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CRCNS: Identifying principles of auditory cortical organization with machine learning

Award Number: R01DC021600
ORGANIZATION: NATIONAL INSTITUTE ON DEAFNESS AND OTHER COMMUNICATION DISORDERS
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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The human auditory system transforms incoming acoustic information into distinct auditory “objects” that can be interpreted, localized, and integrated with information from the other senses. A human listener can resolve, for example, a monophonic musical recording into piano and guitar, or parse speech audio into a sequence of words. We do not currently understand how this is achieved, nor how transformations in sound processing across cortical regions contribute, especially beyond primary auditory cortex. On the other hand, we now have available another, more easily investigated system that—as of this last decade—solves such problems at human performance levels: the artificial neural network (ANN). Although crude as biophysical models, ANNs strongly resemble biological neural networks in terms of computation and representation. We propose to compare single-unit electrophysiology in macaque auditory cortex with state-of-the-art ANNs trained to solve ecologically relevant auditory tasks. This combination allows us to track how transformations in perceptual representations are distributed and instantiated in the brain; to experiment with multiple ANN architectures and tasks to test hypotheses about why the representations take the forms we observe; and to refine iteratively our stimulus protocols and models. Our objectives are (1) to evaluate these ANNs as encoding models for neurons in macaque auditory cortex, recorded during auditory discrimination tasks; (2) to use the internal structure of ANNs to generate and test novel hypotheses about the topographical and hierarchical organization of non-primary auditory cortex; and (3) to demonstrate “stimulus- based control” of neurons throughout nonprimary auditory cortex: optimizing stimuli via the ANN and then playing to the animals in closed-loop neurophysiology experiments.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2024 ( Subtotal = $379,319 )
2024	2024	UNIVERSITY OF CALIFORNIA, DAVIS	1850 RESEARCH PARK DR STE 300	DAVIS	CA	95618	YOLO	USA	Research Related to Deafness and Communication Disorders	000	2	7/10/2024	NON-COMPETING CONTINUATION	$379,319
														Subtotal = $379,319

Issue Date FY: 2023 ( Subtotal = $354,609 )
2023	2023	UNIVERSITY OF CALIFORNIA, DAVIS	1850 RESEARCH PARK DR, STE 300	DAVIS	CA	95618	YOLO	USA	Research Related to Deafness and Communication Disorders	000	1	7/12/2023	NEW	$354,609
														Subtotal = $354,609

Grand Total All Awards = $733,928

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CRCNS: Identifying principles of auditory cortical organization with machine learning

Award Number: R01DC021600

ORGANIZATION: NATIONAL INSTITUTE ON DEAFNESS AND OTHER COMMUNICATION DISORDERS

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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