Adaptive Deep Brain Stimulation In Advanced Parkinson Disease
By S. Little, A. Pogosyan, Spencer Neal, B. Zavala, Ludvic U. Zrinzo, Marwan I. Hariz, T. Foltynie, P. Limousin, K. Ashkan, J. Fitzgerald and 3 more. Annals of Neurology, 2013
1,263 citations recorded by the source corpus.
Brain–computer interfaces (BCIs) could potentially be used to interact with pathological brain signals to intervene and ameliorate their effects in disease states. Here, we provide proof‐of‐principle of this approach by using a BCI to interpret pathological brain activity in patients with advanced Parkinson disease (PD) and to use this feedback to control when therapeutic deep brain stimulation (DBS) is delivered. Our goal was to demonstrate that by personalizing and optimizing stimulation in real time, we could improve on both the efficacy and efficiency of conventional continuous DBS.
Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Neurology
View Paper: https://www.semanticscholar.org/paper/22b2bcdbabc47757505cceaeefe8d93be2d2d1ae
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In Cellular and Molecular Neuroscience
In Cognitive Neuroscience
- Vladimir Litvak
- André Moraes Bastos
- Karl J. Friston
- Dimitris A. Pinotsis
- Michael W. Spratling
- Rafal Bogacz
- W. D. Penny
- Klaas E. Stephan
In Neurology
Citations in the corpus
- LFP and oscillations—what do they tell us? (2015, background): “Recent studies point to a causal role of beta in movement slowing; transcranial alternating current stimulation in the beta band slows voluntary movement in healthy subjects [36,37] and adaptive DBS triggered by high beta power appears to be superior to constant DBS in ameliorating Parkinsonian symp”
- Neural representations of visual memory in inferotemporal cortex reveal a generalizable framework for translating between spikes and field potentials (2026, unknown): “Both measures serve important roles: spiking activity is essential for advancing our understanding of neural coding [7], while field potentials provide insights into human brain function and guide therapies such as brain machine interfaces and neuromodulation [8, 9].”