EPFL's LogSync Chip Reads Brain Network Activity on Under 200 Microwatts

Why single-region sensing falls short

Deep brain stimulation (DBS) delivers electrical pulses to specific brain areas through an implant to modulate neural activity. It is already widely used for movement disorders such as Parkinson's disease, and researchers are increasingly exploring it for severe psychiatric illnesses including major depression, post-traumatic stress disorder, and obsessive-compulsive disorder.

Most existing DBS systems work in an "open loop" manner, according to EPFL: stimulation follows predefined settings instead of adapting continuously to the patient's brain activity. Even among closed-loop, or adaptive, systems, many rely on signals from a single brain region. That is a major limitation for psychiatric disorders, where clinically relevant information may be spread across networks of interacting 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.

How LogSync works

Shoaran and her team built a low-power, implantable neural system-on-chip. LogSync records brain activity and extracts biomarkers that describe the strength of brain waves (oscillations) and the synchrony between signals from different brain regions. A machine-learning algorithm then analyzes these network-level biomarkers to distinguish cognitive and emotional states, and generates stimulation triggers when specific states are detected.

The chip measures approximately 4x2 mm. Another innovation is its use of logarithmic computations, which simplify the complex operations needed for brain-network analysis and real-time biomarker extraction and decoding.

The work was published in the IEEE Journal of Solid-State Circuits. It was developed as part of a CHF 6.6 million grant from the US National Institute of Mental Health (NIMH) to build implantable systems that can measure and control oscillatory brain networks for severe psychiatric illnesses, particularly mood and anxiety disorders. It builds on the lab's earlier work on brain-to-text decoding and closed-loop neuromodulation.

Testing in human recordings and rats

The researchers evaluated LogSync using human brain recordings from previous psychiatric experiments. One dataset captured changes in cognitive engagement during a mental task, while another captured emotional arousal as participants watched video clips. The algorithm distinguished these cognitive and emotional states from the neural recordings alone.

In further experiments in rats at the University of Minnesota, the implant tracked ongoing oscillations and generated stimulation triggers at predefined phases of brain activity.

Shoaran says the main challenge was delivering this functionality within the very limited power budget of an implant. "Our entire system is co-designed, meaning the algorithms and hardware are developed together with the constraints of implant in mind," she says. According to her, this allowed network-level signal processing and decoding on a single chip while keeping power consumption under 200 microwatts.

Wider uses and next steps

Initial validation focused on psychiatric applications, but EPFL says the ability to extract brain-network biomarkers and trigger precisely timed stimulation applies more broadly to next-generation neurotechnology. It names adaptive DBS for movement disorders, closed-loop non-invasive stimulation, and emerging focused-ultrasound interfaces.

In parallel, the lab is developing machine-learning methods that learn directly from neural recordings rather than from predefined biomarkers. Its ICML 2026 work uses self-supervised learning to capture neural activity across regions, channels, and time. EPFL says this supports efforts to bring intelligent neural interfaces closer to clinical use, including through Infera Neuro, an EPFL spin-off co-founded by Shoaran.

For now, the evidence comes from earlier human recordings and rat experiments. The source does not describe tests of LogSync in patients, so its clinical role in future psychiatric therapies remains a goal rather than a demonstrated result.