Universal Brain has received U.S. Food and Drug Administration 510(k) clearance for the UB ERP System, a platform designed to acquire, analyze, store, and report electrical brain activity using electroencephalography and event-related potentials. The California-based neurotechnology company said the milestone supports its effort to introduce objective brain-function measurements into psychiatric care and central nervous system research. FDA records show the Class II device was cleared on June 30, 2026, after the agency determined it was substantially equivalent to legally marketed predicate systems.
A Faster Approach to Brain Measurement
The UB ERP System combines a proprietary dry-electrode EEG cap with Neurotique ERP software, enabling clinicians to collect neural signals while patients complete cognitive and emotional tasks. Universal Brain said the process can move from device setup to analyzed results in less than five minutes, potentially reducing the time and operational complexity associated with conventional EEG equipment. The system measures both standard EEG activity and event-related potentials, which capture changes in electrical activity following specific visual stimuli or tasks.
Regulatory Scope and Limitations
Under its cleared indications, the prescription system may be used with adult and adolescent patients in healthcare facilities or clinics under the direction of a healthcare professional. It is intended to assist with the acquisition and interpretation of brain-activity data, but it does not independently diagnose psychiatric or neurological conditions. The FDA documentation states that a clinical expert must interpret the recorded EEG signals and event-related potentials alongside other clinical findings, an important limitation that distinguishes measurement support from an autonomous diagnostic claim.
Evidence Supporting Clearance
The FDA reviewed the device through the traditional 510(k) pathway, using Medeia’s NeuralScan System as the primary predicate and Cumulus Neuroscience’s Functional Neurophysiology Platform as a secondary predicate. Regulatory documents describe seven EEG channels, dry electrodes, blink-detection capabilities, visual tasks, and software that generates reports containing measures such as ERP amplitude and latency. Bench testing, software verification, electrical safety assessments, usability work, and a clinical study supported the application, with the study reporting successful P300 measurement across several tasks and no adverse events.
Clinical Development and Commercial Plans
Universal Brain is now conducting two depression studies intended to expand evidence for the platform’s potential role in monitoring and predicting treatment response. A multicenter U.S. study with Adams Clinical sites in Boston and New York will evaluate brain function before and after first-line antidepressant treatment, while a Japanese study will follow patients for 24 weeks after treatment begins. The company also appointed Ohio State University psychiatry chair K. Luan Phan as chief medical adviser and reported receiving a $2 million grant from the Japan Agency for Medical Research and Development.
Precision Psychiatry Ambitions
Founded in 2022 by physician and chief executive Kazu Okuda, Universal Brain is developing the platform around a broader concept it calls neurotyping, which groups patients according to functional neural measurements rather than symptoms alone. The company ultimately wants to support treatment selection, therapeutic-response monitoring, patient classification, and biomarker development for psychiatric clinical trials, although those broader applications extend beyond the system’s current cleared claims. Universal Brain said it is preparing for a commercial launch later in 2026 while continuing to collect larger datasets across psychiatric interventions.
The FDA clearance gives Universal Brain a regulated foundation for marketing a rapid EEG and ERP measurement system in U.S. clinical settings, but it does not establish the device as a standalone psychiatric diagnostic or treatment-selection tool. Its commercial relevance will depend on whether ongoing studies demonstrate that the measurements can reliably improve clinical decisions, predict treatment outcomes, or strengthen drug-development programs. For psychiatry, where care still depends heavily on reported symptoms and iterative prescribing, the platform represents a notable attempt to make objective neural data more practical in everyday workflows.