EPFL develops implantable LogSync chip for brain-network decoding
EPFL researchers developed LogSync, a low-power implantable neural system-on-chip that records brain activity and extracts biomarkers describing oscillation strength and synchrony across brain regions. A machine-learning algorithm uses these network-level signals to distinguish cognitive and emotional states and generate stimulation triggers. The researchers evaluated the system with human brain recordings from earlier psychiatric experiments and rat experiments at the University of Minnesota; the report does not describe a clinical trial involving implanted LogSync devices in humans. The chip measures approximately 4×2 mm, and Shoaran said its co-designed hardware and algorithms kept power consumption under 200 microwatts. The work was published in the IEEE Journal of Solid-State Circuits.
The report says many existing closed-loop deep brain stimulation systems rely on signals from a single brain region, while clinically relevant information for psychiatric disorders may be distributed across interacting networks. LogSync extends the lab’s prior work to network-level biomarkers and adaptive decoding, while its validation remains preclinical.
EPFL researchers have developed an implantable neural chip that tracks communication across brain regions, identifying cognitive and emotional states in real time.
Deep brain stimulation (DBS) is a therapeutic technique that delivers electrical pulses to specific areas of the brain via an implant to modulate neural activity. It is already widely used for movement disorders such as Parkinson’s disease, and researchers are increasingly exploring its potential for severe psychiatric illnesses including major depression, post-traumatic stress disorder, and obsessive-compulsive disorder.
However, most existing DBS systems operate in what engineers call an “open loop” manner: stimulation is delivered according to predefined settings rather than continuously adapting to the patient’s brain activity. Even among closed-loop, or adaptive systems, many rely on signals recorded from a single brain region. This is a major limitation for psychiatric disorders, where clinically relevant information may be distributed across networks of interacting brain regions.
“Our work is based on the growing body of research suggesting that psychiatric disorders arise more from disruptions in communication between brain regions than from dysfunction of any single region,” explains Mahsa Shoaran, head of the Integrated Neurotechnologies Lab in EPFL’s School of Engineering and Neuro-X Institute.
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