Journal of Neurology Neurosurgery & Psychiatry, Journal Year: 2024, Volume and Issue: unknown, P. jnnp - 332014
Published: April 19, 2024
Rapid eye movement (REM) sleep behaviour disorder (RBD) is one of the most common problems and represents a key prodromal marker in Parkinson's disease (PD). It remains unclear whether how basal ganglia nuclei, structures that are directly involved pathology PD, implicated occurrence RBD.
Language: Английский
Nature reviews. Neuroscience, Journal Year: 2023, Volume and Issue: 24(6), P. 347 - 362
Published: April 12, 2023
Language: Английский
Citations
100
Trends in Neurosciences, Journal Year: 2023, Volume and Issue: 46(6), P. 472 - 487
Published: April 25, 2023
Deep brain stimulation (DBS) is an effective treatment and has provided unique insights into the dynamic circuit architecture of disorders. This Review illustrates our current understanding pathophysiology movement disorders their underlying circuits that are modulated with DBS. It proposes principles pathological network synchronization patterns like beta activity (13–35 Hz) in Parkinson's disease. We describe alterations from microscale including local synaptic via modulation mesoscale hypersynchronization to changes whole-brain macroscale connectivity. Finally, outlook on advances for clinical innovations next-generation neurotechnology provided: preoperative connectomic targeting feedback controlled closed-loop adaptive DBS as individualized network-specific interventions.
Language: Английский
Citations
48
Cyborg and Bionic Systems, Journal Year: 2023, Volume and Issue: 4
Published: Jan. 1, 2023
Cross-frequency coupling (CFC) reflects (nonlinear) interactions between signals of different frequencies. Evidence from both patient and healthy participant studies suggests that CFC plays an essential role in neuronal computation, interregional interaction, disease pathophysiology. The present review discusses methodological advances challenges the computation with particular emphasis on potential solutions to spurious coupling, inferring intrinsic rhythms a targeted frequency band, causal interferences. We specifically focus literature exploring context cognition/memory tasks, sleep, neurological disorders, such as Alzheimer's disease, epilepsy, Parkinson's disease. Furthermore, we highlight implication for optimization invasive noninvasive neuromodulation rehabilitation. Mainly, could support advancing understanding neurophysiology cognition motor control, serve biomarker symptoms, leverage therapeutic interventions, e.g., closed-loop brain stimulation. Despite evident advantages investigative translational tool neuroscience, further improvements are required facilitate practical correct use cyborg bionic systems field.
Language: Английский
Citations
46
Nature Medicine, Journal Year: 2023, Volume and Issue: 29(11), P. 2854 - 2865
Published: Nov. 1, 2023
Language: Английский
Citations
46
npj Digital Medicine, Journal Year: 2025, Volume and Issue: 8(1)
Published: Jan. 4, 2025
Abstract Adaptive deep brain stimulation (DBS) provides individualized therapy for people with Parkinson’s disease (PWP) by adjusting the in real-time using neural signals that reflect their motor state. Current algorithms, however, utilize condensed and manually selected features which may result a less robust biased therapy. In this study, we propose Neural-to-Gait Neural network (N2GNet), novel learning-based regression model capable of tracking gait performance from subthalamic nucleus local field potentials (STN LFPs). The LFP data were acquired when eighteen PWP performed stepping place, ground reaction forces measured to track weight shifts representing performance. By exhibiting stronger correlation compared higher-correlation beta power two leads outperforming other evaluated designs, N2GNet effectively leverages comprehensive frequency band, not limited range, solely STN LFPs.
Language: Английский
Citations
2
eLife, Journal Year: 2022, Volume and Issue: 11
Published: May 27, 2022
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 adaptive deep stimulation (DBS) are now available. can extend utility DBS but impact neural source, computational methods and PD pathophysiology on performance unknown. This represents an unmet need future neurotechnology. To address this, we developed invasive brain-signal approach based intraoperative sensorimotor electrocorticography (ECoG) subthalamic LFP to predict grip-force, a representative movement application, 11 patients undergoing DBS. We demonstrate that ECoG is superior accurate grip-force decoding. Gradient boosted decision trees (XGBOOST) outperformed other model architectures. negatively correlated with motor impairment, which could be attributed beta bursts preparation period. highlights capacity encode vigor. Finally, connectomic analysis individual channels across by using their fingerprints. Our study provides neurophysiological framework aid individualized precision-medicine intelligent
Language: Английский
Citations
51
Journal of Neurology, Journal Year: 2025, Volume and Issue: 272(4)
Published: March 12, 2025
Abstract Next-generation neurostimulators capable of running closed-loop adaptive deep brain stimulation (aDBS) are about to enter the clinical landscape for treatment Parkinson’s disease. Already promising results using aDBS have been achieved symptoms such as bradykinesia, rigidity and motor fluctuations. However, heterogeneity freezing gait (FoG) with its wide range presentations exacerbation cognitive emotional load make it more difficult predict treat. Currently, a successful strategy ameliorate FoG lacks robust oscillatory biomarker. Furthermore, technical implementation suppressing an upcoming episode in real-time represents significant challenge. This review describes neurophysiological signals underpinning explains how is currently being implemented. we offer discussion addressing both theoretical practical areas that will need be resolved if going able unlock full potential treat FoG.
Language: Английский
Citations
1
Ageing Research Reviews, Journal Year: 2023, Volume and Issue: 93, P. 102147 - 102147
Published: Nov. 28, 2023
Cardinal motor symptoms in Parkinson's disease (PD) include bradykinesia, rest tremor and/or rigidity. This symptomatology can additionally encompass abnormal gait, balance and postural patterns at advanced stages of the disease. Besides pharmacological surgical therapies, physical exercise represents an important strategy for management these impairments. Traditionally, diagnosis classification such abnormalities have relied on partially subjective evaluations performed by neurologists during short temporally scattered hospital appointments. Emerging sports medical methods, including wearable sensor-based movement assessment computational-statistical analysis, are paving way more objective systematic diagnoses everyday life conditions. These approaches hold promise to facilitate customizing clinical trials specific PD groups, as well personalizing neuromodulation therapies prescriptions each individual, remotely regularly, according progression or symptoms. We aim summarize benefits with a emphasis gait deficits, provide overview recent advances analysis approaches, notably from science community, value prognosis. Although techniques becoming increasingly available, their standardization optimization purposes is critically missing, especially translation complex neurodegenerative disorders PD. highlight importance integrating state-of-the-art combination other motor, electrophysiological neural biomarkers, improve understanding diversity phenotypes, response dynamics progression.
Language: Английский
Citations
14
Movement Disorders, Journal Year: 2023, Volume and Issue: 39(2), P. 424 - 428
Published: Dec. 18, 2023
Abstract Background Transcutaneous vagus nerve stimulation (VNS) showed early evidence of efficacy for the gait treatment Parkinson's disease (PD). Objectives Providing data on neurophysiological and clinical effects transauricular VNS (taVNS). Methods Ten patients with recording deep brain (DBS) have been enrolled in a within participant design pilot study, double‐blind crossover sham‐controlled trial taVNS. Subthalamic local field potentials (β band power), Unified Disease Rating Scales (UPDRS), digital timed‐up‐and‐go test (TUG) were measured compared real versus sham taVNS during medication‐off/DBS‐OFF condition. Results The left induced reduction total β power contralateral (ie, right) subthalamic nucleus an improvement TUG time, speed, variability. taVNS‐induced correlated speed. No major changes observed at UPDRS. Conclusions is promising strategy management PD gait, deserving prospective trials chronic neuromodulation. © 2023 Authors. Movement Disorders published by Wiley Periodicals LLC behalf International Parkinson Disorder Society.
Language: Английский
Citations
12
Brain Sciences, Journal Year: 2024, Volume and Issue: 14(3), P. 196 - 196
Published: Feb. 21, 2024
Brain-Computer Interfaces (BCIs) aim to establish a pathway between the brain and an external device without involvement of motor system, relying exclusively on neural signals. Such systems have potential provide means communication for patients who lost ability speak due neurological disorder. Traditional methodologies decoding imagined speech directly from signals often deploy static classifiers, that is, decoders are computed once at beginning experiment remain unchanged throughout BCI use. However, this approach might be inadequate effectively handle non-stationary nature electroencephalography (EEG) learning accompanies use, as parameters expected change, all more in real-time setting. To address limitation, we developed adaptive classifier updates its based incoming data real time. We first identified optimal (the update coefficient, UC) used Linear Discriminant Analysis (LDA) classifier, using previously recorded EEG dataset, acquired while healthy participants controlled binary syllable decoding. subsequently tested effectiveness optimization control Twenty performed two sessions imagery syllables, LDA randomized order. As hypothesized, led better performances than one task. Furthermore, were closely aligned both datasets, same These findings highlight reliability classifiers improvement can shorten training time favor development multi-class BCIs, representing clear interest non-invasive notably characterized by low accuracies.
Language: Английский
Citations
4