首页|New Neural Computation Data Has Been Reported by a Researcher at Graduate School of Medicine (CA3 Circuit Model Compressing Sequential Information in Theta Osci llation and Replay)
New Neural Computation Data Has Been Reported by a Researcher at Graduate School of Medicine (CA3 Circuit Model Compressing Sequential Information in Theta Osci llation and Replay)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on neural computation is the subject of a new report. According to news reporting originating from the Gr aduate School of Medicine by NewsRx correspondents, research stated, “The hippoc ampus plays a critical role in the compression and retrieval of sequential infor mation.” Our news correspondents obtained a quote from the research from Graduate School of Medicine: “During wakefulness, it achieves this through theta phase precessio n and theta sequences. Subsequently, during periods of sleep or rest, the compre ssed information reactivates through sharp-wave ripple events, manifesting as me mory replay. However, how these sequential neuronal activities are generated and how they store information about the external environment remain unknown. We de veloped a hippocampal cornu ammonis 3 (CA3) computational model based on anatomi cal and electrophysiological evidence from the biological CA3 circuit to address these questions. The model comprises theta rhythm inhibition, place input, and CA3-CA3 plastic recurrent connection. The model can compress the sequence of the external inputs, reproduce theta phase precession and replay, learn additional sequences, and reorganize previously learned sequences.”
Graduate School of MedicineComputationNeural Computation
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