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Related Concept Videos

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...
Propagation of Action Potentials01:23

Propagation of Action Potentials

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...
Action Potential: Phases of Stimulation01:28

Action Potential: Phases of Stimulation

The action potential is a complex electrical event that occurs in excitable cells, such as neurons and muscle cells. It consists of several distinct phases, each with specific characteristics.
Resting Phase:
In this phase, the cell's membrane is at its resting potential, typically around -70 millivolts (mV) for neurons. Inside the cell, there is a higher concentration of potassium ions (K+) and a lower concentration of sodium ions (Na+). Voltage-gated sodium channels are closed, and...
Transient and Steady-state Response01:24

Transient and Steady-state Response

In control systems, test signals are essential for evaluating performance under various conditions. The ramp function is effective for systems undergoing gradual changes, while the step function is suitable for assessing systems facing sudden disturbances. For systems subjected to shock inputs, the impulse function is the most appropriate test signal.
These test signals are integral in designing control systems to exhibit two key performance aspects: transient response and steady-state response.

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Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays
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Phase-response curves and synchronized neural networks.

Roy M Smeal1, G Bard Ermentrout, John A White

  • 1Department of Bioengineering, Brain Institute, University of Utah, Salt Lake City, 20 South 2030 East, UT 84112, USA. roy.smeal@m.cc.utah.edu

Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
|July 7, 2010
PubMed
Summary

Phase-response curves (PRCs) predict neuronal synchronization but rely on assumptions that need careful consideration. This review examines PRC theory

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Area of Science:

  • Computational Neuroscience
  • Systems Neuroscience
  • Neural Oscillations

Background:

  • Phase-response curves (PRCs) are crucial for understanding synchronization in neuronal networks.
  • PRCs quantify how synaptic inputs alter the timing of neural oscillations.
  • Synchronization of neuronal activity is a common phenomenon in brain structures like the cortex.

Purpose of the Study:

  • To critically evaluate the core assumptions underpinning the application of PRCs in neuronal network analysis.
  • To determine the validity and limitations of PRC-based predictions for neural synchronization.

Main Methods:

  • Review and analysis of the principal assumptions of phase-response curve theory.
  • Examination of existing experimental and theoretical findings related to PRC validity.
  • Comparison of reduced models with more realistic neural models for PRC analysis.

Main Results:

  • The assumption of noise-tolerant oscillations is not universally applicable.
  • Spike-rate adaptation partially limits, but does not invalidate, PRC analysis.
  • Synaptic location, input summation linearity, network structure, and neuronal heterogeneity significantly impact PRC predictions.

Conclusions:

  • While powerful, PRC theory requires careful consideration of its underlying assumptions for accurate synchronization predictions.
  • Further refinement of methods for synaptic stimulation and distinguishing oscillation origins is needed.
  • Heterogeneity in neuronal frequencies can abolish synchrony even when PRC analysis is otherwise valid.