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Related Concept Videos

Frequency-dependent Selection01:21

Frequency-dependent Selection

When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
Long-term Potentiation01:35

Long-term Potentiation

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.
Long-term Potentiation01:25

Long-term Potentiation

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
LTP can occur when presynaptic neurons...
Neuroplasticity01:01

Neuroplasticity

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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Related Experiment Video

Updated: May 21, 2026

Ex Vivo Optogenetic Interrogation of Long-Range Synaptic Transmission and Plasticity from Medial Prefrontal Cortex to Lateral Entorhinal Cortex
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Frequency selectivity emerging from spike-timing-dependent plasticity.

Matthieu Gilson1, Moritz Bürck, Anthony N Burkitt

  • 1NeuroEngineering Laboratory, Department of Electrical and Electronic Engineering, University of Melbourne, VIC 3010, Australia. gilson@brain.riken.jp

Neural Computation
|June 28, 2012
PubMed
Summary
This summary is machine-generated.

Spike-timing-dependent plasticity enables neurons to learn and identify specific frequencies. Synaptic delays and location determine a neuron's best modulation frequency (BMF) after unsupervised training.

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Systems Neuroscience

Background:

  • Periodic neuronal activity is fundamental across brain regions.
  • Neuronal circuits act as bandpass filters, identifying preferred frequencies (best modulation frequency, BMF).
  • The emergence of neuronal circuitry for BMF identification remains unclear.

Purpose of the Study:

  • To demonstrate how spike-timing-dependent plasticity (STDP) can induce frequency-dependent learning.
  • To explain the development of input selectivity for frequency identification.
  • To investigate the role of synaptic delays and neuronal architecture in BMF tuning.

Main Methods:

  • Mathematical analysis of learning dynamics in plastic inhibitory connections.
  • Modeling inhomogeneous postsynaptic responses based on dendritic location.
  • Investigating the influence of synaptic delays and postsynaptic potentials (PSPs) on STDP.

Main Results:

  • STDP leads to frequency-dependent learning and input selectivity.
  • Synaptic delays are critical for organizing weight specialization.
  • Neuron's BMF after learning can match the training frequency.
  • Proximal (distal) synapses with shorter (longer) delays preferentially respond to higher (lower) frequencies.

Conclusions:

  • Unsupervised training enables neurons to respond maximally to specific frequencies.
  • Synaptic delays and dendritic location dictate frequency tuning.
  • The model predicts clustered synapse formation on dendritic branches for specific BMFs.