Proceedings of the Annual Meeting of the Cognitive Science Society

Computational models of cognitive development have beenfrequently used to model impairments found in developmentaldisorders but relatively rarely to simulate behaviouralinterventions to remediate these impairments. One area ofcontroversy in practices of intervention is whether it is betterto attempt to remediate an area of weakness or to build on thechild’s strengths. We present an artificial neural networkmodel of productive vocabulary development simulatingchildren with word-finding difficulties. We contrast anintervention to remediate weakness (additional practice onnaming) with interventions to improve strengths (improvingphonological and semantic knowledge). Remediatingweakness served to propel the system more quickly along thesame atypical trajectory, while improving strengths producedlong-term increases in final vocabulary size. A combinationyielded the best outcome. The model represents the firstmechanistic demonstration of how interventions targetingstrengths may serve to improve behavioural outcomes indevelopmental disorders. The observed effects in the modelare in line with those observed empirically for children withword-finding difficulties.