Synchronization can Control Regularization in Neural Systems via Correlated Noise Processes
Year: 2012
Type: conference-paper
Abstract: To learn reliable rules that can generalize to novel situations, the brain must be ca-pable of imposing some form of regularization. Here we suggest, through theoreti-cal and computational arguments, that the combination of noise with synchroniza-tion provides a plausible mechanism for regularization in the nervous system. The functional role of regularization is considered in a general context in which cou-pled computational systems receive inputs corrupted by correlated noise. Noise on the inputs is shown to impose regularization, and when synchronization upstream induces time-varying correlations across noise variables, the degree of regular-ization can be calibrated over time. The resulting qualitative behavior matches experimental data from visual cortex. 1
Authors: Jake Bouvrie, Jean-jeacques Slotine
Institutions: Duke University, Massachusetts Institute of Technology
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
Award: G7213618887
OpenAlex ID: W2149801003