Modeling ketamine effects on synaptic plasticity during the mismatch negativity

André Schmidt1, Andreea O Diaconescu, Michael Kometer

  • 1University Hospital of Psychiatry, Neuropsychopharmacology and Brain Imaging.

Insights

Ketamine reduces mismatch negativity (MMN) by altering synaptic plasticity, not neuronal adaptation. This finding, derived from advanced modeling, links neurophysiological changes to ketamine

Area of Science:

  • Neuroscience
  • Psychopharmacology
  • Computational Psychiatry

Background:

  • Mismatch negativity (MMN) is an electrophysiological response sensitive to auditory changes.
  • Ketamine, an NMDA-receptor antagonist, is known to affect MMN amplitudes.
  • Existing MMN theories involve neuronal adaptation and predictive coding mechanisms.

Purpose of the Study:

  • To investigate the specific mechanisms by which ketamine reduces MMN amplitudes.
  • To differentiate the roles of neuronal adaptation and synaptic plasticity in ketamine's effects on MMN.
  • To link model-based estimates of ketamine's neurophysiological effects to cognitive outcomes.

Main Methods:

  • Applied dynamic causal modeling (DCM) and Bayesian model selection to EEG data.
  • Utilized data from a cross-over, double-blind, placebo-controlled ketamine study.
  • Employed a predictive coding framework to unify MMN theories.

Main Results:

  • Replicated findings that both adaptation and short-term plasticity are essential for MMN generation.
  • Identified significant ketamine effects on synaptic plasticity, but not adaptation.
  • Observed a selective ketamine effect on the forward connection from the left auditory cortex to the superior temporal gyrus.
  • Found that model-based estimates of ketamine's effects on synaptic plasticity correlated with cognitive and control impairments.

Conclusions:

  • Ketamine's reduction of MMN is primarily mediated by effects on synaptic plasticity, not adaptation.
  • The study proposes a specific neurophysiological mechanism for ketamine's impact on MMN.
  • This modeling approach demonstrates the potential for inferring synaptic function and drug modulation from EEG data.

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