作者mulkcs (mulkcs)
看板Cognitive
標題[新知] 奈米等級下的神經結構!
時間Wed Aug 5 00:48:14 2015
文章內容沒有很豐富, 主要就是說他們開了一套新技術搭配電顯可以觀察非常細微的神經
結構, 約30nm左右, 可以看到axon, glia甚至dendrites, mitochondria.
話不多說請直接看影片:
https://www.youtube.com/watch?v=nEOpUypJgyw
看完影片我覺得只有嘆為觀止, 但裡面有提到一個點, 很多結構比我們預期想的還要複雜
, 並沒有很整齊, 但又不是完全的隨機. 這裡面應該蠻多需要後續研究的地方...
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New ‘VAST’ tool gives neuroscientists previously unachievable brain images
at a nanoscale resolution
A new imaging tool developed by Boston scientists could do for the brain what
the telescope did for space exploration. In the first demonstration of how
the technology works, published July 30 in the journal Cell, the researchers
look inside the brain of an adult mouse at a scale previously unachievable,
generating images at a nanoscale resolution. The inventors’ long-term goal
is to make the resource available to the scientific community in the form of
a national brain observatory.
“I’m a strong believer in bottom up-science, which is a way of saying that
I would prefer to generate a hypothesis from the data and test it,” says
senior study author Jeff Lichtman, of Harvard University. “For people who
are imagers, being able to see all of these details is wonderful and we’re
getting an opportunity to peer into something that has remained somewhat
intractable for so long. It’s about time we did this, and it is what people
should be doing about things we don’t understand.”
The researchers have begun the process of mining their imaging data by
looking first at an area of the brain that receives sensory information from
mouse whiskers, which help the animals orient themselves and are even more
sensitive than human fingertips. The scientists used a program called VAST,
developed by co-author Daniel Berger of Harvard and the Massachusetts
Institute of Technology, to assign different colors and piece apart each
individual “object” (e.g., neuron, glial cell, blood vessel cell, etc.).
“The complexity of the brain is much more than what we had ever imagined,”
says study first author Narayanan “Bobby” Kasthuri, of the Boston
University School of Medicine. “We had this clean idea of how there’s a
really nice order to how neurons connect with each other, but if you actually
look at the material it’s not like that. The connections are so messy that it
’s hard to imagine a plan to it, but we checked and there’s clearly a
pattern that cannot be explained by randomness.”
The researchers see great potential in the tool’s ability to answer
questions about what a neurological disorder actually looks like in the
brain, as well as what makes the human brain different from other animals and
different between individuals. Who we become is very much a product of the
connections our neurons make in response to various life experiences. To be
able to compare the physical neuron-to-neuron connections in an infant, a
mathematical genius, and someone with schizophrenia would be a leap in our
understanding of how our brains shape who we are (or vice versa).
The cost and data storage demands for this type of research are still high,
but the researchers expect expenses to drop over time (as has been the case
with genome sequencing). To facilitate data sharing, the scientists are now
partnering with Argonne National Laboratory with the hopes of creating a
national brain laboratory that neuroscientists around the world can access
within the next few years.
“It’s bittersweet that there are many scientists who think this is a total
waste of time as well as a big investment in money and effort that could be
better spent answering questions that are more proximal,” Lichtman says. “
As long as data is showing you things that are unexpected, then you’re
definitely doing the right thing. And we are certainly far from being out of
the surprise element. There’s never a time when we look at this data that we
don’t see something that we’ve never seen before.”
網址:
http://www.psypost.org/2015/07/new-vast-tool-gives-neuroscientists-previously
-unachievable-brain-images-at-a-nanoscale-resolution-36291
(
http://0rz.tw/nBHsO )
影片:
https://www.youtube.com/watch?v=nEOpUypJgyw
論文:
http://www.cell.com/cell/abstract/S0092-8674%2815%2900824-7
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