Sound-Induced Synchronization of Neural Activity Between and Within Three Auditory Cortical Areas

2000 ◽  
Vol 83 (5) ◽  
pp. 2708-2722 ◽  
Author(s):  
Jos J. Eggermont
Keyword(s):  
Auditory Cortex ◽  
Stimulus Intensity ◽  
Primary Auditory Cortex ◽  
Noise Burst ◽  
Stimulus Onset ◽  
Feature Binding ◽  
Intensity Level ◽  
Correlation Strength ◽  
The Difference ◽  
Peak Correlation

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. II. Relative Latency and Interspike Interval Representation

1998 ◽  
Vol 80 (4) ◽  
pp. 2151-2161 ◽  
Author(s):  
Jos J. Eggermont
Keyword(s):  
Auditory Cortex ◽  
Interspike Interval ◽  
Primary Auditory Cortex ◽  
Noise Burst ◽  
Intensity Level ◽  
Neural Firing ◽  
Response Latencies ◽  
Interval Representation ◽  
Intensity Functions ◽  
Spike Latency

Eggermont, Jos J. Azimuth coding in primary auditory cortex of the cat. II. Relative latency and interspike interval representation. J. Neurophysiol. 80: 2151–2161, 1998. This study was designed to explore a potential representation of sound azimuth in the primary auditory cortex (AI) of the cat by the relative latencies of a population of neurons. An analysis of interspike intervals (ISI) was done to asses azimuth information in the firings of the neurons after the first spike. Thus latencies of simultaneously recorded single-unit (SU) spikes and local field potentials (LFP) in AI of cats were evaluated for sound presented from nine speakers arranged horizontally in the frontal half field in a semicircular array with a radius of 55 cm and the cat's head in the center. SU poststimulus time histograms (PSTH) were made for each speaker location for a 100-ms window after noise-burst onset using 1-ms bins. PSTH peak response latencies for SUs and LFPs decreased monotonically with intensity, and most of the change occurred within 15 dB of the threshold at that particular azimuth. After correction for threshold differences, all latency-intensity functions had roughly the same shape, independent of sound azimuth. Differences with the minimum spike latency observed in an animal at each intensity were calculated for all azimuth-intensity combinations. This relative latency showed a weakly sigmoidal dependence on azimuth that was independent of intensity level >40 dB SPL. SU latency differences also were measured with respect to the latencies of the LFP triggers, simultaneously recorded on the same electrode. This difference was independent of stimulus intensity and showed a nearly linear dependence on sound azimuth. The mean differences across animals for both measures, however, were only significant between contralateral azimuths on one hand and frontal and ipsilateral azimuths on the other hand. Mean unit-LFP latency differences showed a monotonic dependence on azimuth with nearly constant variance and may provide the potential for an unbiased conversion of azimuth into neural firing times. The general trend for the modal ISI was the same as for relative spike latency: the shortest ISIs were found for contralateral azimuths (ISI usually 3 ms) and the longer ones for ipsilateral azimuths (the most frequent ISI was 4 ms, occasionally 5 ms was found). This trend was also independent of intensity level. This suggests that there is little extra information in the timing of extra spikes in addition to that found in the peak PSTH latency.

Neural Responses in Primary Auditory Cortex Mimic Psychophysical, Across-Frequency-Channel, Gap-Detection Thresholds

2000 ◽  
Vol 84 (3) ◽  
pp. 1453-1463 ◽  
Author(s):  
Jos J. Eggermont
Keyword(s):  
Auditory Cortex ◽  
Cortical Neurons ◽  
Primary Auditory Cortex ◽  
Noise Burst ◽  
Gap Detection ◽  
Frequency Content ◽  
Neural Responses ◽  
Frequency Channel ◽  
Interval Representations ◽  
Onset Response

Responses of single- and multi-units in primary auditory cortex were recorded for gap-in-noise stimuli for different durations of the leading noise burst. Both firing rate and inter-spike interval representations were evaluated. The minimum detectable gap decreased in exponential fashion with the duration of the leading burst to reach an asymptote for durations of 100 ms. Despite the fact that leading and trailing noise bursts had the same frequency content, the dependence on leading burst duration was correlated with psychophysical estimates of across frequency channel (different frequency content of leading and trailing burst) gap thresholds in humans. The duration of the leading burst plus that of the gap was represented in the all-order inter-spike interval histograms for cortical neurons. The recovery functions for cortical neurons could be modeled on basis of fast synaptic depression and after-hyperpolarization produced by the onset response to the leading noise burst. This suggests that the minimum gap representation in the firing pattern of neurons in primary auditory cortex, and minimum gap detection in behavioral tasks is largely determined by properties intrinsic to those, or potentially subcortical, cells.

scholarly journals Dissociable influences of primary auditory cortex and the posterior auditory field on neuronal responses in the dorsal zone of auditory cortex

2015 ◽  
Vol 113 (2) ◽  
pp. 475-486
Author(s):  
Melanie A. Kok ◽  
Daniel Stolzberg ◽  
Trecia A. Brown ◽  
Stephen G. Lomber
Keyword(s):  
Auditory Cortex ◽  
Receptive Fields ◽  
Primary Auditory Cortex ◽  
Population Level ◽  
Noise Burst ◽  
Hierarchical Organization ◽  
Neuronal Responses ◽  
Tone Frequency ◽  
Hierarchical Processing ◽  
Auditory Field

Current models of hierarchical processing in auditory cortex have been based principally on anatomical connectivity while functional interactions between individual regions have remained largely unexplored. Previous cortical deactivation studies in the cat have addressed functional reciprocal connectivity between primary auditory cortex (A1) and other hierarchically lower level fields. The present study sought to assess the functional contribution of inputs along multiple stages of the current hierarchical model to a higher order area, the dorsal zone (DZ) of auditory cortex, in the anaesthetized cat. Cryoloops were placed over A1 and posterior auditory field (PAF). Multiunit neuronal responses to noise burst and tonal stimuli were recorded in DZ during cortical deactivation of each field individually and in concert. Deactivation of A1 suppressed peak neuronal responses in DZ regardless of stimulus and resulted in increased minimum thresholds and reduced absolute bandwidths for tone frequency receptive fields in DZ. PAF deactivation had less robust effects on DZ firing rates and receptive fields compared with A1 deactivation, and combined A1/PAF cooling was largely driven by the effects of A1 deactivation at the population level. These results provide physiological support for the current anatomically based model of both serial and parallel processing schemes in auditory cortical hierarchical organization.

scholarly journals Time Course of Forward Masking Tuning Curves in Cat Primary Auditory Cortex

1997 ◽  
Vol 77 (2) ◽  
pp. 923-943 ◽  
Author(s):  
Michael Brosch ◽  
Christoph E. Schreiner
Keyword(s):  
Receptive Field ◽  
Auditory Cortex ◽  
Stimulus Onset Asynchrony ◽  
Time Course ◽  
Tuning Curve ◽  
Primary Auditory Cortex ◽  
Stimulus Onset ◽  
Cortical Cells ◽  
Tuning Curves ◽  
Onset Asynchrony

Brosch, Michael and Christoph E. Schreiner. Time course of forward masking tuning curves in cat primary auditory cortex. J. Neurophysiol. 77: 923–943, 1997. 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.

Neural Correlates of Gap Detection in Three Auditory Cortical Fields in the Cat

1999 ◽  
Vol 81 (5) ◽  
pp. 2570-2581 ◽  
Author(s):  
Jos J. Eggermont
Keyword(s):  
Auditory Cortex ◽  
Lower Boundary ◽  
Primary Auditory Cortex ◽  
Noise Burst ◽  
Neural Correlates ◽  
Lower Envelope ◽  
Gap Detection ◽  
Modal Values ◽  
Onset Response ◽  
Gap Values

Neural correlates of gap detection in three auditory cortical fields in the cat. Mimimum detectable gaps in noise in humans are independent of the position of the gap, whereas in cat primary auditory cortex (AI) they are position dependent. The position dependence in other cortical areas is not known and may resolve this contrast. This study presents minimum detectable gap-in-noise values for which single-unit (SU), multiunit (MU) recordings and local field potentials (LFPs) show an onset response to the noise after the gap. The gap, which varied in duration between 5 and 70 ms, was preceded by a noise burst of either 5 ms (early gap) or 500 ms (late gap) duration. In 10 cats, simultaneous recordings were made with one electrode each in AI, anterior auditory field (AAF), and secondary auditory cortex (AII). In nine additional cats, two electrodes were inserted in AI and one in AAF. Minimum detectable gaps based on SU, MU, or LFP data in each cortical area were the same. In addition, very similar minimum early-gap values were found in all three areas (means, 36.1–41.7 ms). The minimum late-gap values were also similar in AI and AII (means, 11.1 and 11.7 ms), whereas AAF showed significantly larger minimum late-gap durations (mean 21.5 ms). For intensities >35 dB SPL, distributions of minimum early-gap durations in AAF and AII had modal values at ∼45 ms. In AI, the distribution was more uniform. Distributions for minimum late-gap duration were skewed toward low values (mode at 5 ms), but high values (≤60 ms) were found infrequently as well. A small fraction of units showed a response after the gap only for early-gap durations <20 ms. In AI and AII, the mean minimum early- and late-gap durations decreased significantly with increase in the neuron’s characteristic frequency (CF), whereas the lower boundary for the minimum early gap was CF independent. The findings suggest that human within-perceptual-channel gap detection, showing no dependence of the minimum detectable gap on the duration of the leading noise burst, likely is based on the lower envelope of the distribution of neural minimum gap values of units in AI and AAF. In contrast, across-perceptual-channel gap detection, which shows a decreasing minimum detectable gap with increasing duration of the leading noise burst, likely is based on the comparison ofon responses from populations of neurons that converge on units in AII.

Differential Representation of Species-Specific Primate Vocalizations in the Auditory Cortices of Marmoset and Cat

2001 ◽  
Vol 86 (5) ◽  
pp. 2616-2620 ◽  
Author(s):  
Xiaoqin Wang ◽  
Siddhartha C. Kadia
Keyword(s):  
Auditory Cortex ◽  
Primary Auditory Cortex ◽  
Cortical Processing ◽  
Neural Responses ◽  
The Difference ◽  
Auditory Cortices ◽  
Species Specific ◽  
Primate Vocalizations ◽  
Marmoset Monkeys

A number of studies in various species have demonstrated that natural vocalizations generally produce stronger neural responses than do their time-reversed versions. The majority of neurons in the primary auditory cortex (A1) of marmoset monkeys responds more strongly to natural marmoset vocalizations than to the time-reversed vocalizations. However, it was unclear whether such differences in neural responses were simply due to the difference between the acoustic structures of natural and time-reversed vocalizations or whether they also resulted from the difference in behavioral relevance of both types of the stimuli. To address this issue, we have compared neural responses to natural and time-reversed marmoset twitter calls in A1 of cats with those obtained from A1 of marmosets using identical stimuli. It was found that the preference for natural marmoset twitter calls demonstrated in marmoset A1 was absent in cat A1. While both cortices responded approximately equally to time-reversed twitter calls, marmoset A1 responded much more strongly to natural twitter calls than did cat A1. This differential representation of marmoset vocalizations in two cortices suggests that experience-dependent and possibly species-specific mechanisms are involved in cortical processing of communication sounds.

Sound Localization Deficits During Reversible Deactivation of Primary Auditory Cortex and/or the Dorsal Zone

2008 ◽  
Vol 99 (4) ◽  
pp. 1628-1642 ◽  
Author(s):  
Shveta Malhotra ◽  
G. Christopher Stecker ◽  
John C. Middlebrooks ◽  
Stephen G. Lomber
Keyword(s):  
Auditory Cortex ◽  
Sound Localization ◽  
Primary Auditory Cortex ◽  
Noise Burst ◽  
Orienting Response ◽  
Error Rates ◽  
Broadband Noise ◽  
Physiological Data ◽  
Anterior Ectosylvian Sulcus ◽  
Auditory Field

We examined the contributions of primary auditory cortex (A1) and the dorsal zone of auditory cortex (DZ) to sound localization behavior during separate and combined unilateral and bilateral deactivation. From a central visual fixation point, cats learned to make an orienting response (head movement and approach) to a 100-ms broadband noise burst emitted from a central speaker or one of 12 peripheral sites (located in front of the animal, from left 90° to right 90°, at 15° intervals) along the horizontal plane. Following training, each cat was implanted with separate cryoloops over A1 and DZ bilaterally. Unilateral deactivation of A1 or DZ or simultaneous unilateral deactivation of A1 and DZ (A1/DZ) resulted in spatial localization deficits confined to the contralateral hemifield, whereas sound localization to positions in the ipsilateral hemifield remained unaffected. Simultaneous bilateral deactivation of both A1 and DZ resulted in sound localization performance dropping from near-perfect to chance (7.7% correct) across the entire field. Errors made during bilateral deactivation of A1/DZ tended to be confined to the same hemifield as the target. However, unlike the profound sound localization deficit that occurs when A1 and DZ are deactivated together, deactivation of either A1 or DZ alone produced partial and field-specific deficits. For A1, bilateral deactivation resulted in higher error rates (performance dropping to ∼45%) but relatively small errors (mostly within 30° of the target). In contrast, bilateral deactivation of DZ produced somewhat fewer errors (performance dropping to only ∼60% correct), but the errors tended to be larger, often into the incorrect hemifield. Therefore individual deactivation of either A1 or DZ produced specific and unique sound localization deficits. The results of the present study reveal that DZ plays a role in sound localization. Along with previous anatomical and physiological data, these behavioral data support the view that A1 and DZ are distinct cortical areas. Finally, the findings that deactivation of either A1 or DZ alone produces partial sound localization deficits, whereas deactivation of either posterior auditory field (PAF) or anterior ectosylvian sulcus (AES) produces profound sound localization deficits, suggests that PAF and AES make more significant contributions to sound localization than either A1 or DZ.

Azimuthal sensitivity of neurons in primary auditory cortex of cats. I. Types of sensitivity and the effects of variations in stimulus parameters

1990 ◽  
Vol 64 (3) ◽  
pp. 872-887 ◽  
Author(s):  
R. Rajan ◽  
L. M. Aitkin ◽  
D. R. Irvine ◽  
J. McKay
Keyword(s):  
Auditory Cortex ◽  
Stimulus Intensity ◽  
Primary Auditory Cortex ◽  
Companion Paper ◽  
Broadband Noise ◽  
Central Field ◽  
Sound Sources ◽  
Common Effect ◽  
Response Range ◽  
Definition Of

1. Preliminary to studying the organization of azimuthal sensitivity of neurons along frequency-band strips in the primary auditory cortex (AI) of cat (see companion paper), this study examined the sensitivity of 251 units in cat AI to variations in the azimuthal location of sound sources in the frontal hemifield. Most units (231) were tested with tones at the characteristic frequency (CF; frequency to which the unit had the lowest threshold). Unit CFs ranged from 5 to 36 kHz. A large number of units (91) were tested with broadband noise stimuli, and a few units were also tested at other frequencies within the cell's tuning response area. 2. When tested at stimulus intensities 20-30 dB above CF or noise threshold, the different forms of azimuthal sensitivity exhibited by AI neurons could be divided into (1) contra-field azimuth functions; (2) ipsi-field functions; (3) central-field functions; (4) omnidirectional functions, and (5) multipeaked functions. Contra-field azimuth functions were the most prevalent, with 45.9% of units tested with CF tones and 42.9% of units tested with noise exhibiting this type of azimuthal sensitivity. Ipsi-field azimuthal sensitivity was found in 16.9% of units tested with CF tones and 19.8% of units tested with noise. Central-field azimuthal sensitivity was seen in 10.8% of units tested with CF tones and 17.6% of units tested with noise. Omnidirectional azimuthal sensitivity was seen in 19.9% of units tested with CF tones and 17.6% of units tested with noise, whereas multipeaked azimuthal sensitivity was found in 6.5% of units tested with CF tones and 5.5% of units tested with noise. 3. The effects of increasing stimulus intensity on azimuthal sensitivity were examined in 185 units tested with CF tones and 67 units tested with noise. For four major classes of azimuthal sensitivity (contra-field, ipsi-field, central-field and omnidirectional), the most common effect (approximately 60% of each class) was for the azimuth function to remain constant in form by the defining criteria for these classes. The next most common effect for all classes except omnidirectional azimuth functions was for an expansion of the azimuthal range eliciting responses. (The definition of omnidirectionality precluded any expansion of the response range in this class of azimuth function). A smaller number of units in some classes showed a compression of the azimuth function to a smaller response range, and others showed more complex expansive and compressive effects with increasing stimulus intensity.(ABSTRACT TRUNCATED AT 400 WORDS)

scholarly journals Local and Global Spatial Organization of Interaural Level Difference and Frequency Preferences in Auditory Cortex

2017 ◽  
Vol 28 (1) ◽  
pp. 350-369 ◽  
Author(s):  
Mariangela Panniello ◽  
Andrew J King ◽  
Johannes C Dahmen ◽  
Kerry M M Walker
Keyword(s):  
Auditory Cortex ◽  
Spatial Organization ◽  
Mammalian Species ◽  
Primary Auditory Cortex ◽  
Global Scale ◽  
Interaural Level Difference ◽  
Contralateral Ear ◽  
The Difference ◽  
Interaural Level Differences

Abstract Despite decades of microelectrode recordings, fundamental questions remain about how auditory cortex represents sound-source location. Here, we used in vivo 2-photon calcium imaging to measure the sensitivity of layer II/III neurons in mouse primary auditory cortex (A1) to interaural level differences (ILDs), the principal spatial cue in this species. Although most ILD-sensitive neurons preferred ILDs favoring the contralateral ear, neurons with either midline or ipsilateral preferences were also present. An opponent-channel decoder accurately classified ILDs using the difference in responses between populations of neurons that preferred contralateral-ear-greater and ipsilateral-ear-greater stimuli. We also examined the spatial organization of binaural tuning properties across the imaged neurons with unprecedented resolution. Neurons driven exclusively by contralateral ear stimuli or by binaural stimulation occasionally formed local clusters, but their binaural categories and ILD preferences were not spatially organized on a more global scale. In contrast, the sound frequency preferences of most neurons within local cortical regions fell within a restricted frequency range, and a tonotopic gradient was observed across the cortical surface of individual mice. These results indicate that the representation of ILDs in mouse A1 is comparable to that of most other mammalian species, and appears to lack systematic or consistent spatial order.

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