In a bid to unravel the complexities of the human brain and shed light on the origins of various mental illnesses and neurological disorders, Google Research, in collaboration with a consortium of prestigious institutions, has embarked on an ambitious five-year, $33 million project. Dollars. The company aims to pioneer advances in the field of connectomics, which seeks to map the intricate network of cellular connections within the brain. This innovative initiative, supported by the National Institutes of Health (NIH) Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative, is led by researchers at Harvard University, with contributions from the Allen Institute, MIT , the University of Cambridge, Princeton University, and Johns Hopkins University, along with guidance from advisors at HHMI’s Janelia Research Campus.
The main challenge facing the scientific community lies in understanding the functioning of the human brain, a marvel of computational complexity made up of billions of cells. Mental and neurodegenerative diseases, including dementia, remain a mystery due to the lack of a comprehensive understanding of the brain’s intricate network. The nascent field of connectomics holds immense promise for unraveling these mysteries and potentially offers avenues for effective treatments.
The current venture will focus on mapping a tiny portion (2-3%) of the mouse brain, focusing on the hippocampus region. This area is essential in memory encoding, attention and spatial navigation. By mapping the connectivity of this crucial segment, the researchers aim to lay the foundation for future efforts aimed at a comprehensive understanding of the entire mouse brain and, by extension, the human brain.
In 2021, Google Research and its Harvard partners achieved a major milestone by mapping one cubic millimeter of the human brain, a data set known as the H01 data set. However, mapping the entire connectome of the human brain requires an unprecedented amount of data: up to a zettabyte, currently beyond the capabilities of existing technology. Focusing on the mouse brain, which offers a more manageable scope, presents an invaluable opportunity to gain relevant insights into human brain function and dysfunction.
To accomplish this effort, the project will amass an extraordinary data set, spanning approximately 25,000 terabytes or 25 petabytes of brain data. This data set, projected to be one of the largest in biology, dwarfs the scale of previous connectome mapping projects. For perspective, the data collected from mapping the mouse hippocampal region alone is equivalent to more than 48,800 Pixel phones stacked to the height of the Empire State Building.
The company also encompasses the development of tools and technologies designed to manage massive connectomic data sets. These include flood filling networks, which use deep learning to trace the pathways of neurons in three-dimensional brain volumes, and self-supervised learning technology, SegCLR, to automatically extract vital information from segmented volumes. The core connectomics infrastructure will be strengthened to handle unprecedented scale of data.
In conclusion, Google Research’s bold effort to map the mouse brain represents a critical step toward unraveling the enigma of neurological disorders. Through the collaborative efforts of leading research institutions and the application of cutting-edge technologies, this project promises to deepen our understanding of the brain and has the potential to revolutionize treatments for a spectrum of neurological conditions. As the initiative gains momentum, the scientific community eagerly anticipates the revelations that a look into a mouse’s mind can reveal about our own.
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Niharika is a Technical Consulting Intern at Marktechpost. She is a third-year student currently pursuing her B.tech degree at the Indian Institute of technology (IIT), Kharagpur. She is a very enthusiastic person with a keen interest in machine learning, data science and artificial intelligence and an avid reader of the latest developments in these fields.
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