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Related Concept Videos

Long-term Potentiation01:35

Long-term Potentiation

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Long-term potentiation, or LTP, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTP is the process of synaptic strengthening that occurs over time between pre- and postsynaptic neuronal connections. The synaptic strengthening of LTP works in opposition to the synaptic weakening of long-term depression (LTD) and together are the main mechanisms that underlie learning and memory.
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Long-term Potentiation01:25

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Long-term potentiation, or LTP, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTP is the process of synaptic strengthening that occurs over time between pre and postsynaptic neuronal connections. The synaptic strengthening of LTP works in opposition to the synaptic weakening of long-term depression (LTD) and together are the main mechanisms that underlie learning and memory.
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Neuroplasticity reflects the brain's remarkable capacity to adapt and evolve, responding dynamically to learning, experiences, or injury by reorganizing its neural circuitry. This reorganization involves creating new neural connections and refining old ones through a series of biological processes that contribute to the brain's lifelong development and adaptability.
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Long-term depression, or LTD, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTD is the process of synaptic weakening that occurs over time between pre and postsynaptic neuronal connections. The synaptic weakening of LTD works in opposition to synaptic strengthening by long-term potentiation (LTP) and together are the main mechanisms that underlie learning and memory.
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Long-term depression, or LTD, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTD is the process of synaptic weakening that occurs over time between pre and postsynaptic neuronal connections. The synaptic weakening of LTD works in opposition to synaptic strengthening by long-term potentiation (LTP) and together are the main mechanisms that underlie learning and memory.
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Plasticity is the property where an object loses its elasticity and undergoes irreversible deformation, even after the deformation forces are eliminated. If a material deforms irreversibly without increasing stress or load, then this is called ideal plasticity. For example, when a force is applied to an aluminum rod, it changes its shape, but it does not return to its original shape once the force is removed. Plastic deformation or ductility is thus a permanent deformation or change in the...
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    Network motifs guide synaptic plasticity in the hippocampus. This study reveals how these connectivity patterns reorganize during long-term potentiation, balancing network efficiency and stability for memory encoding.

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    Area of Science:

    • Neuroscience
    • Computational Neuroscience
    • Systems Neuroscience

    Background:

    • Neural circuit complexity poses challenges for understanding network-level synaptic plasticity.
    • Network motifs, recurrent functional connectivity patterns, offer a framework for analysis.

    Purpose of the Study:

    • To dissect long-term potentiation (LTP)-induced network reorganization in hippocampal CA1-CA3 circuits using network motifs.
    • To assess the role of motif evolution in network stability, synaptic strength, and criticality-redundancy trade-offs.

    Main Methods:

    • High-density microelectrode array (HD-MEA) recordings to track network LTP.
    • Systematic analysis of motif evolution before and after high-frequency stimulation.
    • Graph-theoretic analysis to characterize network reorganization trajectories.

    Main Results:

    • LTP-induced reorganization follows a structured, motif-guided trajectory.
    • Early-phase motif recruitment enhances network efficiency.
    • Later phases involve refinement, balancing efficiency with stability.

    Conclusions:

    • Structured connectivity, via network motifs, enables adaptive network-level plasticity.
    • This plasticity balances network efficiency and stability, crucial for memory encoding.
    • Findings offer a framework for understanding memory disorders.