Brain stimulation has, for many decades, been considered as a potential solution for the unmet needs of the many people living with drug-resistant epilepsy. Clinically, there are several different approaches in use, including vagus nerve stimulation (VNS), deep brain stimulation of the thalamus, and responsive neurostimulation (RNS). Across populations of patients, all deliver reductions in seizure load and SUDEP risk, yet do so variably, and the improvements seem incremental rather than transformative. In contrast, within the field of experimental neuroscience, the transformational impact of optogenetic stimulation is evident; by providing a means to control subsets of neurons in isolation, it has revolutionized our ability to dissect out the functional relations within neuronal microcircuits. It is worth asking, therefore, how pre-clinical optogenetics research could advance clinical practice in epilepsy? Here, we review the state of the clinical field, and the recent progress in pre-clinical animal research. We report various breakthrough results, including the development of new models of seizure initiation, its use for seizure prediction, and for fast, closed-loop control of pathological brain rhythms, and what these experiments tell us about epileptic pathophysiology. Finally, we consider how these pre-clinical research advances may be translated into clinical practice.
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http://dx.doi.org/10.1093/brain/awae385 | DOI Listing |
NPJ Digit Med
January 2025
Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA.
Adaptive deep brain stimulation (DBS) provides individualized therapy for people with Parkinson's disease (PWP) by adjusting the stimulation in real-time using neural signals that reflect their motor state. Current algorithms, however, utilize condensed and manually selected neural features which may result in a less robust and biased therapy. In this study, we propose Neural-to-Gait Neural network (N2GNet), a novel deep learning-based regression model capable of tracking real-time gait performance from subthalamic nucleus local field potentials (STN LFPs).
View Article and Find Full Text PDFBMC Geriatr
January 2025
Department of Rehabilitation Medicine (Rehabilitation Center), Qilu Hospital of Shandong University, No. 107, Wenhuaxi Road, Jinan , Shandong, 250012, China.
Background: Mild cognitive impairment (MCI) is a high-risk factor for dementia and dysphagia; therefore, early intervention is vital. The effectiveness of intermittent theta burst stimulation (iTBS) targeting the right dorsal lateral prefrontal cortex (rDLPFC) remains unclear.
Methods: Thirty-six participants with MCI were randomly allocated to receive real (n = 18) or sham (n = 18) iTBS.
Brain Stimul
January 2025
Department of Electrical and Computer Engineering, Worcester Polytechnic Institute, Worcester, MA, USA, 01609; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA 02129; Department of Mathematics, Worcester Polytechnic Institute, Worcester, MA, USA, 01609.
Brain Stimul
January 2025
Department of Physical Medicine and Rehabilitation, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, Texas; TIRR Memorial Hermann Hospital, Houston, Texas. Electronic address:
Brain Stimul
January 2025
Department of Biomedical Engineering, 36 S Wasatch Dr, Salt Lake City, 84112, UT, United States.
Emerging neurostimulation methods aim to selectively modulate deep brain structures. Guiding these therapies has presented a substantial chal- lenge, since imaging modalities such as MRI limit the spectrum of benefi- ciaries. In this study, we assess the guidance accuracy of a neuronavigation method that does not require taking MRI scans.
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