With funding from the Department of Energy’s (DOE’s) Laboratory Directed Research and Development (LDRD) program, Berkeley Lab researchers from the Computational Research Division (CRD) and the Biosciences Area are collaborating to explore how brain-inspired computer chips might benefit science.
Around the world, various ‘Brain Initiatives’ are generating a tsunami of neuroscience data. But without a coherent strategy to analyze, manage and understand the data, advancements in the field will be limited. That’s why Kristofer Bouchard, research scientist in Biological Systems & Engineering Division, assembled an international team of interdisciplinary researchers to develop a plan to overcome the big data challenge. Read more at the Computational Research Division News Page.
For the first time, a new tool developed at Berkeley Lab allows researchers to interactively explore the hierarchical processes that happen in the brain when it is resting or performing tasks. Scientists also hope that the tool can shed some light on how neurological diseases like Alzheimer’s spread throughout the brain.
The software, called Brain Modulyzer, was created by researchers in the Computational Research Division and Kris Bouchard from the Biological Systems & Engineering Division in conjunction with computer scientists at University of California, Davis (UC Davis) and with input from neuroscientists at UC San Francisco (UCSF). The software combines multiple coordinated views of functional magnetic resonance imaging (fMRI) data—like heat maps, node link diagrams and anatomical views—to provide context for brain connectivity data. For more, read the press release by Linda Vu at the Berkeley Lab News Center.
The report on the multi-institutional Neuro-Workshop held June 2, 2016 at Berkeley Lab (LBNL) is now available. The workshop was convened to discuss relevant technological capabilities for the national Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative. Participants also explored collaborative opportunities that would address neuroscience “grand challenges” in support of the Department of Energy (DOE) contribution to BRAIN and other national scientific challenges.
Bengalese finches, songbirds that have been used to research the learning, perception, and production of bird song, are the model system used by Berkeley Lab scientist Kristofer Bouchard and Michael Brainard of UC San Francisco to determine the relationship between song sequence structure and brain activity. As reported in their PNAS article published last week, “Auditory-induced neural dynamics in sensory-motor circuitry predict learned temporal and sequential statistics of birdsong,” the researchers studied how the birds brain forms predictions for the timing and identity of specific “syllables” that it has learned to sing.