Computational cognitive models are a fundamental tool in behavioral neuroscience. They instantiate in software precise hypotheses about the cognitive ...
Jun 26, 2023 · We adopt an alternative approach to learn parsimonious cognitive models directly from data. We fit behavior data using a recurrent neural network.
Computational cognitive models are a fundamental tool in behavioral neuroscience. They instantiate in software precise hypotheses about the cognitive ...
Disentangled RNNs are a recurrent neural network architecture including several architectural features that are designed to encourage networks to learn simple, ...
May 30, 2024 · Here, we adopt an alternative approach to learn parsimonious cognitive models directly from data. We fit behavior data using a recurrent neural ...
Jun 26, 2023 · Our experimental and computational paradigm provides a novel way for quantifying how and what aspects of emotional events affect human behavior.
Jul 3, 2023 · We explore automatically learning interpretable models using "Disentangled RNNs". biorxiv.org. Cognitive Model Discovery via Disentangled RNNs.
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Here, we adopt an alternative approach to learn parsimonious cognitive models directly from data. We fit behavior data using a recurrent neural network that is ...
Hybrid neural-cognitive models reveal how memory shapes human reward learning ... Cognitive model discovery via disentangled RNNs. Kevin Miller, Maria ...
Sep 26, 2023 · For example, researchers can fit neural networks directly to behavior data and then assess the relative conse- quences of tightening or relaxing ...