HCC: advancing non-invasive brain sensing methods to improve passive brain-computer interfaces

The National Science Foundation Division of Computing and Communication Foundations awarded $700,000 to Trustees of Tufts College on October 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to advance non-invasive brain-computer interfaces using functional near-infrared spectroscopy.

The project develops improved hardware, software, and mathematical techniques to distinguish between task-positive and default-mode networks in the prefrontal cortex—regions associated with logical problem-solving and mind wandering, respectively. Current fNIRS-based brain-computer interfaces lack the measurement specificity needed to target deeper cortical regions reliably. The award funds personalized dual-slope frequency-domain near-infrared spectroscopy, which captures both intensity and phase information from modulated light to enable depth-sensitive measurements. By individualizing configurations to each person's anatomy, the method achieves higher spatial specificity while maintaining practical advantages for wearable devices. The project also develops user interfaces that monitor and respond to a user's brain state in real-time, subtly adjusting interface elements or tasks when the system detects changes in mental workload or its specific components, improving performance without distraction.

Work is performed in Medford, Massachusetts. The period of performance runs from October 1, 2026, through September 30, 2029. The assistance type is a Project Grant.

Abstract

This project seeks to advance brain-computer interfaces (bcis) by creating new brain measurement techniques and developing user interfaces that monitor and respond to a user?s brain state in real-time. For example, when a system detects changes in overall mental workload or in specific components of workload, the user interface will respond by subtly changing the interface itself or the tasks presented to the user in ways that improve performance without distracting the user. The project uses passive, non-invasive optical measurements via functional near-infrared spectroscopy (fnirs), which is a technology that shows promise for developing low cost, easy to use devices in the future. By advancing wearable technology with precision brain measurement and feedback capability, the project will enable future more responsive, accessible BCI devices while spurring further advances in neuroscience. While previous BCI work has focused on overall mental workload as its main measurement, this project will develop improved hardware, software, and mathematical techniques that will be able to distinguish more specifically between the two key networks in the prefrontal cortex, the task-positive and default-mode networks that are associated with logical problem-solving and mind wandering, respectively. Current fnirs-based bcis lack the necessary measurement specificity to target deeper cortical regions and distinguish these regions reliably. The project addresses this limitation through personalized dual-slope frequency-domain near-infrared spectroscopy. Unlike continuous-wave spectroscopy, this technique captures both intensity and phase information from modulated light, enabling depth-sensitive measurements. By individualizing dual-slope configurations to each person's anatomy, the method will achieve higher spatial specificity while maintaining the practical advantages and convenience of fnirs. This will enable bcis to access previously underutilized brain regions for improved adaptive interfaces. Overall, the project seeks to transform the field of implicit or passive brain-computer interfaces by introducing practical, low-cost brain measurement techniques and leveraging them to create and evaluate new kinds of user interfaces. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.- subawards are not planned for this award.