Biology subjects

Buran, B. N.

Publications and source records attributed to Buran, B. N..

5 recordsLinked to original sources

bioRxiv2025

Predicting cochlear synaptopathy in mice with varying degrees of outer hair cell dysfunction using auditory evoked potentials

Human temporal bones suggest a steady decline of cochlear synapses with age and greater synapse loss in adults with a history of military or occupational noise exposure. However, there is currently no validated method of diagnosing this type of cochlear deafferentation in living humans. Animal models indicate that cochlear synaptopathy is associated with reduced auditory brainstem response (ABR) wave 1 amplitude and envelope following response (EFR) magnitude for a sinusoidally amplitude modulated (SAM) tone. However, translating the SAM EFR to humans is complicated because it is difficult to obtain this measurement in humans using the same modulation frequency that showed the strongest relationship with synaptopathy in mice (1000 Hz). Computational modeling suggests that EFR magnitude measured with a rectangular amplitude modulated (RAM) tone may be a more sensitive measure of synaptopathy than the SAM EFR. In addition, because synaptopathy likely co-occurs with outer hair cell dysfunction, a diagnostic assay for synaptopathy needs to be robust even when auditory thresholds are abnormal. This study compared the relative ability of the ABR, SAM EFR, and RAM EFR to predict synapse numbers in mice with a large range of auditory thresholds and degrees of synaptopathy. The results indicate that the RAM EFR modulated at 1000 Hz is the single best predictor of synapse number when there is a broad loss of synapses across frequency, while combining RAM EFR and ABR further improves synapse prediction. In contrast, focal synaptopathy is best predicted by ABR wave 1 amplitude. Significance StatementThis study assessed the relative ability of two auditory evoked potentials to identify cochlear synaptopathy, a type of cochlear deafferentation that occurs with age and noise exposure, in mice. Performance of these measures in the presence of outer hair cell (OHC) damage was also evaluated because synaptopathy is expected to often co-occur with OHC dysfunction. Concrete recommendations of measurements to use for non-invasive diagnosis of synaptopathy in humans are provided. This represents a significant advance toward diagnosis of a condition that is thought to have a high prevalence in humans. The ability to identify individuals with cochlear synaptopathy is vital for furthering our understanding of how this auditory deficit impairs auditory perception and the future development of treatment options.

neuroscience↗

bioRxiv2024

ABRpresto: An algorithm for automatic thresholding of the Auditory Brainstem Response using resampled cross-correlation across subaverages

The auditory brainstem response (ABR) is an essential diagnostic indicator of overall cochlear health, used extensively in both basic research and clinical studies. A key quantification of the ABR is threshold, the lowest sound level that elicits a response. Because the morphology of ABR waveforms shift with stimulus level and the overall signal-to-noise ratio is low, threshold estimation is not straightforward. Although several algorithmic approaches have been proposed, the current standard practice remains the visual evaluation of ABR waveforms as a function of stimulus level. We developed an algorithm based on the cross-correlation of two independent averages of responses to the same stimulus. For each stimulus level, the individual responses to each tone-pip are randomly split into two groups. The median waveform for each group is calculated, and then the normalized cross-correlation between these median waveforms is obtained. This process is repeated 500 times to obtain a resampled cross-correlation distribution. For each frequency, the mean values of these distributions are computed for each level and fit with a sigmoid or a power law function to estimate the threshold. Algorithmic thresholds demonstrated robust and accurate performance, achieving 92% accuracy within {+/-}10 dB of human-rated thresholds on a large pool of mouse data. This performance was better than that of several published algorithms on the same dataset. This algorithm has now fully replaced the manual estimation of ABR thresholds for our preclinical studies, thereby saving significant time and enhancing objectivity in the process.

physiology↗

bioRxiv2019

Optimizing auditory brainstem response acquisition using interleaved frequencies

Auditory brainstem responses (ABRs) require averaging responses to hundreds or thousands of repetitions of a stimulus (e.g., tone pip) to obtain a measurable evoked response at the scalp. Fast repetition rates lead to changes in ABR amplitude and latency due to adaptation. To minimize the effect of adaptation, stimulus rates are sometimes as low as 10 to 13.3 stimuli per second, requiring long acquisition times. The trade-off between reducing acquisition time and minimizing the effect of adaptation on ABR responses is an especially important consideration for studies of cochlear synaptopathy, which use the amplitude of short latency responses (wave 1) to assess auditory nerve survival. It has been proposed that adaptation during ABR acquisition can be reduced by interleaving tones at different frequencies, rather than testing each frequency serially. With careful ordering of frequencies and levels in the stimulus train, adaptation in the auditory nerve can be minimized, thereby permitting an increase in the rate at which tone bursts are presented. However, widespread adoption of this stimulus design has been hindered by lack of available software. Here, we develop and validate an interleaved stimulus design to optimize the rate of ABR measurement while minimizing adaptation. We implement this method in an open-source data acquisition software tool that permits either serial or interleaved ABR measurements. The open-source software library, psiexperiment, is compatible with widely-used ABR hardware. Consistent with previous studies, careful design of an interleaved stimulus train can reduce ABR acquisition time by more than half, with minimal effect on ABR thresholds and wave 1 latency, while improving measures of wave 1 amplitude.

neuroscience↗

bioRxiv2019

Streaming of repeated noise in primary and secondary fields of auditory cortex

Statistical regularities in natural sounds facilitate the perceptual segregation of auditory sources, or streams. Repetition is one cue that drives stream segregation in humans, but the neural basis of this perceptual phenomenon remains unknown. We demonstrated a similar perceptual ability in animals by training ferrets to detect a stream of repeating noise samples (foreground) embedded in a stream of random samples (background). During passive listening, we recorded neural activity in primary (A1) and secondary (PEG) fields of auditory cortex. We used two context-dependent encoding models to test for evidence of streaming of the repeating stimulus. The first was based on average evoked activity per noise sample and the second on the spectro-temporal receptive field (STRF). Both approaches tested whether changes in the neural response to repeating versus random stimuli were better modeled by scaling the response to both streams equally (global gain) or by separately scaling the response to the foreground versus background stream (stream-specific gain). Consistent with previous observations of adaptation, we found an overall reduction in global gain when the stimulus began to repeat. However, when we measured stream-specific changes in gain, responses to the foreground were enhanced relative to the background. This enhancement was stronger in PEG than A1. In A1, enhancement was strongest in units with low sparseness (i.e., broad sensory tuning) and with tuning selective for the repeated sample. Enhancement of responses to the foreground relative to the background provides evidence for stream segregation that emerges in A1 and is refined in PEG.

neuroscience↗

bioRxiv2019

Pupil-associated states modulate excitability but not stimulus selectivity in primary auditory cortex

Recent research in mice indicates that luminance-independent fluctuations in pupil size predict variability in spontaneous and evoked activity of single neurons in auditory and visual cortex. These findings suggest that pupil is an indicator of large-scale changes in arousal state that affect sensory processing. However, it is not known whether pupil-related state also influences the selectivity of auditory neurons. We recorded pupil size and single-unit spiking activity in the primary auditory cortex (A1) of non-anesthetized male and female ferrets during presentation of natural vocalizations and tone stimuli that allow measurement of frequency and level tuning. Neurons showed a systematic increase in both spontaneous and sound-evoked activity when pupil was large, as well as desynchronization and a decrease in trial-to-trial variability. Relationships between pupil size and firing rate were non-monotonic in some cells. In most neurons, several measurements of tuning, including acoustic threshold, spectral bandwidth, and best frequency, remained stable across large changes in pupil size. Across the population, however, there was a small but significant decrease in acoustic threshold when pupil was dilated. In some recordings, we observed rapid, saccade-like eye movements during sustained pupil constriction, which may indicate sleep. Including the presence of this state as a separate variable in a regression model of neural variability accounted for some, but not all, of the variability and non-monotonicity associated with changes in pupil size.\n\nNew & NoteworthyCortical neurons vary in their response to repeated stimuli, and some portion of the variability is due to fluctuations in network state. By simultaneously recording pupil and single-neuron activity in auditory cortex of ferrets, we provide new evidence that network state affects the excitability of auditory neurons, but not sensory selectivity. In addition, we report the occurrence of possible sleep states, adding to evidence that pupil provides an index of both sleep and physiological arousal.

neuroscience↗