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      Adaptive deep brain stimulation for Parkinson’s disease using motor cortex sensing

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          Abstract

          <div class="section"> <a class="named-anchor" id="S1"> <!-- named anchor --> </a> <h5 class="section-title" id="d7744719e214">Objective</h5> <p id="P1">Contemporary deep brain stimulation for Parkinson’s disease is delivered continuously, and adjustments based on patient’s changing symptoms must be made manually by a trained clinician. Patients may be subjected to energy intensive settings at times when they are not needed, possibly resulting in stimulation-induced adverse effects, such as dyskinesia. One solution is “adaptive” DBS, in which stimulation is modified in real time based on neural signals that co-vary with the severity of motor signs or of stimulation-induced adverse effects. </p> <p id="P2">Here we show the feasibility of adaptive DBS using a fully implanted neural prosthesis.</p> </div><div class="section"> <a class="named-anchor" id="S2"> <!-- named anchor --> </a> <h5 class="section-title" id="d7744719e221">Approach</h5> <p id="P3">We demonstrate adaptive deep brain stimulation in two patients with Parkinson’s disease using a fully implanted neural prosthesis that is enabled to utilize brain sensing to control stimulation amplitude (Activa PC+S). We used a cortical narrowband gamma (60-90 Hz) oscillation related to dyskinesia to decrease stimulation voltage when gamma oscillatory activity is high (indicating dyskinesia) and increase stimulation voltage when it is low. </p> </div><div class="section"> <a class="named-anchor" id="S3"> <!-- named anchor --> </a> <h5 class="section-title" id="d7744719e226">Main Results</h5> <p id="P4">We demonstrate the feasibility of “adaptive deep brain stimulation” in two patients with Parkinson’s disease. In short term in-clinic testing, energy savings were substantial (38-45%), and therapeutic efficacy was maintained. </p> </div><div class="section"> <a class="named-anchor" id="S4"> <!-- named anchor --> </a> <h5 class="section-title" id="d7744719e231">Significance</h5> <p id="P5">This is the first demonstration of adaptive DBS in Parkinson’s disease using a fully implanted device and neural sensing. Our approach is distinct from other strategies utilizing basal ganglia signals for feedback control. </p> </div>

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          Most cited references15

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          Functional mapping of human sensorimotor cortex with electrocorticographic spectral analysis. II. Event-related synchronization in the gamma band.

          N Crone (1998)
          It has been shown in animals that neuronal activity in the 'gamma band' (>30 Hz) is associated with cortical activation and may play a role in multi-regional and multi-modal integration of cortical processing. Studies of gamma activity in human scalp EEG have typically focused on event-related synchronization (ERS) in the 40 Hz band. To assess further the gamma band ERS further, as an index of cortical activation and as a tool for human functional brain mapping, we recorded subdural electrocorticographic (ECoG) signals in five clinical subjects while they performed visual-motor decision tasks designed to activate the representations of different body parts in sensorimotor cortex. ECoG spectral analysis utilized a mixed-effects analysis of variance model in which within-trial temporal dependencies were accounted for. Taking an exploratory approach, we studied gamma ERS in 10-Hz-wide bands (overlapping by 5 Hz) ranging from 30 to 100 Hz, and compared these findings with changes in the alpha (8-13 Hz) and beta (15-25 Hz) bands. Gamma ERS (observed in three out of subjects) occurred in two broad bands-'low gamma' included the 35-45 and 40-50 Hz bands, and 'high gamma' the 75-85, 80-90, 85-95 and 90-100 Hz bands. The temporal and spatial characteristics of low and high gamma ERS were distinct, suggesting relatively independent neurophysiological mechanisms. Low gamma ERS often began after onset of the motor response and was sustained through much of it, in parallel with event-related desynchronization (ERD) in the alpha band. High gamma ERS often began during, or slightly before, the motor response and was transient, ending well before completion of the motor response. These temporal differences in low and high gamma suggest different functional associations with motor performance. Compared with alpha and beta ERD, the topographical patterns of low and high gamma ERS were more discrete and somatotopically specific and only occurred over contralateral sensorimotor cortex during unilateral limb movements (alpha and beta ERD were also observed ipsilaterally). Maps of sensorimotor function inferred from gamma ERS were consistent with maps generated by cortical electrical stimulation for clinical purposes. In addition, different task conditions in one subject produced consistent differences in both motor response latencies and onset latency of gamma ERS, particularly high gamma ERS. Compared with alpha and beta ERD, the topography of gamma ERS is more consistent with traditional maps of sensorimotor functional anatomy. In addition, gamma ERS may provide complementary information about cortical neurophysiology that is useful for mapping brain function in humans.
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            Spectral changes in cortical surface potentials during motor movement.

            In the first large study of its kind, we quantified changes in electrocorticographic signals associated with motor movement across 22 subjects with subdural electrode arrays placed for identification of seizure foci. Patients underwent a 5-7 d monitoring period with array placement, before seizure focus resection, and during this time they participated in the study. An interval-based motor-repetition task produced consistent and quantifiable spectral shifts that were mapped on a Talairach-standardized template cortex. Maps were created independently for a high-frequency band (HFB) (76-100 Hz) and a low-frequency band (LFB) (8-32 Hz) for several different movement modalities in each subject. The power in relevant electrodes consistently decreased in the LFB with movement, whereas the power in the HFB consistently increased. In addition, the HFB changes were more focal than the LFB changes. Sites of power changes corresponded to stereotactic locations in sensorimotor cortex and to the results of individual clinical electrical cortical mapping. Sensorimotor representation was found to be somatotopic, localized in stereotactic space to rolandic cortex, and typically followed the classic homunculus with limited extrarolandic representation.
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              Gamma Oscillations in the Hyperkinetic State Detected with Chronic Human Brain Recordings in Parkinson's Disease.

              Hyperkinetic states are common in human movement disorders, but their neural basis remains uncertain. One such condition is dyskinesia, a serious adverse effect of medical and surgical treatment for Parkinson's disease (PD). To study this, we used a novel, totally implanted, bidirectional neural interface to obtain multisite long-term recordings. We focus our analysis on two patients with PD who experienced frequent dyskinesia and studied them both at rest and during voluntary movement. We show that dyskinesia is associated with a narrowband gamma oscillation in motor cortex between 60 and 90 Hz, a similar, though weaker, oscillation in subthalamic nucleus, and strong phase coherence between the two. Dyskinesia-related oscillations are minimally affected by voluntary movement. When dyskinesia persists during therapeutic deep brain stimulation (DBS), the peak frequency of this signal shifts to half the stimulation frequency. These findings suggest a circuit-level mechanism for the generation of dyskinesia as well as a promising control signal for closed-loop DBS.
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                Author and article information

                Journal
                Journal of Neural Engineering
                J. Neural Eng.
                IOP Publishing
                1741-2560
                1741-2552
                August 01 2018
                August 01 2018
                May 09 2018
                : 15
                : 4
                : 046006
                Article
                10.1088/1741-2552/aabc9b
                6021210
                29741160
                2629001e-30ad-44e9-9938-b4c2feaeb4eb
                © 2018

                http://iopscience.iop.org/info/page/text-and-data-mining

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