By Jeremy Gungabeesoon | 6 November 2019
Brain-machine interfaces (BMIs) are devices that translate brain signals into information that can be used for various purposes. Much of the research with BMIs thus far has focused on using this information to control external devices, such as robotic limbs, that can restore lost motor function in paralyzed patients. Scientists are beginning to design BMIs that translate brain signals into emotion and mood states.
A group of scientists led by Maryam Shanechi, at University of Southern California, are interested in neuropsychiatric disorders such as depression and anxiety. One of their goals is to use machine learning to understand the brain signals that are associated with specific mood states. In one of their recent studies, electrodes were implanted directly onto the surface of the brain of patients, and brain activity was recorded over multiple days. Patients’ mood states were assessed using a self-report questionnaire that the researchers termed Immediate Mood Scaler (IMS). Shanechi and her colleagues then designed a computer algorithm that could predict IMS scores based on recorded brain activity. In this way, BMIs may be able to help us understand the neural mechanisms of how emotions arise, change, and dissipate.
Electrical stimulation could be used to regulate aberrant brain signal and restore emotional function in patients with treatment-resistant neuropsychiatric disorders. In theory, these devices would constantly monitor a patient’s brain activity and automatically apply stimulation to treat abnormal mood states. Such an invasive approach brings up concerns of safety, privacy, and identity. Altering our emotions would lead to a change in the way we perceive and experience the world, which poses the question of how much control we truly have over our thoughts and actions. With the potential emergence of these devices, extensive discussion of these ethical considerations will be of utmost importance.
My Perspective Article is out in @NatureNeuro discussing brain-machine interfaces and providing a perspective on how to extend them to help treat neuropsychiatric disorders through mood state decoding and neural dynamic modeling https://t.co/LjfOmxw7tX@NatureBiotech @USCViterbi
— Maryam Shanechi (@MaryamShanechi) September 24, 2019
News Article: Maryam Shanechi designs machines to read minds. ScienceNews
Original Article: Brain–machine interfaces from motor to mood. Nature Neuroscience
The State of Brain-Machine Interfaces – Prof. Maryam Shanechi
Bin He: Brain Computer Interface: Sending Neurological Signals to an External Device
Will brain-computer interfaces transform human lives? | Inside Story
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