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.

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.

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.

Representation of Spectral and Temporal Sound Features in Three Cortical Fields of the Cat. Similarities Outweigh Differences

1998 ◽  
Vol 80 (5) ◽  
pp. 2743-2764 ◽  
Author(s):  
Jos J. Eggermont
Keyword(s):  
Auditory Cortex ◽  
Frequency Tuning ◽  
Tuning Curve ◽  
Primary Auditory Cortex ◽  
Temporal Coding ◽  
Modulation Transfer ◽  
Temporal Response ◽  
Response Latencies ◽  
Response Properties ◽  
Sound Features

Eggermont, Jos J. Representation of spectral and temporal sound features in three cortical fields of the cat. Similarities outweigh differences. J. Neurophysiol. 80: 2743–2764, 1998. This study investigates the degree of similarity of three different auditory cortical areas with respect to the coding of periodic stimuli. Simultaneous single- and multiunit recordings in response to periodic stimuli were made from primary auditory cortex (AI), anterior auditory field (AAF), and secondary auditory cortex (AII) in the cat to addresses the following questions: is there, within each cortical area, a difference in the temporal coding of periodic click trains, amplitude-modulated (AM) noise bursts, and AM tone bursts? Is there a difference in this coding between the three cortical fields? Is the coding based on the temporal modulation transfer function (tMTF) and on the all-order interspike-interval (ISI) histogram the same? Is the perceptual distinction between rhythm and roughness for AM stimuli related to a temporal versus spatial representation of AM frequency in auditory cortex? Are interarea differences in temporal response properties related to differences in frequency tuning? The results showed that: 1) AM stimuli produce much higher best modulation frequencies (BMFs) and limiting rates than periodic click trains. 2) For periodic click trains and AM noise, the BMFs and limiting rates were not significantly different for the three areas. However, for AM tones the BMF and limiting rates were about a factor 2 lower in AAF compared with the other areas. 3) The representation of stimulus periodicity in ISIs resulted in significantly lower mean BMFs and limiting rates compared with those estimated from the tMTFs. The difference was relatively small for periodic click trains but quite large for both AM stimuli, especially in AI and AII. 4) Modulation frequencies <20 Hz were represented in the ISIs, suggesting that rhythm is coded in auditory cortex in temporal fashion. 5) In general only a modest interdependence of spectral- and temporal-response properties in AI and AII was found. The BMFs were correlated positively with characteristic frequency in AAF. The limiting rate was positively correlated with the frequency-tuning curve bandwidth in AI and AII but not in AAF. Only in AAF was a correlation between BMF and minimum latency was found. Thus whereas differences were found in the frequency-tuning curve bandwidth and minimum response latencies among the three areas, the coding of periodic stimuli in these areas was fairly similar with the exception of the very poor representation of AM tones in AII. This suggests a strong parallel processing organization in auditory cortex.

Functional topography of cat primary auditory cortex: response latencies

1997 ◽  
Vol 181 (6) ◽  
pp. 615-633 ◽  
Author(s):  
J. R. Mendelson ◽  
C. E. Schreiner ◽  
M. L. Sutter
Keyword(s):  
Auditory Cortex ◽  
Primary Auditory Cortex ◽  
Response Latencies ◽  
Functional Topography

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.

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.

Physiology and topography of neurons with multipeaked tuning curves in cat primary auditory cortex

1991 ◽  
Vol 65 (5) ◽  
pp. 1207-1226 ◽  
Author(s):  
M. L. Sutter ◽  
C. E. Schreiner
Keyword(s):  
High Resolution ◽  
Auditory Cortex ◽  
High Frequency ◽  
Primary Auditory Cortex ◽  
Frequency Separation ◽  
Similar Response ◽  
Dorsal Part ◽  
Response Latencies ◽  
Tuning Curves ◽  
Frequency Peak

1. The physiology and topography of single neuron responses along the isofrequency domain of the middle- and high-frequency portions [characteristic frequencies (CFs) greater than 4 kHz] of the primary auditory cortex (AI) were investigated in the barbiturate-anesthetized cat. Single neurons were recorded at several locations along the extent of isofrequency contours, defined from initial multiple-unit mapping. For each neuron a high-resolution excitatory tuning curve was determined, and for some neurons high-resolution two-tone tuning curves were recorded to measure inhibitory/suppressive areas. 2. A physiologically distinct population of neurons was found in the dorsal part of cat AI. These neurons exhibited two or three distinct excitatory frequency ranges, whereas most neurons in AI responded with excitation to a single narrow frequency range. These were called multipeaked neurons because of the shape of their tuning curves. At frequencies between the excitatory regions, the multipeaked neurons were inhibited or unresponsive. 3. Multipeaked neurons exhibited several distinct threshold minima in their frequency tuning curves. Most of the multipeaked neurons (88%) displayed two frequency minima, whereas the rest exhibited three minima. 4. The frequency separation between threshold minima was less than 1 octave in 71% of the double-peaked neurons recorded. Occasionally, the frequency peaks of these neurons closely corresponded to a response to second and third harmonics without a response to the fundamental frequency. 5. Multipeaked neurons exhibited a wide range of total bandwidths (highest excitatory frequency minus lowest excitatory frequency expressed in octaves). Bandwidths of the isolated peaks within the same neuron were also quite variable. 6. Response latencies to tones with frequencies within each peak of a multipeaked neuron could vary considerably. In 71% (17) of the neurons, tones corresponding to the high-frequency peak (CFh) elicited a longer response latency (greater than 4 ms) than those corresponding to the low-frequency peak (CF1). 7. Inhibitory/suppressive bands, as demonstrated with a two-tone paradigm, were often present between the peaks. Typically, neurons with excitatory peaks of similar response latencies showed an inhibitory band located between the peaks. 8. Ninety percent of the topographically localized multipeaked neurons were in the dorsal part of AI (greater than 1 mm dorsal to the maximum in the sharpness-of-tuning map). Although these neurons were restricted to dorsal AI, only 35% of neurons in this region were multipeaked. 9. Multipeaked neurons could show decreased response latencies and thresholds to two-tone combinations.(ABSTRACT TRUNCATED AT 400 WORDS)

Neural Representations of Sinusoidal Amplitude and Frequency Modulations in the Primary Auditory Cortex of Awake Primates

2002 ◽  
Vol 87 (5) ◽  
pp. 2237-2261 ◽  
Author(s):  
Li Liang ◽  
Thomas Lu ◽  
Xiaoqin Wang
Keyword(s):  
Auditory Cortex ◽  
Cortical Neurons ◽  
Neural Coding ◽  
Discharge Rate ◽  
Modulation Frequency ◽  
Primary Auditory Cortex ◽  
Modulation Transfer ◽  
Response Latencies ◽  
Low Frequencies ◽  
Discharge Patterns

We investigated neural coding of sinusoidally modulated tones (sAM and sFM) in the primary auditory cortex (A1) of awake marmoset monkeys, demonstrating that there are systematic cortical representations of embedded temporal features that are based on both average discharge rate and stimulus-synchronized discharge patterns. The rate-representation appears to be coded alongside the stimulus-synchronized discharges, such that the auditory cortex has access to both rate and temporal representations of the stimulus at high and low frequencies, respectively. Furthermore, we showed that individual auditory cortical neurons, as well as populations of neurons, have common features in their responses to both sAM and sFM stimuli. These results may explain the similarities in the perception of sAM and sFM stimuli as well as the different perceptual qualities effected by different modulation frequencies. The main findings include the following. 1) Responses of cortical neurons to sAM and sFM stimuli in awake marmosets were generally much stronger than responses to unmodulated tones. Some neurons responded to sAM or sFM stimuli but not to pure tones. 2) The discharge rate-based modulation transfer function typically had a band-pass shape and was centered at a preferred modulation frequency (rBMF). Population-averaged mean firing rate peaked at 16- to 32-Hz modulation frequency, indicating that the A1 was maximally excited by this frequency range of temporal modulations. 3) Only approximately 60% of recorded units showed statistically significant discharge synchrony to the modulation waveform of sAM or sFM stimuli. The discharge synchrony-based best modulation frequency (tBMF) was typically lower than the rBMF measured from the same neuron. The distribution of rBMF over the population of neurons was approximately one octave higher than the distribution of tBMF. 4) There was a high degree of similarity between cortical responses to sAM and sFM stimuli that was reflected in both discharge rate- or synchrony-based response measures. 5) Inhibition appeared to be a contributing factor in limiting responses at modulation frequencies above the rBMF of a neuron. And 6) neurons with shorter response latencies tended to have higher tBMF and maximum discharge synchrony frequency than those with longer response latencies. rBMF was not significantly correlated with the minimum response latency.

scholarly journals Spontaneous activity is correlated with coding density in primary auditory cortex

2016 ◽  
Vol 116 (6) ◽  
pp. 2789-2798 ◽  
Author(s):  
David A. Bender ◽  
Ruiye Ni ◽  
Dennis L. Barbour
Keyword(s):  
Auditory Cortex ◽  
Spontaneous Activity ◽  
Primary Auditory Cortex ◽  
Wide Band ◽  
Single Unit Activity ◽  
Spontaneous Firing ◽  
Response Latencies ◽  
Sensory Stimuli ◽  
Sensory Modalities ◽  
Different Levels

Sensory neurons across sensory modalities and specific processing areas have diverse levels of spontaneous firing rates (SFRs) in the absence of sensory stimuli. However, the functional significance of this spontaneous activity is not well-understood. Previous studies in the auditory system have demonstrated that different levels of spontaneous activity are correlated with a variety of physiological and anatomic properties, suggesting that neurons with differing SFRs make unique contributions to the encoding of auditory stimuli. Additionally, altered SFRs are a correlate of tinnitus, arising in several auditory areas after exposure to ototoxic substances and noise trauma. In this study, we recorded single-unit activity from primary auditory cortex of awake marmoset monkeys while delivering wide-band random-spectrum stimuli and white Gaussian noise (WGN) to examine any divergences in stimulus encoding properties across SFR classes. We found that higher levels of spontaneous activity were associated with both higher levels of activation relative to suppression across a variety of wide-band stimuli and higher driven rates in response to WGN. Moreover, response latencies to WGN were negatively correlated with the level of activation in response to both stimulus types. These findings are consistent with a novel view of the role spontaneous spiking may play during normal stimulus processing in primary auditory cortex and how it may malfunction in cases of tinnitus.

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