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Related Concept Videos

Integration of Synaptic Events01:28

Integration of Synaptic Events

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Synaptic integration mainly includes the summation of graded potentials. Graded potentials, regardless of their type, cause subtle alterations in membrane voltage, resulting in either depolarization or hyperpolarization. These incremental changes, when combined or summed, can propel the neuron toward its threshold. Consider, for example, a membrane experiencing a +15 mV shift, causing it to depolarize from -70 mV to -55 mV. In this scenario, graded potentials govern the membrane's ability to...
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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 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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Plasticity00:58

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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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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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Adaptive control of synaptic plasticity integrates micro- and macroscopic network function.

Daniel N Scott1,2, Michael J Frank3,4

  • 1Cognitive Linguistic, and Psychological Sciences, Brown University, Providence, RI, USA. daniel_scott@brown.edu.

Neuropsychopharmacology : Official Publication of the American College of Neuropsychopharmacology
|August 29, 2022
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Summary
This summary is machine-generated.

Metaplasticity, the adaptive control of neural plasticity, bridges microscopic synaptic changes to macroscopic brain functions, impacting learning and behavior. Understanding this process is key to deciphering brain disorders.

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Area of Science:

  • Computational Neuroscience
  • Neurobiology
  • Machine Learning

Background:

  • Synaptic plasticity is crucial for learning and development.
  • The link between microscopic neural interactions and macroscopic behavior is not well understood.
  • Computational models offer insights but are often disconnected from biological data.

Purpose of the Study:

  • To explore the relationship between neural plasticity and network computations.
  • To bridge computational neuroscience, machine learning, and biological data.
  • To understand how metaplasticity influences learning and brain function across scales.

Main Methods:

  • Review of computational neuroscience and machine learning models of neural plasticity.
  • Analysis of how synaptic plasticity features affect network computations and vice versa.
  • Examination of biological mechanisms controlling plasticity, including calcium dynamics and neuromodulation.

Main Results:

  • Metaplasticity acts as a crucial link across different scales of neural organization.
  • Metaplasticity governs synaptic learning rules, network properties, and activity routing.
  • Dysregulation of metaplasticity may underlie neurological and psychiatric disorders.

Conclusions:

  • Metaplasticity provides a framework for understanding how synaptic changes drive network-level functions.
  • The study of metaplasticity is essential for linking computational models to biological reality.
  • Investigating metaplasticity offers insights into the pathophysiology of conditions like autism, schizophrenia, and Parkinson's disease.