One of the greatest challenges in
neuroscience is to identify the map of synaptic connections between neurons.
Called the ‘connectome’, it is the holy grail that will explain how information
flows in the brain. In a landmark paper, published the week of 17th of
September in the Proceedings of the National Academy of Sciences, the EPFL's
Blue Brain Project (BBP) has identified key principles that determine
synapse-scale connectivity by virtually reconstructing a cortical microcircuit
and comparing it to a mammalian sample. These principles now make it possible
to predict the locations of synapses in the neocortex. A longstanding
neuroscientific mystery has been whether all the neurons grow independently and
just take what they get as their branches bump into each other, or are the
branches of each neuron specifically guided by chemical signals to find all its
target. To solve the mystery, researchers looked in a virtual reconstruction of
a cortical microcircuit to see where the branches bumped into each other. To
their great surprise, they found that the locations on the model matched that
of synapses found in the equivalent real-brain circuit with an accuracy ranging
from 75 percent to 95 percent.
This means that neurons grow as
independently of each other as physically possible and mostly form synapses at
the locations where they randomly bump into each other. A few exceptions were
also discovered pointing out special cases where signals are used by neurons to
change the statistical connectivity. By taking these exceptions into account,
the Blue Brain team can now make a near perfect prediction of the locations of
all the synapses formed inside the circuit. The goal of the BBP is to integrate
knowledge from all the specialized branches of neuroscience, to derive from it
the fundamental principles that govern brain structure and function, and
ultimately, to reconstruct the brains of different species -- including the
human brain -- in silico. To achieve these results, a team from the Blue Brain
Project set about virtually reconstructing a cortical microcircuit based on
unparalleled data about the geometrical and electrical properties of neurons --
data from over nearly 20 years of painstaking experimentation on slices of
living brain tissue. Each neuron in the circuit was reconstructed into a 3D
model on a powerful Blue Gene supercomputer. About 10,000 of virtual neurons
were packed into a 3D space in random positions according to the density and
ratio of morphological types found in corresponding living tissue. The
researchers then compared the model back to an equivalent brain circuit from a
real mammalian brain.
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