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Mendeley readers
| Title |
Transcranial magnetic stimulation as a tool for understanding neurophysiology in Huntington's disease: A review
|
|---|---|
| Published in |
Neuroscience & Biobehavioral Reviews, May 2013
|
| DOI | 10.1016/j.neubiorev.2013.05.009 |
| Pubmed ID | |
| Authors |
April L. Philpott, Paul B. Fitzgerald, Tarrant D.R. Cummins, Nellie Georgiou-Karistianis |
| Abstract |
Structural and functional magnetic resonance imaging modalities have been critical in advancing our understanding of the neuroanatomical and pathophysiological changes that emerge during the premanifest and symptomatic stages of Huntington's disease (HD). However, the relationship between underlying neuropathology and the motor, cognitive and behavioural changes associated with the disorder still remain poorly understood. Less conventional technologies, such as transcranial magnetic stimulation (TMS) and electroencephalography (EEG), provide a unique opportunity to further investigate the causal relationships between targeted neural circuits and objective neurophysiological responses together with overt behaviours. In this review, we discuss previous successful applications of TMS in other neurological disorders and its prospective use in HD. We also address the added value of multimodal TMS techniques, such as TMS-EEG, in investigating the integrity of neural networks in non-motor regions in HD. We conclude that neurophysiological outcome measures are likely to contribute towards characterising further the trajectory of decline across functional domains in HD, enhance understanding of underlying neural mechanisms, and offer new avenues for elucidating sensitive endophenotypic biomarkers of disease progression. |
Mendeley readers
The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 1% |
| Serbia | 1 | 1% |
| Singapore | 1 | 1% |
| Canada | 1 | 1% |
| Unknown | 78 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 17 | 21% |
| Student > Bachelor | 11 | 13% |
| Researcher | 11 | 13% |
| Student > Master | 6 | 7% |
| Student > Doctoral Student | 5 | 6% |
| Other | 10 | 12% |
| Unknown | 22 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 15 | 18% |
| Medicine and Dentistry | 12 | 15% |
| Agricultural and Biological Sciences | 11 | 13% |
| Neuroscience | 10 | 12% |
| Engineering | 5 | 6% |
| Other | 9 | 11% |
| Unknown | 20 | 24% |