of cochlear-implant stimuli: dependence on electrode configuration.

This study examines patterns of auditory cortical activity elicited by single-pulse cochlear implant stimuli that vary in electrode configuration, cochlear place of stimulation, and stimulus level. Recordings were made from the primary auditory cortex (area A1) of ketamine-anesthetized guinea pigs. The spatiotemporal pattern of neural spike activity was measured simultaneously across 16 cortical locations spanning approximately 2-3 octaves of the tonotopic axis. Such a pattern, averaged over 40 presentations of any particular stimulus, was defined as the "cortical image" of that stimulus. Acutely deafened guinea pigs were implanted with a 6-electrode animal version of the 22-electrode Nucleus banded electrode array (Cochlear). Cochlear electrode configurations consisted of monopolar (MP), bipolar (BP + N) with N inactive electrodes between the active and return electrodes (0 < or = N < or = 4), tripolar (TP) with one active electrode and two flanking return electrodes, and common ground (CG) with one active electrode and as many as five return electrodes. Cortical images typically showed a focus of maximum spike probability and minimum latency. Spike probabilities tended to decrease, and latencies tended to increase, with increasing cortical distance from that focus. Cortical images of TP stimuli were the most spatially compact, followed by BP + N images, and then MP images, which were the broadest. Images of CG stimuli were rather variable across animals and stimulus channels. The locations of cortical images shifted systematically from caudal to rostral as the cochlear place of stimulation changed from basal to apical. At the most sensitive cortical site for each condition, the dynamic ranges over which spike rates increased with increased current level were restricted to about 1-2 dB, regardless of configuration. Dynamic ranges tended to increase with increasing cortical distance from the most sensitive site. Electrode configurations that produced compact cortical images (e.g., TP and BP + 0) showed the greatest range of thresholds within each cortical image and the largest dynamic range at cortical sites removed from the most sensitive site.