Is autism due to brain desynchronization?

Int J Dev Neurosci. 2005 Apr-May;23(2-3):253-63. doi: 10.1016/j.ijdevneu.2004.09.002.

Abstract

The hypothesis is presented that a disruption in brain synchronization contributes to autism by destroying the coherence of brain rhythms and slowing overall cognitive processing speed. Particular focus is on the inferior olive, a precerebellar structure that is reliably disrupted in autism and which normally generates a coherent 5-13 Hz rhythmic output. New electrophysiological data reveal that the continuity of the rhythmical oscillation in membrane potential generated by inferior olive neurons requires the formation of neuronal assemblies by the connexin36 protein that mediates electrical synapses and promotes neuronal synchrony. An experiment with classical eyeblink conditioning is presented to demonstrate that the inferior olive is necessary to learn about sequences of stimuli presented at intervals in the range of 250-500 ms, but not at 700 ms, revealing that a disruption of the inferior olive slows stimulus processing speed on the time scale that is lost in autistic children. A model is presented in which the voltage oscillation generated by populations of electrically synchronized inferior olivary neurons permits the utilization of sequences of stimuli given at, or faster than, 2 per second. It is expected that the disturbance in inferior olive structure in autism disrupts the ability of inferior olive neurons to become electrically synchronized and to generate coherent rhythmic output, thereby impairing the ability to use rapid sequences of cues for the development of normal language skill. Future directions to test the hypothesis are presented.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.
  • Review

MeSH terms

  • Animals
  • Autistic Disorder / etiology*
  • Brain / physiopathology*
  • Conditioning, Classical / physiology
  • Cortical Synchronization / adverse effects*
  • Dyslexia / physiopathology
  • Humans
  • Infant
  • Neural Networks, Computer
  • Neurophysiology / methods
  • Sudden Infant Death