Graduation Year


Document Type

Campus Only Senior Thesis

Degree Name

Bachelor of Arts



Reader 1

Professor Sarah Marzen

Reader 2

Professor John Milton

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2020 Rachel Taubman


Biological neural networks encode predictive information about their environment with high energy efficiency and minimal learning supervision. In this study, a Hopfield-like recurrent neural network with two biologically-based learning rules consistently improves both prediction and energy efficiency in multiple parameter regimes with a two-state hidden Markov Model stimulus. The network also exhibits emergent synaptic normalization, which suggests that this feature observed in neurons may emerge from an interaction of other learning rules.

This thesis is restricted to the Claremont Colleges current faculty, students, and staff.