Posts tagged blue brain project
Posts tagged blue brain project
At EPFL’s Blue Brain facilities, computer models of individual neurons are being assembled into neural circuits that produce electrical signals akin to brain waves. The results, published in the journal Neuron, are helping solve the mystery of how and why these signals arise in the brain.
For almost a century, scientists have been studying brain waves to learn about mental health and the way we think. Yet the way billions of interconnected neurons work together to produce brain waves remains unknown. Now, scientists from EPFL’s Blue Brain Project in Switzerland, at the core of the European Human Brain Project, and the Allen Institute for Brain Science in the United States, show in the July 24th edition of the journal Neuron how a complex computer model is providing a new tool to solve the mystery.
The brain is composed of many different types of neurons, each of which carry electrical signals. Electrodes placed on the head or directly in brain tissue allow scientists to monitor the cumulative effect of this electrical activity, called electroencephalography (EEG) signals. But what is it about the structure and function of each and every neuron, and the way they network together, that give rise to these electrical signals measured in a mammalian brain?
Modeling Brain Circuitry
The Blue Brain Project is working to model a complete human brain. For the moment, Blue Brain scientists study rodent brain tissue and characterize different types of neurons to excruciating detail, recording their electrical properties, shapes, sizes, and how they connect.
To answer the question of brain-wave origin, researchers at EPFL’s Blue Brain Project and the Allen Institute joined forces with the help of the Blue Brain modeling facilities. Their work is based on a computer model of a neural circuit the likes of which have never been seen before, encompassing an unprecedented amount of detail and simulating 12,000 neurons.
“It is the first time that a model of this complexity has been used to study the underlying properties of brain waves,” says EPFL scientist Sean Hill.
In observing their model, the researchers noticed that the electrical activity swirling through the entire system was reminiscent of brain waves measured in rodents. Because the computer model uses an overwhelming amount of physical, chemical and biological data, the supercomputer simulation allows scientists to analyze brain waves at a level of detail simply unattainable with traditional monitoring of live brain tissue.
“We need a computer model because it is impossible to relate the electrical activity of potentially billions of individual neurons and the resulting brain waves at the same time,” says Hill. “Through this view, we’re able to provide an interpretation, at the single-neuron level, of brain waves that are measured when tissue is actually probed in the lab.”
Finding brain wave analogs
Neurons are somewhat like tiny batteries, needing to be charged in order to fire off an electrical impulse known as a “spike”. It is through these “spikes” that neurons communicate with each other to produce thought and perception. To “recharge” a neuron, charged particles called ions must travel through miniscule ionic channels. These channels are like gates that regulate electrical current. Ultimately, the accumulation of multiple electrical signals throughout the entire circuit of neurons produces brain waves.
The challenge for scientists in this study was to incorporate into the simulation the thousands of parameters, per neuron, that describe these electrical properties. Once they did that, they saw that the overall electrical activity in their model of 12,000 neurons was akin to observations of brain activity in rodents, hinting at the origin of brain waves.
“Our model is still incomplete, but the electrical signals produced by the computer simulation and what was actually measured in the rat brain have some striking similarities,” says Allen Institute scientist Costas Anastassiou.
Hill adds, “For the first time, we show that the complex behavior of ion channels on the branches of the neurons contributes to the shape of brain waves.”
There is still much work to be done in order to arrive at a complete simulation. While the model’s electrical signals are analogous to in vivo measurements, researchers warn that there are still many open questions as well as room to improve the model. For instance, the simulation is modeled on neurons that control the hind-limb, while in vivo data represent brain waves coming from neurons that have a similar function but control whiskers instead.
“Even so, the computer model we used allowed us to characterize, and more importantly quantify, key features of how neurons produce these signals,” says Anastassiou.
The scientists are currently studying similar brain wave phenomena in larger and more realistic neural circuits.
This computer model is drawing cellular biophysics and cognitive neuroscience closer together, in order to achieve the same goal: understanding the brain. But the two disciplines share neither the methods nor the scientific language. By simulating electrical brain activity and relating the behavior of single neurons to brain waves, the researchers aim to bridge this gap, opening the way to better tools for diagnosing mental disorders, and on a deeper level, offering a better understanding of ourselves.
To handle large amounts of data from detailed brain models, IBM, EPFL, and ETH Zürich are collaborating on a new hybrid memory strategy for supercomputers. This will help the Blue Brain Project and the Human Brain Project achieve their goals.
Motivated by extraordinary requirements for neuroscience, IBM Research, EPFL, and ETH Zürich through the Swiss National Supercomputing Center CSCS, are exploring how to combine different types of memory – DRAM, which is standard for computer memory, and flash memory that is akin to USB sticks – for less expensive and optimal supercomputing performance.
The Blue Brain Project, for example, is building detailed models of the rodent brain based on vast amounts of information – incorporating experimental data and a large number of parameters – to describe each and every neuron and how they connect to each other. The building blocks of the simulation consist of realistic representations of individual neurons, including characteristics like shape, size, and electrical behavior.
Given the roughly 70 million neurons in the brain of a mouse, a huge amount of data needs to be accessed for the simulation to run efficiently.
“Data-intensive research has supercomputer requirements that go well beyond high computational power,” says EPFL professor Felix Schürmann of the Blue Brain Project in Lausanne. “Here, we investigate different types of memory and how it is used, which is crucial to build detailed models of the brain. But the applications for this technology are much broader.”
70 Million Neurons for the New IBM Blue Gene/Q
The Blue Brain Project has acquired a new IBM Blue Gene/Q supercomputer to be installed at CSCS in Lugano, Switzerland. This machine has four times the memory of the supercomputer used by the Blue Brain Project up to now, but this still may not be enough to model the mouse brain at the desired level of detail.
The challenge for scientists is to modify the supercomputer so that it can model not only more neurons—as many as the 70 million in the mouse brain—but with even more detail while using fewer resources. The researchers aspire to do just that by engineering different types of memory. The Blue Gene/Q comes equipped with 64 terabytes of DRAM memory. But this type of memory, which is ubiquitous in personal computers, loses data almost instantaneously when the power is turned off.
The scientists plan to boost the supercomputer’s capacity by combining DRAM with another type of memory that has made its way into everyday devices, from cameras to mobile phones: flash memory. Unlike DRAM, flash memory can retain information, even without power, and is much more affordable. The Blue Brain Project’s new supercomputer efficiently integrates 128 terabytes of flash memory with the 64 terabytes of DRAM memory.
“These technological advancements will not only help scientists model the brain, but they will also contribute to future evidence-based systems,” says IBM Research computational scientist Alessandro Curioni, who is based in Zurich.
To take full advantage of this novel mix of memory, IBM has been developing a scalable memory system architecture, while EPFL and ETH Zürich researchers are working on high-level software to optimize this hybrid memory for large-scale simulations and interactive supercomputing.
“The resulting machine may not necessarily be the fastest supercomputer in the world, but it will certainly open up new avenues for data-intensive science,” says ETH Zürich professor and CSCS director Thomas Schulthess. “The results of this collaboration will support scientific investigations across all types of data intensive applications including astronomy, geosciences and healthcare.”
Towards the Human Brain
The Blue Brain Project has recently become the core of an even more ambitious project, the European Flagship Human Brain Project, also coordinated by EPFL. The Human Brain Project faces the daunting task of providing the technical tools to integrate as much data as possible into detailed models of the human brain by 2023. Estimated at 90 billion neurons, the human brain compared to that of a mouse contains roughly a thousand times more neurons. The new strategy to use hybrid memory is an important step towards helping the Human Brain Project meet its 10-year goal.
As it goes with research and innovation, a scientific pursuit is pushing the boundaries of technology, leading to new and more powerful tools. The Blue Brain and Human Brain Projects have brought into perspective the need to deal with complex and unusual calculations, requiring supercomputer technology where speed is simply not enough.
Bluebrain is a ten-year documentary film-in-the-making about the twenty-first century race to reverse engineer the human brain. Such is the goal of The Blue Brain Project, based in Lausanne, Switzerland, one of the highest-profile neuroscience projects in the world today. Blue Brain’s audacious leader is Henry Markram, who publicly announced in 2009 that he seeks to reverse-engineer a human brain with digital simulations of all the physical properties of every neuron, powered by IBM supercomputers, by 2020. Director Noah Hutton began shooting in 2009, focusing exclusively on Markram’s Blue Brain Project— but starting in Year 3, the scope of the film has expanded to include the work of other prominent projects and labs seeking to understand the brain through different methods, including Sebastian Seung of M.I.T., Rafael Yuste of Columbia University, and Jeff Lichtman of Harvard University.
The film will continue to survey the work of other projects and their leaders in years to come, with yearly shorts released ahead of a full re-edit into a documentary feature due for completion in 2020. As the Blue Brain simulation is built over the course of this decade, so too will this documentary about a historic quest in human history. Through yearly updates from Blue Brain and other prominent scientists, philosophers, and ethicists, Bluebrain will track a crucial decade in the human mind’s relentless drive to understand itself.
Scientists to simulate human brain inside a supercomputer
Scientists at its forerunner, the Switzerland-based Blue Brain Project, have been working since 2005 to feed a computer with vast quantities of data and algorithms produced from studying tiny slivers of rodent gray matter.
Last month they announced a significant advancement when they were able to use their simulator to accurately predict the location of synapses in the neocortex, effectively mapping out the complex electrical brain circuitry through which thoughts travel.
Henry Markram, the South African-born neuroscientist who heads the project, said the breakthrough would have taken “decades, if not centuries” to chart using a real neocortex. He said it was proof their concept, dubbed “brain in a box” by Nature magazine, would work.
Now the team are joining forces with other scientists to create the Human Brain Project. As its name suggests, they aim to scale up their model to recreate an entire human brain.
It is a step that will need both a huge increase in funding and access to computers so advanced that they have yet to be built.
If their current bid for €1 billion ($1.3 billion) of European Commission funding over the next 10 years is successful, Markram predicts that his computer neuroscientists are a decade away from producing a synthetic mind that could, in theory, talk and interact in the same way humans do.
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 PNAS, 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.
“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.