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autohrf-an R package for generating data-informed event models for general linear modeling of task-based fMRI data
ID
Purg Suljič, Nina
(
Avtor
),
ID
Demšar, Jure
(
Avtor
),
ID
Anticevic, Alan
(
Avtor
),
ID
Repovš, Grega
(
Avtor
)
PDF - Predstavitvena datoteka,
prenos
(6,15 MB)
MD5: 89F5482AF64B81A32618A81C9394755B
URL - Izvorni URL, za dostop obiščite
https://www.frontiersin.org/articles/10.3389/fnimg.2022.983324/full?&utm_source=Email_to_authors_&utm_medium=Email&utm_content=T1_11.5e1_author&utm_campaign=Email_publication&field=&journalName=Frontiers_in_Neuroimaging&id=983324
Galerija slik
Izvleček
The analysis of task-related fMRI data at the level of individual participants is commonly based on general linear modeling (GLM), which allows us to estimate the extent to which the BOLD signal can be explained by the task response predictors specified in the event model. The predictors are constructed by convolving the hypothesized time course of neural activity with an assumed hemodynamic response function (HRF). However, our assumptions about the components of brain activity, including their onset and duration, may be incorrect. Their timing may also differ across brain regions or from person to person, leading to inappropriate or suboptimal models, poor fit of the model to actual data, and invalid estimates of brain activity. Here, we present an approach that uses theoretically driven models of task response to define constraints on which the final model is computationally derived using actual fMRI data. Specifically, we developed autohrf–an R package that enables the evaluation and data-driven estimation of event models for GLM analysis. The highlight of the package is the automated parameter search that uses genetic algorithms to find the onset and duration of task predictors that result in the highest fitness of GLM based on the fMRI signal under predefined constraints. We evaluated the usefulness of the autohrf package on two original datasets of task-related fMRI activity, a slow event-related spatial working memory study and a mixed state-item study using the flanker task, and on a simulated slow event-related working memory data. Our results suggest that autohrf can be used to efficiently construct and evaluate better task-related brain activity models to gain a deeper understanding of BOLD task response and improve the validity of model estimates. Our study also highlights the sensitivity of fMRI analysis with GLM to precise event model specification and the need for model evaluation, especially in complex and overlapping event designs.
Jezik:
Angleški jezik
Ključne besede:
fMRI
,
GLM
,
assumed modeling
,
task-related activity
,
autohrf
,
R
,
functional magnetic resonance imaging
,
brain
,
general linear modeling
,
computer software
Vrsta gradiva:
Članek v reviji
Tipologija:
1.01 - Izvirni znanstveni članek
Organizacija:
FF - Filozofska fakulteta
FRI - Fakulteta za računalništvo in informatiko
Status publikacije:
Objavljeno
Različica publikacije:
Objavljena publikacija
Datum objave:
05.12.2022
Leto izida:
2022
Št. strani:
24 str.
PID:
20.500.12556/RUL-152347
UDK:
159.91:004.4R
ISSN pri članku:
2813-1193
DOI:
10.3389/fnimg.2022.983324
COBISS.SI-ID:
135318787
Datum objave v RUL:
21.11.2023
Število ogledov:
1055
Število prenosov:
44
Metapodatki:
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Objavi na:
Gradivo je del revije
Naslov:
Frontiers in neuroimaging
Skrajšan naslov:
Front. neuroimaging
Založnik:
Frontiers Media SA
ISSN:
2813-1193
COBISS.SI-ID:
105382915
Licence
Licenca:
CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:
http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:
To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
Sekundarni jezik
Jezik:
Slovenski jezik
Ključne besede:
funkcijsko magnetnoresonančno slikanje fMRI
,
možgani
,
splošno linearno modeliranje
,
predpostavljeno modeliranje
,
računalniški programi
,
R
Projekti
Financer:
ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:
J3-9264
Naslov:
Razstavljanje kognicije: Mehanizmi in reprezentacije delovnega spomina
Financer:
ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:
P3-0338
Naslov:
Fiziološki mehanizmi nevroloških motenj in bolezni
Financer:
ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:
P5-0110
Naslov:
Psihološki in nevroznanstveni vidiki kognicije
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