Binaural cues occurring in natural environments are frequently time varying, either from the motion of a sound source or through interactions between the cues produced by multiple sources. Yet, a broad understanding of how the auditory system processes dynamic binaural cues is still lacking. In the current study, we directly compared neural responses in the inferior colliculus (IC) of unanesthetized rabbits to broadband noise with time-varying interaural time differences (ITD) with responses to noise with sinusoidal amplitude modulation (SAM) over a wide range of modulation frequencies. On the basis of prior research, we hypothesized that the IC, one of the first stages to exhibit tuning of firing rate to modulation frequency, might use a common mechanism to encode time-varying information in general. Instead, we found weaker temporal coding for dynamic ITD compared with amplitude modulation and stronger effects of adaptation for amplitude modulation. The differences in temporal coding of dynamic ITD compared with SAM at the single-neuron level could be a neural correlate of "binaural sluggishness," the inability to perceive fluctuations in time-varying binaural cues at high modulation frequencies, for which a physiological explanation has so far remained elusive. At ITD-variation frequencies of 64 Hz and above, where a temporal code was less effective, noise with a dynamic ITD could still be distinguished from noise with a constant ITD through differences in average firing rate in many neurons, suggesting a frequency-dependent tradeoff between rate and temporal coding of time-varying binaural information. Humans use time-varying binaural cues to parse auditory scenes comprising multiple sound sources and reverberation. However, the neural mechanisms for doing so are poorly understood. Our results demonstrate a potential neural correlate for the reduced detectability of fluctuations in time-varying binaural information at high speeds, as occurs in reverberation. The results also suggest that the neural mechanisms for processing time-varying binaural and monaural cues are largely distinct.
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http://dx.doi.org/10.1152/jn.00797.2016 | DOI Listing |
Methods
August 2022
Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072 China; Tianjin Key Laboratory of Brain Science and Neuroengineering, Tianjin 300072 China; Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072 China. Electronic address:
The human auditory system extracts valid information in noisy environments while ignoring other distractions, relying primarily on auditory attention. Studies have shown that the cerebral cortex responds differently to the sound source locations and that auditory attention is time-varying. In this work, we proposed a data-driven encoder-decoder architecture model for auditory attention detection (AAD), denoted as AAD-transformer.
View Article and Find Full Text PDFHear Res
October 2021
Research Group Comparative Neuroscience, Leibniz Institute for Neurobiology, Magdeburg, Germany.
Sounds consisting of multiple simultaneous or consecutive components can be detected by listeners when the stimulus levels of the components are lower than those needed to detect the individual components alone. The mechanisms underlying such spectral, spectrotemporal, temporal, or across-ear integration are not completely understood. Here, we report threshold measurements from human subjects for multicomponent stimuli (tone complexes, tone sequences, diotic or dichotic tones) and for their individual sinusoidal components in quiet.
View Article and Find Full Text PDFNeurosci Lett
September 2021
Department of Audiology, School of Rehabilitation Sciences, Iran University of Medical Sciences, Tehran, Iran. Electronic address:
Background And Aim: Tinnitus is known as a common clinical symptom, and it comprehensively is essential to understand the underlying mechanisms. Time-varying EEG is considered an appropriate technique to explore brain regions and related activities, and nonlinear methods may extract the irregularities in the EEG signal and gather more expanded information. Therefore, we studied Shannon Entropy in EEG raw data obtained from normal subjects and compared it to data from chronic tinnitus sufferers before and after an intervention.
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September 2021
Department of Experimental Psychology, University of Louisville, 2301 S 3rd St, Louisville, KY 40292, United States; Heuser Hearing Institute, 117 E Kentucky St, Louisville, KY 40203, United States.
Previous work has explored novel binaural combinations of reverberation and the resulting perceived reverberation strength (reverberance). The present study examines the perceptual effects of additional binaural combinations of reverberation with the goal of explaining reverberance in terms of basic psychoacoustic principles. Stimuli were generated using virtual space techniques simulating a speech source 3 m to the listener's right in a moderately reverberant environment.
View Article and Find Full Text PDFJ Neurosci
July 2021
Department of Neuroscience, University of Texas at Austin, Austin, Texas 78712
The neurons of the medial superior olive (MSO) of mammals extract azimuthal information from the delays between sounds reaching the two ears [interaural time differences (ITDs)]. Traditionally, all models of sound localization have assumed that MSO neurons represent a single population of cells with specialized and homogeneous intrinsic and synaptic properties that enable the detection of synaptic coincidence on a timescale of tens to hundreds of microseconds. Here, using patch-clamp recordings from large populations of anatomically labeled neurons in brainstem slices from male and female Mongolian gerbils (s), we show that MSO neurons are far more physiologically diverse than previously appreciated, with properties that depend regionally on cell position along the topographic map of frequency.
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