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Contents contributed and discussions participated by Matvey Ezhov

Matvey Ezhov

Halloween nightmare scenario, early 2020's « dw2 - 1 views

  • On the other hand, Shane observes that people who are working on the program of Friendly AI do not expect to have made significant progress in the same timescale: By the early 2020’s, there will be no practical theory of Friendly AI.
Matvey Ezhov

NeuroLex - 1 views

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    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.
Matvey Ezhov

Whole Brain Project™ - 1 views

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    "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."
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    Wooooohooo!!!!!!
Matvey Ezhov

Karl Friston - 0 views

  • 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.
Matvey Ezhov

You can control your Marilyn Monroe neuron - 2 views

  • Another experiment designed to test how well the subjects could control the single neurons was a fade experiment in which the subject was shown a combined image of two faces: Josh Brolin (star of Goonies) and Marilyn Monroe, and told to think of Josh Brolin. The electrodes sent data on the Josh Brolin and Marilyn Monroe neurons to the computer, which brightened the image of the one causing most neuron firing. As the subject thought of Brolin, the image of Monroe faded out.
    • Matvey Ezhov
       
      This points that grandmother's cells correlates for consciousness, right?
Matvey Ezhov

DirectX compute - будущее вычислений на видеокартах - PCNEWS.RU - 5 views

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    Еще есть OpenCL от Apple. На хабре много инфы и обзоров по нему.
Matvey Ezhov

Do Bayesian statistics rule the brain? - 0 views

  • 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.
  • 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.
Matvey Ezhov

Is this a unified theory of the brain? (Bayesian theory in New Scientist) - 1 views

  • 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.
  • 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.
  • A crucial element of the approach is that the probabilities are based on experience, but they change when relevant new information, such as visual information about the object’s location, becomes available. “The brain is an inferential agent, optimising its models of what’s going on at this moment and in the future,” says Friston. In other words, the brain runs on Bayesian probability.
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  • “In short, everything that can change in the brain will change to suppress prediction errors, from the firing of neurons to the wiring between them, and from the movements of our eyes to the choices we make in daily life,” he says.
  • Friston created a computer simulation of the cortex with layers of “neurons” passing signals back and forth. Signals going from higher to lower levels represent the brain’s internal predictions, while signals going the other way represent sensory input. As new information comes in, the higher neurons adjust their predictions according to Bayesian theory.
  • Volunteers watched two sets of moving dots, which sometimes moved in synchrony and at others more randomly, to change the predictability of the stimulus. The patterns of brain activity matched Friston’s model of the visual cortex reasonably well.
  • Friston’s results have earned praise for bringing together so many disparate strands of neuroscience. “It is quite certainly the most advanced conceptual framework regarding an application of these ideas to brain function in general,” says Wennekers. Marsel Mesulam, a cognitive neurologist from Northwestern University in Chicago, adds: “Friston’s work is pivotal. It resonates entirely with the sort of model that I would like to see emerge.”
  • “The final equation you write on a T-shirt will be quite simple,” Friston predicts.
  • There’s work still to be done, but for now Friston’s is the most promising approach we’ve got. “It will take time to spin off all of the consequences of the theory – but I take that property as a sure sign that this is a very important theory,” says Dehaene. “Most other models, including mine, are just models of one small aspect of the brain, very limited in their scope. This one falls much closer to a grand theory.”
Matvey Ezhov

Technology Review: Intelligence Explained - page 2 - 1 views

  • In 2007, Jung and Richard Haier, now professor emeritus of psychology at the University of California, Irvine, developed the first comprehensive theory drawn from neuroimaging of how the brain gives rise to intelligence.
    • Matvey Ezhov
       
      we need to find them
  • Applying existing theories of how information flows in the brain, Jung and Haier hypothesized that neural signals travel from nodes near the back of the brain, where sensory data is collected and synthesized, to those in the frontal lobes, which are responsible for decision making and planning. The connections between these nodes, they argued, are just as critical as the nodes themselves.
Matvey Ezhov

» Python in neuroscience - 1 views

  • Some already exist specifically for neural data analysis and simulation, such as PyMVPA2 and Brian3 respectively.
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    A widely used open-source programming language, Python is becoming the language of choice for neural data analysis and simulation.
Matvey Ezhov

Technology Review: Intelligence Explained (!) - 0 views

  • "Scientists are now able to switch the focus from particular regions of the brain to the connections between those regions," says Sherif Karama, a psychiatrist and a neuroscientist at McGill University's Montreal Neurological Institute.
  • A quantifiable "general intelligence factor," known as g, can be statistically extracted from scores on a battery of intelligence tests.
  • In 2001, Thompson showed that it is correlated with volume in the frontal cortex, a result consistent with a number of studies that have linked intelligence to overall brain size.
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  • In 2007, Jung and Richard Haier, now professor emeritus of psychology at the University of California, Irvine, developed the first comprehensive theory drawn from neuroimaging of how the brain gives rise to intelligence.
    • Matvey Ezhov
       
      Attention! To Research.
  • As we "evolved from worms to humans," says George Bartzokis, a professor of psychiatry at UCLA, the number of non-neural cells in the brain increased 50 times more than the number of neurons. He adds, "My hypothesis has always been that what gives us our cognitive capacity is not actually the number of neurons, which can vary tremendously between human individuals, but rather the quality of our connections."
  • The type of MRI typically used for medical scans does not show the finer details of the brain's white matter. But with a technique called diffusion tensor imaging (DTI), which uses the scanner's magnet to track the movement of water molecules in the brain, scientists have developed ways to map out neural wiring in detail. While water moves randomly within most brain tissue, it flows along the insulated neural fibers like current through a wire.
Matvey Ezhov

Technology Review: Intelligence Explained - page 1 - 1 views

  • "Scientists are now able to switch the focus from particular regions of the brain to the connections between those regions," says Sherif Karama, a psychiatrist and a neuroscientist at McGill University's Montreal Neurological Institute.
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