mr. wolfram is usually full of hyperbole, but i await his most recent creation with excitement. 2009-05-05: 5m lines of Mathematica code make up WolframAlpha.
the easiest way to create WolframAlpha without Mathematica would have been to write Mathematica first, then use it.
Quant shops aren’t sitting around idly. They are pressing into new realms of computational finance, applying concepts from molecular physics, mathematical linguistics, artificial intelligence and other scientific disciplines.
a technique that could allow neurologists to draw a detailed wiring plan of the mammalian brain by inserting genes coding for fluorescent proteins into mice. Dubbed ‘Brainbow’, the system reveals individual neurons within the nervous system in up to 90 different colors.
By making it glow like a jellyfish. Coming to a brain near you, soon? 2007-12-31: Like a computer
If we look back over recent centuries we will see the brain described as a hydrodynamic machine, clockwork, and as a steam engine. When I was a child in the 1950’s I read that the human brain was a telephone switching network. Later it became a digital computer, and then a massively parallel digital computer. A few years ago someone put up their hand after a talk I had given at the University of Utah and asked a question I had been waiting for a couple of years: “Isn’t the human brain just like the world wide web?” The brain always seems to be one of the most advanced technologies that we humans currently have.
In neuroscience, too, Mr Hawkins is going his own way. Most neuroscientists are experimentalists, and focus on a small part of the brain. Mr Hawkins, by contrast, is interested in the big picture of how the brain works. In essence, his theory holds that the brain processes information using pattern-recognition “nodes” arranged hierarchically, much like the organogram of a large company. Over time, nodes at each level in the hierarchy identify and learn frequently observed patterns. When a known pattern triggers a node, it sends a signal to the next level up in the hierarchy. As multiple signals move up the hierarchy, nodes at higher levels learn to identify and predict more complex patterns. Predictions are passed down the hierarchy so that mismatches between predicted and observed patterns can be recognized.
You’ve probably seen the “connectome” map of the major networks between different functional areas of the human brain. Cool graphic. But this is just an average. It raises a lot of questions: How does this map relate to your brain? Do these connections persist over a period of months or more? Or do they vary with different conditions (happy or sad mood, etc.)? And what if you’re a schizophrenic, alcoholic, meditator, or videogamer, etc., how does your connectome look?
These questions obsessed Stanford psychologist Russell Poldrack, leading to his “MyConnectome project.” In the noble DIY tradition of Marie Curie, Jonas Salk, and Albert Hoffman, he started off his day by climbing into an MRI machine and scanning his brain for 10 minutes Tuesdays and Thursdays every week for a year and a half — making his brain the most studied in the world.
He also fasted and drew blood on Tuesdays for testing with metabolomics (chemical fingerprints in biological fluids) and genomics (gene tests, performed by 23andMe). The results — the most complete study of the brain’s network connections over time — are published in open-access Nature Communications.
These topological players provide a strong mathematical framework for measuring the activity of a neural network, and the process a brain undergoes when exposed to stimuli. The framework works without parameters (for example there is no measurement of distance between neurons in the model) and one can study the local structure by considering cliques, or how they bind together to form a global structure with cavities. By continuing to study the topological properties of these emerging and disappearing structures alongside neuroscientists we could come closer to understanding our own brains!
Unity 3D game-engine lies at the heart of Glass Brain, data visualization of real-time brain function. Neuroscape’s unique multidisciplinary approach involves the development of custom-designed, closed-loop systems that integrate recent technological advances in software (e.g., 3D video game engines, multimodal recording and brain computer interface algorithms) with the latest innovations in hardware (e.g., virtual reality, motion capture, GPU computing, wearable physiological recordings, and transcranial brain stimulation). Building effective closed-loop technologies necessitates collaborative development teams of experienced designers, programmers, multimedia engineers, UI experts, and artist/musicians, working closely with our Core scientists to generate engaging interactive experiences complete with adaptivity, rewards, art, music, and story.
Janelia researchers released a wiring diagram of the fly brain that contains 25k neurons and the 20m connections between them. The so-called “connectome” corresponds to the fly’s hemibrain, a region that’s 250 micrometers across—the size of a dust mite. It’s ~33% of the total fly brain, and contains many of the critical regions responsible for memory, navigation, and learning.
By analyzing the connectome of just a small part of the fly brain — the central complex, which plays an important role in navigation — Dr. Jayaraman and his colleagues identified 10s of new neuron types and pinpointed neural circuits that appear to help flies make their way through the world. The work could ultimately help provide insight into how all kinds of animal brains, including our own, process a flood of sensory information and translate it into appropriate action. “Being able to trace that activity through that circuit — from sensory back to motor through this complex intermediate circuit — is really amazing. The connectome showed us a lot more than we thought it was going to.”
Connectomics is making important progress even where it can’t yet be large scale and where only partial connectomes exist. Neuroscientists uncovered 10s of new neuron types and circuits that seem to aid in fly navigation. The work was hailed as a major milestone in revealing how flies incorporate sensory information and translate it into action. The successes of connectomics can be bittersweet. For many years, a central criticism of connectomics has been that it is insufficient to explain how the brain functions. Despite having had a map of the brain of C. elegans for decades, scientists still struggle to draw meaningful conclusions about its neural functions. To Lichtman, parsing the seemingly limitless interconnectivity of more complex brains is a challenge that tests the limits of human and artificial intelligence.
In the last decade or so, advances in computer processing power have allowed researchers to transform ultrasound technology. Instead of emitting individual beams, these newer ultrasound systems send out a series of plane waves—an array of ultrasound beams that together form a plane—that hit their target at different angles. The resulting images are composites that are multiple orders of magnitude sharper than conventional ultrasound, MRI, or CT scans, without the trade-offs faced by other imaging methods. MRI machines, for example, demand hugely powerful and expensive magnets to improve their resolution. The new forms of ultrasound can also work 100x faster than conventional ultrasound tools, which is especially useful during medical emergencies, when time is of the essence. Such speeds allow ultrasound to track seizures as they happen.
Ultrasound imaging could read brain activity, revealing how a person wants to move their hand to the left, and that data could be fed into a computer that controls a robotic arm. X-rays that map the exact geometry of a skull can guide a model of exactly how the skull distorts ultrasound waves. And that model can be used to correct ultrasound images so they appear undistorted, as though there weren’t any skull there at all.
Scientists have generated the first complete connectome of a complex animal — the fruit fly Drosophila melanogaster. The map shows all 3016 neurons and 548k synapses tightly packed in a young Drosophila’s brain, which is smaller than a poppy seed. “Now we have a reference brain. We can look at what happens to connectivity in models of Alzheimer’s and Parkinson’s diseases and of any degenerative disease.”
Until now, scientists had mapped the connectomes of only the worms Caenorhabditis elegans and Platynereis dumerilii, and the larva of the sea squirt Ciona intestinalis. Drosophila was an ideal model for connectome studies, because scientists have already sequenced its genome, and the larvae have transparent bodies. Fruit flies also exhibit sophisticated behaviors — including learning, navigating landscapes, processing smells and weighing the risks and benefits of an action.
A voxel of the new images measures 5 microns, 64m times smaller than a clinical MRI voxel. New insights from mouse imaging will in turn lead to a better understanding of conditions in humans, such as how the brain changes with age, diet, or even with neurodegenerative diseases like Alzheimer’s.
We provide insights into the underlying mechanisms by focusing on song production in 2 contexts in Drosophila melanogaster: near versus far from a female. Using quantitative behaviour, modelling, broad-range optogenetics, circuit manipulations and neural recordings, we found that simple song (of primarily the pulse mode) is driven by low-level or brief activation of pC2 brain neurons, which drive a pair of pIP10 brain-to-VNC descending neurons. To generate complex bouts, stronger, longer-duration pC2 neuron activity simultaneously drives pIP10 and recruits P1a neurons to functionally disinhibit core circuitry in the VNC, allowing pIP10 descending signals to produce rapid alternations of pulse and sine song. Song alternations are facilitated by combination of mutual inhibition and rebound excitability in pulse-driving and sine-driving neurons of the VNC, allowing for sine song production without the need for excitatory drive. Here, the sensory context, encoded ultimately by acute P1a neural activity, determines which song repertoire (simple pulse or complex) is accessible to descending commands, effectively implementing context dependence via two operational modes of a single circuit.
Each of these projects is important in its own right, but as they progress — some have been going more than 10 years — there is a need for better communication between them. Several of the projects are using similar or identical technologies. It makes sense for the teams to liaise more closely, at the very least to begin a discussion on how to establish shared data standards, which they have not yet done.
The sequence of Busy Beaver numbers, BB(1), BB(2), and so on, grows faster than any computable sequence. Faster than exponentials, stacked exponentials, the Ackermann sequence, you name it. Because if a Turing machine could compute a sequence that grows faster than Busy Beaver, then it could use that sequence to obtain the D‘s—the beaver dams. And with those D’s, it could list the Busy Beaver numbers, which (sound familiar?) we already know is impossible. The Busy Beaver sequence is non-computable, solely because it grows stupendously fast—too fast for any computer to keep up with it, even in principle.
a fun mind expander with ackermann numbers and busy beaver functions
Aliens on dark worlds might develop a very keen sense of temperature and use this for both communication and exploring their environment. While humans can sense gross changes in temperature, some animals on Earth posses thermal sensors far finer than ours. For example, the mosquito can register differences of as little as one 5-hundredths of a degree centigrade at a distance of 1 centimeter. Some fish such as the sole respond to temperature changes in the water of as little as 0.03 degrees Centigrade. The bedbug can crawl along a wall of a bedroom, sense a tiny area of exposed skin, and jump to it. Humans sense relative temperatures. We know that one glass of tea is hotter than another. But we can’t tell precisely how hot it is. Other creatures on Earth sense absolute temperature. For example, some fish can be trained to recognize a particular temperature within 1 degree of accuracy irrespective of whether the fish came out of a previously warmer or colder environment. Some birds have the ability to maintain their nests at a precise temperature and make small alterations to the nest if it becomes a degree too hot or cold.