Patient specific intracranial neural signatures of obsessions and compulsions in the ventral striatum.
Egill Axfjord FridgeirssonMelisse N BaisNadine EijskerRajat M ThomasDirk J A SmitIsidoor O BergfeldP Richard SchuurmanPepijn van den MunckhofPelle de KoningNienke VulinkMartijn FigeeAli MazaheriGuido A van WingenDamiaan DenysPublished in: Journal of neural engineering (2023)
Objective . Deep brain stimulation is a treatment option for patients with refractory obsessive-compulsive disorder. A new generation of stimulators hold promise for closed loop stimulation, with adaptive stimulation in response to biologic signals. Here we aimed to discover a suitable biomarker in the ventral striatum in patients with obsessive compulsive disorder using local field potentials. Approach. We induced obsessions and compulsions in 11 patients undergoing deep brain stimulation treatment using a symptom provocation task. Then we trained machine learning models to predict symptoms using the recorded intracranial signal from the deep brain stimulation electrodes. Main results. Average areas under the receiver operating characteristics curve were 62.1% for obsessions and 78.2% for compulsions for patient specific models. For obsessions it reached over 85% in one patient, whereas performance was near chance level when the model was trained across patients. Optimal performances for obsessions and compulsions was obtained at different recording sites. Significance . The results from this study suggest that closed loop stimulation may be a viable option for obsessive-compulsive disorder, but that intracranial biomarkers are patient and not disorder specific. Clinical Trial: Netherlands trial registry NL7486.
Keyphrases
- deep brain stimulation
- obsessive compulsive disorder
- parkinson disease
- clinical trial
- machine learning
- patients undergoing
- end stage renal disease
- chronic kidney disease
- case report
- newly diagnosed
- study protocol
- rheumatoid arthritis
- ejection fraction
- optic nerve
- phase iii
- resistance training
- prognostic factors
- open label
- patient reported
- big data
- artificial intelligence
- high glucose
- spinal cord injury
- combination therapy
- drug induced
- diabetic rats
- peritoneal dialysis
- stress induced
- electron transfer
- high intensity