The human brain has 100 billion nerve cells and trillions of connections between them. Understanding the workings of such a complex and dynamic organ requires new tools and technologies. Materials scientists are developing probes to form gentle but sensitive and reliable interfaces to stimulate and record signals from thousands of individual neurons at once. Our engineers are developing ways to manipulate neural circuits with electricity, light, ultrasound and magnetic fields, and others are listening to the brain, interpreting the language of neural signals and using that language to drive robotic arms or to type on a computer. New tools will enable as yet unimagined discoveries and will allow us to repair and even to augment the human brain.
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Center for Mind, Brain, Computation and Technology (MBCT)
The MBCT program at Wu Tsai Neuro aims to inspire new advances in our understanding of neuroscience and its applications, and to give future generations of scientists the tools to investigate the emergent functions of the brain and to contribute to the development of artificial systems that emulate them.
Center for Neural Data Science (CNDS)
This collaboration between Wu Tsai Neuro and Stanford Data Science that fosters new interdisciplinary collaborations between our world-class departments here at Stanford, creating a synergistic environment for developing novel analytical methods and driving transformative discoveries in brain research.
Stanford Neuroengineering (NeuroE)
Stanford NeuroE is 1) a community of Stanford researchers dedicated to neuroengineering applications, 2) a partnership with industry and the public for education and advancement to deliver new therapies for brain disease, and 3) a hub for interdisciplinary training spanning neuroscience, engineering, devices, and data.
Marlowe
Stanford is making a substantial investment in a large, high-performance, GPU-based computational instrument called Marlowe. As envisioned, the infrastructure and the Research Data Science team will offer investigators the ability to build, analyze, and use large-scale models for new types of scientific discoveries.