With the increase of people suffering from various neural disorders, the need for brain-computer interfaces (BCIs) to regain sensory-motor or cognitive functions are expected to become acute in the coming decades. However, the existing BCIs can only control simple motions, e.g., grasping, and are far from realizing our vision to help paralyzed patients to walk again. This is due to the lack of a high-bandwidth wireless BCI, capable of supporting the recording from a large number of neurons with high spatial and temporal resolution, while having large spatial coverage, brain-wide. In IoN, we target to achieve a breakthrough in the ability to transfer data from intracortical recording devices, e.g., multi-electrode arrays, by developing a transcranial telemetry system that enables the efficient transfer at high data rate from such high channel count sensors (e.g., imec’s Neuropixels with 1000 channels). Most importantly, it will also fulfil the form factor required for minimally-invasive surgery, needed to minimize the surgical risk and the complications after insertion. Furthermore, IoN will significantly scale up brain-wide recordings, by introducing a new telemetry network that has the capacity to support 16 distributed recording nodes (enabling a total of 16,000 channels), which has never been demonstrated from any BCIs before. To reach these challenging targets, we propose i) a novel hybrid signal propagation method to achieve a 500Mbps data rate with a 10mm^2 implant area, 20× smaller than the state-of-the-art; ii) a completely new “spike-Aloha” protocol to maximize the network capacity, supporting 166× more channels. The technology developed in IoN will be an important transformational step to revolutionize the way neuroscientists and neurologists collect and process brain-wide neural data. By introducing this miniature, energy-efficient, and high-capacity wireless telemetry network, we want to help patients with disability to regain the quality of life.

In-vivo neural recording and transmission of a vast number of neurons is essential in comprehending the brain and nervous system. However, the core challenge in the field of high-channel-count in-vivo neural recording is the limitation in transferring data posed by the bandwidth and energy consumption, which currently lacks a viable telemetry solution to effectively address this challenge. This PoC project introduces a novel retinomorphic encoding method, SpikeZip, which offers several advantages over existing approaches for processing neural data, such as low information loss, minimal latency, and reduced hardware overhead. The technical advances demonstrated in this project will have significant impacts on various applications areas, such as neuroscience research with free-moving small animals, low-latency closed-loop neuromodulation, implantable brain-computer interfaces, and cognitive prosthetics. The proposed method has the potential to revolutionize the way we record and process neural data, enabling us to better understand the brain's cognitive functions and develop new therapies for various neurological disorders. This PoC project will develop a robust demonstration system and rigorously validate it in small animal studies, with settings that can be effectively applied and translated across a diverse range of neuroscience and neurotherapeutic applications. SpikeZip will develop a go-to-market strategy that highlights the technology's unique features and benefits, with a focus on IP and licensing opportunities, and engaging with industry partners to identify promising commercialization opportunities.

Grant Preparation (General Information screen) — Provide an overall description of your project (including context and overall objectives, planned activities and main achievements, and expected results and impacts (on target groups, change procedures, capacities, innovation etc)). This summary should give readers a clear idea of what your project is about.Use the project summary from your proposal. The NEHIL project, an EU-Korea partnership, is set to transform the landscape of digital technologies through groundbreaking neuromorphic architectures and advanced heterogenous integration such as LiDAR systems. This collaborative initiative aims to develop two innovative neuromorphic computing architectures that are crucial for tackling the complex demands of modern data-intensive applications. The first system utilizes FeFET-based Compute-in-Memory (CIM) accelerators, which are designed to support hybrid models of SNN and ANN. These accelerators enhance processing speeds and reduce power consumption, making them ideal for real-time, high-resolution data processing challenges like those found in autonomous vehicle navigation. The second system employs photonic integrated circuits based on reservoir computing (RC) principles, significantly easing manufacturing while enhancing the processing of dynamic data streams. The work involves integrating these neuromorphic systems with state-of-the-art FMCW LiDAR technologies. This integration aims to overcome traditional challenges such as high energy consumption and environmental sensitivity, setting new standards for resolution, accuracy, and cost-efficiency. Specific targets for the NEHIL project include reducing power consumption in object recognition tasks by 50% and achieving a proof-of-concept for ultra-low latency LiDAR signal processing using the FeFET-based CIM and RC architectures. With this approach we exploit the LiDAR’s high-resolution capabilities in adverse weather conditions; reducing power consumption, packaging size and manufacturing cost compared to the state of the art. This collaboration extends its benefits beyond the automotive industry, enhancing capabilities in diverse sectors such as telecom, healthcare, smart cities, security, predictive maintenance, infrastructure management, industrial automation.

The REMPOWER project embarks on a pioneering journey to harness the untapped potential of space-based solar power (SBSP) through innovative rectenna technology and sub-THz wireless energy transmission. However, SBSP also faces many challenges, such as high launch costs, technical difficulties, and potential safety and security issues. At its core, REMPOWER is driven by four pivotal technical objectives associated with the capture and rectification of a sub-THz high energy beam: 100 GHz Modular, Flexible and Lightweight Rectenna: REMPOWER will develop rectenna technologies capable of capturing energy at 100 GHz. These modular rectenna technologies will provide modularity, flexibility at panel level and will allow the reduction of the weight of the final solution. High Efficiency and high power rectification: REMPOWER’s advanced diode and rectifier modeling and design will allow tackling high rectification efficiency, and high power handling capability, despite the sub-THz constraint. This will yield high output DC power while limiting the cost related to the number of required non-linear devices. Nonlinear Rectifier and Rectenna Characterization: REMPOWER will introduce a novel approach by subjecting rectifiers to wideband signals, enabling a comprehensive analysis of amplitudes and phases across multiple intermodulation frequencies. This breakthrough will unveils intricate nonlinear behaviors for heightened efficiency. Scalable Rectenna Arrays for Large Surfaces: REMPOWER will focus on scalability to enable high-power transmission, to reduce design and manufacturing costs and to improve modularity and flexibility. The progress within REMPOWER transcends current technological boundaries, offering promise for sustainable in-space mobility solutions and renewable energy generation. By conquering the challenges of high-frequency energy capture, REMPOWER will reshape the future of space exploration, energy generation, and sustainability.