Biodiversity: A boon for brain research
Published on Apr 17, 2014
How two unlikely microbes (that don't even have brains) led to the development of one of today's most promising brain research techniques--which is being used to study many diseases including schizophrenia and Parkinson's.
Optogenetics and Enhancing Brain Functions-A World Economic Forum Discussion-Ideas @Davos-WIRED
Published on Apr 23, 2014
With optogenetics, the ability to restore and enhance brain function is becoming a reality. In this World Economic Forum discussion, Nature magazine neuroscience editor I-han Chou explains how the radical method works and the ethical issues it could cause.
NSF's 2014 Alan T. Waterman Awardee Feng Zhang discusses his research on the brain
Published on May 12, 2014
NSF's 2014 Alan T. Waterman Awardee Feng Zhang discusses the work of his research team on the brain. Zhang is an investigator at the McGovern Institute for Brain Research at MIT and a core member of the Broad Institute of MIT and Harvard. He spoke with NSF's Lisa-Joy Zgorski during his visit to NSF in May of 2014 to receive the Alan T. Waterman Award.
Can Brain Implants Make Us Smarter?
Published on Aug 20, 2014
Is it possible for us to significantly boost our intelligence within a lifetime? Studies show that changes in our lifestyle like exercise and nutrition can help increase brain power - but these improvements are modest at best. Perhaps the future of intelligence will come in the form of a brain implant? We’ve already seen some amazing research to get computers and brains to communicate more easily - and the future implications are limitless!
Carol Dweck: The power of believing that you can improve
Published on Dec 17, 2014
Carol Dweck researches “growth mindset” — the idea that we can grow our brain's capacity to learn and to solve problems. In this talk, she describes two ways to think about a problem that’s slightly too hard for you to solve. Are you not smart enough to solve it … or have you just not solved it yet? A great introduction to this influential field.
Harvard computer system fuels our understanding of the brain
Published on Jan 28, 2015
Faculty and researchers are using big data to answer society’s most challenging questions, and doing it with the help of FAS Research Computing (FASRC). Founded in 2007, FASRC had one goal: to provide Harvard faculty, students, and staff with leading-edge computational resources.
By building a centralized, high-performance computing environment called Odyssey, FASRC gave researchers the keys to unlock the information inside big data. Users have access to more than 60,000 CPUs and 15 petabytes of storage. At peak usage during a day, Odyssey churns through data so fast that it would take a traditional desktop more than 140 years to process the same information.
For more information, visit
"Harvard’s Odyssey unlocks big data"
Faculty, researchers find high-performance computer system fuels our understanding of the brain
January 26, 2015
The Neurochemistry of Flow States, with Steven Kotler
Published on Feb 27, 2015
Steven Kotler explains the neurochemical changes during flow states that strengthen motivation, creativity and learning. "The brain produces a giant cascade of neurochemistry. You get norepinephrine, dopamine, anandamide, serotonin and endorphins. All five of these are performance enhancing neurochemicals." Kotler discusses how each amplifies intellectual and cognitive performance.
See-through brains
Published on Apr 10, 2013
Scientists have come up with a way to make whole brains transparent, so they can be labelled with molecular markers and imaged using a light microscope. The technique, called CLARITY, enabled its creators to produce the detailed 3D visualisations you see in this video. It works in mouse brains and human brains; here the team use it to look into the brain of a 7-year-old boy who had autism.
Original research paper: https://www.nature.com/articles/nature12107
Nature News story:
"See-through brains clarify connections"
Technique to make tissue transparent offers three-dimensional view of neural networks.
by Helen Shen
April 10, 2013
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