Satyabrata Parida
Overview
Explore the profile of Satyabrata Parida including associated specialties, affiliations and a list of published articles.
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13
Citations
38
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Recent Articles
1.
Wingert J, Parida S, Norman-Haignere S, David S
bioRxiv
. 2024 Nov;
PMID: 39574636
Auditory cortex encodes information about nonlinear combinations of spectro-temporal sound features. Convolutional neural networks (CNNs) provide an architecture for generalizable encoding models that can predict time-varying neural activity evoked by...
2.
Parida S, Yurasits K, Cancel V, Zink M, Mitchell C, Ziliak M, et al.
Commun Biol
. 2024 Nov;
7(1):1517.
PMID: 39548272
Current tests of hearing fail to diagnose pathologies in ~10% of patients seeking help for hearing difficulties. Neural ensemble responses to perceptually relevant cues in the amplitude envelope, termed envelope...
3.
Parida S, Yurasits K, Cancel V, Zink M, Mitchell C, Ziliak M, et al.
bioRxiv
. 2024 Feb;
PMID: 38352339
Auditory neural coding of speech-relevant temporal cues can be noninvasively probed using envelope following responses (EFRs), neural ensemble responses phase-locked to the stimulus amplitude envelope. EFRs emphasize different neural generators,...
4.
Deloche F, Parida S, Sivaprakasam A, Heinz M
J Assoc Res Otolaryngol
. 2024 Jan;
25(1):35-51.
PMID: 38278969
Purpose: Frequency selectivity is a fundamental property of the peripheral auditory system; however, the invasiveness of auditory nerve (AN) experiments limits its study in the human ear. Compound action potentials...
5.
Suresh C, Leng K, Washnik N, Parida S
J Otol
. 2023 Jul;
18(3):152-159.
PMID: 37497332
Background/purpose: With increasing accessibility to the Internet, patients frequently use the Internet for hearing healthcare information. No study has examined the information about hearing loss available in the Mandarin language...
6.
Parida S, Liu S, Sadagopan S
Commun Biol
. 2023 May;
6(1):456.
PMID: 37130918
For robust vocalization perception, the auditory system must generalize over variability in vocalization production as well as variability arising from the listening environment (e.g., noise and reverberation). We previously demonstrated...
7.
Sadagopan S, Kar M, Parida S
Hear Res
. 2023 Jan;
429:108697.
PMID: 36696724
To generate insight from experimental data, it is critical to understand the inter-relationships between individual data points and place them in context within a structured framework. Quantitative modeling can provide...
8.
Kar M, Pernia M, Williams K, Parida S, Schneider N, McAndrew M, et al.
Elife
. 2022 Oct;
11.
PMID: 36226815
Vocal animals produce multiple categories of calls with high between- and within-subject variability, over which listeners must generalize to accomplish call categorization. The behavioral strategies and neural mechanisms that support...
9.
Montes-Lourido P, Kar M, Pernia M, Parida S, Sadagopan S
Hear Res
. 2022 Sep;
424:108603.
PMID: 36099806
For gaining insight into general principles of auditory processing, it is critical to choose model organisms whose set of natural behaviors encompasses the processes being investigated. This reasoning has led...
10.
Parida S, Heinz M
Hear Res
. 2022 Aug;
426:108586.
PMID: 35953357
Listeners with sensorineural hearing loss (SNHL) have substantial perceptual deficits, especially in noisy environments. Unfortunately, speech-intelligibility models have limited success in predicting the performance of listeners with hearing loss. A...