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      Long-term wireless streaming of neural recordings for circuit discovery and adaptive stimulation in patients with Parkinson’s disease

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          Abstract

          Neural recordings in humans using invasive devices can elucidate the circuits underlying brain disorders, but have so far been limited to short recordings from externalized brain leads in a hospital setting or from implanted sensing devices that provide only intermittent, brief streaming of time series data. Here we report the use of an implantable two-way neural interface for wireless, multichannel streaming of field potentials in five patients with Parkinson’s disease for up to 15 months after implantation. Bilateral 4-channel motor cortex and basal ganglia field potentials streamed at home for over 2,600 hours were paired with behavioral data from wearable monitors for the neural decoding of states of inadequate or excessive movement. We validated patient-specific neurophysiological biomarkers during normal daily activities and used those patterns for adaptive deep brain stimulation. This technological approach may be widely applicable to brain disorders treatable by invasive neuromodulation.

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          Most cited references48

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          MDS clinical diagnostic criteria for Parkinson's disease.

          This document presents the Movement Disorder Society Clinical Diagnostic Criteria for Parkinson's disease (PD). The Movement Disorder Society PD Criteria are intended for use in clinical research but also may be used to guide clinical diagnosis. The benchmark for these criteria is expert clinical diagnosis; the criteria aim to systematize the diagnostic process, to make it reproducible across centers and applicable by clinicians with less expertise in PD diagnosis. Although motor abnormalities remain central, increasing recognition has been given to nonmotor manifestations; these are incorporated into both the current criteria and particularly into separate criteria for prodromal PD. Similar to previous criteria, the Movement Disorder Society PD Criteria retain motor parkinsonism as the core feature of the disease, defined as bradykinesia plus rest tremor or rigidity. Explicit instructions for defining these cardinal features are included. After documentation of parkinsonism, determination of PD as the cause of parkinsonism relies on three categories of diagnostic features: absolute exclusion criteria (which rule out PD), red flags (which must be counterbalanced by additional supportive criteria to allow diagnosis of PD), and supportive criteria (positive features that increase confidence of the PD diagnosis). Two levels of certainty are delineated: clinically established PD (maximizing specificity at the expense of reduced sensitivity) and probable PD (which balances sensitivity and specificity). The Movement Disorder Society criteria retain elements proven valuable in previous criteria and omit aspects that are no longer justified, thereby encapsulating diagnosis according to current knowledge. As understanding of PD expands, the Movement Disorder Society criteria will need continuous revision to accommodate these advances.
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            Machine learning. Clustering by fast search and find of density peaks.

            Cluster analysis is aimed at classifying elements into categories on the basis of their similarity. Its applications range from astronomy to bioinformatics, bibliometrics, and pattern recognition. We propose an approach based on the idea that cluster centers are characterized by a higher density than their neighbors and by a relatively large distance from points with higher densities. This idea forms the basis of a clustering procedure in which the number of clusters arises intuitively, outliers are automatically spotted and excluded from the analysis, and clusters are recognized regardless of their shape and of the dimensionality of the space in which they are embedded. We demonstrate the power of the algorithm on several test cases.
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              Deep brain stimulation: current challenges and future directions

              The clinical use of deep brain stimulation (DBS) is among the most important advances in the clinical neurosciences in the past two decades. As a surgical tool, DBS can directly measure pathological brain activity and can deliver adjustable stimulation for therapeutic effect in neurological and psychiatric disorders correlated with dysfunctional circuitry. The development of DBS has opened new opportunities to access and interrogate malfunctioning brain circuits and to test the therapeutic potential of regulating the output of these circuits in a broad range of disorders. Despite the success and rapid adoption of DBS, crucial questions remain, including which brain areas should be targeted and in which patients. This Review considers how DBS has facilitated advances in our understanding of how circuit malfunction can lead to brain disorders and outlines the key unmet challenges and future directions in the DBS field. Determining the next steps in DBS science will help to define the future role of this technology in the development of novel therapeutics for the most challenging disorders affecting the human brain.
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                Author and article information

                Journal
                9604648
                20305
                Nat Biotechnol
                Nat Biotechnol
                Nature biotechnology
                1087-0156
                1546-1696
                19 March 2021
                03 May 2021
                September 2021
                03 November 2021
                : 39
                : 9
                : 1078-1085
                Affiliations
                [1 ]Department of Neurological Surgery, University of California, San Francisco, San Francisco CA
                [2 ]Department of Neurology, University of California, San Francisco, San Francisco CA
                [3 ]Mayo Systems Electrophysiology Laboratory, Department of Neurology, Mayo Clinic, Rochester MN
                [4 ]School of Engineering and Carney Institute, Brown University, Providence RI
                [5 ]Department of Engineering Science, University of Oxford and MRC Brain Network Dynamics Unit
                Author notes

                Author Contributions

                R.G., S.L. and P.A.S conceived the study and experiments. J.L.O., C.A.R., P.S.L, D.D.W, N.B.G., I.B. and M.S.L., provided clinical care and supervision, R.P. wrote the software interface for Summit RC+S, R.G., S.L. and R.W. collected data, R.G., S.L., S.W., C.D.H, H.E.W, G.A.W, V.K., D.B. and T.D. provided key analytic tools, R.G. and P.A.S drafted manuscript and figures.

                Corresponding author information: Correspondence and requests for materials should be addressed to R.G. roee.gilron@ 123456ucsf.edu
                Article
                NIHMS1684406
                10.1038/s41587-021-00897-5
                8434942
                33941932
                2c166597-5821-462c-a507-0747690a59cb

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                Biotechnology
                Biotechnology

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