Keywords: Functional Connectivity, Brain Connectivity, Dyslexia, Dynamic Causal Modeling
Motivation: Alterations in functional connectivity between regions involved in reading and visuo-attention networks have been associated with developmental dyslexia. However, the causal relationship between regional activity remains unknown.
Goal(s): We aimed to investigate the causal relationship between regions of the visuo-attention network in developmental dyslexia and typical readers during a coherent motion detection task.
Approach: Using Dynamic Causal Modeling, the causal connectivity between regions in the cortex and cerebellum was estimated to understand aberrant network function.
Results: Children with developmental dyslexia showed remarkable differences in patterns of excitatory and inhibitory communication between cerebellum and visuo-attention regions compared to typical reader children.
Impact: Dynamic Causal Modeling can evaluate cortico-cerebellar causal relationship (i.e., effective connectivity) in healthy subjects and in neurodevelopmental conditions such as developmental dyslexia. New evidence points toward a critical role of the cerebellum in reading impairment, with potential consequences for intervention.
This study was partially supported by “Ricerca Corrente 2023” funds provided by the Italian Ministry of Health. CGWK receives funding from Horizon2020 [Research and Innovation Action Grants Human Brain Project 945539 (SGA3)], BRC (#BRC704/CAP/CGW), MRC (#MR/S026088/1), Ataxia UK, Rosetrees Trust (#PGL22/100041 and #PGL21/10079). CGWK is a shareholder in Queen Square Analytics Ltd. H2020 Research and Innovation Action Grants Human Brain Project 785907 and 945539 (SGA2 and SGA3) to ED'A and FP. Moreover, the project was supported by the MNL Project “Local Neuronal Microcircuits” of the Centro Fermi (Rome, Italy) This work was also supported by #NEXTGENERATIONEU (NGEU) and funded by the Ministry of University and Research (MUR), National Recovery and Resilience Plan (NRRP), project MNESYS (PE0000006) - A Multiscale integrated approach to the study of the nervous system in health and disease (DN. 1553 11.10.2022)
1. Seghier, M. L., Zeidman, P., Neufeld, N. H., Leff, A. P., & Price, C. J. (2010). Identifying abnormal connectivity in patients using dynamiccausal modeling of FMRI responses. Frontiers in systems neuroscience, 4, 142.
2. Nicolson, R. I., Fawcett, A. J., & Dean, P. (2001). Developmental dyslexia: the cerebellar deficit hypothesis. Trends in neurosciences, 24(9), 508-511.
3. Friston, K. J., Harrison, L., & Penny, W. (2003). Dynamic causal modelling. Neuroimage, 19(4), 1273-1302.
4. Mascheretti, S., Peruzzo, D., Andreola, C., Villa, M., Ciceri, T., Trezzi, V., ... & Arrigoni, F. (2021). Selecting the most relevant brain regions to classify children with developmental dyslexia and typical readers by using complex magnocellular stimuli and multiple kernel learning. Brain Sciences, 11(6), 722.
5. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, 4th ed.; American Psychiatric Association: Washington, DC, USA, 2006.
6. Hoeft, F., Hernandez, A., McMillon, G., Taylor-Hill, H., Martindale, J. L., Meyler, A., ... & Gabrieli, J. D. (2006). Neural basis of dyslexia: a comparison between dyslexic and nondyslexic children equated for reading ability. Journal of Neuroscience, 26(42), 10700-10708.
7. Turkeltaub, P. E., Gareau, L., Flowers, D. L., Zeffiro, T. A., & Eden, G. F. (2003). Development of neural mechanisms for reading. Nature neuroscience, 6(7), 767-773.
8. Corbetta, M., & Shulman, G. L. (2011). Spatial neglect and attention networks. Annual review of neuroscience, 34, 569-599.
9. Gebauer, D., Fink, A., Kargl, R., Reishofer, G., Koschutnig, K., Purgstaller, C., ... & Enzinger, C. (2012). Differences in brain function and changes with intervention in children with poor spelling and reading abilities. PloS one, 7(5), e38201.
10. Rosa, M. J., Friston, K., & Penny, W. (2012). Post-hoc selection of dynamic causal models. Journal of neuroscience methods, 208(1), 66–78. https://doi.org/10.1016/j.jneumeth.2012.04.013
11. Mariën, P., Ackermann, H., Adamaszek, M. et al. Consensus Paper: Language and the Cerebellum: an Ongoing Enigma. Cerebellum 13, 386–410 (2014). https://doi.org/10.1007/s12311-013-0540-5
12. Li, H., Kepinska, O., Caballero, J. N., Zekelman, L., Marks, R. A., Uchikoshi, Y., ... & Hoeft, F. (2021). Decoding the role of the cerebellum in the early stages of reading acquisition. Cortex, 141, 262-279.
13. Alvarez, T. A., & Fiez, J. A. (2018). Current perspectives on the cerebellum and reading development. Neuroscience & Biobehavioral Reviews, 92, 55-66.
14. Paulesu, E., Danelli, L., & Berlingeri, M. (2014). Reading the dyslexic brain: multiple dysfunctional routes revealed by a new meta-analysis of PET and fMRI activation studies. Frontiers in human neuroscience, 8, 830.
15. Ito, M. (2008). Control of mental activities by internal models in the cerebellum. Nature Reviews Neuroscience, 9(4), 304-313.
16. Nummenmaa, L., Hyönä, J., & Calvo, M. G. (2006). Eye movement assessment of selective attentional capture by emotional pictures. Emotion, 6(2), 257.
17. Cai, W., & Leung, H. C. (2009). Cortical activity during manual response inhibition guided by color and orientation cues. Brain research, 1261, 20-28.
18. Richlan, F. (2012). Developmental dyslexia: dysfunction of a left hemisphere reading network. Frontiers in human neuroscience, 6, 120.
19. Ashburn, S. M., Flowers, D. L., Napoliello, E. M., & Eden, G. F. (2020). Cerebellar function in children with and without dyslexia during single word processing. Human brain mapping, 41(1), 120-138.
20. Barth, A. E., Denton, C. A., Stuebing, K. K., Fletcher, J. M., Cirino, P. T., Francis, D. J., & Vaughn, S. (2010). A test of the cerebellar hypothesis of dyslexia in adequate and inadequate responders to reading intervention. Journal of the International Neuropsychological Society, 16(3), 526-536.
21. Nicolson, R. I., & Fawcett, A. J. (2011). Dyslexia, dysgraphia, procedural learning and the cerebellum. Cortex, 47(1), 117-127.
22. Zeidman, P., Jafarian, A., Corbin, N., Seghier, M. L., Razi, A., Price, C. J., & Friston, K. J. (2019). A guide to group effective connectivity analysis, part 1: First level analysis with DCM for fMRI. Neuroimage, 200, 174-190.