2014
DOI: 10.1080/2326263x.2014.912885
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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… Show more

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Cited by 48 publications
(23 citation statements)
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“…By extensive recording of neural activity in distinct cell-types in the rodent hippocampus, researchers have also begun to decode neural activity to predict behavior . This logic has been applied in humans to develop "affective brain-computer interfaces" that decode and rectify aberrant patterns of neuronal activity to disrupt pathological behavior (Widge et al, 2014;Grosenick et al, 2015). Deep brain stimulation is already in use for multiple indications including treatment refractory depression (Holtzheimer and Mayberg, 2011) and has proven effective in combination with exposure therapy to improve fear extinction learning (Marin et al, 2014).…”
Section: Decoding Neural Activity To Modify Behaviormentioning
confidence: 99%
“…By extensive recording of neural activity in distinct cell-types in the rodent hippocampus, researchers have also begun to decode neural activity to predict behavior . This logic has been applied in humans to develop "affective brain-computer interfaces" that decode and rectify aberrant patterns of neuronal activity to disrupt pathological behavior (Widge et al, 2014;Grosenick et al, 2015). Deep brain stimulation is already in use for multiple indications including treatment refractory depression (Holtzheimer and Mayberg, 2011) and has proven effective in combination with exposure therapy to improve fear extinction learning (Marin et al, 2014).…”
Section: Decoding Neural Activity To Modify Behaviormentioning
confidence: 99%
“…EEG-based emotion recognition might serve as a form of communication for the disabled (Kashihara, 2014). Alternatively it could be used to develop a human-like human-computer interface (Liu et al, 2014), to control neural stimulation (Widge et al, 2014) or for neuromarketing (Kong et al, 2013). Each of these potential applications poses unique requirements for research and require a fairly high rate of emotion identification to be successful.…”
Section: Discussionmentioning
confidence: 99%
“…This is particularly attractive because it does not require external connections, which may minimize surgical complications or infective risk. It has been theorized that closed-loop DBS might be used to target neuroplasticity, where a relatively short course of treatment could normalize brain circuits by strengthening or weakening target synapses (Widge, Dougherty, & Moritz, 2014). Wireless stimulators would be an excellent option for such treatments, since patients could come to the office for brief treatment courses and otherwise avoid the complications of batteries and wires.…”
Section: Next-generation Technologies Under Developmentmentioning
confidence: 99%
“…It is not yet clear how a pathological state can be differentiated from a healthy state. Progress has been made in “affective decoding” to generally classify emotions, but there are reasons to believe that this healthy-volunteer research will not work well in clinical populations (Widge et al, 2014). Furthermore, psychiatric diagnoses are highly heterogeneous and likely contain multiple neurological entities.…”
Section: Ongoing Challenges and Limitations Of Closed-loop Approachesmentioning
confidence: 99%
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