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Journal article

Physiologically informed neuromodulation

Abstract:
The rapid evolution of neuromodulation techniques includes an increasing amount of research into stimulation paradigms that are guided by patients' neurophysiology, to increase efficacy and responder rates. Treatment personalisation and target engagement have shown to be effective in fields such as Parkinson's disease, and closed-loop paradigms have been successfully implemented in cardiac defibrillators. Promising avenues are being explored for physiologically informed neuromodulation in psychiatry. Matching the stimulation frequency to individual brain rhythms has shown some promise in transcranial magnetic stimulation (TMS). Matching the phase of those rhythms may further enhance neuroplasticity, for instance when combining TMS with electroencephalographic (EEG) recordings. Resting-state EEG and event-related potentials may be useful to demonstrate connectivity between stimulation sites and connected areas. These techniques are available today to the psychiatrist to diagnose underlying sleep disorders, epilepsy, or lesions as contributing factors to the cause of depression. These technologies may also be useful in assessing the patient's brain network status prior to deciding on treatment options. Ongoing research using invasive recordings may allow for future identification of mood biomarkers and network structure. A core limitation is that biomarker research may currently be limited by the internal heterogeneity of psychiatric disorders according to the current DSM-based classifications. New approaches are being developed and may soon be validated. Finally, care must be taken when incorporating closed-loop capabilities into neuromodulation systems, by ensuring the safe operation of the system and understanding the physiological dynamics. Neurophysiological tools are rapidly evolving and will likely define the next generation of neuromodulation therapies.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.jns.2021.120121

Authors

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
Somerville College
Role:
Author


Publisher:
Elsevier
Journal:
Journal of the Neurological Sciences More from this journal
Volume:
434
Article number:
120121
Publication date:
2021-12-28
Acceptance date:
2021-12-21
DOI:
EISSN:
1878-5883
ISSN:
0022-510X
Pmid:
34998239


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