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Related Concept Videos

Propagation of Action Potentials01:23

Propagation of Action Potentials

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The propagation of an action potential refers to the process by which a nerve impulse, or "action potential," travels along a neuron.
Neurons (nerve cells) have a resting membrane potential, with a slightly negative charge inside compared to outside. This is maintained by ion channels, such as sodium (Na+) and potassium (K+) channels, which control the flow of ions. When a stimulus, like a touch or a signal from another neuron, triggers the neuron, sodium channels open, allowing sodium ions to...
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Neural Circuits01:25

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Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
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The Role of Ion Channels in Neuronal Computation01:19

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A postsynaptic neuron usually receives numerous impulses from several other presynaptic neurons. The axon hillock of the postsynaptic neuron integrates all these signals and determines the likelihood of firing an action potential.
Sometimes a single EPSP is strong enough to induce an action potential in the postsynaptic neuron. However, multiple presynaptic inputs must often create EPSPs around the same time for the postsynaptic neuron to be sufficiently depolarized to fire an action potential....
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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...
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Neuroplasticity01:01

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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 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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Related Experiment Video

Updated: May 17, 2025

Inducing Long-Term Plasticity of Intrinsic Neuronal Excitability in Neurons of the Dorsal Lateral Geniculate Nucleus
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Synaptic plasticity facilitates oscillations in a V1 cortical column model with multiple interneuron types.

Giulia Moreni1, Licheng Zou1, Cyriel M A Pennartz1,2

  • 1Cognitive and Systems Neuroscience Group, Faculty of Science, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands.

Frontiers in Computational Neuroscience
|May 15, 2025
PubMed
Summary

Neural rhythms in the brain may not be inherent but emerge from learning. Introducing synaptic plasticity to a cortical model induced oscillations, suggesting a link between experience and brain rhythms.

Keywords:
cortical columninterneuronsoscillationssynaptic plasticityvisual cortex

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Systems Neuroscience

Background:

  • Neural rhythms are common in brain recordings but their origin (circuit structure vs. function) remains debated.
  • Understanding the emergence of neural oscillations is crucial for deciphering brain function.

Purpose of the Study:

  • To investigate whether neural rhythms are intrinsic to cortical microcircuits or arise from functional processes.
  • To explore the role of synaptic plasticity in generating neural oscillations within a computational model.

Main Methods:

  • Developed a spiking network model of a mouse V1 cortical column with detailed cell types (pyramidal, PV, SST, VIP interneurons) and receptor dynamics.
  • Incorporated long-term synaptic plasticity via a spike-timing-dependent plasticity (STDP) rule into the model.
  • Analyzed the emergence of rhythmic activity and its dependence on cell types and connectivity patterns.

Main Results:

  • The model accurately reproduced in vivo cell-type-specific firing rates but lacked rhythmic activity initially.
  • Introduction of STDP-based synaptic plasticity induced broad-band (15-60 Hz) oscillations.
  • Oscillations depended on all modeled interneuron types and specific experience-dependent connectivity.

Conclusions:

  • Neural rhythms may not be fundamental properties of cortical circuits but can emerge through learning-induced structural changes.
  • Synaptic plasticity plays a critical role in the generation of neural oscillations.
  • Experience-dependent modifications of neural circuits are essential for generating functional rhythmic activity.