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Poster Session A: Tuesday, August 12, 1:30 – 4:30 pm, de Brug & E‑Hall

Sequential Memory Generation in the Neuroidal Model

Eben Miles Sherwood¹, Patrick Riley Perrine¹, Mugizi Robert Rwebangira¹; ¹California Polytechnic State University, San Luis Obispo

Presenter: Patrick Riley Perrine

Understanding the process of memory formation in neural systems is of great interest in the field of neuroscience. The Neuroidal Model poses a plausible theory for how memories are created within a computational context. Previously, the algorithm JOIN has been used to show how the brain could perform conjunctive and disjunctive coding to store memories. A limitation of JOIN is that it does not consider the coding of temporal information in a meaningful manner. We propose $\texttt{SeqMem}$, a similar algorithmic primitive that is designed to encode a series of items within a random graph model. We investigate the feasibility of this procedure empirically by observing its stability in our model. Our goal here is to inspire further work in scaling our methods to function at a human-level magnitude of computation.

Topic Area: Methods & Computational Tools

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