Heterogeneous Neuronal Responses to Frequency-Modulated Tones in the Primary Auditory Cortex of Awake Cats

Previous studies in anesthetized animals reported that the primary auditory cortex (A1) showed homogenous phasic responses to FM tones, namely a transient response to a particular instantaneous frequency when FM sweeps traversed a neuron's tone-evoked receptive field (TRF). Here, in awake cats, we report that A1 cells exhibit heterogeneous FM responses, consisting of three patterns. The first is continuous firing when a slow FM sweep traverses the receptive field of a cell with a sustained tonal response. The duration and amplitude of FM response decrease with increasing sweep speed. The second pattern is transient firing corresponding to the cell's phasic tonal response. This response could be evoked only by a fast FM sweep through the cell's TRF, suggesting a preference for fast FM. The third pattern was associated with the off response to pure tones and was composed of several discrete response peaks during slow FM stimulus. These peaks were not predictable from the cell's tonal response but reliably reflected the time when FM swept across specific frequencies. Our A1 samples often exhibited a complex response pattern, combining two or three of the basic patterns above, resulting in a heterogeneous response population. The diversity of FM responses suggests that A1 use multiple mechanisms to fully represent the whole range of FM parameters, including frequency extent, sweep speed, and direction.

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Spectral response patterns of auditory cortex neurons to harmonic complex tones in alert monkey (Macaca mulatta)

Journal of Neurophysiology ◽

10.1152/jn.1990.64.1.282 ◽

1990 ◽

Vol 64 (1) ◽

pp. 282-298 ◽

Cited By ~ 51

Author(s):

D. W. Schwarz ◽

R. W. Tomlinson

Keyword(s):

Receptive Field ◽

Auditory Cortex ◽

Pure Tone ◽

Response Pattern ◽

Response Patterns ◽

Neuronal Responses ◽

Harmonic Complex ◽

Tuning Curves ◽

Complex Tones ◽

Pure Tones

1. The auditory cortex in the superior temporal region of the alert rhesus monkey was explored for neuronal responses to pure and harmonic complex tones and noise. The monkeys had been previously trained to recognize the similarity between harmonic complex tones with and without fundamentals. Because this suggested that they could preceive the pitch of the lacking fundamental similarly to humans, we searched for neuronal responses relevant to this perception. 2. Combination-sensitive neurons that might explain pitch perception were not found in the surveyed cortical regions. Such neurons would exhibit similar responses to stimuli with similar periodicities but differing spectral compositions. The fact that no neuron with responses to a fundamental frequency responded also to a corresponding harmonic complex missing the fundamental indicates that cochlear distortion products at the fundamental may not have been responsible for missing fundamental-pitch perception in these monkeys. 3. Neuronal responses can be expressed as relatively simple filter functions. Neurons with excitatory response areas (tuning curves) displayed various inhibitory sidebands at lower and/or higher frequencies. Thus responses varied along a continuum of combined excitatory and inhibitory filter functions. 4. Five elementary response classes along this continuum are presented to illustrate the range of response patterns. 5. “Filter (F) neurons” had little or no inhibitory sidebands and responded well when any component of a complex tone entered its pure-tone receptive field. Bandwidths increased with intensity. Filter functions of these neurons were thus similar to cochlear nerve-fiber tuning curves. 6. ”High-resolution filter (HRF) neurons” displayed narrow tuning curves with narrowband widths that displayed little growth with intensity. Such cells were able to resolve up to the lowest seven components of harmonic complex tones as distinct responses. They also responded well to wideband stimuli. 7. “Fundamental (F0) neurons” displayed similar tuning bandwidths for pure tones and corresponding fundamentals of harmonic complexes. This response pattern was due to lower harmonic complexes. This response pattern was due to lower inhibitory sidebands. Thus these cells cannot respond to missing fundamentals of harmonic complexes. Only physically present components in the pure-tone receptive field would excite such neurons. 8. Cells with no or very weak responses to pure tones or other narrowband stimuli responded well to harmonic complexes or wideband noise.(ABSTRACT TRUNCATED AT 400 WORDS)

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Functional Organization of Squirrel Monkey Primary Auditory Cortex: Responses to Pure Tones

Journal of Neurophysiology ◽

10.1152/jn.2001.85.4.1732 ◽

2001 ◽

Vol 85 (4) ◽

pp. 1732-1749 ◽

Cited By ~ 75

Author(s):

Steven W. Cheung ◽

Purvis H. Bedenbaugh ◽

Srikantan S. Nagarajan ◽

Christoph E. Schreiner

Keyword(s):

Receptive Field ◽

Auditory Cortex ◽

Squirrel Monkey ◽

Spatial Organization ◽

Functional Organization ◽

Primary Auditory Cortex ◽

Complex Sound ◽

Sound Coding ◽

Field Gradients ◽

Pure Tones

The spatial organization of response parameters in squirrel monkey primary auditory cortex (AI) accessible on the temporal gyrus was determined with the excitatory receptive field to pure tone stimuli. Dense, microelectrode mapping of the temporal gyrus in four animals revealed that characteristic frequency (CF) had a smooth, monotonic gradient that systematically changed from lower values (0.5 kHz) in the caudoventral quadrant to higher values (5–6 kHz) in the rostrodorsal quadrant. The extent of AI on the temporal gyrus was ∼4 mm in the rostrocaudal axis and 2–3 mm in the dorsoventral axis. The entire length of isofrequency contours below 6 kHz was accessible for study. Several independent, spatially organized functional response parameters were demonstrated for the squirrel monkey AI. Latency, the asymptotic minimum arrival time for spikes with increasing sound pressure levels at CF, was topographically organized as a monotonic gradient across AI nearly orthogonal to the CF gradient. Rostral AI had longer latencies (range = 4 ms). Threshold and bandwidth co-varied with the CF. Factoring out the contribution of the CF on threshold variance, residual threshold showed a monotonic gradient across AI that had higher values (range = 10 dB) caudally. The orientation of the threshold gradient was significantly different from the CF gradient. CF-corrected bandwidth, residual Q10, was spatially organized in local patches of coherent values whose loci were specific for each monkey. These data support the existence of multiple, overlying receptive field gradients within AI and form the basis to develop a conceptual framework to understand simple and complex sound coding in mammals.

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Sparse Coding in Temporal Association Cortex Improves Complex Sound Discriminability

10.1101/2020.12.09.417303 ◽

2020 ◽

Author(s):

L Feigin ◽

G Tasaka ◽

I Maor ◽

A Mizrahi

Keyword(s):

Auditory Cortex ◽

Population Analysis ◽

Primary Auditory Cortex ◽

Association Cortex ◽

Temporal Association ◽

Neuronal Responses ◽

Complex Sound ◽

Pure Tones ◽

Auditory Cortices ◽

Auditory Field

AbstractThe mouse auditory cortex is comprised of several auditory fields spanning the dorso-ventral axis of the temporal lobe. The ventral most auditory field is the temporal association cortex (TeA), which remains largely unstudied. Using Neuropixels probes, we simultaneously recorded from primary auditory cortex (AUDp), secondary auditory cortex (AUDv) and TeA, characterizing neuronal responses to pure tones and frequency modulated (FM) sweeps in awake head-restrained mice. As compared to primary and secondary auditory cortices, single unit responses to pure tones in TeA were sparser, delayed and prolonged. Responses to FMs were also sparser. Population analysis showed that the sparser responses in TeA render it less sensitive to pure tones, yet more sensitive to FMs. When characterizing responses to pure tones under anesthesia, the distinct signature of TeA was changed considerably as compared to that in awake mice, implying that responses in TeA are strongly modulated by non-feedforward connections. Together with the known connectivity profile of TeA, these findings suggest that sparse representation of sounds in TeA supports selectivity to higher-order features of sounds and more complex auditory computations.

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

Journal of Neurophysiology ◽

10.1152/jn.00682.2014 ◽

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.

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Responses of neurons in the marmoset primary auditory cortex to interaural level differences: comparison of pure tones and vocalizations

Frontiers in Neuroscience ◽

10.3389/fnins.2015.00132 ◽

2015 ◽

Vol 9 ◽

Cited By ~ 12

Author(s):

Leo L. Lui ◽

Yasamin Mokri ◽

David H. Reser ◽

Marcello G. P. Rosa ◽

Ramesh Rajan

Keyword(s):

Auditory Cortex ◽

Primary Auditory Cortex ◽

Pure Tones ◽

Interaural Level Differences

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A functional model of the slope sensitivity of the primary auditory cortex neurons in awake cats.

The Journal of the Acoustical Society of America ◽

10.1121/1.4782632 ◽

2008 ◽

Vol 124 (4) ◽

pp. 2455-2455

Author(s):

Kenji Ozawa ◽

Yoshikazu Koike ◽

Hiromi Wakagi ◽

Yu Sato ◽

Sohei Chimoto

Keyword(s):

Auditory Cortex ◽

Functional Model ◽

Primary Auditory Cortex ◽

Awake Cats

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Sensory Input Directs Spatial and Temporal Plasticity in Primary Auditory Cortex

Journal of Neurophysiology ◽

10.1152/jn.2001.86.1.326 ◽

2001 ◽

Vol 86 (1) ◽

pp. 326-338 ◽

Cited By ~ 118

Author(s):

Michael P. Kilgard ◽

Pritesh K. Pandya ◽

Jessica Vazquez ◽

Anil Gehi ◽

Christoph E. Schreiner ◽

...

Keyword(s):

Receptive Field ◽

Auditory Cortex ◽

Carrier Frequency ◽

Basal Forebrain ◽

Sensory Input ◽

Cortical Plasticity ◽

Primary Auditory Cortex ◽

Cortical Response ◽

Modulation Rate ◽

A1 Neurons

The cortical representation of the sensory environment is continuously modified by experience. Changes in spatial (receptive field) and temporal response properties of cortical neurons underlie many forms of natural learning. The scale and direction of these changes appear to be determined by specific features of the behavioral tasks that evoke cortical plasticity. The neural mechanisms responsible for this differential plasticity remain unclear partly because important sensory and cognitive parameters differ among these tasks. In this report, we demonstrate that differential sensory experience directs differential plasticity using a single paradigm that eliminates the task-specific variables that have confounded direct comparison of previous studies. Electrical activation of the basal forebrain (BF) was used to gate cortical plasticity mechanisms. The auditory stimulus paired with BF stimulation was systematically varied to determine how several basic features of the sensory input direct plasticity in primary auditory cortex (A1) of adult rats. The distributed cortical response was reconstructed from a dense sampling of A1 neurons after 4 wk of BF-sound pairing. We have previously used this method to show that when a tone is paired with BF activation, the region of the cortical map responding to that tone frequency is specifically expanded. In this report, we demonstrate that receptive-field size is determined by features of the stimulus paired with BF activation. Specifically, receptive fields were narrowed or broadened as a systematic function of both carrier-frequency variability and the temporal modulation rate of paired acoustic stimuli. For example, the mean bandwidth of A1 neurons was increased (+60%) after pairing BF stimulation with a rapid train of tones and decreased (−25%) after pairing unmodulated tones of different frequencies. These effects are consistent with previous reports of receptive-field plasticity evoked by natural learning. The maximum cortical following rate and minimum response latency were also modified as a function of stimulus modulation rate and carrier-frequency variability. The cortical response to a rapid train of tones was nearly doubled if BF stimulation was paired with rapid trains of random carrier frequency, while no following rate plasticity was observed if a single carrier frequency was used. Finally, we observed significant increases in response strength and total area of functionally defined A1 following BF activation paired with certain classes of stimuli and not others. These results indicate that the degree and direction of cortical plasticity of temporal and receptive-field selectivity are specified by the structure and schedule of inputs that co-occur with basal forebrain activation and suggest that the rules of cortical plasticity do not operate on each elemental stimulus feature independently of others.

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