The Wyss Institute for Biologically Inspired Engineering at Harvard University recently announced a cross-institutional consortium to map neural circuits within the brain to improve understanding of neuropathological disorders.
The consortium will be conducted under a $21 million contract from the Intelligence Advanced Research Projects Activity (IARPA).
Researchers will use the Wyss Institute’s fluorescent in-situ RNA sequencing (FISSEQ) method to identify neuronal cells that work together to produce specific brain functions.
The consortium will further the goals of President Barack Obama’s BRAIN initiative to improve the understanding of the human mind and establish new treatment methods for neuropathological disorders such as Alzheimer’s disease, schizophrenia, autism and epilepsy.
“Historically, the mapping of neuronal paths and circuits in the brain has required brain tissue to be sectioned and visualized by electron microscopy. Complete neurons and circuits are then reconstructed by aligning the individual electron microsope images, this process is costly and inaccurate due to use of only one color (grey),” study researcher George Church, PhD, of Harvard Medical School, said in a press release. “We are taking an entirely new approach to neuronal connectomics — immensely colorful barcodes — that should overcome this obstacle; and by integrating molecular and physiological information we are looking to render a high-definition map of neuronal circuits dedicated first to specific sensations, and in the future to behaviors and cognitive tasks.”
To map neural connections, the consortium will use Barcoding of Individual Neuronal Connections (BOINC) to genetically engineer mice and barcode each neuron with a unique RNA sequence.
Researchers will also provide sensory stimulus to barcoded mice, to highlight corresponding circuits within the complex neuronal map.
Wyss Institute is partnering with another Machine Intelligence from Cortical Networks (MICrONS) team to develop computational models of neural circuits and novel machine learning algorithms.
Source – The Wyss Institute