Individual differences in rate of acquiring stable neural representations of tasks in fMRI.

Task-related functional magnetic resonance imaging (fMRI) is a widely-used tool for studying the neural processing correlates of human behavior in both healthy and clinical populations. There is growing interest in mapping individual differences in fMRI task behavior and neural responses. By utilizi...

Full description

Bibliographic Details
Main Authors: Ming-Hua Chung, Bradford Martins, Anthony Privratsky, G Andrew James, Clint D Kilts, Keith A Bush
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2018-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC6261022?pdf=render
_version_ 1818314315866832896
author Ming-Hua Chung
Bradford Martins
Anthony Privratsky
G Andrew James
Clint D Kilts
Keith A Bush
author_facet Ming-Hua Chung
Bradford Martins
Anthony Privratsky
G Andrew James
Clint D Kilts
Keith A Bush
author_sort Ming-Hua Chung
collection DOAJ
description Task-related functional magnetic resonance imaging (fMRI) is a widely-used tool for studying the neural processing correlates of human behavior in both healthy and clinical populations. There is growing interest in mapping individual differences in fMRI task behavior and neural responses. By utilizing neuroadaptive task designs accounting for such individual differences, task durations can be personalized to potentially optimize neuroimaging study outcomes (e.g., classification of task-related brain states). To test this hypothesis, we first retrospectively tracked the volume-by-volume changes of beta weights generated from general linear models (GLM) for 67 adult subjects performing a stop-signal task (SST). We then modeled the convergence of the volume-by-volume changes of beta weights according to their exponential decay (ED) in units of half-life. Our results showed significant differences in beta weight convergence estimates of optimal stopping times (OSTs) between go following successful stop trials and failed stop trials for both cocaine dependent (CD) and control group (Con), and between go following successful stop trials and go following failed stop trials for Con group. Further, we implemented support vector machine (SVM) classification for 67 CD/Con labeled subjects and compared the classification accuracies of fMRI-based features derived from (1) the full fMRI task versus (2) the fMRI task truncated to multiples of the unit of half-life. Among the computed binary classification accuracies, two types of task durations based on 2 half-lives significantly outperformed the accuracies using fully acquired trials, supporting this length as the OST for the SST. In conclusion, we demonstrate the potential of a neuroadaptive task design that can be widely applied to personalizing other task-based fMRI experiments in either dynamic real-time fMRI applications or within fMRI preprocessing pipelines.
first_indexed 2024-12-13T08:47:42Z
format Article
id doaj.art-baf81dc948c64adeabb8d4c1a200a50b
institution Directory Open Access Journal
issn 1932-6203
language English
last_indexed 2024-12-13T08:47:42Z
publishDate 2018-01-01
publisher Public Library of Science (PLoS)
record_format Article
series PLoS ONE
spelling doaj.art-baf81dc948c64adeabb8d4c1a200a50b2022-12-21T23:53:26ZengPublic Library of Science (PLoS)PLoS ONE1932-62032018-01-011311e020735210.1371/journal.pone.0207352Individual differences in rate of acquiring stable neural representations of tasks in fMRI.Ming-Hua ChungBradford MartinsAnthony PrivratskyG Andrew JamesClint D KiltsKeith A BushTask-related functional magnetic resonance imaging (fMRI) is a widely-used tool for studying the neural processing correlates of human behavior in both healthy and clinical populations. There is growing interest in mapping individual differences in fMRI task behavior and neural responses. By utilizing neuroadaptive task designs accounting for such individual differences, task durations can be personalized to potentially optimize neuroimaging study outcomes (e.g., classification of task-related brain states). To test this hypothesis, we first retrospectively tracked the volume-by-volume changes of beta weights generated from general linear models (GLM) for 67 adult subjects performing a stop-signal task (SST). We then modeled the convergence of the volume-by-volume changes of beta weights according to their exponential decay (ED) in units of half-life. Our results showed significant differences in beta weight convergence estimates of optimal stopping times (OSTs) between go following successful stop trials and failed stop trials for both cocaine dependent (CD) and control group (Con), and between go following successful stop trials and go following failed stop trials for Con group. Further, we implemented support vector machine (SVM) classification for 67 CD/Con labeled subjects and compared the classification accuracies of fMRI-based features derived from (1) the full fMRI task versus (2) the fMRI task truncated to multiples of the unit of half-life. Among the computed binary classification accuracies, two types of task durations based on 2 half-lives significantly outperformed the accuracies using fully acquired trials, supporting this length as the OST for the SST. In conclusion, we demonstrate the potential of a neuroadaptive task design that can be widely applied to personalizing other task-based fMRI experiments in either dynamic real-time fMRI applications or within fMRI preprocessing pipelines.http://europepmc.org/articles/PMC6261022?pdf=render
spellingShingle Ming-Hua Chung
Bradford Martins
Anthony Privratsky
G Andrew James
Clint D Kilts
Keith A Bush
Individual differences in rate of acquiring stable neural representations of tasks in fMRI.
PLoS ONE
title Individual differences in rate of acquiring stable neural representations of tasks in fMRI.
title_full Individual differences in rate of acquiring stable neural representations of tasks in fMRI.
title_fullStr Individual differences in rate of acquiring stable neural representations of tasks in fMRI.
title_full_unstemmed Individual differences in rate of acquiring stable neural representations of tasks in fMRI.
title_short Individual differences in rate of acquiring stable neural representations of tasks in fMRI.
title_sort individual differences in rate of acquiring stable neural representations of tasks in fmri
url http://europepmc.org/articles/PMC6261022?pdf=render
work_keys_str_mv AT minghuachung individualdifferencesinrateofacquiringstableneuralrepresentationsoftasksinfmri
AT bradfordmartins individualdifferencesinrateofacquiringstableneuralrepresentationsoftasksinfmri
AT anthonyprivratsky individualdifferencesinrateofacquiringstableneuralrepresentationsoftasksinfmri
AT gandrewjames individualdifferencesinrateofacquiringstableneuralrepresentationsoftasksinfmri
AT clintdkilts individualdifferencesinrateofacquiringstableneuralrepresentationsoftasksinfmri
AT keithabush individualdifferencesinrateofacquiringstableneuralrepresentationsoftasksinfmri