[HTML][HTML] Machine learning based brain signal decoding for intelligent adaptive deep brain stimulation
Sensing enabled implantable devices and next-generation neurotechnology allow real-time
adjustments of invasive neuromodulation. The identification of symptom and disease …
adjustments of invasive neuromodulation. The identification of symptom and disease …
Machine learning for adaptive deep brain stimulation in Parkinson's disease: closing the loop
AM Oliveira, L Coelho, E Carvalho… - Journal of …, 2023 - Springer
Parkinson's disease (PD) is the second most common neurodegenerative disease bearing a
severe social and economic impact. So far, there is no known disease modifying therapy …
severe social and economic impact. So far, there is no known disease modifying therapy …
Deep brain stimulation creates informational lesion through membrane depolarization in mouse hippocampus
Deep brain stimulation (DBS) is a promising neuromodulation therapy, but the
neurophysiological mechanisms of DBS remain unclear. In awake mice, we performed high …
neurophysiological mechanisms of DBS remain unclear. In awake mice, we performed high …
Implantable pulse generators for deep brain stimulation: challenges, complications, and strategies for practicality and longevity
Deep brain stimulation (DBS) represents an important treatment modality for movement
disorders and other circuitopathies. Despite their miniaturization and increasing …
disorders and other circuitopathies. Despite their miniaturization and increasing …
Landscape and future directions of machine learning applications in closed-loop brain stimulation
AS Chandrabhatla, IJ Pomeraniec, TM Horgan… - NPJ Digital …, 2023 - nature.com
Brain stimulation (BStim) encompasses multiple modalities (eg, deep brain stimulation,
responsive neurostimulation) that utilize electrodes implanted in deep brain structures to …
responsive neurostimulation) that utilize electrodes implanted in deep brain structures to …
Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson's disease
Brain signal decoding promises significant advances in the development of clinical brain
computer interfaces (BCI). In Parkinson's disease (PD), first bidirectional BCI implants for …
computer interfaces (BCI). In Parkinson's disease (PD), first bidirectional BCI implants for …
[HTML][HTML] Neural interface systems with on-device computing: machine learning and neuromorphic architectures
Highlights•Neural interfaces continue to improve in channel count and form factor.•Low-
power machine learning and neuromorphic processors can be integrated onto neural …
power machine learning and neuromorphic processors can be integrated onto neural …
Closed-loop neural prostheses with on-chip intelligence: A review and a low-latency machine learning model for brain state detection
The application of closed-loop approaches in systems neuroscience and therapeutic
stimulation holds great promise for revolutionizing our understanding of the brain and for …
stimulation holds great promise for revolutionizing our understanding of the brain and for …
[HTML][HTML] Wearable sensor-driven responsive deep brain stimulation for essential tremor
Background Deep brain stimulation (DBS) is an effective surgical therapy for individuals with
essential tremor (ET). However, DBS operates continuously, resulting in adverse effects …
essential tremor (ET). However, DBS operates continuously, resulting in adverse effects …
[HTML][HTML] Neuronal oscillations predict deep brain stimulation outcome in Parkinson's disease
Background Neuronal oscillations are linked to symptoms of Parkinson's disease. This
relation can be exploited for optimizing deep brain stimulation (DBS), eg by informing a …
relation can be exploited for optimizing deep brain stimulation (DBS), eg by informing a …