arrow
返回

Decomposing Simon task BOLD activation using a drift-diffusion model framework

delete2020-03-03
delete3
delete
OA
AI
J
James R. McIntosh *
P
Paul Sajda
DOI:10.1038/s41598-020-60943-1delete
delete原文链接
delete分享
delete收藏
查看原文
摘要

摘要

En 中文
The Simon effect is observed in spatial conflict tasks where the response time of subjects is increased if stimuli are presented in a lateralized manner so that they are incongruous with the response information that they represent symbolically. Previous studies have used fMRI to investigate this phenomenon, and while some have been driven by considerations of an underlying model, none have attempted to directly tie model and BOLD response together. It is likely that this is due to Simon models having been predominantly descriptive of the phenomenon rather than capturing the full spectrum of behavior at the level of individual subjects. Sequential sampling models (SSM) which capture full response distributions for correct and incorrect responses have recently been extended to capture conflict tasks. In this study we use our freely available framework for fitting and comparing non-standard SSMs to fit the Simon effect SSM (SE-SSM) to behavioral data. This model extension includes specific estimates of automatic response bias and a conflict counteraction parameter to individual subject behavioral data. We apply this approach in order to investigate whether our task specific model parameters have a correlate in BOLD response. Under the assumption that the SE-SSM reflects aspects of neural processing in this task, we go on to examine the BOLD correlates with the within trial expected decision-variable. We find that the SE-SSM captures the behavioral data and that our two conflict specific model parameters have clear across subject BOLD correlates, while other model parameters, as well as more standard behavioral measures do not. We also find that examining BOLD in terms of the expected decision-variable leads to a specific pattern of activation that would not be otherwise possible to extract.
Keyword:
ANTERIOR CINGULATE CORTEX
MEDIAL FRONTAL-CORTEX
INDIVIDUAL-DIFFERENCES
TEMPORAL DYNAMICS
DECISION-MODEL
CONFLICT TASKS
STROOP
OPTIMIZATION
MECHANISMS
STIMULUS
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Scientific Reports 封面图
Scientific Reports
IF:
3.9
论文数:
28.2W
被引数:
83.5W

机构

C
Columbia University
学者数:
7.1W
论文数: 6.4W
被引数: 263
引用论文

引用论文

err分享
err收藏
err分享
err收藏
学者 查看更多内容