Periodic Reporting for period 1 - CROSSBRAIN (Distributed and federated cross-modality actuation through advanced nanomaterials and neuromorphic learning)
Reporting period: 2022-11-01 to 2023-10-31
The CROSSBRAIN project aims to develop a revolutionary neural interface platform consisting of wireless, implantable microbots compatible with Magnetic Resonance Imaging. These microbots sense and modulate electrical activity at cellular and circuit levels, utilizing advanced nanoactuation methods, nano-electronics, and wireless energy harvesting. The platform integrates extreme edge computing, nanomaterials with specific properties, biocompatible coatings, and preventive measures against glial scarring. The microbots, equipped with nanomaterial-coated electrodes, offer various stimulation modalities, including electro-mechano-magneto-thermo-optical principles. They are endovascularly implanted, capable of delivering genetic material, and operate under networked control with wireless power supply. The project aims to achieve closed-loop sensing, prediction, and actuation for personalized neuromodulation, with case studies in Parkinson’s Disease and Epilepsy animal models. The objectives include developing functional polymeric electrode coatings, designing and microfabricating the CROSSBRAIN device platform, creating an AI-based controller, and optimizing and demonstrating the platform through comprehensive testing and validation in animal models.
CROSSBRAIN team is developing essential functional nanomaterials that are like tiny, high-tech blocks. These materials demonstrate responsiveness to mechanical stimulation, such as touch, the ability to release substances upon electrical triggering, and the capacity to generate thermal stimulation as necessary. The groundwork for various innovative applications is being established by the team.
Other efforts are directed towards the device fabrication through the development of CMOS analog frontend circuits, a power management unit, and antennas. Optimization of the antennas is underway to miniaturize the µBots and encouraging results from biocompatibility tests at SISSA suggest the successful integration of the µBots with neuronal cells. This part of the project forms a critical foundation for advancing CROSSBRAIN devices.
Another part of the team is working on the brain signals devising a spiking computational architecture for an efficient brain signal processing. Various chips and circuits are undergoing testing to ensure seamless functionality. The overarching objective is to create a system that is friendly to the hardware it is running on.
Finally, an assessment is being conducted by the team to evaluate the overall synergy of the components. They are checking to see if the devices are safe and effective by studying how they interact with rat brain cells. They are also using 3D virtual histology method to visualize how the devices are distributed in the brain. All of this is essential for making sure the CROSSBRAIN project reaches its goals.
Other efforts are directed towards the device fabrication through the development of CMOS analog frontend circuits, a power management unit, and antennas. Optimization of the antennas is underway to miniaturize the µBots and encouraging results from biocompatibility tests at SISSA suggest the successful integration of the µBots with neuronal cells. This part of the project forms a critical foundation for advancing CROSSBRAIN devices.
Another part of the team is working on the brain signals devising a spiking computational architecture for an efficient brain signal processing. Various chips and circuits are undergoing testing to ensure seamless functionality. The overarching objective is to create a system that is friendly to the hardware it is running on.
Finally, an assessment is being conducted by the team to evaluate the overall synergy of the components. They are checking to see if the devices are safe and effective by studying how they interact with rat brain cells. They are also using 3D virtual histology method to visualize how the devices are distributed in the brain. All of this is essential for making sure the CROSSBRAIN project reaches its goals.
During the first year of the CROSSBRAIN project, a lot of progress was made in creating new materials for neurostimulation. Scientists from different fields like materials, neuroscience, and engineering worked together to make nanomaterials that can be used to stimulate the brain precisely. These materials can turn electrical signals into different types of signals for better control. These achievements match the project's goals of exploring new ways to stimulate the brain.
UNITOV and CSIC worked together to study patterns in brain activity using the recurrent neural network (RNN) topologies. UNITOV created a liquid state machine that is parsimonious in terms of size, which is advantageous for future hardware implementation.
For the implantation of the µBots a groundbreaking strategy was devised, utilizing needle-like shuttles and hydrogels to mitigate tissue damage. This innovation extends beyond µBot implantation, impacting neurobiology, neurology, and cognitive science. The goal of improving this method is to get more consistent and reliable data compared to traditional implantation methods. The special X-ray technology, called synchrotron radiation-based X-ray phase-contrast 3D virtual histology (XPCT), is under testing for studying the effects of µBot implantation. It gives detailed insights into changes in the brain, blood vessels, and structures. XPCT helps understand how µBots interact with the brain, making it easier to figure out the best ways to put them in. This technology allows a thorough study of brain markers without having to do aggressive treatments on slices of brain tissue.
UNITOV and CSIC worked together to study patterns in brain activity using the recurrent neural network (RNN) topologies. UNITOV created a liquid state machine that is parsimonious in terms of size, which is advantageous for future hardware implementation.
For the implantation of the µBots a groundbreaking strategy was devised, utilizing needle-like shuttles and hydrogels to mitigate tissue damage. This innovation extends beyond µBot implantation, impacting neurobiology, neurology, and cognitive science. The goal of improving this method is to get more consistent and reliable data compared to traditional implantation methods. The special X-ray technology, called synchrotron radiation-based X-ray phase-contrast 3D virtual histology (XPCT), is under testing for studying the effects of µBot implantation. It gives detailed insights into changes in the brain, blood vessels, and structures. XPCT helps understand how µBots interact with the brain, making it easier to figure out the best ways to put them in. This technology allows a thorough study of brain markers without having to do aggressive treatments on slices of brain tissue.