Neural chip decodes interactions between brain regions

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.The INL team at EPFL's Geneva campus. From left: Amitabh Yadav, Jieun Joo, Mahsa Shoaran, Jinhan Liu, and Daney Alex. 2026 EPFL / Lundi13 - CC-BY-SA 4.0Shoaran and her team have developed a low-power, implantable neural system-on-chip. Dubbed LogSync, it records brain activity and extracts biomarkers that describe the strength of brain waves (oscillations) and synchrony between signals from different brain regions. A machine-learning algorithm then analyzes these network-level biomarkers to distinguish cognitive and emotional states, and generate stimulation triggers when specific states are detected.The work, published in the IEEE Journal of Solid-State Circuits, was developed as part of a CHF 6.6 million grant from the US National Institute for Mental health (NIMH) to develop implantable systems capable of measuring and controlling oscillatory brain networks for severe psychiatric illnesses, particularly mood and anxiety disorders. It builds on the lab's previous work on brain-to-text decoding and closed-loop neuromodulation, extending these concepts to network-level biomarkers and adaptive …