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Tilikum the killer whale (Orcinus orca) made news recently in the tragic death of his Sea World trainer, Dawn Brancheau. Tilikum pulled Brancheau into the water when he grabbed her floating ponytail — much like a cat might grab yarn attached to a stick. Complex play behavior is a sign of intelligence, but unfortunately little is known of the circuitry of even a cat’s brain, much less the massive brain of an orca — roughly four times the size of a human brain. See Also The Race to Reverse Engineer the Human Brain Ray Kurzweil Interview Brain on a Chip MIT neuroscientists are developing computerized techniques to map the millions of miles of neuronal circuits in the brain that may one day shed some light on the differences between Homo sapiens sapiens and other species, and will likely clarify how those neurons give rise to intelligence, personality, and memory. Developing connectomes (maps of neurons and synapses) may have just as much impact as sequencing the human genome. Here’s a video showing 3D rotating nodes and edges in a small connectome:

Remember the last time that something a friend did caught you off guard? Probably—and that's because the human brain is specially tuned to remember things that are out of the ordinary. But just how the brain treats those instances has remained uncertain. Some scientists had hypothesized that an unexpected stimulus would trigger a loop that involved both the hippocampus (responsible in part for long-term memory) and nucleus accumbens (involved in reward and pleasure) to make those memories super sticky. But without peering into these centers, researchers could not know for sure.

Scientists at the Johns Hopkins University Applied Physics Laboratory (APL) were awarded no less than $34.5 million by the Defense Advanced Research Projects Agency (DARPA) to continue their outstanding work in the field of prosthetic limb testing, which has seen them come up with the most advanced model yet. Their Modular Prosthetic Limb (MPL) system is just about ready to be tested on human subjects, as it has proved successful with monkeys. Basically, the prosthetic arm is controlled by the brain through micro-arrays that are implanted (gently) in the head. They record brain signals and send the commands to the computer software that controls the arm. To be honest, it will be interesting to see just how these hair-chips are attached to the brain, but the APL say clinical tests have shown the devices to be entirely harmless. The monkeys didn’t mind them too much, at least.

Researchers at MIT’s McGovern Institute for Brain Research are working on a new mathematical model to mimic the human brain's ability to identify objects. The model can predict human performance on certain visual-perception tasks suggesting it’s a good indication of what's actually happening in the brain. Researchers are hoping the new findings will make their way into future object-recognition systems for automation, mobile robotics, and other applications.

Scientists have great expectations that nanotechnologies will bring them closer to the goal of creating computer systems that can simulate and emulate the brain's abilities for sensation, perception, action, interaction and cognition while rivaling its low power consumption and compact size. DARPA for instance, the U.S. military's research outfit known for projects that are pushing the envelope on what is technologically possible, has a program called SyNAPSE that is trying to develop electronic neuromorphic machine technology that scales to biological levels. Started in late 2008 and funded with $4.9 million, the goal of the initial phase of the SyNAPSE project is to "develop nanometer scale electronic synaptic components capable of adapting the connection strength between two neurons in a manner analogous to that seen in biological systems, as well as, simulate the utility of these synaptic components in core microcircuits that support the overall system architecture."

Each new generation of astronomers discovers that the universe is much bigger than their predecessors imagined. The same is also true of brain complexity. Every era’s most advanced technologies, when applied to the study of the brain, keep uncovering more layers of nested complexity, like a set of never ending Russian dolls. We now know that there are up to 1,000 different subtypes of nerve cells and supporting actors—the glia and astrocytes—within the nervous system. Each cell type is defined by its chemical constituents, neuronal morphology, synaptic architecture and input-output processing.

Imagine you're a Brontosaurus1 with your face in a prehistoric tree top, munching on fresh leaves. Your relatives have ruled planet Earth for more than 150 million years. Huge and strong, you feel invincible. You're not. Fast forward about 65 million years. A creature much smaller and weaker dominates the Earth now, with brains instead of brawn. Its brain is a lot larger relative to its body size – plenty big enough to conceive a way to scan the cosmos for objects like the colossal asteroid that wrought the end of your kind. Right: An artist's concept of NASA's Wide-field Infrared Survey Explorer (WISE). [more] The creature designed and built WISE, NASA's Wide-field Infrared Survey Explorer, to search for "dark" objects in space like brown dwarf stars, vast dust clouds, and Earth-approaching asteroids. WISE finds them by sensing their heat in the form of infrared light most other telescopes can't pick up.

Researchers at CMU and Intel are attempting to map and understand human brain activity well enough that individual words can be detected. Currently, giant MRI machines are being used but the future holds smaller devices that can be worn like a helmet according to Dean Pomerleau, senior researcher at Intel. The efficiency and productivity of word detection will be superior to existing technology that allows an operator to simply control a cursor. This technology will no doubt make its way into robotic telepresence applications including remote surgery and construction in dangerous environments such as the ocean and space.

The race to create tiny wireless sensors that could monitor anything from pressure in the eyes and brain to the stability of bridges appears to be heating up. Earlier this month, IEEE Spectrum reported on two approaches to creating an almost-indefinitely-running sensor using piezoelectric systems to convert tiny vibrations into power. Now, another team from the University of Michigan has created an alternative approach that uses solar power to keep the sensor running autonomously for many years.

I remember when, a decade ago, Kevin Warwick, a professor at the University of Reading, in the U.K., implanted a radio chip in his own arm. The feat caused quite a stir. The implant allowed him to operate doors, lights, and computers without touching anything. On a second version of the project he could even control an electric wheelchair and produce artificial sensations in his brain using the implanted chip. Warwick had become, in his own words, a cyborg. The idea of a cyborg -- a human-machine hybrid -- is common in science fiction and although the term dates back to the 1960s it still generates a lot of curiosity. I often hear people asking, When will we become cyborgs? When will humans and machines merge? Although some researchers might have specific time frames in mind, I think a better answer is: It's already happening. When we look back at the history of technology, we tend to see distinct periods -- before the PC and after the PC, before the Internet and after the Internet, and so forth -- but in reality most technological advances unfold slowly and gradually. That's particularly true with the technologies that are allowing us to modify and enhance our bodies.

Walking, swallowing, respiration and many other key functions in humans and other animals are controlled by Central Pattern Generators (CPGs). In essence, CPGs are small, autonomous neural networks that produce rhythmic outputs, usually found in animal's spinal cords rather than their brains. Their relative simplicity and obvious success in biological systems has led to some success in using CPGs in robotics. However, current systems are restricted to very simple CPGs (e.g., restricted to a single walking gait). A recent breakthrough at the BCCN at the University of Göttingen, Germany has now allowed to achieve 11 basic behavioral patterns (various gaits, orienting, taxis, self-protection) from a single CPG, closing in on the 10–20 different basic behavioral patterns found in a typical cockroach. The trick: Work with a chaotic, rather than a stable periodic CPG regime. For more on CPGs, listen to the latest episode of the Robots podcast on Chaos Control, which interviews Poramate Manoonpong, one of the lead researchers in Göttingen, and Alex Pitti from the University of Tokyo who uses chaos controllers that can synchronize to the dynamics of the body they are controlling.