This $330,000 Project Grant awarded by the National Science Foundation (NSF) Engineering program (CFDA 47.041) to Yale University will develop an implantable neural interface platform that integrates three key innovations: 1) optimized resistive RAM memory for efficient data storage, 2) programmable analog front-end circuits for high-density neural signal acquisition, and 3) specialized processors for energy-efficient computation of neural network operations. The goal is to create a powerful...
This $319,999 Project Grant from the National Science Foundation (NSF) Engineering program (CFDA 47.041) will support the development of an advanced implantable neural interface platform called "NEUROFLEX" at the University of Notre Dame. The project aims to integrate three key innovations: 1) optimized resistive RAM memory for efficient data storage, 2) programmable analog front-end circuits for high-density neural signal acquisition, and 3) specialized processors for...
This Project Grant award from the National Science Foundation's (NSF) Engineering program provides $150,000 to Baylor University to conduct collaborative research on large-scale wireless RF networks of microchip sensors. The key objectives are to: 1) build a microsensor system and demonstrate low-error rate and efficient asynchronous, encoded wireless transmission in the laboratory using fabricated microchips, and 2) decode signals from a hypothetical brain implant composed of up to 8,000...
This NSF Engineering program Project Grant award to Brown University, totaling $383,560, will support the development of a large-scale wireless network of microchip sensors for monitoring physiological signals and brain activity. The overarching goal is to create an "all-in-one" approach to build a wireless network of thousands of sub-millimeter size sensors that can efficiently transmit and decode sparse event-driven signals, taking inspiration from the brain's neural activity. The...
This $600,000 Project Grant from the National Science Foundation's Division of Information and Intelligent Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), will fund research at The Pennsylvania State University to develop a fully wireless, flexible electrical-acoustic implant for high-resolution neural stimulation and recording across large-scale brain circuits. The implant is intended to provide minimally invasive ultrasound neuromodulation and...
This $337,422 Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) aims to develop a novel "neuron-to-neuron interface" that can transmit signals between individual neurons in the brains of two zebrafish larvae. The researchers at the University of Illinois seek to create a system that allows synchronized behavioral outputs in both a "sender" and "receiver" fish by transmitting neural signals optically between their...
This National Science Foundation (NSF) Engineering program (CFDA 47.041) Project Grant award of $599,918 to the Massachusetts Institute of Technology (MIT) aims to develop a novel bioelectronic brain implant that can autonomously implant itself without the need for invasive surgery. The proposed technology would enable high-resolution brain stimulation and neural activity control, with the potential to revolutionize medical interventions for neurological disorders and enable new neuroscience...
This National Science Foundation (NSF) Engineering Program (CFDA 47.041) Project Grant award of $100,001 to the University of Wisconsin System provides funding for research on highly sensitive magnetoelectric nanostructures for neural recording and stimulation. The project aims to develop injectable nanoscale agents that can enable minimally invasive direct access to the brain at the cellular scale, transforming the way brain signals are acquired and advancing neuroscience and neurology. Key...
This $129,226 Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) supports the development of soft, biocompatible ion-based transistors for responsive neuroelectronic devices. The project aims to create integrated circuits using these ion-gated transistors to enable efficient interaction with neural circuits, with the goal of transforming the design of bioelectronic devices for enhanced diagnosis and therapy of neuropsychiatric diseases. The...
This $1,550,000 federal Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) will fund the development of a novel "neuron-soft brain organoid-computer interface" system for advanced computational tasks. The key products and services to be delivered under this 4-year grant include:
(1) Developing soft, high-density bioelectronic interfaces to seamlessly integrate with 3D brain organoids for long-term neural recording and stimulation.
(2)...
This $432,452 Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) aims to advance the theoretical and engineering foundations of wireless neural interfaces. The key products and services to be delivered under this 5-year grant, which runs from May 1, 2025 to April 30, 2030, include:
Developing a novel architecture for wireless power transmission to miniaturized neural implants using programmable near-field electromagnetic fields and multiple focused power beams to increase power without increasing thermal absorption in biological tissues.
Scaling communication bandwidth through antenna-circuit co-design and high-order modulation schemes to enable real-time data transmission with minimal latency under power and form-factor constraints.
Creating a large-scale neural electrode array and high-count readout circuitry with a novel readout/routing-sharing architecture to reduce the number of amplifiers and interconnects required for high-channel-count neural recording interfaces at ultra-fine scales.
This cross-disciplinary research project, awarded to New York University, seeks to establish the foundation for the next generation of neurotechnology by addressing key challenges in powering, communication, and data acquisition for brain-machine interface systems.