title: Affective Brain-Computer Interfaces As Enabling Technology for Responsive Psychiatric Stimulation.
abstract: There is a pressing clinical need for responsive neurostimulators, which sense a patient's brain activity and deliver targeted electrical stimulation to suppress unwanted symptoms. This is particularly true in psychiatric illness, where symptoms can fluctuate throughout the day. Affective BCIs, which decode emotional experience from neural activity, are a candidate control signal for responsive stimulators targeting the limbic circuit. Present affective decoders, however, cannot yet distinguish pathologic from healthy emotional extremes. Indiscriminate stimulus delivery would reduce quality of life and may be actively harmful. We argue that the key to overcoming this limitation is to specifically decode volition, in particular the patient's intention to experience emotional regulation. Those emotion-regulation signals already exist in prefrontal cortex (PFC), and could be extracted with relatively simple BCI algorithms. We describe preliminary data from an animal model of PFC-controlled limbic brain stimulation and discuss next steps for pre-clinical testing and possible translation.
authors.affiliation: Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, USA, and Harvard Medical School, Boston, MA, USA ; Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA.
authors.forename: Alik S
authors.initials: AS
authors.lastname: Widge
authors.affiliation: Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, USA, and Harvard Medical School, Boston, MA, USA.
authors.forename: Darin D
authors.initials: DD
authors.lastname: Dougherty
authors.affiliation: Departments of Rehabilitation Medicine and Physiology & Biophysics, Graduate Program in Neuroscience, and the Center for Sensorimotor Neural Engineering, University of Washington, Seattle, WA, USA.
authors.forename: Chet T
authors.initials: CT
authors.lastname: Moritz
keywords: affect decoding; deep brain stimulation; hybrid BCI; invasive BCI; mental disorders; prefrontal cortex