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Tabrizi, S. J.

Publications and source records attributed to Tabrizi, S. J..

2 recordsLinked to original sources

Dynamics of cortical degeneration over a decade in Huntington's Disease

The neurodegenerative process is typically slowly progressive and complex. While simple models of neurodegeneration suggest that brain changes progress at a near constant rate, previous research shows regional variation within the temporal progression of atrophy, indicating that over the course of neurodegeneration, different regions may undergo changing rates of atrophy. Characterization of long-term dynamic brain changes in neurodegeneration requires both extensive longitudinal MRI datasets and an advanced modeling framework. Until recently, both of these elements were not available. Here, we implement a novel dynamic systems approach to infer patterns of regional progression spatially and temporally in a unique longitudinal dataset with up to seven annual individual brain scans per participant from 49 Huntingtons Disease (HD) gene-carriers. We map participant-and group-level trajectories of cortical atrophy in HD using a decade of data that encompasses motor symptom onset and, for the first time, show that neurodegenerative brain changes exhibit complex temporal dynamics of atrophy with substantial regional variation in progressive cortical atrophy. Some fronto-occipital cortical areas show an almost constant rate of atrophy, while medial-inferior temporal areas undergo only minor change. Interestingly, cortical sensory-motor areas were found to show a noticeable acceleration of atrophy following HD diagnosis. Furthermore, we establish links between individual atrophy and genetic markers of HD (CAG repeat length), as well as showing that cortical motor network changes predict subsequent decline in task-based motor performance, demonstrating face-validity of the model. Our findings highlight the complex pattern of dynamic cortical change occurring in HD that can help to resolve the biological underpinnings of HD progression.

neuroscience

Activity-is better than connectivity-neurofeedback training in Huntington’s disease

Non-invasive methods, such as neurofeedback training (NFT), could support cognitive symptom management in Huntingtons disease (HD) by targeting brain regions whose function is impaired. The aim of our single-blind, sham-controlled study was to collect rigorous evidence regarding the feasibility of NFT in HD by examining two different methods, activity and connectivity real-time fMRI NFT. Thirty-two HD gene-carriers completed 16 runs of NFT training, using an optimized real-time fMRI protocol. Participants were randomized into four groups, two treatment groups, one receiving neurofeedback derived from the activity of the Supplementary Motor Area (SMA), and another receiving neurofeedback based on the correlation of SMA and left striatum activity (connectivity NFT), and two sham control groups, matched to each of the treatment groups. We examined differences between the groups during NFT training sessions and after training at follow-up sessions. Transfer of training was measured by measuring the participants ability to upregulate NFT target levels without feedback (near transfer), as well as by examining change in objective, a-priori defined, behavioural measures of cognitive and psychomotor function (far transfer) before and at 2 months after training. We found that the treatment group had significantly higher NFT target levels during the training sessions compared to the control group. However, we did not find robust evidence of better transfer in the treatment group compared to controls, or a difference between the two NFT methods. We also did not find evidence in support of a relationship between change in cognitive and psychomotor function and NFT learning success. We conclude that although there is evidence that NFT can be used to guide participants to regulate the activity and connectivity of specific regions in the brain, evidence regarding transfer of learning and clinical benefit was not robust. Although the intervention is non-invasive, given the costs and absence of reliable evidence of clinical benefit, we cannot recommend real-time fMRI NFT as a potential intervention in HD.

neuroscience