Functional Specialisation and Effective Connectivity During Self-paced Unimanual and Bimanual Tapping of Hand Fingers: An Extended Analysis Using Dynamic Causal Modeling and Bayesian Model Selection for Group Studies
- Author:
Ahmad Nazlim Yusoff
;
Aini Ismafairus Abd Hamid
;
Khairiah Abdul Hamid
;
Wan Ahmad Kamil Wan Abdullah
;
Mazlyfarina Mohamad
;
Hanani Abdul Manan
- Publication Type:Journal Article
- Keywords:
Primary motor area, Supplementary motor area, BA44, Bayes rule, Statistical Parametric Mapping
- From:Malaysian Journal of Medicine and Health Sciences
2011;7(2):17-36
- CountryMalaysia
- Language:English
-
Abstract:
Introduction: This multiple-subject fMRI study continue to further investigate brain activation within
and effective connectivity between the significantly (p<0.001) activated primary motor area (M1),
supplementary motor area (SMA) with the inclusion of BA44 during unimanual (UNIright and UNIleft)
and bimanual (BIM) self-paced tapping of hand fingers. Methods: The activation extent (spatial and
height) and effective connectivity were analysed using statistical parametric mapping (SPM), dynamic
causal modeling (DCM) and the novel method of Bayesian model selection (BMS) for group studies.
Results: Group results for UNIright and UNIleft showed contra-lateral and ipsi-lateral involvement of M1
and SMA. The results for BIM showed bilateral activation in M1, SMA and BA44. A larger activation
area but with lower percentage of signal change (PSC) are observed in the left M1 due to the control
on UNIright as compared to the right M1 due to the control on UNIleft. This is discussed as due to the
influence of the tapping rate effects that is greater than what would be produced by the average effects
of the dominant and sub-dominant hand. However, the higher PSC observed in the right M1 is due
to a higher control demand used by the brain in coordinating the tapping of the sub-dominant hand
fingers. Connectivity analysis indicated M1 as the intrinsic input for UNIright and UNIleft while for BIM,
the inputs were both M1s. During unilateral finger tapping, the contra-lateral M1 acts as the input
center which in turn triggers the propagation of signal unidirectionally to other regions of interest. The
results obtained for BIM (BIMleft and BIMright) however yield a model with less number of significant
connection. M1-M1 connection is unidirectional for UNIleft and UNIright originating from contra-lateral
M1, and is inhibited during BIM. Conclusion: By taking into consideration the presence of outliers that
could have arisen in any subject under study, BMS for group study has successfully chosen a model that
has the best balance between accuracy (fit) and complexity.
