Episodic memory organizes experience in time, so that we can review past events and anticipate the future. In a hippocampus-dependent memory task, spike timing in pairs of simultaneously active CA1 neurons with overlapping place fields distinguished the start and end of trials. At the common starting point of different journeys, the relative spike timing of the neurons was highly correlated. As the rat approached a common goal from different starting points, however, temporal firing patterns were strongly modulated across journeys even if the cells fired in the same spatial locations within fields, implying that different processes influenced when and where cells fire. Spike timing within hippocampal ensembles may thereby help parse the beginning from the end of episodes in memory.
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http://dx.doi.org/10.1073/pnas.0508688103 | DOI Listing |
ACS Appl Mater Interfaces
January 2025
School of Materials Science and Engineering, Gyeongsang National University, Jinju, Gyeongsangnam-do 52828, Republic of Korea.
Advances in the semiconductor industry have been limited owing to the constraints imposed by silicon-based CMOS technology; hence, innovative device design approaches are necessary. This study focuses on "more than Moore" approaches, specifically in neuromorphic computing. Although MoS devices have attracted attention as neuromorphic computing candidates, their performances have been limited due to environment-induced perturbations to carrier dynamics and the formation of defect states.
View Article and Find Full Text PDFbioRxiv
December 2024
Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
Song acquisition behavior observed in the songbird system provides a notable example of learning through trial- and-error which parallels human speech acquisition. Studying songbird vocal learning can offer insights into mechanisms underlying human language. We present a computational model of song learning that integrates reinforcement learning (RL) and Hebbian learning and agrees with known songbird circuitry.
View Article and Find Full Text PDFAt cellular and circuit levels, drug addiction is considered a dysregulation of synaptic plasticity. In addition, dysfunction of the glutamate transporter 1 (GLT-1) in the nucleus accumbens (NAc) has also been proposed as a mechanism underlying drug addiction. However, the cellular and synaptic impact of GLT-1 alterations in the NAc remain unclear.
View Article and Find Full Text PDFBiomed Eng Lett
January 2025
Department of Computer Engineering, Kwangwoon University, Seoul, 01897 Republic of Korea.
Robotic systems rely on spatio-temporal information to solve control tasks. With advancements in deep neural networks, reinforcement learning has significantly enhanced the performance of control tasks by leveraging deep learning techniques. However, as deep neural networks grow in complexity, they consume more energy and introduce greater latency.
View Article and Find Full Text PDFACS Appl Bio Mater
January 2025
Unconventional Computing Laboratory, University of the West of England, Bristol BS16 1QY, U.K.
This study examines the relationship between chondroitin sulfate, proteinoids, and computational neuron models, with a specific emphasis on the Izhikevich neuron model. We investigate the effect of chondroitin sulfate-proteinoid complexes on the behavior and dynamics of simulated neurons. Through the use of computational simulations, we provide evidence that these biomolecular components have the power to regulate the responsiveness of neurons, the patterns of their firing, and the ability of their synapses to change within the Izhikevich architecture.
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