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Session: Poster Session 1 (Even numbers)
Session starts: Thursday 26 January, 16:00
Presentation starts: 16:00

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Martina Lamberti (University of Twente)
Shiven Tripathi (Indian Institute of Technology Kanpur)
Sarah Marzen (Claremont McKenna College)
Joost le Feber (University of Twente)

Abstract:
Several studies have suggested that memory and prediction are crucial neuronal functions directing our actions. When an external input is perceived, its immediate registration is observed as short (seconds) lasting activity changes, which can be seen as short-term memory, whereas long-term memory refers to connectivity changes on time scales of minutes to hours. Prediction can be defined as the ability to reduce uncertainty on future sensory input, and has been hypothesized to depend on memory, particularly on short-term memory. Recent work showed that retinal cells predict visual stimuli, but it is yet unknown whether prediction is a general capability of neuronal networks. Here, we determined whether in vitro neural networks predict external stimuli, and if prediction depends on (short-term and long-term) memory. We used multi electrodes arrays (MEAs) with 59 recording electrodes on which rat primary cortical neurons were plated. We electrically or optogenetically stimulated for 20 hours with interstimulus intervals (ISIs) taken from a known distribution. Repeated electrical stimulation at one electrode has been shown to induce significant long-term connectivity changes, interpreted as long-term memory traces. In contrast, optogenetic stimulation did not. We used mutual information to quantify to what extent recorded activity reduced the uncertainty on future stimuli (MIfuture; prediction), or recent past stimuli (MIpast; short-term memory). Activity provided significant information on past stimulation, indicating that stimulus responses clearly deviated from spontaneous activity. MIfuture reflected the distribution of ISIs, suggesting that it largely depended on stimulus responses. This was confirmed by masking stimulus responses which largely reduced MIfuture. Throughout 20h of stimulation, MIfuture linearly depended on MIpast. However, during electrical stimulation this dependency on short-term memory significantly decreased with time, suggesting that other features gradually took over. Optogenetic stimulation, in contrast to electrical stimulation, did not induce long-term memory traces and showed unchanged dependency of MIfuture on MIpast. We conclude that random neuronal networks predict future stimuli, predominantly based on short-term memory of past stimuli. With the induction of long term memory traces, the dependency on short-term memory becomes less dominant.