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Adaptive population codes for flexible visually-guided behaviors

Award Number: R01EY025872
ORGANIZATION: NATIONAL EYE INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 06/01/2025
PERIOD OF PERFORMANCE END DATE: 05/31/2029

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Adaptive population codes for flexible visually-guided behaviors - Summary/Abstract Traditional models of visual information processing propose that stable perceptual and mnemonic representations are supported by persistent activity in neurons that are selective for relevant stimulus features. However, there is an emerging focus on the importance of reducing redundancy in neural codes to achieve more efficient processing. For example, the visual system adapts to overall lightness levels and to frequently encountered stimuli, allowing neural codes to maintain a useful dynamic range and to expend less energy encoding expected stimuli. In addition to dynamics induced by recent stimulus history, recent work in machine learning and in animal model systems reveals that codes also drift over short and long time scales, often while preserving population-level geometric relationships between different stimulus representations. While many factors likely contribute to this set of phenomena, here we focus on the general hypothesis that dynamics induced by stimulus history and other factors support efficient yet error-tolerant codes. For example, recent work in our lab suggests that the perceptual distortions induced by adaptation (e.g. the classic motion after-effect) are offset by a flexible decoding scheme that utilizes a prior for temporal stability to compensate. Short-term dynamics, particularly during visual working memory, at least partially reflect a reduction in the complexity of representations so that only the most behaviorally relevant aspects of sensory information are retained to guide behavior. Finally, long-term dynamics, or representational drift, may reflect a refining of neural codes to support increasingly sparse information processing that is still robust to interference. In the present proposal, we build on this recent empirical and theoretical work to evaluate the functional role of neural dynamics driven by different factors across different time scales. We first test how the flexibility of Bayesian read-out rules allows the visual system to counter the effects of stimulus history to produce continuous and robust representation even in the face of internal and external noise. We then use recurrent neural networks (RNNs) with different processing constraints to show that a drive toward sparser, and more energy efficient, representations is sufficient to induce short and long-term drift in neural codes. Guided by these modelling efforts, we will evaluate the impact of drift on neural codes as measured in human visual cortex using functional magnetic resonance imaging (fMRI) and psychophysics, with a focus on testing hypotheses about the impact of drift on the dimensionality and robustness of feature-selective activation patterns. Collectively, this work will challenge traditional theories of perceptual inference, attentional selection, and working memory that are based on the notion of stable neural codes by providing novel insights into the functional role that pervasive neural dynamics play in visual information processing.


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: 2025 ( Subtotal = $501,958 )
2025	2025	UNIVERSITY OF CALIFORNIA, SAN DIEGO	9500 GILMAN DR	LA JOLLA	CA	92093	SAN DIEGO	USA	Vision Research	001	15	5/7/2025	COMPETING CONTINUATION	$501,958
2025	2025	UNIVERSITY OF CALIFORNIA, SAN DIEGO	9500 GILMAN DR	LA JOLLA	CA	92093	SAN DIEGO	USA	Vision Research	002	15	5/29/2025	COMPETING CONTINUATION	$0
2025	2024	UNIVERSITY OF CALIFORNIA, SAN DIEGO	9500 GILMAN DR	LA JOLLA	CA	92093	SAN DIEGO	USA	Vision Research	000	14	5/1/2025	NON-COMPETING CONTINUATION	$0
														Subtotal = $501,958

Issue Date FY: 2024 ( Subtotal = $395,000 )
2024	2024	UNIVERSITY OF CALIFORNIA, SAN DIEGO	9500 GILMAN DRIVE	LA JOLLA	CA	92093	SAN DIEGO	USA	Vision Research	000	14	11/30/2023	NON-COMPETING CONTINUATION	$395,000
														Subtotal = $395,000

Issue Date FY: 2023 ( Subtotal = $395,000 )
2023	2023	UNIVERSITY OF CALIFORNIA, SAN DIEGO	9500 GILMAN DR	LA JOLLA	CA	92093	SAN DIEGO	USA	Vision Research	000	13	12/8/2022	NON-COMPETING CONTINUATION	$355,500
2023	2023	UNIVERSITY OF CALIFORNIA, SAN DIEGO	9500 GILMAN DRIVE	LA JOLLA	CA	92093	SAN DIEGO	USA	Vision Research	001	13	3/8/2023	NON-COMPETING CONTINUATION	$39,500
														Subtotal = $395,000

Issue Date FY: 2022 ( Subtotal = $383,150 )
2022	2022	UNIVERSITY OF CALIFORNIA, SAN DIEGO	9500 GILMAN DR	LA JOLLA	CA	92093	SAN DIEGO	USA	Vision Research	000	12	11/22/2021	NON-COMPETING CONTINUATION	$355,500
2022	2022	UNIVERSITY OF CALIFORNIA, SAN DIEGO	9500 GILMAN DR	LA JOLLA	CA	92093	SAN DIEGO	USA	Vision Research	001	12	1/31/2022	NON-COMPETING CONTINUATION	$27,650
														Subtotal = $383,150

Issue Date FY: 2021 ( Subtotal = $394,375 )
2021	2021	UNIVERSITY OF CALIFORNIA, SAN DIEGO	9500 GILMAN DR	LA JOLLA	CA	92093	SAN DIEGO	USA	Vision Research	000	11	12/17/2020	COMPETING CONTINUATION	$394,375
2021	2021	UNIVERSITY OF CALIFORNIA, SAN DIEGO	9500 GILMAN DR	LA JOLLA	CA	92093	SAN DIEGO	USA	Vision Research	003	11	5/18/2021	COMPETING CONTINUATION	$51,061
2021	2020	UNIVERSITY OF CALIFORNIA, SAN DIEGO	9500 GILMAN DR	LA JOLLA	CA	92093	SAN DIEGO	USA	Vision Research	001	10	1/22/2021	NON-COMPETING CONTINUATION	$0
2021	2020	UNIVERSITY OF CALIFORNIA, SAN DIEGO	9500 GILMAN DR	LA JOLLA	CA	92093	SAN DIEGO	USA	Vision Research	002	10	5/18/2021	NON-COMPETING CONTINUATION	-$51,061
														Subtotal = $394,375

Issue Date FY: 2020 ( Subtotal = $387,500 )
2020	2020	UNIVERSITY OF CALIFORNIA, SAN DIEGO	9500 GILMAN DR DEPT 621	LA JOLLA	CA	92093	SAN DIEGO	USA	Vision Research	000	10	12/5/2019	NON-COMPETING CONTINUATION	$348,750
2020	2020	UNIVERSITY OF CALIFORNIA, SAN DIEGO	9500 GILMAN DR	LA JOLLA	CA	92093	SAN DIEGO	USA	Vision Research	001	10	1/27/2020	NON-COMPETING CONTINUATION	$38,750
														Subtotal = $387,500

Issue Date FY: 2019 ( Subtotal = $387,500 )
2019	2019	UNIVERSITY OF CALIFORNIA, SAN DIEGO	9500 GILMAN DR DEPT 621	LA JOLLA	CA	92093	SAN DIEGO	USA	Vision Research	000	9	11/28/2018	NON-COMPETING CONTINUATION	$387,500
														Subtotal = $387,500

Issue Date FY: 2018 ( Subtotal = $387,500 )
2018	2018	UNIVERSITY OF CALIFORNIA, SAN DIEGO	9500 GILMAN DR DEPT 621	LA JOLLA	CA	92093	SAN DIEGO	USA	Vision Research	000	8	11/17/2017	NON-COMPETING CONTINUATION	$348,750
2018	2018	UNIVERSITY OF CALIFORNIA, SAN DIEGO	9500 GILMAN DR DEPT 621	LA JOLLA	CA	92093	SAN DIEGO	USA	Vision Research	001	8	5/3/2018	NON-COMPETING CONTINUATION	$38,750
														Subtotal = $387,500

Issue Date FY: 2017 ( Subtotal = $387,500 )
2017	2017	UNIVERSITY OF CALIFORNIA, SAN DIEGO	9500 GILMAN DR DEPT 621	LA JOLLA	CA	92093	SAN DIEGO	USA	Vision Research	001	7	7/10/2017	NON-COMPETING CONTINUATION	$38,750
2017	2017	UNIVERSITY OF CALIFORNIA, SAN DIEGO	9500 GILMAN DR DEPT 621	LA JOLLA	CA	92093	SAN DIEGO	USA	Vision Research	000	7	12/5/2016	NON-COMPETING CONTINUATION	$348,750
														Subtotal = $387,500

Issue Date FY: 2016 ( Subtotal = $387,500 )
2016	2016	UNIVERSITY OF CALIFORNIA-SAN DIEGO	9500 GILMAN DRIVE	LA JOLLA	CA	92093	SAN DIEGO	USA	Vision Research	000	6	11/24/2015	CHANGE OF GRANTEE / TRAINING INSTITUTION / AWARDING INSTITUTION	$387,500
														Subtotal = $387,500

Grand Total All Awards = $4,006,983

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Adaptive population codes for flexible visually-guided behaviors

Award Number: R01EY025872

ORGANIZATION: NATIONAL EYE INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

PERIOD OF PERFORMANCE START DATE: 06/01/2025

PERIOD OF PERFORMANCE END DATE: 05/31/2029

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