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Related Concept Videos

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...
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.
Excitatory and Inhibitory Effects of Neurotransmitters01:29

Excitatory and Inhibitory Effects of Neurotransmitters

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 specific...
Integration of Synaptic Events01:28

Integration of Synaptic Events

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...
Synaptic Signaling01:12

Synaptic Signaling

Neurons communicate at synapses, or junctions, to excite or inhibit the activity of other neurons or target cells, such as muscles. Synapses may be chemical or electrical.
Synaptic Signaling01:09

Synaptic Signaling

Neurons communicate at synapses, or junctions, to excite or inhibit the activity of other neurons or target cells, such as muscles. Synapses may be chemical or electrical.
Most synapses are chemical, meaning an electrical impulse or action potential spurs the release of chemical messengers called neurotransmitters. The neuron sending the signal is called the presynaptic neuron, and the neuron receiving the signal is the postsynaptic neuron.
The presynaptic neuron fires an action potential that...

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Related Experiment Video

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Evaluation of Synaptic Multiplicity Using Whole-cell Patch-clamp Electrophysiology
10:52

Evaluation of Synaptic Multiplicity Using Whole-cell Patch-clamp Electrophysiology

Published on: April 23, 2019

Network effects of synaptic modifications.

H Liljenström1

  • 1Biometry and Systems Analysis Group, Energy & Technology, SLU, Uppsala, Sweden. hans.liljenstrom@et.slu.se

Pharmacopsychiatry
|May 21, 2010
PubMed
Summary
This summary is machine-generated.

This study uses computational models to explore how synaptic modifications impact cortical network dynamics, influenced by neuromodulators and noise. Findings link microscale cellular processes to macroscale cognitive functions, relevant for neuroscience applications.

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Area of Science:

  • Computational Neuroscience
  • Systems Neuroscience
  • Network Neuroscience

Background:

  • Cortical network properties are crucial for cognitive functions.
  • Understanding synaptic modifications' role in network dynamics is essential.
  • Neuromodulators, noise, and chemical agents significantly influence neural activity.

Purpose of the Study:

  • To investigate the role of synaptic modifications in cortical network properties using computational models.
  • To explore how neuromodulators, intrinsic noise, and chemical agents regulate neural dynamics.
  • To link microscale cellular processes to mesoscale network activity and macroscale cognitive functions.

Main Methods:

  • Utilizing computational models of varying complexity.
  • Focusing on complex neurodynamics and their modulation.
  • Analyzing neural circuitry with feedforward and feedback loops between neuron types.

Main Results:

  • Synaptic modifications play a key role in regulating cortical network properties.
  • Neuromodulators, intrinsic noise, and chemical agents modulate neural dynamics.
  • Models successfully link molecular/cellular processes to network-level and cognitive functions.

Conclusions:

  • Computational models provide insights into synaptic plasticity and network function.
  • Findings have implications for understanding learning, memory, and arousal.
  • Results are relevant for clinical and experimental neuroscience, including mental disorders.