Computational model of antidepressant response heterogeneity as multi-pathway neuroadaptation

Mariam B. Camacho, Thomas J. Anastasio

Research output: Contribution to journalArticlepeer-review


Current hypotheses cannot fully explain the clinically observed heterogeneity in antidepressant response. The therapeutic latency of antidepressants suggests that therapeutic outcomes are achieved not by the acute effects of the drugs, but rather by the homeostatic changes that occur as the brain adapts to their chronic administration. We present a computational model that represents the known interactions between the monoaminergic neurotransmitter-producing brain regions and associated non-monoaminergic neurotransmitter systems, and use the model to explore the possible ways in which the brain can homeostatically adjust to chronic antidepressant administration. The model also represents the neuron-specific neurotransmitter receptors that are known to adjust their strengths (expressions or sensitivities) in response to chronic antidepressant administration, and neuroadaptation in the model occurs through sequential adjustments in these receptor strengths. The main result is that the model can reach similar levels of adaptation to chronic administration of the same antidepressant drug or combination along many different pathways, arriving correspondingly at many different receptor strength configurations, but not all of those adapted configurations are also associated with therapeutic elevations in monoamine levels. When expressed as the percentage of adapted configurations that are also associated with elevations in one or more of the monoamines, our modeling results largely agree with the percentage efficacy rates of antidepressants and antidepressant combinations observed in clinical trials. Our neuroadaptation model provides an explanation for the clinical reports of heterogeneous outcomes among patients chronically administered the same antidepressant drug regimen.

Original languageEnglish (US)
Article number925
JournalFrontiers in Pharmacology
Issue numberDEC
StatePublished - Dec 20 2017


  • Depression
  • Dopamine
  • Monoamine
  • Neural network
  • Norepinephrine
  • SSRI
  • Serotonin
  • Systems biology

ASJC Scopus subject areas

  • Pharmacology
  • Pharmacology (medical)


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