Future neural interfaces will read and write population neural activity with high spatial and temporal resolution, for diverse applications. For example, an artificial retina may restore vision to the blind by electrically stimulating retinal ganglion cells. Such devices must tune their function, based on stimulating and recording, to match the function of the circuit.

Science Corporation, founded by former Neuralink president Max Hodak, has unveiled a prototype machine to extend the life of organs for longer periods. Science Corporation, the brain-computer interface startup founded in 2021 by former Neuralink president Max Hodak, is launching a new division of the company with the goal of extending the life of human organs. Alameda, California-based Science is aiming to improve on current perfusion systems that continuously circulate blood through vital organs when they can no longer function on their own. The technology is used to preserve organs for transplant and as a life-support measure for patients when the heart and lungs stop working, but it's clunky and costly. Science wants to make a smaller, more portable system that could provide long-term support.

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Future neural interfaces will read and write population neural activity with high spatial and temporal resolution, for diverse applications. For example, an artificial retina may restore vision to the blind by electrically stimulating retinal ganglion cells. Such devices must tune their function, based on stimulating and recording, to match the function of the circuit. This work tests the idea that using prior information from previous experiments and closed-loop measurements may greatly increase the efficiency of the neural interface. Large-scale, high-density electrical recording and stimulation in primate retina were used as a lab prototype for an artificial retina.

--Advanced neural interfaces are transforming applications ranging from neuroscience research to diagnostic tools (for mental state recognition, tremor and seizure detection) as well as prosthetic devices (for motor and communication recovery). By integrating complex functions into miniaturized neural devices, these systems unlock significant opportunities for personalized assistive technologies and adaptive therapeutic interventions. Leveraging high-density neural recordings, on-site signal processing, and machine learning (ML), these interfaces extract critical features, identify disease neuro-markers, and enable accurate, low-latency neural decoding. Moreover, the synergy between neural interfaces and ML has paved the way for self-sufficient, ubiquitous platforms capable of operating in diverse environments with minimal hardware costs and external dependencies. In this work, we review recent advancements in AI-driven decoding algorithms and energy-efficient System-on-Chip (SoC) platforms for next-generation miniaturized neural devices.

Future neural interfaces will read and write population neural activity with high spatial and temporal resolution, for diverse applications. For example, an artificial retina may restore vision to the blind by electrically stimulating retinal ganglion cells. Such devices must tune their function, based on stimulating and recording, to match the function of the circuit. This work tests the idea that using prior information from previous experiments and closed-loop measurements may greatly increase the efficiency of the neural interface. Large-scale, high-density electrical recording and stimulation in primate retina were used as a lab prototype for an artificial retina.

The brain solves the credit assignment problem remarkably well. For credit to be assigned across neural networks they must, in principle, wait for specific neural computations to finish. How the brain deals with this inherent locking problem has remained unclear. Deep learning methods suffer from similar locking constraints both on the forward and feedback phase. Recently, decoupled neural interfaces (DNIs) were introduced as a solution to the forward and feedback locking problems in deep networks.Here we propose that a specialised brain region, the cerebellum, helps the cerebral cortex solve similar locking problems akin to DNIs.

Getting the neural interface hooked up to a prosthetic takes two steps. First is surgery involving the portions of muscle that remain after a lower-leg amputation. The operation reconnects shin muscle, which contracts to make the ankle flex upward, to calf muscle, which counteracts this movement. The prosthetic can also be fitted at this point. In addition to enabling the prosthetic to move more dynamically, the procedure can reduce phantom-limb pain, and patients are less likely to trip and fall.

Speech or text representation generated by pre-trained models contains modal-specific information that could be combined for benefiting spoken language understanding (SLU) tasks. In this work, we propose a novel pre-training paradigm termed Continuous Integrate-and-Fire Pre-Training (CIF-PT). It relies on a simple but effective frame-to-token alignment: continuous integrate-and-fire (CIF) to bridge the representations between speech and text. It jointly performs speech-to-text training and language model distillation through CIF as the pre-training (PT). Evaluated on SLU benchmark SLURP dataset, CIF-PT outperforms the state-of-the-art model by 1.94% of accuracy and 2.71% of SLU-F1 on the tasks of intent classification and slot filling, respectively. We also observe the cross-modal representation extracted by CIF-PT obtains better performance than other neural interfaces for the tasks of SLU, including the dominant speech representation learned from self-supervised pre-training.

Brain-computer interfaces, also known as neural interfaces, allow people to govern and control their surroundings with just their thoughts. AI Healthtech Startups innovation is the result of years of neuro-engineering study into techniques like electroencephalography (EEG), electrocorticography (ECoG), virtual reality (VR), and augmented reality (AR). As Elon Musk's Neuralink shows, interest in neural interfaces is growing as well. Some new businesses are developing non-invasive brain interfaces for people with disabilities, such as those who are paralyzed or have trouble communicating. Indian newcomer StimVeda is creating a non-invasive brain stimulation device called Ease to help those suffering from depression.