Mathematicians help to unlock brain function. Mathematicians from Queen Mary, University of London will bring researchers one-step closer to understanding how the structure of the brain relates to its function in two recently published studies.
Publishing in Physical Review Letters the researchers from the Complex Networks group at Queen Mary's School of Mathematics describe how different areas in the brain can have an association despite a lack of direct interaction. The team, in collaboration with researchers in Barcelona, Pamplona and Paris, combined two different human brain networks - one that maps all the physical connections among brain areas known as the backbone network, and another that reports the activity of different regions as blood flow changes, known as the functional network. Model Suggests Link between Intelligence and Entropy. +Enlarge image A.
Wissner-Gross/Harvard Univ. & MIT A. D. Wissner-Gross and C. A pendulum that is free to swing through all angles in a plane can be stabilized in the inverted position by sliding the pivot horizontally, in the same way that you can balance a meter stick on your finger. The smallest disks, subjected to causal entropy forces, tend to work in a synchronized fashion to pull down the largest disk, in what the authors present as a primitive example of social cooperation. The second law of thermodynamics—the one that says entropy can only increase—dictates that a complex system always evolves toward greater disorderliness in the way internal components arrange themselves. Entropy measures the number of internal arrangements of a system that result in the same outward appearance.
Hoping to firm up such notions, Wissner-Gross teamed up with Cameron Freer of the University of Hawaii at Manoa to propose a “causal path entropy.” –Don Monroe References R. Q-learning. Q-learning is a model-free reinforcement learning technique.
Specifically, Q-learning can be used to find an optimal action-selection policy for any given (finite) Markov decision process (MDP). It works by learning an action-value function that ultimately gives the expected utility of taking a given action in a given state and following the optimal policy thereafter. When such an action-value function is learned, the optimal policy can be constructed by simply selecting the action with the highest value in each state.
IBM simulates 530 billon neurons, 100 trillion synapses on supercomputer. A network of neurosynaptic cores derived from long-distance wiring in the monkey brain: Neuro-synaptic cores are locally clustered into brain-inspired regions, and each core is represented as an individual point along the ring.
Arcs are drawn from a source core to a destination core with an edge color defined by the color assigned to the source core. (Credit: IBM) Announced in 2008, DARPA’s SyNAPSE program calls for developing electronic neuromorphic (brain-simulation) machine technology that scales to biological levels, using a cognitive computing architecture with 1010 neurons (10 billion) and 1014 synapses (100 trillion, based on estimates of the number of synapses in the human brain) to develop electronic neuromorphic machine technology that scales to biological levels.”
Simulating 10 billion neurons and 100 trillion synapses on most powerful supercomputer Neurosynaptic core (credit: IBM) Two billion neurosynaptic cores DARPA SyNAPSE Phase 0DARPA SyNAPSE Phase 1DARPA SyNAPSE Phase 2. Inspiring Innovation. The core of a TEDx event combines live speakers, performers and TEDTalks to spark deep discussions and connections.
The immersive and uplifting event can be a life-changing experience. TEDxBerkeley 2014 will provide a platform for the Bay Area’s leading visionaries and storytellers to speak to an energised group of thinkers, as well as to the world at large. At this event, 1000 changemakers, innovators, thinkers, creatives, cultural leaders & social pioneers will witness a back-to-back schedule of talks, performances and other multimedia surprises showcasing the theme of Rethink. Redefine. Recreate: pioneering technologies, fresh thinking and new ideas that will foster creativity and action around the world. February 8th, 2014, from 10:00AM (Registration from 8:30AM)
Daniel Romano B Martinho. Daniel Romano B Martinho. Artificial Intelligence - foundations of computational agents. Later Terminator: We’re Nowhere Near Artificial Brains. I can feel it in the air, so thick I can taste it.
Can you? It’s the we’re-going-to-build-an-artificial-brain-at-any-moment feeling. It’s exuded into the atmosphere from news media plumes (“IBM Aims to Build Artificial Human Brain Within 10 Years”) and science-fiction movie fountains…and also from science research itself, including projects like Blue Brain and IBM’s SyNAPSE.
For example, here’s a recent press release about the latter: Today, IBM (NYSE: IBM) researchers unveiled a new generation of experimental computer chips designed to emulate the brain’s abilities for perception, action and cognition. Now, I’m as romantic as the next scientist (as evidence, see my earlier post on science monk Carl Sagan), but even I carry around a jug of cold water for cases like this.