a landmark paper, published this week in PNAS (forthcoming), the EPFL’s Blue Brain Project (BBP) has identified key principles that determine synapse-scale connectivity by virtually reconstructing (in supercomputer) 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, the researchers say.
“This is a major breakthrough, because it would otherwise take decades, if not centuries, to map the location of each synapse in the brain and it also makes it so much easier now to build accurate models,” says Henry Markram, head of the BBP.
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.
A longstanding neuroscientific mystery has been: do all the neurons grow independently and just take what they get, as their branches bump into each other, or is a branch specifically guided by chemical signals to find all its target?
To solve the mystery, a research team from the Blue Brain Project set about virtually reconstructing (simulated on a computer) 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 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.
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.