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- W3158416796 abstract "Abstract 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 brain stimulation (DBS) are now available. Brain signal decoding can extend the clinical utility of adaptive DBS but the impact of neural source, computational methods and PD pathophysiology on decoding performance are unknown. This represents an unmet need for the development of future neurotechnology. To address this, we developed an invasive brain-signal decoding approach based on intraoperative sensorimotor electrocorticography (ECoG) and subthalamic LFP to predict grip-force, a representative movement decoding application, in 11 PD patients undergoing DBS. We demonstrate that ECoG is superior to subthalamic LFP for accurate grip-force decoding. Gradient boosted decision trees (XGBOOST) outperformed other model architectures. ECoG based decoding performance negatively correlated with motor impairment, which could be attributed to subthalamic beta bursts in the motor preparation and movement period. This highlights the impact of PD pathophysiology on the neural capacity to encode movement kinematics. Finally, we developed a connectomic analysis that could predict grip-force decoding performance of individual ECoG channels across patients by using their connectomic fingerprints. Our study provides a neurophysiological and computational framework for invasive brain signal decoding to aid the development of an individualized precision-medicine approach to intelligent adaptive DBS. Significance Statement Neurotechnology will revolutionize the treatment of neurological and psychiatric patients, promising novel treatment avenues for previously intractable brain disorders. However, optimal surgical and computational approaches and their interactions with neurological disorders are unknown. How can recent advances in machine learning and connectomics aid the precision and performance of invasive brain signal decoding strategies? Do the brain disorders treated with such approaches have impact on decoding performance? We propose a real time compatible advanced machine learning pipeline for invasively recorded brain signals in Parkinson’s disease (PD) patients. We report optimal movement decoding strategies with respect to signal source, model architecture and connectomic fingerprint and demonstrate that PD pathophysiology significantly and negatively impacts movement decoding. Our study has broad impacts for the development of smart brain implants for the treatment of PD and other brain disorders." @default.
- W3158416796 created "2021-05-10" @default.
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- W3158416796 date "2021-04-26" @default.
- W3158416796 modified "2023-10-03" @default.
- W3158416796 title "Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson’s disease" @default.
- W3158416796 cites W1498617277 @default.
- W3158416796 cites W1631356348 @default.
- W3158416796 cites W1845781534 @default.
- W3158416796 cites W1967428268 @default.
- W3158416796 cites W1985244573 @default.
- W3158416796 cites W1993407225 @default.
- W3158416796 cites W2011402106 @default.
- W3158416796 cites W2012539045 @default.
- W3158416796 cites W2031170841 @default.
- W3158416796 cites W2032033817 @default.
- W3158416796 cites W2045695716 @default.
- W3158416796 cites W2051572005 @default.
- W3158416796 cites W2076118331 @default.
- W3158416796 cites W2122825543 @default.
- W3158416796 cites W2135825876 @default.
- W3158416796 cites W2141489608 @default.
- W3158416796 cites W2143079975 @default.
- W3158416796 cites W2143685192 @default.
- W3158416796 cites W2151721316 @default.
- W3158416796 cites W2160420173 @default.
- W3158416796 cites W2161472384 @default.
- W3158416796 cites W2161971256 @default.
- W3158416796 cites W2169918686 @default.
- W3158416796 cites W2170232560 @default.
- W3158416796 cites W2344275832 @default.
- W3158416796 cites W2346108182 @default.
- W3158416796 cites W2465311863 @default.
- W3158416796 cites W2515990420 @default.
- W3158416796 cites W2549947442 @default.
- W3158416796 cites W2568766977 @default.
- W3158416796 cites W2583340629 @default.
- W3158416796 cites W2599888381 @default.
- W3158416796 cites W2605334700 @default.
- W3158416796 cites W2606088148 @default.
- W3158416796 cites W2622109244 @default.
- W3158416796 cites W2744169335 @default.
- W3158416796 cites W2770037632 @default.
- W3158416796 cites W2773979760 @default.
- W3158416796 cites W2785323625 @default.
- W3158416796 cites W2786806281 @default.
- W3158416796 cites W2786828489 @default.
- W3158416796 cites W2802450380 @default.
- W3158416796 cites W2807007138 @default.
- W3158416796 cites W2886879362 @default.
- W3158416796 cites W2890134246 @default.
- W3158416796 cites W2892087626 @default.
- W3158416796 cites W2907666668 @default.
- W3158416796 cites W2911097730 @default.
- W3158416796 cites W2911964244 @default.
- W3158416796 cites W2917762754 @default.
- W3158416796 cites W2921964841 @default.
- W3158416796 cites W2944572454 @default.
- W3158416796 cites W2950023299 @default.
- W3158416796 cites W2953279379 @default.
- W3158416796 cites W2954654581 @default.
- W3158416796 cites W2962925453 @default.
- W3158416796 cites W2964618399 @default.
- W3158416796 cites W2977375428 @default.
- W3158416796 cites W2996586346 @default.
- W3158416796 cites W3003435483 @default.
- W3158416796 cites W3004922521 @default.
- W3158416796 cites W3011188171 @default.
- W3158416796 cites W3039120974 @default.
- W3158416796 cites W3040235203 @default.
- W3158416796 cites W3042297668 @default.
- W3158416796 cites W3088686112 @default.
- W3158416796 cites W3089174453 @default.
- W3158416796 cites W3102476541 @default.
- W3158416796 cites W3107060429 @default.
- W3158416796 cites W3108898910 @default.
- W3158416796 cites W3109617942 @default.
- W3158416796 cites W3111484088 @default.
- W3158416796 cites W3120583211 @default.
- W3158416796 cites W3127678637 @default.
- W3158416796 cites W3133718980 @default.
- W3158416796 cites W3134860290 @default.
- W3158416796 cites W3154587456 @default.
- W3158416796 cites W3158340479 @default.
- W3158416796 cites W3214055161 @default.
- W3158416796 cites W4207039587 @default.
- W3158416796 cites W4210458691 @default.
- W3158416796 cites W4213329788 @default.
- W3158416796 cites W4225337513 @default.
- W3158416796 cites W4294214781 @default.
- W3158416796 doi "https://doi.org/10.1101/2021.04.24.441207" @default.