Auditory Processing of Complex Sounds

1990 ◽  
Author(s):  
William P. Shofner
Keyword(s):  
Auditory Processing ◽  
Complex Sounds

Review of Auditory Processing of Complex Sounds.

1988 ◽  
Vol 33 (12) ◽  
pp. 1103-1103
Author(s):  
No authorship indicated
Keyword(s):  
Auditory Processing ◽  
Complex Sounds

Auditory processing of complex sounds: an overview

1992 ◽  
Vol 336 (1278) ◽  
pp. 295-306 ◽  
Keyword(s):  
Auditory System ◽  
Auditory Processing ◽  
Dynamic Range ◽  
Auditory Brainstem ◽  
Frequency Selectivity ◽  
Dorsal Cochlear Nucleus ◽  
Cochlear Nerve ◽  
Complex Sounds ◽  
Wide Range ◽  
Time Coding

The past 30 years has seen a remarkable development in our understanding of how the auditory system - particularly the peripheral system - processes complex sounds. Perhaps the most significant has been our understanding of the mechanisms underlying auditory frequency selectivity and their importance for normal and impaired auditory processing. Physiologically vulnerable cochlear filtering can account for many aspects of our normal and impaired psychophysical frequency selectivity with important consequences for the perception of complex sounds. For normal hearing, remarkable mechanisms in the organ of Corti, involving enhancement of mechanical tuning (in mammals probably by feedback of electro-mechanically generated energy from the hair cells), produce exquisite tuning, reflected in the tuning properties of cochlear nerve fibres. Recent comparisons of physiological (cochlear nerve) and psychophysical frequency selectivity in the same species indicate that the ear’s overall frequency selectivity can be accounted for by this cochlear filtering, at least in band width terms. Because this cochlear filtering is physiologically vulnerable, it deteriorates in deleterious conditions of the cochlea - hypoxia, disease, drugs, noise overexposure, mechanical disturbance - and is reflected in impaired psychophysical frequency selectivity. This is a fundamental feature of sensorineural hearing loss of cochlear origin, and is of diagnostic value. This cochlear filtering, particularly as reflected in the temporal patterns of cochlear fibres to complex sounds, is remarkably robust over a wide range of stimulus levels. Furthermore, cochlear filtering properties are a prime determinant of the ‘place’ and ‘time’ coding of frequency at the cochlear nerve level, both of which appear to be involved in pitch perception. The problem of how the place and time coding of complex sounds is effected over the ear’s remarkably wide dynamic range is briefly addressed. In the auditory brainstem, particularly the dorsal cochlear nucleus, are inhibitory mechanisms responsible for enhancing the spectral and temporal contrasts in complex sounds. These mechanisms are now being dissected neuropharmacologically. At the cortical level, mechanisms are evident that are capable of abstracting biologically relevant features of complex sounds. Fundamental studies of how the auditory system encodes and processes complex sounds are vital to promising recent applications in the diagnosis and rehabilitation of the hearing impaired.

Low level auditory processing of simple and complex sounds in autism

2008 ◽  
Vol 123 (5) ◽  
pp. 3564-3564
Author(s):  
Anna C. Bonnel ◽  
Stephen McAdams ◽  
Bennett K. Smith ◽  
Armando Bertone ◽  
Jake A. Burack ◽  
...  
Keyword(s):  
Auditory Processing ◽  
Complex Sounds ◽  
Low Level

Cortical Processing of Pitch: Excitation or Inhibition?

2008 ◽  
Vol 139 (2_suppl) ◽  
pp. P100-P100 ◽  
Author(s):  
Robert L Harris ◽  
Subrati Nagina ◽  
Steve John Jones
Keyword(s):  
Auditory Processing ◽  
Auditory Evoked Potentials ◽  
Random Noise ◽  
Neuronal Population ◽  
Small Degree ◽  
Complex Sounds ◽  
Short Intervals ◽  
Frequency Representation ◽  
Cortical Regions ◽  
Onset Response

Problem Although tonotopicity provides frequency representation, it does not provide an explicit representation of pitch for complex sounds. For conventional stimuli, it is not possible to vary pitch without varying the spectrum of the sound. It is possible using a regular interval noise(RIN). RIN isolates the neural response associated with the perception of pitch. Several recent studies have identified a specific region in the auditory cortex that contains a cortical representation of pitch. Methods RIN auditory evoked potentials to: 1) determine over what range of temporal periods of RIN evoked a pitch onset response (POR); 2) determine how many cycles of RIN are required for its detection; 3) investigate inter-hemispheric predominance of the POR; 4) investigate if different periodicities are represented in different cortical regions; 5) determine if the degree of refractoriness of the POR is similar when the same pitches occur at regular, short intervals, as when infrequent occurrences of a particular pitch are interspersed with other pitches at the same short intervals. Results 1) a pitch onset response is evoked over the whole range of periodicities giving rise to a sense of musical pitch; 2) at most periodicities less than 2 cycles of RIN are required in order to evoke a response; 3) no marked interhemispheric differences were revealed; 4) evidence for a “periodotopic” distribution of responses was inconclusive; 5) the refractory properties of the response mainly suggested a common neuronal population, but with small degree of pitch specificity. Conclusion There is a striking apparent disparity between human studies, which suggest a large increase in both metabolic and electrophysiological activity when random noise becomes periodic, at whatever pitch, and the animal literature which suggests only a few pitch-selective neurons are excited. We propose a model that explains the observed differences: that the large neuronal population response represents widespread inhibition. Significance The investigation of patients with auditory processing disorders.

scholarly journals Preferred auditory temporal processing regimes and auditory-motor interactions

2020 ◽  
Author(s):  
Pius Kern ◽  
M. Florencia Assaneo ◽  
Dominik Endres ◽  
David Poeppel ◽  
Johanna M. Rimmele
Keyword(s):  
Auditory Processing ◽  
Model Comparison ◽  
Temporal Dynamics ◽  
Auditory Temporal Processing ◽  
Complex Sounds ◽  
Bayesian Model Comparison ◽  
Perceptual Performance ◽  
The Rich ◽  
Processing Regimes ◽  
Theta Range

AbstractDecoding the rich temporal dynamics of complex sounds such as speech is constrained by the underlying neuronal processing mechanisms. Oscillatory theories suggest the existence of one optimal perceptual performance regime at auditory stimulation rates in the delta to theta range (<10 Hz), but reduced performance in the alpha range (10-14 Hz) is controversial. Additionally, the widely discussed motor system contribution to timing remains unclear. We measured rate discrimination thresholds between 4-15 Hz, and auditory-motor coupling strength was estimated through auditory-motor synchronization. In a Bayesian model comparison, high auditory-motor synchronizers showed a larger range of constant optimal temporal judgments than low synchronizers, with performance decreasing in the alpha range. This evidence for optimal auditory processing in the theta range is consistent with preferred oscillatory regimes in auditory cortex that compartmentalize stimulus encoding and processing. The findings suggest, remarkably, that increased auditory-motor interaction might extend such an optimal range towards faster rates.

scholarly journals Linear superposition of responses evoked by individual glottal pulses explain over 80% of the frequency following response to human speech in the macaque monkey

2021 ◽  
Author(s):  
Tobias Teichert ◽  
G. Nike Gnanateja ◽  
Srivatsun Sadagopan ◽  
Bharath Chandrasekaran
Keyword(s):  
Steady State ◽  
Auditory Processing ◽  
High Signal ◽  
Time Varying ◽  
Linear Superposition ◽  
Complex Sounds ◽  
Human Speech ◽  
Frequency Following Response ◽  
Temporal Complexity ◽  
Time Varying Pitch

AbstractThe frequency-following response (FFR) is a scalp-recorded electrophysiological potential that closely follows the periodicity of complex sounds such as speech. It has been suggested that FFRs reflect the linear superposition of responses that are triggered by the glottal pulse in each cycle of the fundamental frequency (F0 responses) and sequentially propagate through auditory processing stages in brainstem, midbrain, and cortex. However, this conceptualization of the FFR is debated, and it remains unclear if and how well a simple linear superposition can capture the spectro-temporal complexity of FFRs that are generated within the highly recurrent and non-linear auditory system. To address this question, we used a deconvolution approach to compute the hypothetical F0 responses that best explain the FFRs in rhesus monkeys to human speech and click trains with time-varying pitch patterns. The linear superposition of F0 responses explained well over 90% of the variance of click train steady state FFRs and well over 80% of mandarin tone steady state FFRs. The F0 responses could be measured with high signal-to-noise ratio and featured several spectro-temporally and topographically distinct components that likely reflect the activation of brainstem (<5ms; 200-1000 Hz), midbrain (5-15 ms; 100-250 Hz) and cortex (15-35 ms; ~90 Hz). In summary, our results in the monkey support the notion that FFRs arise as the superposition of F0 responses by showing for the first time that they can capture the bulk of the variance and spectro-temporal complexity of FFRs to human speech with time-varying pitch. These findings identify F0 responses as a potential diagnostic tool that may be useful to reliably link altered FFRs in speech and language disorders to altered F0 responses and thus to specific latencies, frequency bands and ultimately processing stages.

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