A computationally rich algorithm of synaptic plasticity has been proposed based on the experimental observation that the sign and amplitude of the change in synaptic weight is dictated by the temporal order and temporal contiguity between pre- and postsynaptic activities. For more than a decade, this spike-timing-dependent plasticity (STDP) has been studied mainly in brain slices of different brain structures and cultured neurons. Although not yet compelling, evidences for the STDP rule in the intact brain, including primary sensory cortices, have been provided lastly. From insects to mammals, the presentation of precisely timed sensory inputs drives synaptic and functional plasticity in the intact central nervous system, with similar timing requirements than the in vitro defined STDP rule. The convergent evolution of this plasticity rule in species belonging to so distant phylogenic groups points to the efficiency of STDP, as a mechanism for modifying synaptic weights, as the basis of activity-dependent development, learning and memory. In spite of the ubiquity of STDP phenomena, a number of significant variations of the rule are observed in different structures, neuronal types and even synapses on the same neuron, as well as between in vitro and in vivo conditions. In addition, the state of the neuronal network, its ongoing activity and the activation of ascending neuromodulatory systems in different behavioral conditions have dramatic consequences on the expression of spike-timing-dependent synaptic plasticity, and should be further explored.
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http://dx.doi.org/10.3389/fnsyn.2010.00137 | DOI Listing |
Chaos
January 2025
School of Mathematics and Statistics, University College Dublin, Dublin 4 D04 V1W8, Ireland.
Synaptic plasticity plays a fundamental role in neuronal dynamics, governing how connections between neurons evolve in response to experience. In this study, we extend a network model of θ-neuron oscillators to include a realistic form of adaptive plasticity. In place of the less tractable spike-timing-dependent plasticity, we employ recently validated phase-difference-dependent plasticity rules, which adjust coupling strengths based on the relative phases of θ-neuron oscillators.
View Article and Find Full Text PDFJ Phys Chem Lett
January 2025
Key Laboratory of Atomic and Molecular Physics and Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China.
Research on memristive devices to seamlessly integrate and replicate the dynamic behaviors of biological synapses will illuminate the mechanisms underlying parallel processing and information storage in the human brain, thereby affording novel insights for the advancement of artificial intelligence. Here, an artificial electric synapse is demonstrated on a one-step Mo-selenized MoSe memristor, having not only long-term stable resistive switching characteristics (reset 0.51 ± 0.
View Article and Find Full Text PDFSmall
January 2025
Department of Nano-scale Semiconductor Engineering, Hanyang University, Seoul, 04763, Republic of Korea.
Spiking neurons are essential for building energy-efficient biomimetic spatiotemporal systems because they communicate with other neurons using sparse and binary signals. However, the achievable high density of artificial neurons having a capacitor for emulating the integrate function of biological neurons has a limit. Furthermore, a low-voltage operation (<1.
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.
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