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IEEE Spectrum: The Cat Brain Cliff Notes
More on IBM "Cat's Brain"
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(this is the way most DARPA projects are run--three competitors make everyone work harder)
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Why is that? Jim Olds (who directs George Mason University's Krasnow Institute for Advanced Study, and who is a neuroscientist) explains that what neuroscience is sorely lacking is a unifying principle. "We need an Einstein of neuroscience," he says, "to lay out a fundamental theory of cognition the way Einstein came up with the theory of relativity." Here's what he means by that. What aspect of the brain is the most basic element that, when modeled, will result in cognition? Is it a faithful reproduction of the wiring diagram of the brain? Is it the exact ion channels in the neurons?
But it's a chicken and egg problem, because without a brain-specific theory of relativity, there is no way to identify a basic unit of neuroscience. And without a basic unit of neuroscience, you can't build a model. So, to get anywhere, you must abstract. "[Markram] thinks it's the neuron," says Olds. "But what if that's not what makes a brain work as a brain? What if it's the synaptic spine, or the ion channels?" There are even neuroscientists who think you can never model the brain—because in order to do it you'd have to model down to quantum effects.
No one knows whether, to understand consciousness, neuroscience must account for every synaptic detail. "We do not have a definition of consciousness," says Granger. "Or, worse, we have fifteen mutually incompatible definitions."
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The Neural Prostheses Foundation investigating Transfer of Functions of the Mind (NeuralProstheses.Org)
Практически Мы :)
MIT OpenCourseWare | Brain and Cognitive Sciences | 9.01 Neuroscience and Behavior, Fall 2003 | Home
IEEE Spectrum: IBM Unveils a New Brain Simulator
- IBM is diversifying its neuromorphic systems researches. What next, neurosupercomputer in 2012? I bet they'll make digital cortex much sooner then 2020. - sengrel on 2009-11-20
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The number of neurons and synapses in the simulation exceed those in a cat’s brain;
NeuroLex
The NeuroLex project, supported by the Neuroscience Information Framework project, is a dynamic lexicon of neuroscience terms. Unlike an encyclopedia, a lexicon provides the meaning of a term, and not all there is to know about it.
Whole Brain Catalog™
"The Whole Brain Catalog™ is a ground-breaking, open-source, 3-D virtual environment developed by a team of researchers from UC San Diego under the Whole Brain Project™. The Catalog aims to connect members of the international neuroscience community to facilitate solutions for today’s intractable challenges in brain research through cooperation and crowd sourcing."
Whole Brain Project™
"Simultaneous revolutions in neuroscience research and next generation software tools are merged in the Whole Brain Project™. The project joins neuroscientists and software engineers to employ experimental techniques to visualize and explore the burgeoning new discoveries about the brain’s structure and function. Despite rapid progress in development of new experimental methods, our ability to simultaneously study the brain across all these scales remains quite limited. The Whole Brain Project looks to provide open source networks to help unify the disparate and heterogeneous data of neuroscientists."
Karl Friston
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as providing the most
promising attempt at a unified theory of brain
functions -
Through a Darwinian
process, selecting from the competing models the one
best supported by the evidence, a basis for action
is chosen.
Mind Reading Revisited | Singularity Hub
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The most exciting revelation from this research is the discovery that brain activity of a person thinking about an object, such as a hammer, is very similar to the brain activity of a completely different person that is also thinking of a hammer.
Is this a unified theory of the brain? (Bayesian theory in New Scientist)
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Neuroscientist Karl Friston and his colleagues have proposed a mathematical law that some are claiming is the nearest thing yet to a grand unified theory of the brain. From this single law, Friston’s group claims to be able to explain almost everything about our grey matter.
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Friston’s ideas build on an existing theory known as the “Bayesian brain”, which conceptualises the brain as a probability machine that constantly makes predictions about the world and then updates them based on what it senses.
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Do Bayesian statistics rule the brain?
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Over the past decade, neuroscientists have found that real brains seem to work in this way. In perception and learning experiments, for example, people tend to make estimates - of the location or speed of a moving object, say - in a way that fits with Bayesian probability theory. There's also evidence that the brain makes internal predictions and updates them in a Bayesian manner. When you listen to someone talking, for example, your brain isn't simply receiving information, it also predicts what it expects to hear and constantly revises its predictions based on what information comes next. These predictions strongly influence what you actually hear, allowing you, for instance, to make sense of distorted or partially obscured speech.
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In fact, making predictions and re-evaluating them seems to be a universal feature of the brain. At all times your brain is weighing its inputs and comparing them with internal predictions in order to make sense of the world.
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