» Articles » PMID: 37600217

Mechanisms of Training-Related Change in Processing Speed: A Drift-Diffusion Model Approach

Overview
Journal J Cogn
Publisher Ubiquity Press
Specialty Psychology
Date 2023 Aug 21
PMID 37600217
Authors
Affiliations
Soon will be listed here.
Abstract

Processing speed is a crucial ability that changes over the course of the lifespan. Training interventions on processing speed have shown promising effects and have been associated with improved cognitive functioning. While training-related changes in processing speed are often studied using reaction times (RTs) and error rates, these measures provide limited insight into the mechanisms underlying changes during training. The drift-diffusion model provides estimates of the cognitive processes underlying speeded decision tasks, such as the rate of evidence accumulation (drift rate), response strategies (boundary separation), as well as time for other processes such as stimulus encoding and motor response (non-decision time). In the current study, we analyzed existing data of an extensive multi-session training intervention (von Bastian & Oberauer, 2013) to disentangle changes in drift rate, boundary separation, and non-decision time during training of different speeded choice-RT tasks. During this training intervention, 30 participants performed 20 training sessions over the course of four weeks, completing three tasks each session: a face-matching, a pattern-matching, and a digit-matching task. Our results show that processing speed training increased drift rates throughout training. Boundary separation and non-decision time decreased mostly during the initial parts of training. This pattern of prolonged training-related changes in rate of evidence accumulation as well as early changes in response strategy and non-decision processes was observed across all three tasks. Future research should investigate how these training-related changes relate to improvements in cognitive functioning more broadly.

References
1.
von Bastian C, Reinhartz A, Udale R, Gregoire S, Essounni M, Belleville S . Mechanisms of processing speed training and transfer effects across the adult lifespan: protocol of a multi-site cognitive training study. BMC Psychol. 2022; 10(1):168. PMC: 9270821. DOI: 10.1186/s40359-022-00877-7. View

2.
Lerche V, von Krause M, Voss A, Frischkorn G, Schubert A, Hagemann D . Diffusion modeling and intelligence: Drift rates show both domain-general and domain-specific relations with intelligence. J Exp Psychol Gen. 2020; 149(12):2207-2249. DOI: 10.1037/xge0000774. View

3.
Edwards J, Xu H, Clark D, Guey L, Ross L, Unverzagt F . Speed of processing training results in lower risk of dementia. Alzheimers Dement (N Y). 2017; 3(4):603-611. PMC: 5700828. DOI: 10.1016/j.trci.2017.09.002. View

4.
Lerche V, Voss A, Nagler M . How many trials are required for parameter estimation in diffusion modeling? A comparison of different optimization criteria. Behav Res Methods. 2016; 49(2):513-537. DOI: 10.3758/s13428-016-0740-2. View

5.
van Ravenzwaaij D, Boekel W, Forstmann B, Ratcliff R, Wagenmakers E . Action video games do not improve the speed of information processing in simple perceptual tasks. J Exp Psychol Gen. 2014; 143(5):1794-805. PMC: 4447196. DOI: 10.1037/a0036923. View