That’s Not The Case At All With The Wolf-coyote-dog Hybrid, Which Has Developed Into A Sum Greater

From vision to hand action

Our hands are highly developed grasping organs that are in continuous use. Long before we stir our first cup of coffee in the morning, our hands have executed a multitude of grasps. Directing a pen between our thumb and index finger over a piece of paper with absolute precision appears as easy as catching a ball or operating a doorknob. The neuroscientists Stefan Schaffelhofer and Hansjörg Scherberger of the German Primate Center (DPZ) have studied how the brain controls the different grasping movements. In their research with rhesus macaques, it was found that the three brain areas AIP, F5 and M1 that are responsible for planning and executing hand movements, perform different tasks within their neural network. The AIP area is mainly responsible for processing visual features of objects, such as their size and shape. This optical information is translated into motor commands in the F5 area. The M1 area is ultimately responsible for turning this motor commands into actions. The results of the study contribute to the development of neuroprosthetics that should help paralyzed patients to regain their hand functions (eLife, 2016).

The three brain areas AIP, F5 and M1 lay in the cerebral cortex and form a neural network responsible for translating visual properties of an object into a corresponding hand movement. Until now, the details of how this “visuomotor transformation” are performed have been unclear. During the course of his PhD thesis at the German Primate Center, neuroscientist Stefan Schaffelhofer intensively studied the neural mechanisms that control grasping movements. “We wanted to find out how and where visual information about grasped objects, for example their shape or size, and motor characteristics of the hand, like the strength and type of a grip, are processed in the different grasp-related areas of the brain”, says Schaffelhofer.

For this, two rhesus macaques were trained to repeatedly grasp 50 different objects. At the same time, the activity of hundreds of nerve cells was measured with so-called microelectrode arrays. In order to compare the applied grip types with the neural signals, the monkeys wore an electromagnetic data glove that recorded all the finger and hand movements. The experimental setup was designed to individually observe the phases of the visuomotor transformation in the brain, namely the processing of visual object properties, the motion planning and execution. For this, the scientists developed a delayed grasping task. In order for the monkey to see the object, it was briefly lit before the start of the grasping movement. The subsequent movement took place in the dark with a short delay. In this way, visual and motor signals of neurons could be examined separately.

The results show that the AIP area is primarily responsible for the processing of visual object features. “The neurons mainly respond to the three-dimensional shape of different objects”, says Stefan Schaffelhofer. “Due to the different activity of the neurons, we could precisely distinguish as to whether the monkeys had seen a sphere, cube or cylinder. Even abstract object shapes could be differentiated based on the observed cell activity.”

In contrast to AIP, area F5 and M1 did not represent object geometries, but the corresponding hand configurations used to grasp the objects. The information of F5 and M1 neurons indicated a strong resemblance to the hand movements recorded with the data glove. “In our study we were able to show where and how visual properties of objects are converted into corresponding movement commands”, says Stefan Schaffelhofer. “In this process, the F5 area plays a central role in visuomotor transformation. Its neurons receive direct visual object information from AIP and can translate the signals into motor plans that are then executed in M1. Thus, area F5 has contact to both, the visual and motor part of the brain.”

Knowledge of how to control grasp movements is essential for the development of neuronal hand prosthetics. “In paraplegic patients, the connection between the brain and limbs is no longer functional. Neural interfaces can replace this functionality”, says Hansjörg Scherberger, head of the Neurobiology Laboratory at the DPZ. “They can read the motor signals in the brain and use them for prosthetic control. In order to program these interfaces properly, it is crucial to know how and where our brain controls the grasping movements”. The findings of this study will facilitate to new neuroprosthetic applications that can selectively process the areas’ individual information in order to improve their usability and accuracy.

Physicists Detect Gravitational Waves, Proving Einstein Right

On Thursday (Feb. 11, 2016) at 10:30 a.m. ET, the National Science Foundation will gather scientists from Caltech, MIT and the LIGO Scientific Collaboration in Washington D.C. to update the scientific community on the efforts being made by the Laser Interferometer Gravitational-wave Observatory (LIGO) to detect gravitational waves.

But why is this exciting? And what the heck are “gravitational waves”?

Keep reading

A puzzling expected value

Pick a (uniformly) random real number from the unit interval [0,1] and repeat this until the sum of all chosen numbers exceeds 1. What is the expected number of real values you will pick?

The quite surprising answer is Eulers constant, e ≈ 2.71828.

A demonstration can be found on Wolfram MathWorld.

Today is Copernicus’s 540th birthday. You may remember Copernicus as the man who said “Hey, what if the Earth went around the sun?” To which the Catholic Church replied “Hey, what if we set you on fire?” 

Blowing Bubbles in the Gamma-ray Sky

Did you know our Milky Way galaxy is blowing bubbles? Two of them, each 25,000 light-years tall! They extend above and below the disk of the galaxy, like the two halves of an hourglass. We can’t see them with our own eyes because they’re only apparent in gamma-ray light, the highest-energy light in the universe.

We didn’t even know these humongous structures were smack in the middle of our galaxy until 2010. Scientists found them when they analyzed the first two years of data from NASA’s Fermi Gamma-ray Space Telescope. They dubbed them the “Fermi bubbles” and found that in addition to being really big and spread out, they seem to have well-defined edges. The bubbles’ shape and the light they give off led scientists to think they were created by a rapid release of energy. But by what? And when?

One possible explanation is that they could be leftovers from the last big meal eaten by the supermassive black hole at the center of our galaxy. This monster is more than 4 million times the mass of our own Sun. Scientists think it may have slurped up a big cloud of hydrogen between 6 and 9 million years ago and then burped jets of hot gas that we see in gamma rays and X-rays.

Another possible explanation is that the bubbles could be the remains of star formation. There are massive clusters of stars at very the center of the Milky Way — sometimes the stars are so closely packed they’re a million times more dense than in the outer suburb of the galaxy where we live. If there was a burst of star formation in this area a few million years ago, it could have created the surge of gas needed to in turn create the Fermi bubbles.

It took us until 2010 to see these Fermi bubbles because the sky is filled with a fog of other gamma rays that can obscure our view. This fog is created when particles moving near light speed bump into gas, dust, and light in the Milky Way. These collisions produce gamma rays, and scientists had to factor out the fog to unveil the bubbles.

Scientists continue to study the possible causes of these massive bubbles using the 10 years of data Fermi has collected so far. Fermi has also made many other exciting discoveries — like the the collision of superdense neutron stars and the nature of space-time. Learn more about Fermi and how we’ve been celebrating its first decade in space.

Make sure to follow us on Tumblr for your regular dose of space: http://nasa.tumblr.com

The Newest & Clearest photo of Pluto.

It often seems so quiet after a snowfall because the fresh powder absorbs sound waves. As the snow melts and freezes, it then creates a reflective surface that allows sound to travel farther than normal. Source

She didn’t have to flex this hard 😤😤