Separate mechanisms control spike numbers and inter-spike intervals in transient responses of cat auditory cortex neurons

Temporal coding of echo spectral shape in the bat auditory cortex

Echolocating bats rely upon spectral interference patterns in echoes to reconstruct fine details of a reflecting object’s shape. However, the acoustic modulations required to do this are extremely brief, raising questions about how their auditory cortex encodes and processes such rapid and fine spectrotemporal details. Here, we tested the hypothesis that biosonar target shape representation in the primary auditory cortex (A1) is more reliably encoded by changes in spike timing (latency) than spike rates and that latency is sufficiently precise to support a synchronization-based ensemble representation of this critical auditory object feature space. To test this, we measured how the spatiotemporal activation patterns of A1 changed when naturalistic spectral notches were inserted into echo mimic stimuli. Neurons tuned to notch frequencies were predicted to exhibit longer latencies and lower mean firing rates due to lower signal amplitudes at their preferred frequencies, and both were found to occur. Comparative analyses confirmed that significantly more information was recoverable from changes in spike times relative to concurrent changes in spike rates. With this data, we reconstructed spatiotemporal activation maps of A1 and estimated the level of emerging neuronal spike synchrony between cortical neurons tuned to different frequencies. The results support existing computational models, indicating that spectral interference patterns may be efficiently encoded by a cascading tonotopic sequence of neural synchronization patterns within an ensemble of network activity that relates to the physical features of the reflecting object surface.

Echolocating bats rely upon spectral interference patterns in echoes to reconstruct fine details of a reflecting object’s shape. This study shows that the latency shifts induced by spectral notch patterns can provide the foundation for an avalanche of neuronal synchrony that is sufficient to support encoding of auditory object shape features during active biosonar.

How do auditory cortex neurons represent communication sounds?

A major goal in auditory neuroscience is to characterize how communication sounds are represented at the cortical level. The present review aims at investigating the role of auditory cortex in the processing of speech, bird songs and other vocalizations, which all are spectrally and temporally highly structured sounds. Whereas earlier studies have simply looked for neurons exhibiting higher firing rates to particular conspecific vocalizations over their modified, artificially synthesized versions, more recent studies determined the coding capacity of temporal spike patterns, which are prominent in primary and non-primary areas (and also in non-auditory cortical areas). In several cases, this information seems to be correlated with the behavioral performance of human or animal subjects, suggesting that spike-timing based coding strategies might set the foundations of our perceptive abilities. Also, it is now clear that the responses of auditory cortex neurons are highly nonlinear and that their responses to natural stimuli cannot be predicted from their responses to artificial stimuli such as moving ripples and broadband noises. Since auditory cortex neurons cannot follow rapid fluctuations of the vocalizations envelope, they only respond at specific time points during communication sounds, which can serve as temporal markers for integrating the temporal and spectral processing taking place at subcortical relays. Thus, the temporal sparse code of auditory cortex neurons can be considered as a first step for generating high level representations of communication sounds independent of the acoustic characteristic of these sounds. This article is part of a Special Issue entitled "Communication Sounds and the Brain: New Directions and Perspectives".

Neural correlates of auditory temporal-interval discrimination in cats

Auditory temporal cues are very important in the perception of speech; nevertheless, the neural correlates underlying even a simple temporal task, such as interval discrimination, remain unclear, mainly due to the lack of comparable data of psychophysical and electrophysiological experiments in the same species. To address this, we measured both behavioral and neural responses in cats. Cats' ability to discriminate differences in sound intervals was tested by presenting two identical pure tone markers interrupted by intervals ranging from 10 to 320ms duration. All three subjects could accurately discriminate tones of 80-320ms interval from those of 10ms interval (correct rate>75%), but could not discriminate 20-40ms interval from 10ms interval. Neural responses to the same stimuli were recorded in the primary auditory cortex (A1) of three others awake cats. Consistent with previous studies, we found that the majority of A1 neurons showed a suppressed response to the second tone, and the amount of suppression generally increased with the decrease of intertone interval. Neurometric analysis revealed that neural responses could be used to discriminate the intertone interval, while discrimination performance was dependent on temporal precision to read the neural information. When spike activities were analyzed by 100ms bin size, 80% of neurometric functions matched the cats' psychometric function, suggesting a possible correlation between A1 activities and interval perception.

Neural codes in the thalamocortical auditory system: from artificial stimuli to communication sounds

Over the last 15 years, an increasing number of studies have described the responsiveness of thalamic and cortical neurons to communication sounds. Whereas initial studies have simply looked for neurons exhibiting higher firing rate to conspecific vocalizations over their modified, artificially synthesized versions, more recent studies determine the relative contribution of "rate coding" and "temporal coding" to the information transmitted by spike trains. In this article, we aim at reviewing the different strategies employed by thalamic and cortical neurons to encode information about acoustic stimuli, from artificial to natural sounds. Considering data obtained with simple stimuli, we first illustrate that different facets of temporal code, ranging from a strict correspondence between spike-timing and stimulus temporal features to more complex coding strategies, do already exist with artificial stimuli. We then review lines of evidence indicating that spike-timing provides an efficient code for discriminating communication sounds from thalamus, primary and non-primary auditory cortex up to frontal areas. As the neural code probably developed, and became specialized, over evolution to allow precise and reliable processing of sounds that are of survival value, we argue that spike-timing based coding strategies might set the foundations of our perceptive abilities.

Processing of broadband stimuli across A1 layers in young and aged rats

Presbycusis can be considered a slow age-related peripheral and central deterioration of auditory function which manifests itself as deficits in speech comprehension, especially in noisy environments. The present study examined neural correlates of a simple broadband noise stimulus in primary auditory cortex (A1) of young and aged Fischer-Brown Norway (FBN) rats. Age-related changes in unit responses to broadband noise bursts and spontaneous activity were simultaneously recorded across A1 layers using a single shank, 16-channel electrode. Noise bursts were presented contralateral to the left A1 at 80 dB SPL. Aged A1 units displayed increased spontaneous (29%), peak (24%), and steady state response rates (38%) than did young A1 units. This was true across all A1 layers, although age-related differences were significantly greater for layers I-III (43% vs 18%) than lower layers. There was a significant age-related difference in the depth and duration of post-onset suppression between young and aged upper layer A1 units. The present functional differences across layers were consistent with studies showing greatest losses of gamma-aminobutyric acid (GABA) markers in superficial layers of A1 and with anatomic studies showing highest levels of inhibitory neurons located in superficial cortical layers. The present findings were also consistent with aging studies suggesting loss of functional inhibition in other cortical sensory systems.

Study of the right ear advantage on gap detection tests

Temporal resolution hearing skills are based on the minimum time necessary to segregate or solve acoustic events. This skill is fundamental for speech comprehension and can be assessed by gap detection tests. Some studies point to a right ear advantage over the left ear in temporal resolution tasks, since there is a preferential role of the left hemisphere in analyzing the temporal aspects of the acoustic stimulus.

Aim

determine if there are response differences (gap detection thresholds and percentage of correct answers) between right and left ears in a gap detection test. Study: experimental.

Materials and Methods

the gap detection test was applied to 100 adult individuals, after carrying out other audiologic tests in order to rule out possible hearing and/or auditory processing disorders.

Results

We observed gap detection thresholds and average correct answers percentages, which were similar for both ears, regardless of which ear started the test.

Conclusion

There was no ear advantage in the gap detection task.

First spike latency and spike count as functions of tone amplitude and frequency in the inferior colliculus of mice

Spike counts (SC) or, spike rate and first spike latency (FSL), are both used to evaluate the responses of neurons to amplitudes and frequencies of acoustic stimuli. However, it is unclear which one is more suitable as a parameter for evaluating the responses of neurons to acoustic amplitudes and frequencies, since systematic comparisons between SC and FSL tuned to different amplitudes and frequencies, are scarce. This study systematically compared the precision and stability (i.e., the resolution and the coefficient variation, CV) of SC- and FSL-function as frequencies and amplitudes in the inferior colliculus of mice. The results showed that: (1) the SC-amplitude functions were of diverse shape (monotonic, nonmonotonic and saturated) whereas the FSL-amplitude functions were in close registration, in which FSL decreased with the increase of amplitude and no paradoxical (an increase in FSL with increasing amplitude) or constant (an independence of FSL on amplitude) neuron was observed; (2) the discriminability (resolution) of differences in amplitude and frequency based on FSL are higher than those based on SC; (3) the CVs of FSL for low amplitude stimuli were smaller than those of SC; (4) the fraction of neurons for which BF=CF (within +/-500Hz) obtained from FSL was higher than that from SC at any amplitude of sound. Therefore, SC and FSL may vary, independent from each other and represent different parameters of an acoustic stimulus, but FSL with its precision and stability appears to be a better parameter than SC in evaluation of the response of a neuron to frequency and amplitude in mouse inferior colliculus.

Processing of sounds by population spikes in a model of primary auditory cortex

We propose a model of the primary auditory cortex (A1), in which each iso-frequency column is represented by a recurrent neural network with short-term synaptic depression. Such networks can emit Population Spikes, in which most of the neurons fire synchronously for a short time period. Different columns are interconnected in a way that reflects the tonotopic map in A1, and population spikes can propagate along the map from one column to the next, in a temporally precise manner that depends on the specific input presented to the network. The network, therefore, processes incoming sounds by precise sequences of population spikes that are embedded in a continuous asynchronous activity, with both of these response components carrying information about the inputs and interacting with each other. With these basic characteristics, the model can account for a wide range of experimental findings. We reproduce neuronal frequency tuning curves, whose width depends on the strength of the intracortical inhibitory and excitatory connections. Non-simultaneous two-tone stimuli show forward masking depending on their temporal separation, as well as on the duration of the first stimulus. The model also exhibits non-linear suppressive interactions between sub-threshold tones and broad-band noise inputs, similar to the hypersensitive locking suppression recently demonstrated in auditory cortex. We derive several predictions from the model. In particular, we predict that spontaneous activity in primary auditory cortex gates the temporally locked responses of A1 neurons to auditory stimuli. Spontaneous activity could, therefore, be a mechanism for rapid and reversible modulation of cortical processing.

Responses of neurons in primary auditory cortex (A1) to pure tones in the halothane-anesthetized cat

The responses of primary auditory cortex (A1) neurons to pure tones in anesthetized animals are usually described as having mostly narrow, unimodal frequency tuning and phasic responses. Thus A1 neurons are believed not to carry much information about pure tones beyond sound onset. In awake cats, however, tuning may be wider and responses may have substantially longer duration. Here we analyze frequency-response areas (FRAs) and temporal-response patterns of 1,828 units in A1 of halothane-anesthetized cats. Tuning was generally wide: the total bandwidth at 40 dB above threshold was 4 octaves on average. FRA shapes were highly variable and many were diffuse, not fitting into standard classification schemes. Analyzing the temporal patterns of the largest responses of each unit revealed that only 9% of the units had pure onset responses. About 40% of the units had sustained responses throughout stimulus duration (115 ms) and 13% of the units had significant and informative responses lasting 300 ms and more after stimulus offset. We conclude that under halothane anesthesia, neural responses show many of the characteristics of awake responses. Furthermore, A1 units maintain sensory information in their activity not only throughout sound presentation but also for hundreds of milliseconds after stimulus offset, thus possibly playing a role in sensory memory.

Binary spiking in auditory cortex

Neurons are often assumed to operate in a highly unreliable manner: a neuron can signal the same stimulus with a variable number of action potentials. However, much of the experimental evidence supporting this view was obtained in the visual cortex. We have, therefore, assessed trial-to-trial variability in the auditory cortex of the rat. To ensure single-unit isolation, we used cell-attached recording. Tone-evoked responses were usually transient, often consisting of, on average, only a single spike per stimulus. Surprisingly, the majority of responses were not just transient, but were also binary, consisting of 0 or 1 action potentials, but not more, in response to each stimulus; several dramatic examples consisted of exactly one spike on 100% of trials, with no trial-to-trial variability in spike count. The variability of such binary responses differs from comparably transient responses recorded in visual cortical areas such as area MT, and represent the lowest trial-to-trial variability mathematically possible for responses of a given firing rate. Our study thus establishes for the first time that transient responses in auditory cortex can be described as a binary process, rather than as a highly variable Poisson process. These results demonstrate that cortical architecture can support a more precise control of spike number than was previously recognized, and they suggest a re-evaluation of models of cortical processing that assume noisiness to be an inevitable feature of cortical codes.

Auditory cortical responses elicited in awake primates by random spectrum stimuli

Contrary to findings in subcortical auditory nuclei, auditory cortex neurons have traditionally been described as spiking only at the onsets of simple sounds such as pure tones or bandpass noise and to acoustic transients in complex sounds. Furthermore, primary auditory cortex (A1) has traditionally been described as mostly tone responsive and the lateral belt area of primates as mostly noise responsive. The present study was designed to unify the study of these two cortical areas using random spectrum stimuli (RSS), a new class of parametric, wideband, stationary acoustic stimuli. We found that 60% of all neurons encountered in A1 and the lateral belt of awake marmoset monkeys (Callithrix jacchus) showed significant changes in firing rates in response to RSS. Of these, 89% showed sustained spiking in response to one or more individual RSS, a substantially greater percentage than would be expected from traditional studies, indicating that RSS are well suited for studying these two cortical areas. When firing rates elicited by RSS were used to construct linear estimates of frequency tuning for these sustained responders, the shape of the estimate function remained relatively constant throughout the stimulus interval and across the stimulus properties of mean sound level, spectral density, and spectral contrast. This finding indicates that frequency tuning computed from RSS reflects a robust estimate of the actual tuning of a neuron. Use of this estimate to predict rate responses to other RSS, however, yielded poor results, implying that auditory cortex neurons integrate information across frequency nonlinearly. No systematic difference in prediction quality between A1 and the lateral belt could be detected.

Time course of tonal frequency-response-area of primary auditory cortex neurons in alert cats

Cells in the A1 auditory cortex of alert animals show various response time-courses during pure-tone stimuli: tonic, phasic-tonic, and phasic. Previously the time course of the spike firing rates was examined at a characteristic frequency (CF) or in a range of frequencies including CF. We investigated time-course of the frequency-response-area (FRA) during pure-tone stimuli in A1 cells of alert cats. The short rise/fall time (0.1-2 ms) and long stimulus duration (0.5 s) was used for investigation of the time course. FRA changed with time drastically in the phasic cells, mildly in the phasic-tonic cells, but not in the tonic cells. The best-response frequency (BF) within FRA was constant throughout the stimulus duration in the tonic and phasic-tonic cells, but was difficult to define in the phasic cells. The phasic firing properties of the phasic cells were preserved even during the bandnoise stimuli at various bandwidth and spectral locations. The variability of FRA time-course between cell types may play a role for analyzing auditory spectral cues that vary with a wide range of time constant.

Synaptic modulation of the interspike interval signatures of bursting pyloric neurons

The pyloric network of the lobster stomatogastric nervous system is one of the best described assemblies of oscillatory neurons producing bursts of action potentials. While the temporal patterns of bursts have been investigated in detail, those of spikes have received less attention. Here we analyze the intraburst firing patterns of pyloric neurons and the synaptic interactions shaping their dynamics in millisecond time scales not performed before. We find that different pyloric neurons express characteristic, cell-specific firing patterns in their bursts. Nonlinear analysis of the interspike intervals (ISIs) reveals distinctive temporal structures ('interspike interval signatures'), which are found to depend on the synaptic connectivity of the network. We compare ISI patterns of the pyloric dilator (PD), lateral pyloric (LP), and ventricular dilator (VD) neurons in 1) normal conditions, 2) after blocking glutamatergic synaptic connections, and 3) in various functional configurations of the three neurons. Manipulation of the synaptic connectivity results in characteristic changes in the ISI signatures of the postsynaptic neurons. The intraburst firing pattern of the PD neuron is regularized by the inhibitory synaptic connection from the LP neuron as revealed in current-clamp experiments and also as reconstructed with a dynamic clamp. On the other hand, mutual inhibition between the LP and VD neurons tend to produce more irregular bursts with increased spike jitter. The results show that synaptic interactions fine-tune the output of pyloric neurons. The present data also suggest a way of processing of synaptic information: bursting neurons are capable of encoding incoming signals by altering the fine structure of their intraburst spike patterns.

Computation by ensemble synchronization in recurrent networks with synaptic depression

While computation by ensemble synchronization is considered to be a robust and efficient way for information processing in the cortex (C. Von der Malsburg and W. Schneider (1986) Biol. Cybern. 54: 29-40; W. Singer (1994) Inter. Rev. Neuro. 37: 153-183; J.J. Hopfield (1995) Nature 376: 33-36; E. Vaadia et al. (1995) Nature 373: 515-518), the neuronal mechanisms that might be used to achieve it are yet to be uncovered. Here we analyze a neural network model in which the computations are performed by near coincident firing of neurons in response to external inputs. This near coincident firing is enabled by activity dependent depression of inter-neuron connections. We analyze the network behavior by using a mean-field approximation, which allows predicting the network response to various inputs. We demonstrate that the network is very sensitive to temporal aspects of the inputs. In particular, periodically applied inputs of increasing frequency result in different response profiles. Moreover, applying combinations of different stimuli lead to a complex response, which cannot be easily predicted from responses to individual components. These results demonstrate that networks with synaptic depression can perform complex computations on time-dependent inputs utilizing the ability to generate temporally synchronous firing of single neurons.

Central auditory onset responses, and temporal asymmetries in auditory perception

Historically, central auditory responses have been studied for their sensitivity to various parameters of tone and noise burst stimulation, with response rate plotted as a function of the stimulus variable. The responses themselves are often quite brief, and locked in time to stimulus onset. In the stimulus amplitude domain, it has recently become clear that these responses are actually driven by properties of the stimulus' onset transient, and this has had important implications for how we interpret responses to manipulations of tone (or noise) burst plateau level. That finding was important in its own right, but a more general scrutiny of the available neurophysiological and psychophysical evidence reveals that there is a significant asymmetry in the neurophysiological and perceptual processing of stimulus onsets and offsets: sound onsets have a more elaborate neurophysiological representation, and receive a greater perceptual weighting. Hypotheses about origins of the asymmetries, derived independently from psychophysics and from neurophysiology, have in common a response threshold mechanism which adaptively tracks the ongoing level of stimulation.

Tonal response patterns of primary auditory cortex neurons in alert cats

The firing rates of primary auditory cortex (A1) neurons are known to be modulated only at the onset, offset, and change of a tonal stimulus in anesthetized animals. The tonal response pattern has been rarely investigated in alert animals. We investigated the time-course of A1 neuron responses to a steady tonal stimulus in alert cats. We found four types of firing responses based on statistical evaluation of the time course of the firing rate. The tonic cells (38 cells) showed a significant (P<0.05) firing increase throughout the stimulus period after a relatively long latency (mean, 25.3 ms) with little tendency of adaptation. The phasic-tonic cells (22 cells) showed a significant firing increase throughout the stimulus period after a medium latency (19.8 ms) with tendency of adaptation to less than a half of the maximum excitation level. Phasic cells (15 cells) responded, after a short latency (10.2 ms), at onset and offset of the stimuli. The unresponsive cells (26 cells) did not show a significant firing increase during stimuli. The findings suggest that there is a functional difference between each type of cells: the tonic cells encode information of static auditory signals in their firing rates; the phasic-tonic cells, of the changing auditory signal during the stimulus period; and the phasic cells, of rapid change of the auditory signal at onset and offset.

Auditory thalamus neurons during sleep: changes in frequency selectivity, threshold, and receptive field size

The present study describes how the frequency receptive fields (RF) of auditory thalamus neurons are modified when the state of vigilance of an unanesthetized animal naturally fluctuates among wakefulness (W), slow-wave sleep (SWS), and paradoxical sleep (PS). Systematic quantification of several RF parameters-including strength of the evoked responses, response latency, acoustic threshold, shape of rate-level function, frequency selectivity, and RF size-was performed while undrugged, restrained guinea pigs presented spontaneous alternances of W, SWS, and PS. Data are from 102 cells recorded during W and SWS and from 53 cells recorded during W, SWS, and PS. During SWS, thalamic cells behaved as an homogeneous population: as compared with W, most of them (97/102 cells) exhibited decreased evoked spike rates. The frequency selectivity was enhanced and the RF size was reduced. In contrast during PS, two populations of cells were identified: one (32/53 cells) showed the same pattern of changes as during SWS, whereas the other (21/53 cells) expressed values of evoked spike rates and RF properties that did not significantly differ from those in W. These two populations were equally distributed in the different anatomical divisions of the auditory thalamus. Last, during both SWS and PS, the responses latency was longer and the acoustic threshold was higher than in W but the proportion of monotonic versus nonmonotonic rate-level functions was unchanged. During both SWS and PS, no relationship was found between the changes in burst percentage and the changes of the RF properties. These results point out the dual aspect of sensory processing during sleep. On the one hand, they show that the auditory messages sent by thalamic cells to cortical neurons are reduced both in terms of firing rate at a given frequency and in terms of frequency range. On the other hand, the fact that the frequency selectivity and the rate-level function are preserved suggests that the messages sent to cortical cells are not deprived of informative content, and that the analysis of complex acoustic sounds should remain possible. This can explain why, although attenuated, reactivity to biologically relevant stimuli is possible during sleep.

Sound-induced synchronization of neural activity between and within three auditory cortical areas

Neural synchrony within and between auditory cortical fields is evaluated with respect to its potential role in feature binding and in the coding of tone and noise sound pressure level. Simultaneous recordings were made in 24 cats with either two electrodes in primary auditory cortex (AI) and one in anterior auditory field (AAF) or one electrode each in AI, AAF, and secondary auditory cortex. Cross-correlograms (CCHs) for 1-ms binwidth were calculated for tone pips, noise bursts, and silence (i.e., poststimulus) as a function of intensity level. Across stimuli and intensity levels the total percentage of significant stimulus onset CCHs was 62% and that of significant poststimulus CCHs was 58% of 1,868 pairs calculated for each condition. The cross-correlation coefficient to stimulus onsets was higher for single-electrode pairs than for dual-electrode pairs and higher for noise bursts compared with tone pips. The onset correlation for single-electrode pairs was only marginally larger than the poststimulus correlation. For pairs from electrodes across area boundaries, the onset correlations were a factor 3-4 higher than the poststimulus correlations. The within-AI dual-electrode peak correlation was higher than that across areas, especially for spontaneous conditions. Correlation strengths for between area pairs were independent of the difference in characteristic frequency (CF), thereby providing a mechanism of feature binding for broadband sounds. For noise-burst stimulation, the onset correlation for between area pairs was independent of stimulus intensity regardless the difference in CF. In contrast, for tone-pip stimulation a significant dependence on intensity level of the peak correlation strength was found for pairs involving AI and/or AAF with CF difference less than one octave. Across all areas, driven rate, between-area peak correlation strength, or a combination of the two did not predict stimulus intensity. However, between-area peak correlation strength performs better than firing rate to decide if a stimulus is present or absent.

Azimuth coding in primary auditory cortex of the cat. I. Spike synchrony versus spike count representations

The neural representation of sound azimuth in auditory cortex most often is considered to be average firing rate, and azimuth tuning curves based thereupon appear to be rather broad. Coincident firings of simultaneously recorded neurons could provide an improved representation of sound azimuth compared with that contained in the firing rate in either of the units. In the present study, a comparison was made between local field potentials and several measures based on unit firing rate and coincident firing with respect to their azimuth-tuning curve bandwidth. Noise bursts, covering a 60-dB intensity range, were presented from nine speakers arranged in a semicircular array with a radius of 55 cm in the animal's frontal half field. At threshold intensities, all local field potential (LFP) recordings showed preferences for contralateral azimuths. Multiunit recordings showed in 74% a threshold for contralateral azimuths, in 16% for frontal azimuths, and in only 5% showed an ipsilateral threshold. The remaining 5% were not spatially tuned. Representations for directionally sensitive units based on coincident firings provided significantly sharper tuning (50-60 degrees bandwidth at 25 dB above the lowest threshold) than those based on firing rate (bandwidths of 80-90 degrees). The ability to predict sound azimuth from the directional information contained in the neural population activity was simulated by combining the responses of the 102 single units. Peak firing rates and coincident firings with LFPs at the preferred azimuth for each unit were used to construct a population vector. At stimulus levels of >/=40 dB SPL, the prediction function was sigmoidal with the predicted frontal azimuth coinciding with the frontal speaker position. Sound azimuths >45 degrees from the midline all resulted in predicted values of -90 or 90 degrees, respectively. No differences were observed in the performance of the prediction based on firing rate or coincident firings for these intensities. This suggests that although coincident firings produce narrower azimuth tuning curves, the information contained in the overall neural population does not increase compared with that contained in a firing rate representation. The relatively poor performance of the population vector further suggests that primary auditory cortex does not code sound azimuth by a globally distributed measure of peak firing rate or coincident firing.

First-spike timing of auditory-nerve fibers and comparison with auditory cortex

First-spike timing of auditory-nerve fibers and comparison with auditory cortex. J. Neurophysiol. 78: 2438-2454, 1997. The timing of the first spike of cat auditory-nerve (AN) fibers in response to onsets of characteristic frequency (CF) tone bursts was studied and compared with that of neurons in primary auditory cortex (AI), reported previously. Tones were shaped with cosine-squared rise functions, and rise time and sound pressure level were parametrically varied. Although measurement of first-spike latency of AN fibers was somewhat compromised by effects of spontaneous activity, latency was an invariant and inverse function of the maximum acceleration of peak pressure (i.e., a feature of the 2nd derivative of the stimulus envelope), as previously found in AI, rather than of tone level or rise time. Latency-acceleration functions of all AN fibers were of very similar shape, similar to that observed in AI. As in AI, latency-acceleration functions of different fibers were displaced along the latency axis, reflecting differences in minimum latency, and along the acceleration axis, reflecting differences in sensitivity to acceleration [neuronal transient sensitivity (S)]. S estimates increased with spontaneous rate (SR), but values of high-SR fibers exceeded those in AI. This suggests that S estimates are biased by SR per se, and that unbiased true S values would be less tightly correlated with response properties covarying with SR, such as firing threshold. S estimates varied with CF in a fashion similar to the cat's audiogram and, for low- and medium-SR fibers, matched those for AI neurons. Minimum latency decreased with increasing SR and CF. As in AI, the standard deviation of first-spike timing (SD) in AN was also an inverse function of maximum acceleration of peak pressure. The characteristics of the increase of SD with latency in a given AN fiber/AI neuron and across AN fibers/AI neurons revealed that the precision of first-spike timing to some stimuli can actually be higher in AI than in AN. The data suggest that the basic characteristics of the latency-acceleration functions of transient onset responses seen in cortex are generated at inner hair cell-AN fiber synapses. Implications for signal processing in the auditory system and for first-spike generation and adaptation in AN are discussed.

Stimulus-dependent modulation of spike burst length in cat striate cortical cells

Burst activity, defined by groups of two or more spikes with intervals of < or = 8 ms, was analyzed in responses to drifting sinewave gratings elicited from striate cortical neurons in anesthetized cats. Bursting varied broadly across a population of 507 simple and complex cells. Half of this population had > or = 42% of their spikes contained in bursts. The fraction of spikes in bursts did not vary as a function of average firing rate and was stationary over time. Peaks in the interspike interval histograms were found at both 3-5 ms and 10-30 ms. In many cells the locations of these peaks were independent of firing rate, indicating a quantized control of firing behavior at two different time scales. The activity at the shorter time scale most likely results from intrinsic properties of the cell membrane, and that at the longer scale from recurrent network excitation. Burst frequency (bursts per s) and burst length (spikes per burst) both depended on firing rate. Burst frequency was essentially linear with firing rate, whereas burst length was a nonlinear function of firing rate and was also governed by stimulus orientation. At a given firing rate, burst length was greater for optimal orientations than for nonoptimal orientations. No organized orientation dependence was seen in bursts from lateral geniculate nucleus cells. Activation of cortical contrast gain control at low response amplitudes resulted in no burst length modulation, but burst shortening at optimal orientations was found in responses characterized by supersaturation. At a given firing rate, cortical burst length was shortened by microinjection of gamma-aminobutyric acid (GABA), and bursts became longer in the presence of N-methyl-bicuculline, a GABA(A) receptor blocker. These results are consistent with a model in which responses are reduced at nonoptimal orientations, at least in part, by burst shortening that is mediated by GABA. A similar mechanism contributes to response supersaturation at high contrasts via recruitment of inhibitory responses that are tuned to adjacent orientations. Burst length modulation can serve as a form of coding by supporting dynamic, stimulus-dependent reorganization of the effectiveness of individual network connections.

Auditory cortical onset responses revisited. I. First-spike timing

Sound onsets are salient and behaviorally relevant, and most auditory neurons discharge spikes locked to such transients. The acoustic parameters of sound onsets that shape such onset responses are unknown. In this paper is analyzed the timing of spikes of single neurons in the primary auditory cortex of barbiturate-anesthetized cats to the onsets of tone bursts. By parametric variation of sound pressure level, rise time, and rise function (linear or cosine-squared), the time courses of peak pressure, rate of change of peak pressure, and acceleration of peak pressure during the tones' onsets were systematically varied. For cosine-squared rise function tones of a given frequency and laterality, any neuron's mean first-spike latency was an invariant and inverse function of the maximum acceleration of peak pressure occurring at tone onset. For linear rise function tones, latency was an invariant and inverse function of the rate of change of peak pressure. Thus latency is independent of rise time or sound pressure level per se. Latency-acceleration functions, obtained with cosine-squared rise function tones under different stimulus conditions (frequency, laterality) from any given neuron and across the neuronal pool, were of strikingly similar shape. The same was true for latency-rate of change of peak pressure functions obtained with linear rise function tones. Latency-acceleration/rate of change of peak pressure functions could differ in their extent and in their position within the coordinate system. The positional differences reflect neuronal differences in minimum latency Lmin and in a sensitivity S to acceleration and rate of change of peak pressure (transient sensitivity), a hitherto unrecognized neuronal property that is distinctly different from firing threshold. Estimates of Lmin and S, which were derived by fitting a simple function to the neuronal latency-acceleration/rate of change of peak pressure functions, were independent of rise function. On average, Lmin decreased with increasing characteristic frequency (CF), but varied widely for neurons with the same CF. S varied with CF in a fashion similar to the cat's audiogram and, for a given neuron, varied with frequency. SD of first-spike latency was roughly proportional to the slope of the functions relating latency to acceleration/rate of change of peak pressure. Thus SD increased exponentially, rather than linearly, with mean latency, and did so at about twice the rate for linear than for cosine-squared rise function tones. The proportionality coefficients were quite similar across the neuronal pool and similar for both rise functions. Minimum SD increased nonlinearly with increasing Lmin. These findings suggest a peripheral origin of S and a peripheral establishment of latency-acceleration/rate of change of peak pressure functions. Because of the striking similarity in the shapes of such functions across the neuronal pool, sound onsets will produce orderly and predictable spatiotemporal patterns of first-spike timing, which could be used to instantaneously track rapid transients and to represent transient features by partly scale-invariant temporal codes.

Auditory cortical onset responses revisited. II. Response strength

Most neurons of the auditory pathway discharge spikes locked to the onset of an acoustic stimulus, but it is largely unknown in which way the acoustic parameters of sound onsets shape the neuronal responses. In this paper is analyzed the number of spikes discharged by single neurons in primary auditory cortex of barbiturate-anesthetized cats to the onsets of tones of characteristic frequency. The time course of the peak pressure (i.e., the envelope) was altered by parametrically varying sound pressure level (SPL), rise time, and rise function (linear or cosine-squared). For both rise functions, rise time had manifold, and in some cases dramatic, effects on conventional spike count-level functions. In general, threshold SPL, dynamic range, and the lowest SPL at which monotonic spike count functions saturated increased with prolongation of the rise time. In neurons with mostly nonmonotonic spike count-level functions, "best SPL" increased and the descending high-SPL arms flattened, so that functions obtained with long rise times were often monotonic whereas those obtained with shorter rise times were highly nonmonotonic. Consequently, the "tuning" to SPL was less sharp for longer rise time tones, and spike count versus rise time functions changed from "short-pass" to "long-pass" with an increase in SPL. Systematic effects of rise time persisted when spike counts were plotted against the rate of change of peak pressure or against the maximum acceleration of peak pressure. However, when spike counts were plotted as a function of the instantaneous peak pressure at the time of response initiation, the functions obtained with different rise times, and even with different rise functions, were in close register. This suggests that the stimulus-dependent component of first-spike latency can be viewed as an integration window, during which rate of change of peak pressure is integrated. The window commences with tone onset and its duration is inversely related to the maximum acceleration (or, for linear rise functions, the rate of change) of peak pressure and the neuron's transient sensitivity. The present findings seriously question, for onset responses, the usefulness of the spike count-level function and measures derived from it, such as threshold SPL, dynamic range, best SPL, or degree of nonmonotonicity. They further cast doubt onto the validity of current concepts of intensity coding at cortical levels, because most neurons' onset responses are not indicative of a signal's steady-state SPL. However, they suggest a mechanism by which a neuronal population will sample a given transient in an orderly, sensitivity-dependent, temporal sequence. The sampling rate is automatically adjusted to, and adjusted by, the rapidity of the signal's change. And the instantaneous properties of the transient could be represented by the ratios and spatial distribution of responses across the simultaneously active subpopulation. Such a mechanism could provide the basis for the demonstrated capability of discrimination of rapid transients.

Time course of forward masking tuning curves in cat primary auditory cortex

Nonsimultaneous two-tone interactions were studied in the primary auditory cortex of anesthetized cats. Poststimulatory effects of pure tone bursts (masker) on the evoked activity of a fixed tone burst (probe) were investigated. The temporal interval from masker onset to probe onset (stimulus onset asynchrony), masker frequency, and intensity were parametrically varied. For all of the 53 single units and 58 multiple-unit clusters, the neural activity of the probe signal was either inhibited, facilitated, and/or delayed by a limited set of masker stimuli. The stimulus range from which forward inhibition of the probe was induced typically was centered at and had approximately the size of the neuron's excitatory receptive field. This "masking tuning curve" was usually V shaped, i.e., the frequency range of inhibiting masker stimuli increased with the masker intensity. Forward inhibition was induced at the shortest stimulus onset asynchrony between masker and probe. With longer stimulus onset asynchronies, the frequency range of inhibiting maskers gradually became smaller. Recovery from forward inhibition occurred first at the lower- and higher-frequency borders of the masking tuning curve and lasted the longest for frequencies close to the neuron's characteristic frequency. The maximal duration of forward inhibition was measured as the longest period over which reduction of probe responses was observed. It was in the range of 53-430 ms, with an average of 143 +/- 71 (SD) ms. Amount, duration and type of forward inhibition were weakly but significantly correlated with "static" neural receptive field properties like characteristic frequency, bandwidth, and latency. For the majority of neurons, the minimal inhibitory masker intensity increased when the stimulus onset asynchrony became longer. In most cases the highest masker intensities induced the longest forward inhibition. A significant number of neurons, however, exhibited longest periods of inhibition after maskers of intermediate intensity. The results show that the ability of cortical cells to respond with an excitatory activity depends on the temporal stimulus context. Neurons can follow higher repetition rates of stimulus sequences when successive stimuli differ in their spectral content. The differential sensitivity to temporal sound sequences within the receptive field of cortical cells as well as across different cells could contribute to the neural processing of temporally structured stimuli like speech and animal vocalizations.

Response properties of units in the posterior auditory field deprived of input from the ipsilateral primary auditory cortex

The influence of the ipsilateral primary auditory field (AI) on the response properties of neurons in the posterior auditory field (Field P) was examined in three cats anesthetized with sodium pentobarbital. Rate/level functions were obtained, by extracellular recording, from single units in Field P before (n = 38) and after (n = 50) subpial aspiration of AI. The ablations were primarily confined to the medial ectosylvian gyrus, although in one case extended into the high-frequency portion of the anterior auditory field. Comparisons between the behavior of units isolated before and after AI ablation failed to demonstrate any changes in the response properties of neurons in Field P attributable to the ablation. Nonmonotonic response profiles, first spike latency, variability in latency, threshold and maximal discharge rates of the units to acoustic stimuli were not significantly altered by the AI ablation. These results indicate that the basic response properties of neurons in Field P do not depend on input from the ipsilateral AI. This suggests that these properties are most likely determined by thalamic input or by circuitry within Field P.

After-discharges in the auditory cortex of the mustached bat: No oscillatory discharges for binding auditory information

Action potentials of single or multi-neurons were recorded from the DSCF, FM-FM and DF areas in the auditory cortex of the mustached bat to study stimulus-induced neural oscillation in the auditory system. Out of 125 neurons 120 recorded in these three areas showed after-discharges to a best stimulus. Durations of after-discharges of 120 neurons ranged between 4.8 and 217 ms. In the remaining 5 neurons, the duration of the discharges was shorter that of the stimulus. The PST histograms displaying responses of these 125 neurons showed no oscillatory component locked to the stimulus. 98% of the autocorrelograms of responses (122/125) showed no sign of oscillation, but the remaining two percent showed a very weak oscillatory component that was not stimulus-locked. The duration of the after-discharges had no correlation with the best delay or cortical depth of neurons. After-discharges are common in the auditory cortex of the mustached bat, but oscillatory discharges are very rare, so that neural oscillations play no role in binding various types of biosonar information processed in the different 'specialized' areas in the auditory cortex.

Population responses to multifrequency sounds in the cat auditory cortex: one- and two-parameter families of sounds

Population responses to multi-frequency sounds were recorded in primary auditory cortex of anesthetized cats. The sounds consisted of single-tone stimuli; two-tone stimuli; and nine-tone stimuli, with the tones evenly spaced on a linear frequency scale. The stimuli were presented through a sealed, calibrated sound delivery system. Single units, cluster activity (CA) and the short-time mean absolute value of the envelope of the neural signal (MABS) were recorded extracellularly from six microelectrodes simultaneously. The CA and MABS were interpreted as measures of the activity of large populations of neurons, in contrast with the single unit activity which is presumably recorded from single neurons. The responses of the MABS signal to simple stimuli were generally similar to those of the CA, but were more stable statistically. Thus, the MABS is better suited for studying the activity of populations of neurons. The responses to tones near the best frequency were strongly influenced by a second tone, even when the second tone was outside the single-tone response area. These influences could be both facilitatory and suppressory. They could not be predicted from the responses to single tones. The responses to the nine-tone stimuli could be explained qualitatively by the responses to the two-tone stimuli. It is concluded that the population responses in primary auditory cortex are shaped by the contributions of the individual frequencies appearing in the stimulus and by the interactions between pairs of frequencies. Interactions between stimulus components are therefore a necessary component of any attempt to explain the processing of complex sounds in the auditory cortex. They may play a role in a global representation of the stimulus spectrum in the primary auditory cortex. The presence of higher-order interactions cannot be excluded by the results presented here.

Functional organization of the auditory cortex: maps and mechanisms

Recent studies have led to a better understanding of several aspects of the organization and physiological mechanisms involved in the processing of information in the auditory cortex. A wide range of approaches have revealed new information regarding the histochemistry, cortico-cortical connections, single-unit physiology, and functional spatial organization, as well as mechanisms and effects of representational and learning-induced cortical plasticity.