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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.
Hebbian LTP
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Integration of Synaptic Events01:28

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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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Chemical Synapses01:26

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Chemical synapses are specialized sites between two neurons or between a neuron and a non-neuronal cell like a muscle, glandular or sensory cell.
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Chemical Synapses

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Chemical synapses are specialized sites between two neurons or between a neuron and a non-neuronal cell like a muscle, glandular or sensory cell.
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Excitatory and Inhibitory Effects of Neurotransmitters01:29

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When an action potential reaches the presynaptic axon terminal, it releases neurotransmitters from the neuron into the synaptic cleft at a chemical synapse. The released neurotransmitter can be excitatory or inhibitory. The critical criteria commonly used to determine whether a molecule is a neurotransmitter at a chemical synapse are the molecule's presence in the presynaptic neuron. Second, its release is in response to strong presynaptic depolarization. And lastly, the presence of...
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Precise Synaptic Efficacy Alignment Suggests Potentiation Dominated Learning.

Christoph Hartmann1, Daniel C Miner2, Jochen Triesch2

  • 1Department of Neuroscience, Frankfurt Institute for Advanced StudiesFrankfurt am Main, Germany; International Max Planck Research School for Neural Circuits, Max Planck Institute for Brain ResearchFrankfurt am Main, Germany.

Frontiers in Neural Circuits
|January 22, 2016
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Summary
This summary is machine-generated.

Synaptic normalization combined with spike-timing-dependent plasticity (STDP) can explain how parallel synapses achieve similar strength. This occurs when learning is dominated by potentiation, especially in recurrent neural networks and after sleep.

Keywords:
Kesten processSORNSTDPhomeostasisplasticityself-organizationsynaptic normalizationsynaptic scaling

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Synaptic Plasticity

Background:

  • Recent evidence indicates parallel synapses exhibit remarkably similar strengths.
  • This synaptic alignment has been hypothesized to require long-term activity integration.
  • Spike-timing-dependent plasticity (STDP), a key learning mechanism, is typically considered temporally local.

Purpose of the Study:

  • To investigate if temporally local STDP and synaptic normalization can explain parallel synapse alignment.
  • To model the interaction between STDP and normalization across different neural network complexities.

Main Methods:

  • Analytical modeling of STDP and normalization as a Kesten process in a single neuron.
  • Simulation of a single-neuron model with realistic synapses and independent spiking.
  • Analysis of recurrent neural networks incorporating STDP and correlated activity.

Main Results:

  • Analytical derivation shows alignment requires potentiation-dominated learning.
  • Synaptic efficacy alignment was observed only with long-term potentiation-biased STDP in single-neuron models.
  • In recurrent networks, alignment occurred with both potentiation- and depression-biased STDP due to correlated activity.

Conclusions:

  • Synaptic normalization and STDP-induced potentiation are sufficient for parallel synapse alignment.
  • Recurrent network dynamics amplify alignment effects, supporting potentiation dominance.
  • Sleep may enhance synaptic similarity, while sleep deprivation might reduce it.