Effects of cognitive training on grey matter and functional networks in Huntington’s disease
Poster No:
231
Submission Type:
Abstract Submission
Authors:
Katharine Huynh1,2,3, Nellie Georgiou-Karistianis1, Amit Lampit2, M. Navyaan Siddiqui1,3, Katharina Voigt3, Julie Stout1, Sharna Jamadar1,3
Institutions:
1Monash University, Clayton, Australia, 2The University of Melbourne, Melbourne, Australia, 3Monash Biomedical Imaging, Clayton, Australia
First Author:
Co-Author(s):
Introduction:
Huntington's disease (HD) is a rare, genetically inherited neurodegenerative disease with no available treatments (Bachoud-Lévi, 2019). HD leads to early and progressive cognitive decline, which is underpinned by structural and functional brain changes, particularly in fronto-striatal regions (Langley, 2021; Tabrizi, 2013). Computerised cognitive training (CCT) has been shown to improve cognitive function by inducing changes in brain structure and functional networks in ageing and neurodegenerative conditions (Nguyen, 2019; van Balkom, 2020). The effects and neural mechanisms of CCT in HD are largely unknown (Huynh, 2022). In our pilot trial of CCT in HD, we aimed to explore the effects of CCT on cognition, brain structure, and brain function in a subset of participants who consented to MRI.
Methods:
16 individuals in pre-manifest and early stages of HD were randomised to either an at-home multi-domain CCT intervention involving 2 x 1-hour training sessions per week, over 12 weeks (n = 6) or lifestyle education (n = 10). Participants completed a 1-hour MRI scan at baseline and follow-up, including structural scan and functional MRI with in-scanner processing speed (modified Symbol Digits Modalities Test; Rypma, 2006) and cognitive flexibility tasks (task switching; Meiran, 2000). Structural and functional data were pre-processed using standardised processing pipelines using SPM12, CAT12 toolbox, and CONN toolbox. Analyses examined changes from baseline to follow up in the CCT group, compared to the lifestyle education group, in terms of in-scanner task performance (accuracy and reaction time), grey matter volumes, and functional activity and connectivity of fronto-striatal regions during tasks. Analyses of grey matter volumes were conducted using whole-brain voxel-based morphometry analyses in CAT12. Analyses of functional activity and task-based functional connectivity were conducted using region-of-interest (ROI)-based analyses in SPM and CONN, respectively.
Results:
At baseline, both groups were matched on demographic and clinical variables (including age, sex, years of education, disease burden), and total grey matter volumes. There was evidence of reduced decline in task switching accuracy (p = .04) and improved processing speed (p = .04) in the CCT group, compared to the lifestyle education group. Additionally, there were increased and preserved grey matter volumes in several regions (including left putamen, right middle frontal gyrus, and right middle cingulate) in the CCT group, compared to the lifestyle education group (p's <.001, uncorrected, k > 25). Examination of individual values of grey matter volumes in each region demonstrated consistent effects across participants within each group. However, there were no significant effects of CCT on functional activity and connectivity of frontal-striatal regions during task performance (p's > .05, FDR-corrected). At the individual level, there appeared to be heterogeneity within each group, with both increased and decreased activity and connectivity.
·Regions with significant differences in grey matter volume change between baseline and follow up visits, in computerized cognitive training (CCT) group compared to lifestyle education group.
Conclusions:
Our pilot trial showed some evidence of benefits of a 3-month CCT intervention on cognition. While cognitive effects coincided with increased/preserved grey matter volumes in disease-relevant regions, there were no significant effects on functional activity and connectivity. The differences in results may be attributable to the duration of intervention and follow up, as previous studies of CCT in older adults show that functional changes occur early (at 3 weeks) and disappear with longer duration of training (at 12 weeks), whereas structural changes persist (Lampit, 2015). This may indicate the relatively greater utility of using grey matter volumes as an outcome measure to capture the neural effects of cognitive interventions in HD. Larger trials are required to further examine the effects of CCT on cognition and neural outcomes.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Learning and Memory:
Neural Plasticity and Recovery of Function 2
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI)
fMRI Connectivity and Network Modeling
Other Methods
Keywords:
Cognition
Degenerative Disease
FUNCTIONAL MRI
Movement Disorder
STRUCTURAL MRI
Other - Cognitive training; Huntington's disease
1|2Indicates the priority used for review
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Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Was this research conducted in the United States?
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.
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2. Huynh, K. (2023). Cognition-oriented treatments and physical exercise on cognitive function in Huntington’s disease: A systematic review. Journal of Neurology, 270, 1857–1879.
3. Lampit, A. (2015). Cognitive training-induced short-term functional and long-term structural plastic change is related to gains in global cognition in healthy older adults: A pilot study. Frontiers in Aging Neuroscience, 7, 14.
4. Langley, C. (2021). Fronto-striatal circuits for cognitive flexibility in far from onset Huntington’s disease: Evidence from the Young Adult Study. Journal of Neurology, Neurosurgery & Psychiatry, 92(2), 143.
5. Meiran, N. (2000). Component processes in task switching. Cognitive Psychology, 41(3), 211–253.
6. Nguyen, L. (2019). Cognitive and neural plasticity in old age: A systematic review of evidence from executive functions cognitive training. Ageing Research Reviews, 53, 100912.
7. Rypma, B. (2006). Neural correlates of cognitive efficiency. NeuroImage, 33(3), 969–979.
8. Tabrizi, S. J. (2013). Predictors of phenotypic progression and disease onset in premanifest and early-stage Huntington’s disease in the TRACK-HD study: Analysis of 36-month observational data. The Lancet Neurology, 12(7), 637–649.
9. van Balkom, T. D. (2020). The effects of cognitive training on brain network activity and connectivity in aging and neurodegenerative diseases: A systematic review. Neuropsychology Review, 30(2), 267–286.