Elsevier

Neuroscience

Volume 21, Issue 1, April 1987, Pages 151-165
Neuroscience

Logic operations are properties of computer-simulated interactions between excitable dendritic spines

https://doi.org/10.1016/0306-4522(87)90329-0Get rights and content

Abstract

Neurons in the central nervous system of mammals and many other species receive most of their synaptic inputs in their dendritic branches and spines, but the precise manner in which this information is processed in the dendrites is not understood. In order to gain insight into these mechanisms, simulations of interactions between distal dendritic spines with an excitable membrane have been carried out, using an electrical circuit analysis program for the compartmental representation of a dendrite and several spines. Interactions between responses to single and paired excitatory and inhibitory synaptic inputs have been analyzed. Basic logic operations, including AND gates, OR gates and AND-NOT gates, arise from these interactions.

The results suggest the computational power and precision of excitable spines in distal branches of neuronal dendrites, especially those of pyramidal neurons in the cerebral cortex. The applicability to information processing in distal dendrites is discussed.

References (57)

  • DodgeF.A. et al.

    Action potential of the motoneuron

    IBM J. Res. Div.

    (1973)
  • EcclesJ.C.

    The Physiology of Synapses

    (1964)
  • EcclesJ.C. et al.

    The behaviour of chromatolysed motoneurones studied by intracellular recording

    J. Physiol., Lond.

    (1958)
  • FeldmanM.L.

    Morphology of the neocortical pyramidal neuron

  • FifkovaE. et al.

    Long-lasting morphological changes in dendritic spines of dentate granule cells following stimulation of the entorhinal area

    J. Neurocytol.

    (1977)
  • FinkelA.S. et al.

    The synaptic current evoked in cat spinal motoneurones by impulses in single group Ia axons

    J. Physiol., Lond.

    (1983)
  • GruolD.L.

    Intracellular and single channel analysis of voltage-sensitive ionic mechanisms in the somal and dendritic membranes of cultured cerebellar Purkinje neurons

    Soc. Neurosci. Abstr.

    (1984)
  • HaberlyL.B.

    Structure of the piriform cortex of the opossum. I. Description of neuron types with Golgi methods

    J. comp. Neurol.

    (1983)
  • HodgkinA.L. et al.

    A quantitative description of membrane current and its application to conduction and excitation in nerve

    J. Physiol., Lond.

    (1952)
  • HopfieldJ.J.

    Neurol networks and physical systems with emergent collective computational abilities

  • HopfieldJ.J.

    Neurons with graded response have collective computational properties like those of two-state neurons

  • IBM ASTAP Program Reference Manual SH20-1118-0

    (1973)
  • JackJ.J.B. et al.

    Electric Current-Flow in Excitable Cells

    (1975)
  • JahrC.E. et al.

    An intracellular analysis of dendrodendritic inhibition in the turtle in vitro olfactory bulb

    J. Physiol., Lond.

    (1982)
  • KochC. et al.

    Retinal ganglion cells: a functional interpretation of dendritic morphology

    Phil. Trans. R. Soc. Lond B

    (1982)
  • KufflerS.W. et al.

    Synaptic inhibition in an isolated nerve cell

    J. gen. Physiol.

    (1955)
  • LlinásR. et al.

    Electrophysiological properties of dendrites and somata in alligator Purkinje cells

    J. Neurophysiol.

    (1971)
  • LlinásR. et al.

    Electrophysiological properties of in vitro Purkinje cell somata in mammalian cerebellar slices

    J. Physiol., Lond.

    (1980)
  • Cited by (127)

    • A survey on dendritic neuron model: Mechanisms, algorithms and practical applications

      2022, Neurocomputing
      Citation Excerpt :

      The LCC executes the calculations entirely in binary, and it has extremely fast computation speed and significantly low computational costs compared with other machine learning algorithms requiring floating-point calculations [52–54]. It also verifies the assumption that logical operations could simulate synaptic interactions on dendrites [55–57]. In addition, the DNM was applied to solve various time series prediction problems [58–62].

    • A novel motion direction detection mechanism based on dendritic computation of direction-selective ganglion cells

      2022, Knowledge-Based Systems
      Citation Excerpt :

      Furthermore, recent advances in physiology and morphology suggest that microcircuits play a key role in the generation of direction selectivity [7,56]. These studies also provide further evidence that the interaction between the synaptic and dendritic layers can perform only simple logic operations [49,57–59]. The DNM can generate a unique dendritic structure for each specific task and the simplified structure can be hardwareized by a logic circuit.

    View all citing articles on Scopus
    View full text