Closed-loop neurostimulation for the treatment of psychiatric disorders.
Kristin K SellersJoshua L CohenAnkit N KhambhatiJoline M FanA Moses LeeEdward F ChangAndrew D KrystalPublished in: Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology (2023)
Despite increasing prevalence and huge personal and societal burden, psychiatric diseases still lack treatments which can control symptoms for a large fraction of patients. Increasing insight into the neurobiology underlying these diseases has demonstrated wide-ranging aberrant activity and functioning in multiple brain circuits and networks. Together with varied presentation and symptoms, this makes one-size-fits-all treatment a challenge. There has been a resurgence of interest in the use of neurostimulation as a treatment for psychiatric diseases. Initial studies using continuous open-loop stimulation, in which clinicians adjusted stimulation parameters during patient visits, showed promise but also mixed results. Given the periodic nature and fluctuations of symptoms often observed in psychiatric illnesses, the use of device-driven closed-loop stimulation may provide more effective therapy. The use of a biomarker, which is correlated with specific symptoms, to deliver stimulation only during symptomatic periods allows for the personalized therapy needed for such heterogeneous disorders. Here, we provide the reader with background motivating the use of closed-loop neurostimulation for the treatment of psychiatric disorders. We review foundational studies of open- and closed-loop neurostimulation for neuropsychiatric indications, focusing on deep brain stimulation, and discuss key considerations when designing and implementing closed-loop neurostimulation.
Keyphrases
- mental health
- case report
- palliative care
- minimally invasive
- sleep quality
- chronic kidney disease
- end stage renal disease
- ejection fraction
- parkinson disease
- physical activity
- replacement therapy
- mesenchymal stem cells
- depressive symptoms
- bone marrow
- transcription factor
- big data
- prognostic factors
- deep learning
- blood brain barrier