Cat Primary Auditory Cortex Research Articles

Changes in spontaneous firing rate and neural synchrony in cat primary auditory cortex after localized tone-induced hearing loss

Increase in spontaneous neural activity after noise-induced hearing loss has frequently been associated with the phenomenon of tinnitus. Eighteen juvenile and adult cats were exposed for 2 h to a 6 kHz tone with an intensity of 115 dB SPL at the cat’s head. Seven non-exposed littermates and seven other normal hearing cats were used as age-matched controls. The trauma cats showed localized hearing losses, as assessed by ABR, ranging from less than 20 to 60 dB. The frequency representation in primary auditory cortex was mapped using an eight-electrode array. Single-unit spontaneous activity was recorded for 15 min. Peak cross-correlation coefficients ( R) for unit cluster activity recorded on separate electrodes were calculated. We found elevated spontaneous firing rates in regions with reorganization of the tonotopic map compared to the neurons in the non-reorganized cortical regions in the same animals. A second finding was that in these regions the peak cross-correlation coefficients were also increased relative to the non-reorganized parts. A third finding was that exposed animals showed higher spontaneous activity compared to controls regardless of the presence of cortical reorganization. This may be a correlate of tinnitus in the presence of only minor hearing losses.

Processing of low-probability sounds by cortical neurons.

The ability to detect rare auditory events can be critical for survival. We report here that neurons in cat primary auditory cortex (A1) responded more strongly to a rarely presented sound than to the same sound when it was common. For the rare stimuli, we used both frequency and amplitude deviants. Moreover, some A1 neurons showed hyperacuity for frequency deviants--a frequency resolution one order of magnitude better than receptive field widths in A1. In contrast, auditory thalamic neurons were insensitive to the probability of frequency deviants. These phenomena resulted from stimulus-specific adaptation in A1, which may be a single-neuron correlate of an extensively studied cortical potential--mismatch negativity--that is evoked by rare sounds. Our results thus indicate that A1 neurons, in addition to processing the acoustic features of sounds, may also be involved in sensory memory and novelty detection.

Intracellular characterization of suppressive responses in supragranular pyramidal neurons of cat primary auditory cortex in vivo.

Several suppressive processes shape the response properties of auditory neurons, namely lateral inhibition, non-monotonic rate level function and excitation/inhibition binaural interaction. By combining intracellular recording from and staining of layers 2 and 3 pyramidal neurons (PNs) in cat primary auditory cortex, we demonstrate the temporal aspects of depolarization and hyperpolarization underlying these suppressions using pure tone stimulation. Two populations can be distinguished by the occurrence of hyperpolarization following onset depolarization (O-DEP). In layer 2 PNs there is an absence of hyperpolarization following O-DEP, while in layer 3 PNs hyperpolarization follows O-DEP. The latency of O-DEP is shortest at the neuron's best frequency. The latency shortens as sound intensity increases. In non-monotonic PNs, hyperpolarization onset becomes shorter as sound intensity increases. This earlier onset of hyperpolarization shortens the duration of the preceding O-DEP, resulting in a decreased O-DEP amplitude. Diverse patterns in the temporal interaction of depolarization and hyperpolarization underlie the binaural suppression interaction. These results demonstrate that diverse suppressive responses result from differences in the temporal timing of excitation and inhibition. The present results also suggest the possibility of distinct connections between PNs responding in a similar manner.

Responses of Neurons in Cat Primary Auditory Cortex to Bird Chirps: Effects of Temporal and Spectral Context

The responses of neurons to natural sounds and simplified natural sounds were recorded in the primary auditory cortex (AI) of halothane-anesthetized cats. Bird chirps were used as the base natural stimuli. They were first presented within the original acoustic context (at least 250 msec of sounds before and after each chirp). The first simplification step consisted of extracting a short segment containing just the chirp from the longer segment. For the second step, the chirp was cleaned of its accompanying background noise. Finally, each chirp was replaced by an artificial version that had approximately the same frequency trajectory but with constant amplitude. Neurons had a wide range of different response patterns to these stimuli, and many neurons had late response components in addition, or instead of, their onset responses. In general, every simplification step had a substantial influence on the responses. Neither the extracted chirp nor the clean chirp evoked a similar response to the chirp presented within its acoustic context. The extracted chirp evoked different responses than its clean version. The artificial chirps evoked stronger responses with a shorter latency than the corresponding clean chirp because of envelope differences. These results illustrate the sensitivity of neurons in AI to small perturbations of their acoustic input. In particular, they pose a challenge to models based on linear summation of energy within a spectrotemporal receptive field.

Representation of CV-sounds in cat primary auditory cortex: intensity dependence

The level-dependent representation of simple speech sounds in cat primary auditory cortex (AI) is explored in naive cats and in animals that have been exposed to these sounds in behavioral detection and discrimination tasks. Population analyses of multiple unit responses in the form of post-stimulus time histograms (PSTHs), neurograms, and spatial distribution were made for synthetic consonant–vowel sounds across AI. The temporal profile of cortical responses was robust across neurons, characterized by brief phasic responses at the onset of consonantal burst and voicing. The spectral profile of the sounds, i.e., the formant structure, was only weakly expressed in the response magnitude across characteristic frequency. The spatial response distribution across AI was discontinuous, and consisted of several patches of activation. Intensity-dependence in the spatial activity distribution was more strongly expressed than in population PSTHs and neurograms. Differences attributable to behavioral training were observed for rate-encoding and temporal encoding of speech sounds.

Changes in cat primary auditory cortex after minor-to-moderate pure-tone induced hearing loss

In this paper we present findings in the primary auditory cortex of cats exposed for 2 h to a 115 dB SPL, 6 kHz tone at 36 days, 56 days or 118 days after birth. We evaluate the effects of age at exposure, amount of hearing loss, and time after induction of trauma on the functional reorganization of the cortical tonotopic map. We found a fairly sharp demarcation in the amount of hearing loss (20–25 dB) that caused cortical reorganization. For localized hearing losses, unmasking of excitatory contributions of neighboring frequency regions was found. For cats showing reorganization of the tonotopic map, the frequency-tuning curve bandwidth at 20 dB above threshold at CF (BW 20dB) increased with increasing threshold at CF. Threshold at CF, and BW 20dB increased with time after exposure. Minimum spike latency was initially increased, but subsequently decreased with time after exposure at a rate that was two times faster in cats with reorganized cortex than in cats with normal tonotopic maps, to reach the same asymptotic value. Thresholds at CF were correlated with the peripheral hearing loss at near CF frequencies as estimated from ABR measurements. The correlation between BW 20dB and CF threshold suggests that part of the reorganization could be due to ‘residual’ sensitivity of the high frequency neurons to not-affected lower or higher frequencies. However, for CFs above 6 kHz, the BW 20dB for cats with reorganization of the tonotopic map was significantly lower (on average 0.3 octave, P<0.05) than for cats with normal tonotopic maps. This is not what one would expect in cases of pseudo-plasticity characterized by concurrent shifts in BW 20dB and CF as a result of residual sensitivity to lower frequencies.

Auditory edge detection: a neural model for physiological and psychoacoustical responses to amplitude transients.

Primary segmentation of visual scenes is based on spatiotemporal edges that are presumably detected by neurons throughout the visual system. In contrast, the way in which the auditory system decomposes complex auditory scenes is substantially less clear. There is diverse physiological and psychophysical evidence for the sensitivity of the auditory system to amplitude transients, which can be considered as a partial analogue to visual spatiotemporal edges. However, there is currently no theoretical framework in which these phenomena can be associated or related to the perceptual task of auditory source segregation. We propose a neural model for an auditory temporal edge detector, whose underlying principles are similar to classical visual edge detector models. Our main result is that this model reproduces published physiological responses to amplitude transients collected at multiple levels of the auditory pathways using a variety of experimental procedures. Moreover, the model successfully predicts physiological responses to a new set of amplitude transients, collected in cat primary auditory cortex and medial geniculate body. Additionally, the model reproduces several published psychoacoustical responses to amplitude transients as well as the psychoacoustical data for amplitude edge detection reported here for the first time. These results support the hypothesis that the response of auditory neurons to amplitude transients is the correlate of psychoacoustical edge detection.

Layer V in cat primary auditory cortex (AI): cellular architecture and identification of projection neurons.

The cytoarchitectonic organization and the structure of layer V neuronal populations in cat primary auditory cortex (AI) were analyzed in Golgi, Nissl, immunocytochemical, and plastic-embedded preparations from mature specimens. The major cell types were characterized as a prelude to identifying their connections with the thalamus, midbrain, and cerebral cortex using axoplasmic transport methods. The goal was to describe the structure and connections of layer V neurons more fully. Layer V has three sublayers based on the types of neuron and their sublaminar projections. Four types of pyramidal and three kinds of nonpyramidal cells were present. Classic pyramidal cells had a long apical dendrite, robust basal arbors, and an axon with both local and corticofugal projections. Only the largest pyramidal cell apical dendrites reached the supragranular layers, and their somata were found mainly in layer Vb. Three types departed from the classic pattern; these were the star, fusiform, and inverted pyramidal neurons. Nonpyramidal cells ranged from large multipolar neurons with radiating dendrites, to Martinotti cells, with smooth dendrites and a primary trunk oriented toward the white matter. Many nonpyramidal cells were multipolar, of which three subtypes (large, medium, and small) were identified; bipolar and other types also were seen. Their axons formed local projections within layer V, often near pyramidal neurons. Several features distinguish layer V from other layers in AI. The largest pyramidal neurons were in layer V. Layer V neuronal diversity aligns it with layer VI (Prieto and Winer [1999] J. Comp. Neurol. 404:332--358), and it is consistent with the many connectional systems in layer V, each of which has specific sublaminar and neuronal origins. The infragranular layers are the source for several parallel descending systems. There were significant differences in somatic size among these projection neurons. This finding implies that diverse corticofugal roles in sensorimotor processing may require a correspondingly wide range of neuronal architecture.

Relating cluster and population responses to natural sounds and tonal stimuli in cat primary auditory cortex

Most information about neuronal properties in primary auditory cortex (AI) has been gathered using simple artificial sounds such as pure tones and broad-band noise. These sounds are very different from the natural sounds that are processed by the auditory system in real world situations. In an attempt to bridge this gap, simple tonal stimuli and a standard set of six natural sounds were used to create models relating the responses of neuronal clusters in AI of barbiturate-anesthetized cats to the two classes of stimuli. A significant correlation was often found between the response to the separate frequency components of the natural sounds and the response to the natural sound itself. At the population level, this correlation resulted in a rate profile that represented robustly the spectral profiles of the natural sounds. There was however a significant scatter in the responses to the natural sound around the predictions based on the responses to tonal stimuli. Going the other way, in order to understand better the non-linearities in the responses to natural sounds, responses of neuronal clusters were characterized using second order Volterra kernel analysis of their responses to natural sounds. This characterization predicted reasonably well the amplitude of the response to other natural sounds, but could not reproduce the responses to tonal stimuli. Thus, second order non-linear characterizations, at least those using the Volterra kernel model, do not interpolate well between responses to tones and to natural sounds in auditory cortex.

Sequence sensitivity of neurons in cat primary auditory cortex.

Properties of sequence-sensitive neurons in primary auditory cortex of cats were explored in detail. Stimuli were sequences of two tones, in which the frequency and intensity of the first tone and the temporal separation between the first and second, or probe, tone were parametrically varied. After presentation of the first tone, the responses of 32 single units and 48 multiunits to the probe tone were found to be enhanced up to 140-5270% (median 340%) above the response obtained in the single-tone condition. Probe tone enhancement was induced from a considerable number of sequence conditions and depended on the frequency and intensity of the first tone and on the temporal separation between the onsets of the first and the probe tone. On average, the maximally enhanced response occurred when the first tone was 1 octave below or above the probe tone and its intensity was 14 dB louder than the probe tone. The most effective temporal separation of the tones for an enhancement effect was approximately 100 ms. The range of enhancing tones was largely outside the excitatory tuning curve of a neuron. Results extend previous findings of properties of sequence-sensitive neurons in the auditory cortex of echolocating bats and non-echolocating mammals, and suggest that sequence-sensitive neurons are quite common and involved in the cortical representation of spectrotemporal patterns of acoustic signals.

Neuronal responses in cat primary auditory cortex to natural and altered species-specific calls

We investigated how natural and morphed cat vocalizations are represented in primary auditory cortex (AI). About 40% of the neurons showed time-locked responses to major peaks in the vocalization envelope, 60% only responded at the onset. Simultaneously recorded multi-unit (MU) activity of these peak-tracking neurons on separate electrodes was significantly more synchronous during stimulation than under silence. Thus, the representation of the vocalizations is likely synchronously distributed across the cortex. The sum of the responses to the low and high frequency part of the meow, with the boundary at 2.5 kHz, was larger than the neuronal response to the natural meow itself, suggesting that strong lateral inhibition is shaping the response to the natural meow. In this sense, the neurons are combination-sensitive. The frequency-tuning properties and the response to amplitude-modulated tones of the MU recordings can explain the responses to natural, and temporally and spectrally altered vocalizations. Analysis of the mutual information in the firing rate suggests that the activity of at least 95 recording sites in AI would be needed to reliably distinguish between the nine different vocalizations. This suggests that a distributed representation based on temporal stimulus aspects may be more efficient than one based on firing rate.

Temporal discharge patterns evoked by rapid sequences of wide- and narrowband clicks in the primary auditory cortex of cat.

The present study investigated neural responses to rapid, repetitive stimuli in the primary auditory cortex (A1) of cats. We focused on two important issues regarding cortical coding of sequences of stimuli: temporal discharge patterns of A1 neurons as a function of inter-stimulus interval and cortical mechanisms for representing successive stimulus events separated by very short intervals. These issues were studied using wide- and narrowband click trains with inter-click intervals (ICIs) ranging from 3 to 100 ms as a class of representative sequential stimuli. The main findings of this study are 1) A1 units displayed, in response to click train stimuli, three distinct temporal discharge patterns that we classify as regions I, II, and III. At long ICIs nearly all A1 units exhibited typical stimulus-synchronized response patterns (region I) consistent with previously reported observations. At intermediate ICIs, no clear temporal structures were visible in the responses of most A1 units (region II). At short ICIs, temporal discharge patterns are characterized by the presence of either intrinsic oscillations (at approximately 10 Hz) or a change in discharge rate that was a monotonically decreasing function of ICI (region III). In some A1 units, temporal discharge patterns corresponding to region III were absent. 2) The boundary between regions I and II (synchronization boundary) had a median value of 39.8 ms ICI ([25%, 75%] = [20.4, 58. 8] ms ICI; n = 131). The median boundary between regions II and III was estimated at 6.3 ms ([25%, 75%] = [5.2, 9.7] ms ICI; n = 47) for units showing rate changes (rate-change boundary). 3) The boundary values between different regions appeared to be relatively independent of stimulus intensity (at modest sound levels) or the bandwidth of the clicks used. 4) There is a weak correlation between a unit's synchronization boundary and its response latency. Units with shorter latencies appeared to also have smaller boundary values. And 5) based on these findings, we proposed a two-stage model for A1 neurons to represent a wide range of ICIs. In this model, A1 uses a temporal code for explicitly representing long ICIs and a rate code for implicitly representing short ICIs.

Multiple representations of information in the primary auditory cortex of cats: II. Stability and change in early (

Activity was recorded from single units of the A I cortex of awake animals to identify early (<32 ms) components of the population response to a 70 dB click and establish if they changed after using the click as a CS for conditioning. A 70 dB hiss was used as a discriminative stimulus. Responses to these stimuli were compared before and after a forward order of pairing that produced conditioning and a backward order of pairing that produced weak sensitization (backward conditioning). Averages of discharges in 2 and 4 ms bins distinguished primary (8–12 ms) from secondary (12–16 ms) temporal components of response to the click, and confirmed that the onset of the response was shorter in A I (8 ms, mean of 647 units) than in the adjacent, A II cortex (16 ms, mean of 95 units). (All times include a 1.6 ms transmission delay in sound arrival.) Primary and secondary components of A I responses to click did not change uniformly after changes in behavioral state, and were affected differently by both conditioning and backward conditioning. The percentage of cells with onsets of response to the click at secondary latencies (and to the hiss at tertiary latencies) increased after backward conditioning but not after conditioning, as did the magnitude of activity in response to the click. (The latter had a lesser degree of increase after conditioning.) The primary response to the click did not show these increases. The non-uniform changes suggested that temporal processing of the click was conducted differently in the 8–12 ms post stimulus period than in the 12–16 ms period. Within the total population of cells, it was possible to identify a small subgroup (13%) of highly auditory-responsive units that showed an increased primary response to the click as a CS selectively after conditioning and not after backward conditioning. The secondary component of response in these cells increased after both conditioning and backward conditioning. The percentages of cells responding to the click and hiss at primary latencies did not change significantly after conditioning, even in the subgroup of highly responsive cells. The results characterize differently timed components of rapid responses to acoustic stimuli in the A I cortex, disclose significant temporal differences in primary, secondary and tertiary information processing that affect the representations of the transmitted acoustic message across different behavioral states, and find one representation in a small subgroup of cells that supports the hypothesis that cells of the A I cortex have a selectively potentiated response to the CS after conditioning.

Multiple representations of information in the primary auditory cortex of cats: I. Stability and change in slow components of unit activity after conditioning with a click conditioned stimulus

Recordings of activity were made from 647 single units of the A I cortex of awake cats to evaluate behavioral state-dependent changes in the population response to a 70-dB click. Averages of PST histograms of unit activity were used to assess the changes in response. This report focuses on slow components of the responses disclosed by averages employing bin widths of 16 ms. Responses were compared before and after a Pavlovian blink CR was produced by forward pairing of click conditioned stimuli (CSs) with USs. A backward-paired 70-dB hiss was presented as a discriminative stimulus. Studies were also done after backward pairing of the click CSs (backward conditioning) that produced weak sensitization instead of a conditioned response. There were four main findings. First, components of activity elicited 32–160 ms after presenting the hiss decreased significantly after conditioning and after backward conditioning. The decreases after conditioning represented the most pronounced changes in activity evoked by either clicks or hisses in this behavioral state. Second, baseline firing decreased after both conditioning and backward conditioning. The direction of baseline change was opposite that found in adjacent cortical regions and in A I cortex after operant conditioning employing an acoustic cue. Third, prior to conditioning, unit activity in response to the hiss declined before the sound of the hiss reached its peak or terminated. This decrease was thought to represent a habituatory adaptation of response to a prolonged acoustic stimulus. This type of habituation to a lengthy stimulus has been recognized, behaviorally, but has not been observed previously in the activity of units of the auditory receptive cortex. Fourth, the percentage of click responsive units did not change significantly after the click was used as a CS for conditioning, and despite the accompanying changes in baseline activity, the absolute levels of activity summed in the first 16 ms after click delivery remained stable across behavioral states in which the motor response to the click was altered profoundly. The onset of the conditioned motor response began 20 ms after the click, and was shown earlier to depend on rapid, potentiated transmission through the cochlear nucleus and motor cortex for its generation. Thus the stability of the response to the click in the primary auditory receptive cortex was unexpected. This led us to make further analyses of the data with 2- and 4-ms bin widths (see companion report) that eventually disclosed a potentiated response to the click. The findings show stability and change in the response to the click as a CS, depending on the band pass (bin width) used for analysis of spike activity. In the representation disclosed by low pass filtering in this study, the response was stable. This representation provided information suitable for identifying commonalties of the click signals across varying behavioral states. The representations of the click and hiss contained in the slow components of the population response in the A I cortex were uncorrelated with the selective potentiation of activity in motor cortex and behavioral performance in response to click as a CS after conditioning. Although changes in the activity evoked by hisses occurred after conditioning, the changes also occurred after backward conditioning when only small, sensitized behavioral responses to clicks and hisses were observed. Basic theoretical considerations about information transmission in complex neural networks plus clinical observations comparing derangements of linguistic and non-linguistic cortical functions in humans suggest that multiple representations of conditioned stimulus inputs may exist in local populations of cortical neurons. Together, our studies provide evidence for two different, concurrent representations of information about a click CS encoded in the spike activity of the A I cortex.

Regional variations of noise-induced changes in operating range in cat AI

Regional differences in spectral integration of neurons in cat primary auditory cortex (AI) suggest that regions differ in effects of background noise on operating characteristics of neurons. Therefore, tone-response threshold, best level (peak-rate intensity), dynamic range, and sharpness of tuning in quiet and in continuous broadband noise were mapped for single neurons along the isofrequency domain of AI. Neurons did not show an excitatory response to the noise. Noise invariably increased the tone-response threshold and best levels. Consequently, the dynamic ranges and receptive fields shifted to higher intensity levels without changes of average sharpness of tuning. These shifts were linearly related to noise level and showed little inter-neuronal variability for neurons in the central, mostly sharply tuned part of AI. In more dorsal and ventral parts of AI, neurons were more variable in tone-response threshold, dynamic range and best level, and no systematic relationship between increase in noise level, threshold increase and best-level increase was observed. We conclude that linear shifts in the operating range of neurons in central AI in the presence of continuous noise backgrounds do not affect other response properties and may relate to the unaltered analysis and representation of spectral components of sounds. In contrast, neurons in dorsal and ventral AI change response properties in a non-predictable way in the presence of noise in accordance with the more complex receptive field properties in those areas.

Auditory cortical responses to the interactive effects of interaural intensity disparities and frequency.

Under natural conditions, stimuli reaching the two ears contain multiple acoustic components. Rarely does a stimulus containing only one component (e.g. pure tone burst) exist outside the realm of the laboratory. For example, in sound localization the simultaneous presence of multiple cues (spectral content, level, phase, etc.) serves to increase the number of available cues and provide the listener with more information, thereby helping to reduce errors in locating the sound source. The present study was designed to explore the relationship between two acoustic parameters: stimulus frequency and interaural intensity disparities (IIDs). By varying both stimulus frequency and IIDs for each cell, we hoped to gain insight into how multiple cues are processed. To this end, we examined the responses of neurons in cat primary auditory cortex (AI) to determine if their sensitivity to IIDs changed as a function of stimulus frequency. IIDs ranging from +30 to -30 dB were presented at different frequencies (frequency was always the same in the two ears). We found that approximately half of the units examined exhibited responses to IIDs that varied as a function of stimulus frequency (i.e. displayed some form of IID x Freq dependency). The remaining units displayed IID responses that were not clearly related to stimulus frequency.

Correlated cortical populations can enhance sound localization performance.

Neurons within cortical populations often evidence some degree of response correlation. Correlation has generally been regarded as detrimental to the decoding performance of a theoretical vector-averaging observer making inferences about the physical world-for example, an observer estimating the location of a sound source. However, if an alternative decoder is considered, in this case a Maximum Likelihood estimator, performance can improve when responses in the population are correlated. Improvement in sound localization performance is demonstrated analytically using Fisher information, and is also shown using Monte Carlo simulations based on recordings from single neurons in cat primary auditory cortex.

Neuronal responses in cat primary auditory cortex to electrical cochlear stimulation. III. Activation patterns in short- and long-term deafness.

The effects of auditory deprivation on the spatial distribution of cortical response thresholds to electrical stimulation of the adult cat cochlea were evaluated. Threshold distributions for single- and multiple-unit responses from the middle cortical layers were obtained on the ectosylvian gyrus in three groups of animals: adult, acutely implanted animals ("acute group"); adult animals, 2 wk after deafening and implantation ("short-term group"); adult, neonatally deafened animals ("long-term group") implanted after 2-5 years of deafness. For all three groups, we observed similar patterns of circumscribed regions of low response thresholds in the region of primary auditory cortex (AI). A dorsal and a ventral region of low response thresholds were found separated by a narrow, anterior-posterior strip of elevated thresholds. The two low-threshold regions in the acute and the short-term group were arranged cochleotopically. This was reflected in a systematic shift of the cortical locations with minimum thresholds as a function of cochlear position of the radial and monopolar stimulation electrodes. By contrast, the long-term deafened animals maintained only weak or no signs of cochleotopicity. In some cases of this group, significant deviations from a simple tri-partition of the dorsoventral axis of AI was observed. Analysis of the spatial extent of the low-threshold regions revealed that the activated area in acute cases was significantly smaller than the long- and the short-term cases for both dorsal and ventral AI. There were no significant differences in the rostrocaudal extent of activation between long- and short-term deafening, although the total activated area in the short-term cases was larger than in long-term deafened animals. The width of the narrow high-threshold ridge that separated the dorsal and ventral low-threshold regions was the widest for the acute cases and the narrowest for the short-term deafened animals. The findings of relative large differences in cortical response distributions between the acute and short-term animals suggests that the effects observed in long-term deafened animals are not solely a consequence of loss of peripheral innervation density. The effects may reflect electrode-specific effects or reorganizational changes based on factors such as differences in excitatory and inhibitory balance.

Organization of inhibitory frequency receptive fields in cat primary auditory cortex.

Based on properties of excitatory frequency (spectral) receptive fields (esRFs), previous studies have indicated that cat primary auditory cortex (A1) is composed of functionally distinct dorsal and ventral subdivisions. Dorsal A1 (A1d) has been suggested to be involved in analyzing complex spectral patterns, whereas ventral A1 (A1v) appears better suited for analyzing narrowband sounds. However, these studies were based on single-tone stimuli and did not consider how neuronal responses to tones are modulated when the tones are part of a more complex acoustic environment. In the visual and peripheral auditory systems, stimulus components outside of the esRF can exert strong modulatory effects on responses. We investigated the organization of inhibitory frequency regions outside of the pure-tone esRF in single neurons in cat A1. We found a high incidence of inhibitory response areas (in 95% of sampled neurons) and a wide variety in the structure of inhibitory bands ranging from a single band to more than four distinct inhibitory regions. Unlike the auditory nerve where most fibers possess two surrounding "lateral" suppression bands, only 38% of A1 cells had this simple structure. The word lateral is defined in this sense to be inhibition or suppression that extends beyond the low- and high-frequency borders of the esRF. Regional differences in the distribution of inhibitory RF structure across A1 were evident. In A1d, only 16% of the cells had simple two-banded lateral RF organization, whereas 50% of A1v cells had this organization. This nonhomogeneous topographic distribution of inhibitory properties is consistent with the hypothesis that A1 is composed of at least two functionally distinct subdivisions that may be part of different auditory cortical processing streams.

Event-related dimensional reductions in the primary auditory cortex of the conscious cat are revealed by new techniques for enhancing the non-linear dimensional algorithms

The analytic algorithms derived from non-linear deterministic models may be more sensitive to differences in physiological data than those based on linear stochastic models. Among the non-linear algorithms the time-dependent dimensional ones appear to be the most sensitive discriminators. In the present study dimensional responses were examined in both electronically and mathematically generated data and in high-resolution physiological data. The latter were event-related potentials (ERPs) recorded from the primary auditory cortex of cats during classical conditioning. Two techniques were found to lengthen and stabilize the linear scaling region in the correlation integral of the dimensional algorithms: (1) linking trials to increase data length; and (2) gain reduction to lower integer-values of noise, combined with algorithmic setting of slopes <0.5 to zero. Of the three dimensional algorithms examined, only the time-dependent Point Correlation Dimension (PD2i) showed low error rates when tracking the dimensional shifts in non-stationary generated data. This algorithm also uniquely distinguished between the conditioned and unconditioned physiological responses. The ERPs had corresponding PD2i's that were significantly different from each other as well as from their own randomized-phase surrogates. The brief dimensional reduction that follows a conditioned stimulus is interpreted to be related to ‘cooperativity’ among the underlying cortical neurons that contribute to its electrogenesis.