Computational modeling of interventions for developmental disorders

Psychol Rev. 2019 Oct;126(5):693-726. doi: 10.1037/rev0000151. Epub 2019 Jun 6.

Abstract

We evaluate the potential of connectionist models of developmental disorders to offer insights into the efficacy of interventions. Based on a range of computational simulation results, we assess factors that influence the effectiveness of interventions for reading, language, and other cognitive developmental disorders. The analysis provides a level of mechanistic detail that is generally lacking in behavioral approaches to intervention. We review an extended program of modeling work in four sections. In the first, we consider long-term outcomes and the possibility of compensated outcomes and resolution of early delays. In the second section, we address methods to remediate atypical development in a single network. In the third section, we address interventions to encourage compensation via alternative pathways. In the final section, we consider the key issue of individual differences in response to intervention. Together with advances in understanding the neural basis of developmental disorders and neural responses to training, formal computational approaches can spur theoretical progress to narrow the gap between the theory and practice of intervention. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Developmental Disabilities / therapy*
  • Humans
  • Individuality
  • Models, Psychological*
  • Neural Networks, Computer*
  • Outcome Assessment, Health Care*