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Computational models of neuromodulation

J M Fellous1, C Linster

  • 1Brandeis University, Volen Center for Complex Systems, Waltham, MA 02254-9110, USA.

Neural Computation
|June 6, 1998
PubMed
Summary
This summary is machine-generated.

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Computational modeling reveals how neuromodulation enhances neural computation. This review details neuromodulation

Area of Science:

  • Computational neuroscience
  • Theoretical neuroscience
  • Systems neuroscience

Background:

  • Neuromodulation plays a critical role in brain function.
  • Understanding the computational roles of neuromodulation is essential.
  • Existing studies often focus on anatomical or chemical aspects.

Purpose of the Study:

  • To review computational modeling studies of neuromodulation.
  • To characterize neuromodulation based on computational and functional roles.
  • To provide a mathematical overview of neuromodulation implementation in models.

Main Methods:

  • Literature review of computational modeling studies.
  • Analysis of neuromodulation's role in central pattern generation, oscillations, sensory processing, and memory.

Related Experiment Videos

  • Mathematical exposition of single-cell and network-level implementations.

    • Main Results:

    • Neuromodulation significantly influences specific computations in diverse neural models.
    • Characterization based on function reveals key computational roles.
    • Mathematical frameworks detail implementation across different scales.

    Conclusions:

    • Neuromodulation increases and controls computational complexity in neural systems.
    • Computational modeling offers a robust framework for understanding neuromodulation's impact.
    • A functional perspective is crucial for characterizing neuromodulatory computations.