Tom Dean

Scalable Neuroscience and the Brain Activity Mapping Project

Friday 19th of April 2013 at 12:30pm
LSA 101

Since the beginning of the year, the European Union and United States have separately announced major initiatives in brain science. The latter is called the Brain Activity Mapping (BAM) Project and the size of the effort and the implications for science and medicine have been compared to the Human Genome Project. A key part of the effort involves developing new scientific instruments capable of observing the activity of large ensembles of neurons in awake behaving humans with the goal of understanding the neural basis for cognition and diagnosing a wide range brain disorders from Parkinson’s to Alzheimer’s. The problem these instruments are intended to solve can be divided conceptually into two parts: recording and reporting. Recording involves sensing and coding for transmission neural activity including membrane potentials, protein expression levels, calcium concentrations and their correlates. Reporting involves conveying the coded information from the locus of the recording — typically deep within the neural tissue of an awake subject — to some external computing or storage device. The technical challenge involved in building these instruments is considerable, perhaps on a par with constructing the Large Hadron Collider (LHC), but while the LHC accelerator ring is 27 kilometers in circumference, the components comprising BAM instruments may include billions of nanoscale parts and be contained entirely within a human skull. This lecture explores several of the key technologies being considered to address the reporting problem including nanoscale communication networks, micron-diameter fiber-optic cables, light and ultrasound microscopy, recombinant DNA and synthetic biology. Why is a research scientist from Google interested in mapping the brain? Google’s mission is to organize the world’s information and make it universally accessible and useful. Information concerning human brain activity certainly ranks high in terms importance to society. The computational and storage requirements for making this data accessible and useful are staggering. Google is perhaps uniquely qualified with the infrastructure and technical wherewithal to assist the scientific community in meeting this challenge.

Annotated slides of talk
Stanford course webpage

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