Fu Yu Kwok1, Beth Ann O'Brien2, Kiat Hong Stacey Tay3, and SH Annabel Chen1,4
1Division of Psychology, Nanyang Technological University, Singapore, Singapore, 2National Institute of Education, Nanyang Technological University, Singapore, Singapore, 3Paediatric Neurology and Developmental Paediatrics, National University Hospital, National University of Singapore, Singapore, Singapore, 4Centre for Research And Development Learning, Nanyang Technological University, Singapore, Singapore
Synopsis
Dynamic causal modeling was
utilized to examine the effective connectivity during verbal working memory in
children with dyslexia and typically developing children. Seven regions of interest—FG,
IFG, IOG, IPL, thalamus, inferior cerebellum and superior cerebellum were
included into the analyses. Results indicated that the effect of dyslexia led
to shift in effective network connectivity. The present study furthered our
understanding of the cerebro-cerebellar effective network connectivity in both
children with dyslexia and typically developing children. In addition, it
provided new insights about the effects of dyslexia on this network. Introduction
Converging findings from
behavioral and neuroimaging studies have shown that verbal working memory (VWM)
is one of the core deficit seen in children with dyslexia. Previous findings
from Chen and Desmond [1, 2] provided evidence for two cerebro-cerebellar
networks for verbal working memory—a frontal/superior cerebellar articulatory
control system and a parietal/inferior cerebellar phonological storage system.
However, the dynamics of effective connectivity in children during verbal
working memory tasks in a cerebro-cerebellar network has yet to be verified. The
present study aimed at clarifying the dynamics of effective connectivity in
both typically developing children and children with dyslexia using Dynamic
Causal Modeling (DCM) during a verbal working memory task.
Methodology
8 children with dyslexia
(mean age=9.0; SD=0.92) and 4 age-matched children (mean age=8.6; SD=0.69) were
recruited for the study. Participants studied in mainstream school
and were administered a health questionnaire to ensure that they were
right-handed and did not have a history of neurological or psychiatric
disorder. As part of the study, participants performed a Sternberg VWM task
(Fig.1) in a 3T MRI Scanner (Trio, Siemens). Functional imaging data were
acquired using: TR=1000ms, TE=30ms, slice thickness=2mm, 60 slices, and 2x2x2mm
3
voxels. Image processing and connectivity analyses were performed using SPM12
and DCM12 (Fig.2), respectively. The optimum model was determined from 8 models
using the random effects Bayesian model selection method.
Results
Comparison of Bayesian model
selection results indicated that children with dyslexia had a clear preference
for model 2 (Fig. 3) while typical developing children show a distinct
preference for model 7 (Fig. 4).
Conclusion
To the best of our
knowledge, this is the first study to examine the dynamics of effective
connectivity in typically developing children and children with dyslexia. Our findings demonstrated that during working memory, children with
dyslexia only modulated the pathway from the IFG to the IPL. For typically
developing children, results indicated bilateral modulatory connectivity
between the IFG and IPL in addition to the modulatory connectivity observed on
both the articulatory control (fronto/superior cerebellar) and phonological WM (parieto/inferior cerebellar) cerebro-cerebellar pathways. Collectively, the present study showed
that the effect of dyslexia caused a shift in the effective connectivity within the cerebro-cerebellar VWM network.
Acknowledgements
This work was supported by a
grant from the Singapore Ministry of Education AcRF Tier 1 (RG63/14).References
[1] Chen, S. A., & Desmond, J. E. (2005). Temporal dynamics of
cerebro-cerebellar network recruitment during a cognitive task.
Neuropsychologia, 43(9), 1227- 1237.
[2] Desmond, J. E., Chen, S. H., & Shieh, P. B. (2005). Cerebellar
transcranial magnetic stimulation impairs verbal working memory. Annals of
Neurology,58(4), 553- 560.