03-03-2011, 12:46 PM
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INTRODUCTION
Some have decided it’s time to just go ahead and create a brain in silico. And to a surprising extent, they’ve done it: Labs around the world are populated with autonomously functioning brains based on what we know so far. These simulations match what happens at the cellular level in the brain when the nerve cells, or neurons, that make up the brain pump ions and produce electrochemical activity that propagates across the synapse from one neuron to another. Robots or avatars activated by these engineered brains are directing movement, perceiving visual objects, and even responding to rewards—exhibiting behaviors associated with our “thinking” brains. Eerily, the most recent simulations show the same oscillating rhythms seen when physicians record human brain
waves using an electroencephalogram (commonly known as an EEG). Computer simulations of the brain already allow experiments impossible to carry out with animals. “As good as modern neuroscience is—and it has been brilliant over the last two decades—we can’t really sample every neuron and every synapse as they are performing a behavior,” notes consciousness researcher Gerald Edelman, MD, PhD, director of the Neurosciences Institute and chair of neurobiology at the Scripps Research Institute in San Diego, California. Researchers are looking to develop even more efficient simulated brains to help produce computers that can think while at the same time accelerating neuroscience. Ultimately brain simulations promise the ability to study the effect of drugs and disease and aid in the design of new therapeutic strategies.
What is BLUE BRAIN
“YES", The IBM is now developing a virtual brain known as the BLUE BRAIN.
It would be the worlds first virtual brain.
Within 30 years, we will be able to scan ourselves into the computers
Alan Turing (1912–1954) started off by wanting to “build the brain” and ended up with a computer. In the 60 years that have followed, computation speed has gone from 1 floating point operation per second (FLOPS) to over 250 trillion — by far the largest man-made growth rate of any kind in the ~10,000 years of human civilization. This is a mere blink of an eye, a single generation, in the 5 million years of human evolution and billions of years of organic life. What will the future hold — in the next 10 years, 100 years, and 1,000 years? These immense calculation speeds have revolutionized science, technology and medicine in numerous and profound ways. In particular, it is becoming increasingly possible to simulate some of nature’s most intimate processes with exquisite accuracy, from atomic reactions to the folding of a single protein, gene networks, molecular interactions, the opening of an ion channel on the surface of a cell, and the detailed activity of a single neuron. As calculation speeds approach and go beyond the petaFLOPS range, it is becoming feasible to make the next series of quantum leaps to simulating networks of neurons, brain regions and, eventually, the whole brain. Turing may,
after all, have provided the means by which to build the brain
WHAT IS VIRTUAL BRAIN
A machine that can function as brain
It can take decision.
It can think.
It can response.
It can keep things in memory.
Function of natural brain
From a biological perspective, there are quantum leaps in the ‘quality’ of intelligence between different levels of an organism Atoms are differentially combined to produce a spectrum of molecules, which are qualitatively very different from atoms in terms of their properties and the information they contain. After all, molecules cannot be understood by the study of atoms alone. DNA molecules can be strung together in numerous sequences to produce different genes, which collectively produce hundreds of thousands of proteins that are qualitatively different from their building blocks. Different combinations of proteins produce qualitatively different types of cell that can be combined in various ways in the brain to produce distinct brain regions that contain and process qualitatively different types of information. The brain seems to make the next quantum leap in the quality of intelligence, beyond the physical structures to form dynamic electrical ‘molecules’. The ultimate question, therefore, is whether the interaction between neurons drives a series of qualitative leaps in the manner in which information is embodied to represent an organism and its world. As computers approach petaFLOPS speeds, it might now be possible to retrace these elementary steps in the emergence of biological intelligence using a detailed, biologically accurate model of the brain.
BRAIN SIMULATION
The main limitations for digital computers in the simulation of biological processes are the extreme temporal and spatial resolution demanded by some biological processes, and the limitations of the algorithms that are used to model biological processes. If each atomic collision is simulated, the most powerful supercomputers still take days to simulate a microsecond of protein folding, so it is, of course, not possible to simulate complex biological systems at the atomic scale. However, models at higher levels, such as the molecular or cellular levels, can capture lower-level processes and allow complex large-scale simulations of biological processes.
The Blue Brain Project’s Blue Gene can simulate a NCC of up to 100,000 highly complex neurons at the cellular level (about five times the number of neurons in Aplysia californica), or as many as 100 million simple neurons (about the same number of neurons found in a mouse brain). However, simulating neurons embedded in microcircuits, microcircuits embedded in brain regions, and brain regions embedded in the whole brain as part of the process of understanding the emergence of complex behaviours of animals is an inevitable progression in understanding brain function and dysfunction, and the question is whether whole-brain simulations are at all possible.
Computational power needs to increase about 1-million-fold before we will be able to simulate the human brain, with 100 billion neurons, at the same level of detail as the Blue Column. Algorithmic and simulation efficiency (which ensure that all possible FLOPS are exploited) could reduce this requirement by two to three orders of magnitude. Simulating the NCC could also act as a test-bed to refine algorithms required to simulate brain function, which can be used to produce field programmable gate array (FPGA)-based chips. FPGAs could increase computational speeds by as much as two orders of magnitude. The FPGAs could, in turn, provide the testing ground for the production of specialized NEURON solver application-specific integrated circuits (ASICs) that could further increase computational speed by another one to two orders of magnitude. It could therefore be possible, in principle, to simulate the human brain even with current technology. The computer industry is facing what is known as a discontinuity, with increasing processor speed leading to unacceptably high power consumption and heat production. This is pushing a qualitatively new transition in the types of processor to be used in future computers. These advances in computing should begin to make genetic- and molecular-level simulations possible.
CURRENT RESEARCH WORK
On 1 July 2005, the Brain Mind Institute (BMI, at the Ecole Polytechnique Fédérale de Lausanne) and IBM (International Business Machines) launched the Blue Brain Project1. Using the enormous computing power of IBM’s prototype Blue Gene/L supercomputer2 (FIG. 1), the aims of this ambitious initiative are to simulate the brains of mammals with a high level of biological accuracy and, ultimately, to study the steps involved in the emergence of biological intelligence.
INTRODUCTION
Some have decided it’s time to just go ahead and create a brain in silico. And to a surprising extent, they’ve done it: Labs around the world are populated with autonomously functioning brains based on what we know so far. These simulations match what happens at the cellular level in the brain when the nerve cells, or neurons, that make up the brain pump ions and produce electrochemical activity that propagates across the synapse from one neuron to another. Robots or avatars activated by these engineered brains are directing movement, perceiving visual objects, and even responding to rewards—exhibiting behaviors associated with our “thinking” brains. Eerily, the most recent simulations show the same oscillating rhythms seen when physicians record human brain
waves using an electroencephalogram (commonly known as an EEG). Computer simulations of the brain already allow experiments impossible to carry out with animals. “As good as modern neuroscience is—and it has been brilliant over the last two decades—we can’t really sample every neuron and every synapse as they are performing a behavior,” notes consciousness researcher Gerald Edelman, MD, PhD, director of the Neurosciences Institute and chair of neurobiology at the Scripps Research Institute in San Diego, California. Researchers are looking to develop even more efficient simulated brains to help produce computers that can think while at the same time accelerating neuroscience. Ultimately brain simulations promise the ability to study the effect of drugs and disease and aid in the design of new therapeutic strategies.
What is BLUE BRAIN
“YES", The IBM is now developing a virtual brain known as the BLUE BRAIN.
It would be the worlds first virtual brain.
Within 30 years, we will be able to scan ourselves into the computers
Alan Turing (1912–1954) started off by wanting to “build the brain” and ended up with a computer. In the 60 years that have followed, computation speed has gone from 1 floating point operation per second (FLOPS) to over 250 trillion — by far the largest man-made growth rate of any kind in the ~10,000 years of human civilization. This is a mere blink of an eye, a single generation, in the 5 million years of human evolution and billions of years of organic life. What will the future hold — in the next 10 years, 100 years, and 1,000 years? These immense calculation speeds have revolutionized science, technology and medicine in numerous and profound ways. In particular, it is becoming increasingly possible to simulate some of nature’s most intimate processes with exquisite accuracy, from atomic reactions to the folding of a single protein, gene networks, molecular interactions, the opening of an ion channel on the surface of a cell, and the detailed activity of a single neuron. As calculation speeds approach and go beyond the petaFLOPS range, it is becoming feasible to make the next series of quantum leaps to simulating networks of neurons, brain regions and, eventually, the whole brain. Turing may,
after all, have provided the means by which to build the brain
WHAT IS VIRTUAL BRAIN
A machine that can function as brain
It can take decision.
It can think.
It can response.
It can keep things in memory.
Function of natural brain
From a biological perspective, there are quantum leaps in the ‘quality’ of intelligence between different levels of an organism Atoms are differentially combined to produce a spectrum of molecules, which are qualitatively very different from atoms in terms of their properties and the information they contain. After all, molecules cannot be understood by the study of atoms alone. DNA molecules can be strung together in numerous sequences to produce different genes, which collectively produce hundreds of thousands of proteins that are qualitatively different from their building blocks. Different combinations of proteins produce qualitatively different types of cell that can be combined in various ways in the brain to produce distinct brain regions that contain and process qualitatively different types of information. The brain seems to make the next quantum leap in the quality of intelligence, beyond the physical structures to form dynamic electrical ‘molecules’. The ultimate question, therefore, is whether the interaction between neurons drives a series of qualitative leaps in the manner in which information is embodied to represent an organism and its world. As computers approach petaFLOPS speeds, it might now be possible to retrace these elementary steps in the emergence of biological intelligence using a detailed, biologically accurate model of the brain.
BRAIN SIMULATION
The main limitations for digital computers in the simulation of biological processes are the extreme temporal and spatial resolution demanded by some biological processes, and the limitations of the algorithms that are used to model biological processes. If each atomic collision is simulated, the most powerful supercomputers still take days to simulate a microsecond of protein folding, so it is, of course, not possible to simulate complex biological systems at the atomic scale. However, models at higher levels, such as the molecular or cellular levels, can capture lower-level processes and allow complex large-scale simulations of biological processes.
The Blue Brain Project’s Blue Gene can simulate a NCC of up to 100,000 highly complex neurons at the cellular level (about five times the number of neurons in Aplysia californica), or as many as 100 million simple neurons (about the same number of neurons found in a mouse brain). However, simulating neurons embedded in microcircuits, microcircuits embedded in brain regions, and brain regions embedded in the whole brain as part of the process of understanding the emergence of complex behaviours of animals is an inevitable progression in understanding brain function and dysfunction, and the question is whether whole-brain simulations are at all possible.
Computational power needs to increase about 1-million-fold before we will be able to simulate the human brain, with 100 billion neurons, at the same level of detail as the Blue Column. Algorithmic and simulation efficiency (which ensure that all possible FLOPS are exploited) could reduce this requirement by two to three orders of magnitude. Simulating the NCC could also act as a test-bed to refine algorithms required to simulate brain function, which can be used to produce field programmable gate array (FPGA)-based chips. FPGAs could increase computational speeds by as much as two orders of magnitude. The FPGAs could, in turn, provide the testing ground for the production of specialized NEURON solver application-specific integrated circuits (ASICs) that could further increase computational speed by another one to two orders of magnitude. It could therefore be possible, in principle, to simulate the human brain even with current technology. The computer industry is facing what is known as a discontinuity, with increasing processor speed leading to unacceptably high power consumption and heat production. This is pushing a qualitatively new transition in the types of processor to be used in future computers. These advances in computing should begin to make genetic- and molecular-level simulations possible.
CURRENT RESEARCH WORK
On 1 July 2005, the Brain Mind Institute (BMI, at the Ecole Polytechnique Fédérale de Lausanne) and IBM (International Business Machines) launched the Blue Brain Project1. Using the enormous computing power of IBM’s prototype Blue Gene/L supercomputer2 (FIG. 1), the aims of this ambitious initiative are to simulate the brains of mammals with a high level of biological accuracy and, ultimately, to study the steps involved in the emergence of biological intelligence.
