Commentary
Simple codes versus efficient codes

https://doi.org/10.1016/0959-4388(95)80032-8Get rights and content

Abstract

Transmission of information is an important function of cortical neurons, so it is conceivable that they have evolved to transmit information efficiently, with low noise and high temporal precision. Such precision is consistent with the output generated by various working models that mimick neuronal activity, from simple integrate-and-fire models to elaborate numerical simulations of realistic-looking neurons. But our current inability to match this data with neurons' detailed spike-generating mechanisms in vivo allows us a wide latitude in interpreting the significance of the various components of their spike code. One extreme hypothesis, the ‘simple’ model, is that each neuron is noisy and slow, performing a simple computation and transmitting a small amount of information. A competing hypothesis, the ‘efficient’ model, postulates that a neuron transmits large amounts of information through precise, complex, single-spike computations. Both hypotheses are broadly consistent with the available data. The conflict may only be resolved with the development of new measurement techniques that will allow one to investigate directly the properties that make a neuron efficient — that is, to be able to measure highly transient, localized events inside the thinnest dendrites, which are currently experimentally inaccessible.

References (47)

  • G Stuart et al.

    Active propagation of somatic action potentials into neocortical pyramidal cell dendrites

    Nature

    (1994)
  • JJ Sloper et al.

    A study of the axon initial segment and proximal axon of neurons in the primate motor and somatic sensory cortices

    Philos Trans R Soc Lond [Biol]

    (1978)
  • A Mason et al.

    Synaptic transmission between individual pyramidal neurons of the rat visual cortex vitro

    J Neurosci

    (1991)
  • Y Komatsu et al.

    Intracortical connectivity revealed by spike-triggered averaging in slice preparations of cat visual cortex

    Brain Res

    (1988)
  • J Deuchars et al.

    Relationships between morphology and physiology of pyramid—pyramid single axon connections in rat neocortex in vitro

    J Physiol

    (1994)
  • W Softky

    Sub-millisecond coincidence detection in active dendritic trees

    Neuroscience

    (1994)
  • H Agmon-Snir et al.

    Signal delay and input synchronization in passive dendritic structures

    J Neurophysiol

    (1993)
  • I Segev et al.

    Computational study of an excitable dendritic spine

    J Neurophysiol

    (1988)
  • C Koch et al.

    Multiplying with synapses

  • B Mel

    NMDA-based pattern discrimination in a model cortical neuron

    Neural Computation

    (1992)
  • R Douglas et al.

    Control of neuronal output by inhibition at the axon initial segment

    Neural Computation

    (1990)
  • W Bialek

    Optimal signal processing in the nervous system

  • J Simmons et al.

    Discrimination of jittered sonar echos by the echolocating bat, eptesicus fuscus: the shape of target images in echolocation

    J Comp Physiol [A]

    (1990)
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