1994 Special Issue
Dynamics of compartmental model neurons

https://doi.org/10.1016/S0893-6080(05)80164-9Get rights and content

Abstract

Recent developments in the dynamics of compartmental model neurons are described. In particular, an explicit analytical expression for the response function of a neuron with arbitrary dendritic tree structure is presented, which provides a general framework for exploring the effects of complex geometries on spatiotemporal pattern processing in neurons. Some examples of how compartmental structure can enhance a neuron's sensitivity to temporal features of an input are given. Shunting contributions are included at a perturbative level, and are shown to have an important influence on the time constants of a neuron's response. The effects of synaptic background activity are also discussed. A solution to the dynamical equations for a compartmental model with somatic potential reset is presented that takes proper account of the electrical coupling between soma and dendrites. Finally, some applications of this work to artificial neural networks are indicated, including an extension of the standard error back propagation algorithm to the case of compartmental neurons with known response function.

References (36)

  • BressloffP.C.

    Integral equations in compartmental model neurodynamics

  • BressloffP.C.

    Green's function approach to analysing the effects of random synaptic background activity

    Journal of Physics A

    (1994)
  • BressloffP.C.

    Dynamics of a compartmental model integrate-and-fire neuron with somatic potential reset

    Physica D

    (1994)
  • BressloffP.C.

    Dynamics of an integrate-and-fire neuron without dendritic potential reset

  • BressloffP.C. et al.

    Compartmental response function for dendritic trees

    Biological Cybernetics

    (1993)
  • BressloffP.C. et al.

    Spatio-temporal pattern processing in a compartmental model neuron

    Physical Review E

    (1993)
  • BressloffP.C. et al.

    Low firing-rates in a compartmental model neuron

    Journal of Physics A

    (1993)
  • ChristodoulouC. et al.

    Modelling of the high firing variability of real cortical neurons with the temporal noisy leaky integrator neuron model

  • Cited by (13)

    • Effects of passive dendritic tree properties on the firing dynamics of a leaky-integrate-and-fire neuron

      2015, Mathematical Biosciences
      Citation Excerpt :

      However, this would again rely primarily on the use numerical simulations. Previous analytical approaches to exploring how dendritic topology affects the function of passive dendrites have relied on a Green’s (or linear response) function approach [11–13,16,27]. These approaches provide a computationally efficient way to determine how the membrane potential of dendritic trees responds to time-varying inputs.

    • Intelligent detectors modelled from the cat's eye

      1997, Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
    • Capacity of the hierarchical multi-layered cortical microcircuit communication channel

      2018, Proceedings of the 5th ACM International Conference on Nanoscale Computing and Communication, NANOCOM 2018
    • Neuronal dynamics: From single neurons to networks and models of cognition

      2014, Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition
    View all citing articles on Scopus
    View full text