scholarly journals Binaural processing by the gecko auditory periphery

2011 ◽  
Vol 105 (5) ◽  
pp. 1992-2004 ◽  
Author(s):  
Jakob Christensen-Dalsgaard ◽  
Yezhong Tang ◽  
Catherine E. Carr
Keyword(s):  
Auditory Nerve ◽  
Auditory Pathway ◽  
Peak Frequency ◽  
Auditory Periphery ◽  
Transmission Delays ◽  
Binaural Processing ◽  
Mouth Cavity ◽  
Tokay Gecko ◽  
Interaural Level Differences ◽  
Nerve Recordings

Lizards have highly directional ears, owing to strong acoustical coupling of the eardrums and almost perfect sound transmission from the contralateral ear. To investigate the neural processing of this remarkable tympanic directionality, we combined biophysical measurements of eardrum motion in the Tokay gecko with neurophysiological recordings from the auditory nerve. Laser vibrometry shows that their ear is a two-input system with approximately unity interaural transmission gain at the peak frequency (∼1.6 kHz). Median interaural delays are 260 μs, almost three times larger than predicted from gecko head size, suggesting interaural transmission may be boosted by resonances in the large, open mouth cavity ( Vossen et al. 2010 ). Auditory nerve recordings are sensitive to both interaural time differences (ITD) and interaural level differences (ILD), reflecting the acoustical interactions of direct and indirect sound components at the eardrum. Best ITD and click delays match interaural transmission delays, with a range of 200–500 μs. Inserting a mold in the mouth cavity blocks ITD and ILD sensitivity. Thus the neural response accurately reflects tympanic directionality, and most neurons in the auditory pathway should be directional.

scholarly journals Simple transformations capture auditory input to cortex

2020 ◽  
Vol 117 (45) ◽  
pp. 28442-28451
Author(s):  
Monzilur Rahman ◽  
Ben D. B. Willmore ◽  
Andrew J. King ◽  
Nicol S. Harper
Keyword(s):  
Auditory Nerve ◽  
Time Course ◽  
Primary Auditory Cortex ◽  
Auditory Pathway ◽  
Auditory Nerve Fiber ◽  
Neural Responses ◽  
Auditory Periphery ◽  
Cortical Responses ◽  
Combined Models ◽  
Simple Models

Sounds are processed by the ear and central auditory pathway. These processing steps are biologically complex, and many aspects of the transformation from sound waveforms to cortical response remain unclear. To understand this transformation, we combined models of the auditory periphery with various encoding models to predict auditory cortical responses to natural sounds. The cochlear models ranged from detailed biophysical simulations of the cochlea and auditory nerve to simple spectrogram-like approximations of the information processing in these structures. For three different stimulus sets, we tested the capacity of these models to predict the time course of single-unit neural responses recorded in ferret primary auditory cortex. We found that simple models based on a log-spaced spectrogram with approximately logarithmic compression perform similarly to the best-performing biophysically detailed models of the auditory periphery, and more consistently well over diverse natural and synthetic sounds. Furthermore, we demonstrated that including approximations of the three categories of auditory nerve fiber in these simple models can substantially improve prediction, particularly when combined with a network encoding model. Our findings imply that the properties of the auditory periphery and central pathway may together result in a simpler than expected functional transformation from ear to cortex. Thus, much of the detailed biological complexity seen in the auditory periphery does not appear to be important for understanding the cortical representation of sound.

scholarly journals Strongly directional responses to tones and conspecific calls in the auditory nerve of the Tokay gecko, Gekko gecko.

2021 ◽  
Author(s):  
Jakob Christensen-Dalsgaard ◽  
Paula T. Kuokkanen ◽  
Jamie Emoto Matthews ◽  
Catherine E. Carr
Keyword(s):  
Auditory Nerve ◽  
Dynamic Range ◽  
Free Field ◽  
High Capacity ◽  
Auditory Pathway ◽  
Sound Sources ◽  
Gekko Gecko ◽  
Sound Direction ◽  
Tokay Gecko ◽  
Field Sound

The configuration of lizard ears, where sound can reach both surfaces of the eardrums, produces a strongly directional ear, but the subsequent processing of sound direction by the auditory pathway is unknown. We report here on directional responses from the first stage, the auditory nerve. We used laser vibrometry to measure eardrum responses in Tokay geckos, and in the same animals recorded 117 auditory nerve single fiber responses to free-field sound from radially distributed speakers. Responses from all fibers showed strongly lateralized activity at all frequencies, with an ovoidal directivity that resembled the eardrum directivity. Geckos are vocal and showed pronounced nerve fiber directionality to components of the call. To estimate the accuracy with which a gecko could discriminate between sound sources, we computed the Fisher information (FI) for each neuron. FI was highest just contralateral to the midline, front and back. Thus, the auditory nerve could provide a population code for sound source direction, and geckos should have a high capacity to differentiate between midline sound sources. In brain, binaural comparisons, for example by IE neurons, should sharpen the lateralized responses and extend the dynamic range of directionality.

MODELING AUDITORY PATHWAY FOR INTELLIGENT INFORMATION ACQUISITION

2004 ◽  
Vol 01 (04) ◽  
pp. 345-356
Author(s):  
HYUNG-MIN PARK ◽  
JONG-HWAN LEE ◽  
TAESU KIM ◽  
UN-MIN BAE ◽  
BYUNG TAEK KIM ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Real World ◽  
Information Acquisition ◽  
Recognition Performance ◽  
Auditory Pathway ◽  
Blind Signal Separation ◽  
Top Down ◽  
Auditory Model ◽  
Time Frequency ◽  
Binaural Processing

An auditory model has been developed for an intelligent speech information acquisition system in real-world noisy environment. The developed mathematical model of the human auditory pathway consists of three components, i.e. the nonlinear feature extraction from cochlea to auditory cortex, the binaural processing at superior olivery complex, and the top-down attention from higher brain to the cochlea. The feature extraction is based on information-theoretic sparse coding throughout the auditory pathway. Also, the time-frequency masking is incorporated as a model of the lateral inhibition in both time and frequency domain. The binaural processing is modeled as the blind signal separation and adaptive noise canceling based on the independent component analysis with hundreds of time-delays for noisy reverberated signals. The Top-Down (TD) attention comes from familiarity and/or importance of the sensory information, i.e. the sound, and a simple but efficient TD attention model had been developed based on the error backpropagation algorithm. Also, the binaural processing and top-down attention are combined for speech signals with heavy noises. This auditory model requires extensive computing, and special hardware had been developed for real-time applications. Experimental results demonstrate much better recognition performance in real-world noisy environments.

scholarly journals Prediction of Human's Ability in Sound Localization Based on the Statistical Properties of Spike Trains along the Brainstem Auditory Pathway

2014 ◽  
Vol 2014 ◽  
pp. 1-11
Author(s):  
Ram Krips ◽  
Miriam Furst
Keyword(s):  
Time Delay ◽  
Lower Bounds ◽  
Sound Localization ◽  
Human Performance ◽  
Acoustic Stimulus ◽  
Auditory Pathway ◽  
Superior Olivary Complex ◽  
Optimal Estimator ◽  
Interaural Time Delay ◽  
Interaural Level Differences

The minimum audible angle test which is commonly used for evaluating human localization ability depends on interaural time delay, interaural level differences, and spectral information about the acoustic stimulus. These physical properties are estimated at different stages along the brainstem auditory pathway. The interaural time delay is ambiguous at certain frequencies, thus confusion arises as to the source of these frequencies. It is assumed that in a typical minimum audible angle experiment, the brain acts as an unbiased optimal estimator and thus the human performance can be obtained by deriving optimal lower bounds. Two types of lower bounds are tested: the Cramer-Rao and the Barankin. The Cramer-Rao bound only takes into account the approximation of the true direction of the stimulus; the Barankin bound considers other possible directions that arise from the ambiguous phase information. These lower bounds are derived at the output of the auditory nerve and of the superior olivary complex where binaural cues are estimated. An agreement between human experimental data was obtained only when the superior olivary complex was considered and the Barankin lower bound was used. This result suggests that sound localization is estimated by the auditory nuclei using ambiguous binaural information.

scholarly journals Fine frequency tuning in monkey auditory cortex and thalamus

2011 ◽  
Vol 106 (2) ◽  
pp. 849-859 ◽  
Author(s):  
Edward L. Bartlett ◽  
Srivatsun Sadagopan ◽  
Xiaoqin Wang
Keyword(s):  
Auditory Cortex ◽  
Auditory Nerve ◽  
Animal Studies ◽  
De Novo ◽  
Frequency Tuning ◽  
Primary Auditory Cortex ◽  
Auditory Pathway ◽  
Nerve Fibers ◽  
Frequency Resolution ◽  
Human Auditory Cortex

The frequency resolution of neurons throughout the ascending auditory pathway is important for understanding how sounds are processed. In many animal studies, the frequency tuning widths are about 1/5th octave wide in auditory nerve fibers and much wider in auditory cortex neurons. Psychophysical studies show that humans are capable of discriminating far finer frequency differences. A recent study suggested that this is perhaps attributable to fine frequency tuning of neurons in human auditory cortex (Bitterman Y, Mukamel R, Malach R, Fried I, Nelken I. Nature 451: 197–201, 2008). We investigated whether such fine frequency tuning was restricted to human auditory cortex by examining the frequency tuning width in the awake common marmoset monkey. We show that 27% of neurons in the primary auditory cortex exhibit frequency tuning that is finer than the typical frequency tuning of the auditory nerve and substantially finer than previously reported cortical data obtained from anesthetized animals. Fine frequency tuning is also present in 76% of neurons of the auditory thalamus in awake marmosets. Frequency tuning was narrower during the sustained response compared to the onset response in auditory cortex neurons but not in thalamic neurons, suggesting that thalamocortical or intracortical dynamics shape time-dependent frequency tuning in cortex. These findings challenge the notion that the fine frequency tuning of auditory cortex is unique to human auditory cortex and that it is a de novo cortical property, suggesting that the broader tuning observed in previous animal studies may arise from the use of anesthesia during physiological recordings or from species differences.

Temporal Damping in Response to Broadband Noise. II. Auditory Nerve

2008 ◽  
Vol 99 (4) ◽  
pp. 1942-1952 ◽  
Author(s):  
Philip X. Joris ◽  
Dries H. Louage ◽  
Marcel van der Heijden
Keyword(s):  
Inferior Colliculus ◽  
Auditory Nerve ◽  
Low Frequency ◽  
Auditory Pathway ◽  
Broadband Noise ◽  
Linear Summation ◽  
Interaural Time Differences ◽  
Oscillatory Response ◽  
Original Report ◽  
Composite Curve

II. Auditory nerve. Low-frequency neurons in the inferior colliculus (IC) show a damped oscillatory response as a function of interaural time differences (ITDs) of broadband noise. It was previously shown that several features of such noise-delay functions are well predicted by the composite curve, generated by the linear summation of responses to tones with varying ITD. This indicates a surprising degree of linearity at the midbrain level of the auditory pathway. A similar comparison between responses to tones and to noise has not been made at a more peripheral, monaural level and it is therefore unclear to what extent this linearity reflects peripheral physiology. Here, we compare cat auditory nerve responses to broadband noise and to isolevel tones. We constructed shuffled autocorrelograms for responses to tones and summed across frequencies to obtain a monaural composite curve. We then compare this composite curve to the shuffled autocorrelogram of responses to broadband noise and find that the match between tonal and noise responses is poorer at the level of the auditory nerve than at the level of the IC. The apparent linearity of responses in the IC is thus even more surprising than was apparent from its original report because it results from mechanisms interposed between the auditory nerve and the IC.

scholarly journals Auditory nerve fibre activity in the tokay gecko

1981 ◽  
Vol 142 (2) ◽  
pp. 203-218 ◽  
Author(s):  
R. A. Eatock ◽  
G. A. Manley ◽  
L. Pawson
Keyword(s):  
Nerve Fibre ◽  
Auditory Nerve ◽  
Auditory Nerve Fibre ◽  
Tokay Gecko
Sign in / Sign up

Export Citation Format

Share Document