Search bioRxivSearch

bioRxiv · 10.1101/687582

Neurofeedback linked suppression of subthalamic beta oscillations speeds up movement initialisation in Parkinsonian Patients

Abstract

Enhanced beta oscillations (13-30 Hz) in the subthalamic nucleus (STN) have been associated with clinical impairment in Parkinsons disease (PD), such as rigidity and slowing of movement, with the suppression of STN beta activity through medication or deep brain stimulation correlating with improvement in these symptoms. Recent studies have also emphasized the importance of the time dynamics of the STN beta oscillations in the pathology of PD. An increased probability of prolonged beta bursts, defined as periods when beta band power exceeds a certain threshold, was more closely related to motor symptoms than average power; and the occurrence of beta bursts just before a go cue slows cued movements. Here we adopted a sequential neurofeedback-behaviour task paradigm to investigate whether patients with PD can learn to suppress pathological beta oscillations recorded from STN with neurofeedback training and whether the training improves the motor performance. Results from twelve patients showed that, compared with the control condition, the neurofeedback training led to reduced incidence and duration of beta bursts in the STN local field potential (LFP) and also reduced the synchrony between the STN LFP and cortical activities measured through EEG in the beta frequency band. The changes were accompanied by a reduced reaction time in cued movements. These results suggest that volitional suppression of beta bursts facilitated by neurofeedback training could help improve movement initialisation in Parkinsons disease.\n\nSignificance StatementOur study suggests that a neurofeedback paradigm which focuses on the time dynamics of the target neural signal can facilitate volitional suppression of pathological beta oscillations in the STN in Parkinsons disease. Neurofeedback training was accompanied by reduced reaction time in cued movements, but associated with increased tremor in tremulous patients. The results strengthen the link between subthalamic beta oscillations and motor impairment, and also suggest that different symptom-specific neural signals could be targeted to improve neuromodulation strategies, either through brain stimulation or neurofeedback training, for patients with tremor and bradykinesia-rigidity.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

He, S., Mostofi, A., Pereira, E., Syed, E., Torrecillos, F., Tinkhauser, G., Fischer, P., Pogsyan, A., Ashkan, K., Hasegawa, H., Li, Y., Brown, P., Tan, H.. 2019-07-01. Neurofeedback linked suppression of subthalamic beta oscillations speeds up movement initialisation in Parkinsonian Patients. https://doi.org/10.1101/687582

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience