Replication Data for: Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson’s disease
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset contains the data required for replication of the results published in the paper titled 'Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson’s disease'. The abstract for the paper is below: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 intraop' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Basal Ganglia","Deep brain stimulation (DBS)","Machine learning","Neuromodulation","Parkinson’s disease"]} <|eot_id|>
 Here is the Description of a dataset. Description:'This dataset contains the data required for replication of the results published in the paper titled 'Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson’s disease'. The abstract for the paper is below: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 intraop' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
This dataset contains the data required for replication of the results published in the paper titled 'Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson’s disease'. The abstract for the paper is below: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 intraop
Basal Ganglia; Deep brain stimulation (DBS); Machine learning; Neuromodulation; Parkinson’s disease