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Related Concept Videos

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...
Neural Circuits01:25

Neural Circuits

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.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
The Role of Ion Channels in Neuronal Computation01:19

The Role of Ion Channels in Neuronal Computation

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.
The Synapse02:47

The Synapse

Neurons communicate with one another by passing on their electrical signals to other neurons. A synapse is the location where two neurons meet to exchange signals. At the synapse, the neuron that sends the signal is called the presynaptic cell, while the neuron that receives the message is called the postsynaptic cell. Note that most neurons can be both presynaptic and postsynaptic, as they both transmit and receive information.
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...
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.

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Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond
08:08

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Published on: June 24, 2015

Balanced synaptic input shapes the correlation between neural spike trains.

Ashok Litwin-Kumar1, Anne-Marie M Oswald, Nathaniel N Urban

  • 1Program for Neural Computation, Carnegie Mellon University and University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America. alk@cmu.edu

Plos Computational Biology
|January 5, 2012
PubMed
Summary
This summary is machine-generated.

Neural synaptic input rates significantly alter how neuron pairs coordinate their firing. High input rates increase spike synchrony, while low rates favor longer-term rate correlations, impacting neural communication.

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Biophysics

Background:

  • Neuronal correlations, influenced by stimuli and context, are crucial for brain function.
  • The underlying biophysical mechanisms modulating these correlations remain largely unknown.

Purpose of the Study:

  • To investigate how the rate of synaptic input affects pairwise spike train correlations.
  • To elucidate the biophysical mechanisms responsible for modulating neuronal correlations.

Main Methods:

  • Combined theoretical modeling and experimental approaches.
  • Analyzed the impact of balanced excitatory and inhibitory synaptic input rates on neuronal firing patterns.

Main Results:

  • The rate of synaptic input significantly modulates the magnitude and timescale of pairwise spike train correlation.
  • High input rates promote spike time synchrony, whereas low input rates favor long-timescale rate correlations.
  • This modulation is attributed to changes in high-frequency input transfer and firing rate gain.

Conclusions:

  • Synaptic input rate is a key biophysical mechanism shaping neuronal correlations.
  • Findings extend the understanding of neural modulation from single neurons to population activity.
  • This work is essential for comprehending neural dynamics across different brain states.