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Flexible inference for animal learning rules using neural networks

Year: 2025

Type: conference-paper

Abstract: learning tasks, setting the stage for improved animal training protocols and the development of behavioral digital twins.

Source: neural information processing systems

DOI: 10.52202/085713-0295

Authors: Yuhan Helena Liu, Victor Geadah, Jonathan Pillow

Institution: Princeton University

Language: English

Topic: Neural Networks and Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: National Institutes of Health, National Institute on Drug Abuse, National Institute of Neurological Disorders and Stroke, National Institute of Biomedical Imaging and Bioengineering

Awards: Adaptive statistical algorithms for learning and control of neural dynamics, Real-time statistical algorithms for controlling neural dynamics and behavior, Neural time-integration underlying higher cognitive function, Mechanisms of neural circuit dynamics in working memory anddecision-making, Mechanisms of persistent neural activity

OpenAlex ID: W4414759528

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