Posts about brain

Driving Via Direct Signals from the Brain

Last year we learned of Google’s Self Driving Car, which is actually making great progress in the real world (cool). And a few years ago I wrote about Toyota’s wheelchair you control with your mind. Now Nissan is looking at cars that you drive aided by accessing brain signals.

This idea is a bit scary to me, the self driving car is less so. But it is great to see us pushing the engineering boundaries forward. It is such a shame that the huge economic failures in the USA, Europe and Japan are rightly grabbing much of the attention these days. If we just reduced the waste and corruption in the political and financial systems it would allow us to take more joy is the great time we do for awesome engineering breakthroughs. Still, if we can try to block out those painful economic realities, these types of breakthroughs are really cool.

The webcast shows the work of the Artificial Intelligence Group of the Freie Universität Berlin in Germany (BrainDriver).

Related: Nissan’s Cars Will Read Your MindResearching Direct Brain Interfaces for Text EntryWave Disk Engine Could Increase Efficiency 5 Times

And Nissan is collaborating with the École Polytechnique Fédérale de Lausanne in Switzerland (EPFL) on a car that uses your brain signals (along with signals the computer gets via its own sensors) to aid in driving.
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Science and Optical Illusions

illusion with color tiles on a cubeMore illusions by R Beau Lotto, lecturer in neuroscience, University College London

The middle tiles on the cube both have the same color, even though they appear very different to most of us.

The science of optical illusions

the two physically identical tiles do indeed now look very different.

Why? The information in the image strongly suggests that the dark brown tile on the top now means a poorly reflective surface under bright light, whereas the bright orange one at the side means a highly reflective surface in shadow.
… [from another illusion]
So why do they look so different? Because your brain takes the image on the retina and creates what it sees according to what the information would have meant in the brain’s past experience of interacting with the world.

In this case the angles suggest depth and perspective and the brain believes the green table is longer than it is while the red table appears squarer.

The beautiful thing about illusions is they make us realise things are never what they seem, and that our experiences of the world shape our understanding of it.

Studying illusions can teach us several things. We can learn that it is easy for our senses to be fooled. We can learn about how the brain works. We can also learn how to take into account how our brain works to try and adjust our opinions (to be careful we are not just interpreting things incorrectly). It is amazing to see some of the wild guidance our brains give us. Normally they do a fantastic job of guiding us through our day but they have weaknesses that can lead us to mistaken conclusions.

Related: Albert Einstein, Marylin Monroe Hybrid ImageWhy Does the Moon Appear Larger on the Horizon?Illusions, Optical and OtherSeeing Patterns Where None Exists

Researching Direct Brain Interfaces for Text Entry

Adam Wilson posted a status update on the social networking Web site Twitter — just by thinking about it. A UW-Madison biomedical engineering doctoral student, Wilson is among a growing group of researchers worldwide who aim to perfect a communication system for users whose bodies do not work, but whose brains function normally. Among those are people who have amyotrophic lateral sclerosis (ALS), brain-stem stroke or high spinal cord injury.

The interface consists, essentially, of a keyboard displayed on a computer screen. “The way this works is that all the letters come up, and each one of them flashes individually,” says Williams. “And what your brain does is, if you’re looking at the ‘R’ on the screen and all the other letters are flashing, nothing happens. But when the ‘R’ flashes, your brain says, ‘Hey, wait a minute. Something’s different about what I was just paying attention to.’ And you see a momentary change in brain activity.”

The system still is not very quick. However, as with texting, users improve as they practice using the interface. “I’ve seen people do up to eight characters per minute,” says Wilson.

Read full press release

Related: Toyota Develops Thought-controlled WheelchairRat Brain Cells, in a Dish, Flying a PlaneThe Brain Hides Information From Us To Prevent MistakesRoachbot: Cockroach Controlled Robot
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Albert Einstein, Marilyn Monroe Hybrid Image

Albert Einstein, Marilyn Monroe Hybrid ImageThis image looks like Albert Einstein up close. If you back up maybe 3-5 meters it will look like Marilyn Monroe. Image by Dr. Aude Oliva.

Hybrid images paper by Aude Oliva, MIT; Antonio Torralba, MIT; and Philippe G. Schyns University of Glasgow.

We present hybrid images, a technique that produces static images with two interpretations, which change as a function of viewing distance. Hybrid images are based on the multiscale processing of images by the human visual system and are motivated by masking studies in visual perception. These images can be used to create
compelling displays in which the image appears to change as the viewing distance changes. We show that by taking into account perceptual grouping mechanisms it is possible to build compelling hybrid images with stable percepts at each distance.

Hybrid images, however, contain two coherent global image interpretations, one of which is of the low spatial frequencies, the other of high spatial frequencies.

For a given distance of viewing, or a given temporal frequency a particular band of spatial frequency dominates visual processing. Visual analysis of the hybrid image still unfolds from global to local perception, but within the selected frequency band, for a given viewing distance, the observer will perceive the global structure of the hybrid first, and take an additional hundred milliseconds to organize the local information into a coherent percept (organization of blobs if the image is viewed at a far distance, or organization of edges for close viewing).

Very cool stuff.

   
Albert Einstein, Marilyn Monroe Hybrid ImageThis is just a smaller image of the above (all I did was shrink the size). For me, this already looks like Marilyn Monroe, but also needs a shorter distance to see the image seem to change.

Related: Illusions, Optical and OtherHow Our Brain Resolves SightSeeing Patterns Where None ExistsMagenta is a Colorposts on scientific explanations of what we experienceComputational Visual Cognition Laboratory at MIT

Robot with Biological Brain

The Living Robot by Joe Kloc

Life for Warwick’s robot began when his team at the University of Reading spread rat neurons onto an array of electrodes. After about 20 minutes, the neurons began to form connections with one another. “It’s an innate response of the neurons,” says Warwick, “they try to link up and start communicating.”

For the next week the team fed the developing brain a liquid containing nutrients and minerals. And once the neurons established a network sufficiently capable of responding to electrical inputs from the electrode array, they connected the newly formed brain to a simple robot body consisting of two wheels and a sonar sensor.

At first, the young robot spent a lot of time crashing into things. But after a few weeks of practice, its performance began to improve as the connections between the active neurons in its brain strengthened. “This is a specific type of learning, called Hebbian learning,” says Warwick, “where, by doing something habitually, you get better at doing it.”

“It’s fun just looking at it as a robot life form, but I think it may also contribute to a better understanding of how our brain works,” he says. Studying the ways in which his robot learns and stores memories in its brain may provide new insights into neurological disorders like Alzheimer’s disease.

Related: Roachbot: Cockroach Controlled RobotRat Brain Cells, in a Dish, Flying a PlaneHow The Brain Rewires ItselfBrain Development

Magenta is a Color

Electromagnetic spectrum chartElectromagnetic spectrum chart from the Wikimedia Commons

Yes, Virgina, there is a magenta by Chris Foresman

There is a nasty rumor making its way around the interconnected series of tubes we call the Internet.

As visible light enters the eye and strikes the cone cells, the cells send electrical signals along the optic nerve to the brain. This is how our body “senses” light. Our brain interprets those three separate sensations to produce the perception that we call “color.”

The truth is, no color actually exists outside of our brain’s perception of it. Everything we call a color—and there are a lot more than what comes in your box of Crayolas—only exists in our heads. We define color in terms of how our brains process the stimuli produced by a mix of wavelengths in the range of 400–700nm hitting specialized cells in our eyes—”one, or any mixture, of the constituents into which light can be separated in a spectrum or rainbow,” says the OED. Elliot’s article might be better titled, “Magenta is not a single wavelength of electromagnetic radiation in the ‘visible’ spectrum, but our brain perceives it anyway.”

This is a great article that uses science to explain interesting details about our brains and how we perceive the external world.

Related: How Our Brain Resolves Sightmore posts using science to explain the worldScience Explains: Flame ColorElectromagnetic SpectrumIllusions, Optical and Other

An Artificial Nerve Networks

When neurons – brain nerve cells – are grown in culture, they don’t form complex ‘thinking’ networks. Moses, Feinerman and Rotem wondered whether the physical structure of the nerve network could be designed to be more brain-like. To simplify things, they grew a model nerve network in one dimension only – by getting the neurons to grow along a groove etched in a glass plate. The scientists found they could stimulate these nerve cells using a magnetic field (as opposed to other systems of lab-grown neurons that only react to electricity).

Experimenting further with the linear set-up, the group found that varying the width of the neuron stripe affected how well it would send signals. Nerve cells in the brain are connected to great numbers of other cells through their axons (long, thin extensions), and they must receive a minimum number of incoming signals before they fire one off in response. The researchers identified a threshold thickness, one that allowed the development of around 100 axons. Below this number, the chance of a response was iffy, while just a few over this number greatly raised the chance a signal would be passed on.

The scientists then took two thin stripes of around 100 axons each and created a logic gate similar to one in an electronic computer. Both of these ‘wires’ were connected to a small number of nerve cells. When the cells received a signal along just one of the ‘wires,’ the outcome was uncertain; but a signal sent along both ‘wires’ simultaneously was assured of a response. This type of structure is known as an AND gate. The next structure the team created was slightly more complex: Triangles fashioned from the neuron stripes were lined up in a row, point to rib, in a way that forced the axons to develop and send signals in one direction only. Several of these segmented shapes were then attached together in a loop to create a closed circuit. The regular relay of nerve signals around the circuit turned it into a sort of biological clock or pacemaker.

Moses: ‘We have been able to enforce simplicity on an inherently complicated system. Now we can ask, ‘What do nerve cells grown in culture require in order to be able to carry out complex calculations?’ As we find answers, we get closer to understanding the conditions needed for creating a synthetic, many-neuron ‘thinking’ apparatus.’

Full press release

Related: Rat Brain Cells, in a Dish, Flying a PlaneThe Brain is Wired to Mull Over DecisionsNanofibers Knit Severed Neurons Together

Brain Reorganizes As It Learns Math

Brain reorganizes to make room for math

It takes years for children to master the ins and outs of arithmetic. New research indicates that this learning process triggers a large-scale reorganization of brain processes involved in understanding written symbols for various quantities.

The findings support the idea that humans’ ability to match specific quantities with number symbols, a skill required for doing arithmetic, builds on a brain system that is used for estimating approximate quantities. That brain system is seen in many nonhuman animals.

When performing operations with Arabic numerals, young adults, but not school-age children, show pronounced activity in a piece of brain tissue called the left superior temporal gyrus, says Daniel Ansari of the University of Western Ontario in London, Canada. Earlier studies have linked this region to the ability to associate speech sounds with written letters, and musical sounds with written notes. The left superior temporal gyrus is located near the brain’s midpoint, not far from areas linked to speech production and understanding.

In contrast, children solving a numerical task display heightened activity in a frontal-brain area that, in adults, primarily serves other functions.

Related: Brain DevelopmentThe Brain Hides Information From Us To Prevent MistakesHow The Brain Rewires Itselfposts about brain research

Bird Brain

Bird-brains smarter than your average ape

In a recent study 20 individuals from the great ape species were unable to transfer their knowledge from the trap-table and trap-tube or vice versa, despite the fact that both these puzzles work in the same way. Strikingly the crows in The University of Auckland study were able to solve the trap-table problem after their experience with the trap-tube.

“The crows appeared to solve these complex problems by identifying causal regularities,” says Professor Russell Gray of the Department of Psychology. “The crows’ success with the trap-table suggests that the crows were transferring their causal understanding to this novel problem by analogical reasoning. However, the crows didn’t understand the difference between a hole with a bottom and one without. This suggests the level of cognition here is intermediate between human-like reasoning and associative learning.”

“It was very surprising to see the crows solve the trap-table,” says PhD student Alex Taylor. “The trap table puzzle was visually different from the trap-tube in its colour, shape and material. Transfer between these two distinct problems is not predicted by theories of associative learning and is something not even the great apes have so far been able to do.”

Related: Cool Crow ResearchOrangutan Attempts to Hunt Fish with SpearBackyard Wildlife: CrowsDolphins Using Tools to Hunt

Rat Brain Cells, in a Dish, Flying a Plane

Adaptive Flight Control With Living Neuronal Networks on Microelectrode Arrays (open access paper) by Thomas B. DeMarse and Karl P. Dockendorf Department of Biomedical Engineering, University of Florida

investigating the ability of living neurons to act as a set of neuronal weights which were used to control the flight of a simulated aircraft. These weights were manipulated via high frequency stimulation inputs to produce a system in which a living neuronal network would “learn” to control an aircraft for straight and level flight.

A system was created in which a network of living rat cortical neurons were slowly adapted to control an aircraft’s flight trajectory. This was accomplished by using high frequency stimulation pulses delivered to two independent channels, one for pitch, and one for roll. This relatively simple system was able to control the pitch and roll of a simulated aircraft.

When Dr. Thomas DeMarse first puts the neurons in the dish, they look like little more than grains of sand sprinkled in water. However, individual neurons soon begin to extend microscopic lines toward each other, making connections that represent neural processes. “You see one extend a process, pull it back, extend it out — and it may do that a couple of times, just sampling who’s next to it, until over time the connectivity starts to establish itself,” he said. “(The brain is) getting its network to the point where it’s a live computation device.”

To control the simulated aircraft, the neurons first receive information from the computer about flight conditions: whether the plane is flying straight and level or is tilted to the left or to the right. The neurons then analyze the data and respond by sending signals to the plane’s controls. Those signals alter the flight path and new information is sent to the neurons, creating a feedback system.

“Initially when we hook up this brain to a flight simulator, it doesn’t know how to control the aircraft,” DeMarse said. “So you hook it up and the aircraft simply drifts randomly. And as the data come in, it slowly modifies the (neural) network so over time, the network gradually learns to fly the aircraft.”

Although the brain currently is able to control the pitch and roll of the simulated aircraft in weather conditions ranging from blue skies to stormy, hurricane-force winds, the underlying goal is a more fundamental understanding of how neurons interact as a network, DeMarse said.

Related: Neural & Hybrid Computing Laboratory @ University of Florida – UF Scientist: “Brain” In A Dish Acts As Autopilot, Living ComputerRoachbot: Cockroach Controlled RobotNew Neurons in Old Brainsposts on brain researchViruses and What is LifeGreat Self Portrait of Astronaut Engineer

New Neurons are Needed for New Memories

New neurons are needed for new memories

Around 15 years ago, researchers discovered that the adult rodent brain contains discrete populations of stem cells which continue to divide and produce new cells throughout life. This discovery was an important one, as it overturned a persistent dogma in neuroscience which held that the adult mammalian brain cannot regenerate.
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This study shows that inhibiting neurogenesis has strikingly different consequences in two distinct regions of the brain. In the olfactory bulb, it leads to significant shrinkage but apparently does not alter smell-related behaviour. In the hippocampus, the effect on structure is not so marked, but it is clear that newly-generated neurons are necessary for the processes of learning and memory. Exactly how the new cells contribute to memory formation is still unknown.

More interesting stuff. Related: How The Brain Rewires ItselfScientists Witness the Birth of a Brain CellNew Neurons in Old BrainsNo Sleep, No New Brain Cells