Biggest Structure in the Universe Explained (Infographic)
Astronomers have discovered a huge formation of 73 quasars representing the largest structure yet observed in the universe.
The quasar group is very distant, and therefore existed when the universe was much younger than it is now. A quasar is a very energetic black-hole-powered galactic nucleus. Quasars first appeared in the very early universe, soon after the Big Bang. The light from a quasar is so intense that it can be visible from across the universe.
A remarkable thing about the new discovery is that the structure is larger than cosmological theory says is possible.
The currently accepted Cosmological Principle, based on the work of Albert Einstein, suggests that the largest structures we should be able to find would be about 370 megaparsecs across (more than 1.2 billion light-years). The newly found quasar group is 1,200 megaparsecs across, a distance that would take four billion years to cross at the speed of light.
The largest structures that we know that are close to Earth are super clusters of galaxies surrounding vast voids in space. The Sloan Great Wall is the largest such structure and is at the top end of the size limit set by the Cosmological Principle.
Singing Mice Show Signs of Learning
Guys who imitate Luciano Pavarotti or Justin Bieber to get the girls aren’t alone. Male mice may do a similar trick, matching the pitch of other males’ ultrasonic serenades. The mice also have certain brain features, somewhat similar to humans and song-learning birds, which they may use to change their sounds, according to a new study.
“We are claiming that mice have limited versions of the brain and behavior traits for vocal learning that are found in humans for learning speech and in birds for learning song,” said Duke neurobiologist Erich Jarvis, who oversaw the study. The results appear Oct. 10 in PLOS ONE and are further described in a review article in Brain and Language.
[Arriaga, G. et. al. (2012) “Mouse vocal communication system: are ultrasounds learned or innate?” Brain and Language]
The discovery contradicts scientists’ 60-year-old assumption that mice do not have vocal learning traits at all. “If we’re not wrong, these findings will be a big boost to scientists studying diseases like autism and anxiety disorders,” said Jarvis, who is a Howard Hughes Medical Institute investigator. “The researchers who use mouse models of the vocal communication effects of these diseases will finally know the brain system that controls the mice’s vocalizations.”
Babies Are Born Scientists
Very young children’s learning and thinking is strikingly similar to much learning and thinking in science, according to Alison Gopnik, professor of psychology and affiliate professor of philosophy at the University of California, Berkeley. Gopnik’s findings are described in the Sept 28 issue of the journal Science. She spoke about her work in a video briefing with NSF. New research methods and mathematical models provide a more precise and formal way to characterize children’s learning mechanisms than in the past. Gopnik and her colleagues found that young children, in their play and interactions with their surroundings, learn from statistics, experiments and from the actions of others in much the same way that scientists do.
Researchers from the Centre for Addiction and Mental Health (CAMH) have identified a new role of a chemical involved in controlling the genes underlying memory and learning.
“The brain is a plastic tissue, and we know that learning and memory require various genes to be expressed,” says CAMH Senior Scientist Dr. Art Petronis, who is a senior author on the new study. “Our research has identified how the chemical 5-hmC may be involved in the epigenetic processes allowing this plasticity.” Dr. Petronis is head of the Krembil Family Epigenetics Laboratory in CAMH’s Campbell Family Mental Health Research Institute.
5-hmC is an epigenetic modification of DNA, and was discovered in humans and mice in 2009. DNA modifications are chemical changes to DNA. They flag genes to be turned “on” - signalling the genome to make a protein - or turned “off.” As the overwhelming majority of cells in an individual contain the same genetic code, this pattern of flags is what allows a neuron to use the same genome as a blood or liver cell, but create a completely different and specialized cellular environment.
The research, published online in Nature Structural & Molecular Biology, sheds light on the role of 5-hmC. Intriguingly, it is more abundant in the brain than in other tissues in the body, for reasons not clear to date.
The CAMH team of scientists examined DNA from a variety of tissues, including the mouse and human brain, and looked at where 5-hmC was found in the genome. They detected that 5-hmC had a unique distribution in the brain: it was highly enriched in genes related to the synapse, the dynamic tips of brain cells. Growth and change in the synapse allow different brain cells to “wire” together, which allows learning and memory.
“This enrichment of 5-hmC in synapse-related genes suggests a role for this epigenetic modification in learning and memory,” says Dr. Petronis.
The team further showed that 5-hmC had a special distribution even within the gene. The code for one gene can be edited and “spliced” to create several different proteins. Dr. Petronis found that 5-hmC is located at “splice junctions,” the points where the gene is cut before splicing.
“5-hmC may signal the cell’s splicing machinery to generate the diverse proteins that, in turn, give rise to the unprecedented complexity of the brain,” he says.
The research team is continuing to investigate the role of 5-hmC in more detail, and to determine whether 5-hmC function is different in people with bipolar disorder and schizophrenia compared to people without these diagnoses.
This research was funded by the U.S National Institutes of Health, the Canadian Institutes of Health Research, and the Tapscott Chair in Schizophrenia Studies at the University of Toronto.
The Centre for Addiction and Mental Health (CAMH) is Canada’s largest mental health and addiction teaching hospital, as well as one of the world’s leading research centres in the area of addiction and mental health. CAMH combines clinical care, research, education, policy development and health promotion to help transform the lives of people affected by mental health and addiction issues.
The best way to learn is to teach. Now a classroom robot that helps Japanese children learn English has put that old maxim to the test.
(Image: Sinopix/Rex Features)
Shizuko Matsuzoe and Fumihide Tanaka at the University of Tsukuba, Japan, set up an experiment to find out how different levels of competence in a robot teacher affected children’s success in learning English words for shapes.
They observed how 19 children aged between 4 and 8 interacted with a humanoid Nao robot in a learning game in which each child had to draw the shape that corresponded to an English word such as ‘circle’, ‘square’, ‘crescent’, or ‘heart’.
The researchers operated the robot from a room next to the classroom so that it appeared weak and feeble, and the children were encouraged to take on the role of carers. The robot could then either act as an instructor, drawing the correct shape for the child, or make mistakes and act as if it didn’t know the answer.
When the robot got a shape wrong, the child could teach the robot how to draw it correctly by guiding its hand. The robot then either “learned” the English word for that shape or continued to make mistakes.
Robot learner aids learning
Matsuzoe and Tanaka found that the children did best when the robot appeared to learn from them. This also made the children more likely to want to continue learning with the robot. The researchers will present their results at Ro-Man - an international symposium on robot and human interactive communication - in September.
“Anything that gets a person more actively engaged and motivated is going to be beneficial to the learning process,” says Andrea Thomaz , director of the Socially Intelligent Machines lab at the Georgia Institute of Technology in Atlanta. “So needing to teach the robot is a great way of doing that.”
The idea of students learning by teaching also agrees with a lot of research in human social learning, she says. The process of teaching a robot is akin to what happens in peer-to-peer learning, where students teach each other or work in groups to learn concepts – common activities in most classrooms.
Scripps Research Institute Scientists Uncover a New Pathway that Regulates Information Processing in the Brain
Scientists at The Scripps Research Institute (TSRI) have identified a new pathway that appears to play a major role in information processing in the brain. Their research also offers insight into how imbalances in this pathway could contribute to cognitive abnormalities in humans.
The study, published in the November 9, 2012 issue of the journal Cell, focuses on the actions of a protein called HDAC4. The researchers found that HDAC4 is critically involved in regulating genes essential for communication between neurons.
“We found that HDAC4 represses these genes, and its function in a given neuron is controlled by activity of other neurons forming a circuit,” said TSRI Assistant Professor Anton Maximov, senior investigator for the study.
Google simulates brain networks to recognize speech and images
This summer Google set a new landmark in the field of artificial intelligence with software that learned how to recognize cats, people, and other things simply by watching YouTube videos (see “Self-Taught Software“).
That technology, modeled on how brain cells operate, is now being put to work making Google’s products smarter, with speech recognition being the first service to benefit, Technology Review reports.
Google’s learning software is based on simulating groups of connected brain cells that communicate and influence one another. When such a neural network, as it’s called, is exposed to data, the relationships between different neurons can change. That causes the network to develop the ability to react in certain ways to incoming data of a particular kind — and the network is said to have learned something.
By studying how birds master songs used in courtship, scientists at Duke University have found that regions of the brain involved in planning and controlling complex vocal sequences may also be necessary for memorizing sounds that serve as models for vocal imitation.
In a paper appearing in the September 2012 issue of the journal Nature Neuroscience, researchers at Duke and Harvard universities observed the imitative vocal learning habits of male zebra finches to pinpoint which circuits in the birds’ brains are necessary for learning their songs.
Knowing which brain circuits are involved in learning by imitation could have broader implications for diagnosing and treating human developmental disorders, the researchers said. The finding shows that the same circuitry used for vocal control also participates in auditory learning, raising the possibility that vocal circuits in our own brain also help encode auditory experience important to speech and language learning.
People who bear the genetic mutation for Huntington’s disease learn faster than healthy people. The more pronounced the mutation was, the more quickly they learned. This is reported by researchers from the Ruhr-Universität Bochum and from Dortmund in the journal Current Biology. The team has thus demonstrated for the first time that neurodegenerative diseases can go hand in hand with increased learning efficiency. “It is possible that the same mechanisms that lead to the degenerative changes in the central nervous system also cause the considerably better learning efficiency” says Dr. Christian Beste, head of the Emmy Noether Junior Research Group “Neuronal Mechanisms of Action Control” at the RUB.
Passive learning through repeated stimulus presentation
In a previous study, the Bochum psychologists reported that the human sense of vision can be changed in the long term by repeatedly exposing subjects to certain visual stimuli for short periods (we reported in May 2011). The task of the participants was to detect changes in the brightness of stimuli. They performed better if they had viewed the stimuli passively for a while first. In the current study, the researchers presented the same task to 29 subjects with the genetic mutation for Huntington’s disease, who, however, did not yet show any symptoms. They also tested 45 control subjects without such mutations in the genome. In both groups, the learning efficiency was better after passive stimulus presentation than without the passive training. Subjects with the Huntington’s mutation, however, increased their performance twice as fast as those without the mutation.
Glutamate may have paradoxical effect
Degenerative diseases of the nervous system are based on complex changes. A key mechanism is an increased release of the neurotransmitter glutamate. However, since glutamate is also important for learning, in some cases it could lead to the paradoxical effect: better learning efficiency despite degeneration of the nerve cells.
Detecting differences in brightness under aggravated conditions
In each experimental run, the subjects saw two consecutive small bars on a computer screen that either had the same or different brightness. Sometimes, however, not only the brightness changed from bar one to bar two, but also the orientation of the bar (vertical or horizontal). “Normally, the distraction stimulus, i.e. the change in orientation, draws all the attention” Christian Beste explains. “But after the passive training with the visual stimuli, the distraction stimulus has no effect at all.” The shift of attention from the non-relevant to the relevant properties of the stimulus was also visible in the electroencephalogram (EEG) in brain areas for early visual processing.
Better performance with stronger mutation
In Huntington’s disease, a short segment of a gene is repeated. The number of repetitions determines when the disease breaks out. In the present study, a greater number of repetitions was, however, also associated with higher learning efficiency. “This shows that neurodegenerative changes can cause paradoxical effects” says Christian Beste. “The everyday view that neurodegenerative changes fundamentally entail deterioration of various functions can no longer be maintained in this dogmatic form.”
Derek Heisler shoots Bill Nye, a beautiful set of portraits for one of our greatest educators. Love the Superman one. Very appropriate, no?
In this Through the Lens I had the opportunity to photograph Bill Nye The Science Guy for the SETI Institute. For most, Bill doesn’t need an introduction. He filled our Saturdays will learning, laughter, and fun. I can definitely say that Bill played a part in my curiosity towards the Sciences.
While chatting on our way to my portrait area, we talked about how technology is affecting the brain. He was exactly how I remember him on TV so many years ago. During the shoot I mentioned that I was also an Engineer and that I had worked with control systems. He immediately perked up and said “I’ve got something for you! Remind me after we’re done”. I was curious like a child again! When we wrapped up the session, he grabbed his laptop and placed it on the table nearby. Without grabbing a chair he kneeled down to get to eye level with his laptop. He then began to explain how he had just been at a conference and someone (I apologize for forgetting his name) had revisited how control loops should be done. It was just a simple change that made increased efficiency of the system. I stepped back and had a fan boyish moment where I realized I was getting a personal Saturday Bill Nye The Science Guy lesson!
Bill is a genuine Educator. He does what he does, because of his passion for Science and sharing knowledge. We can all learn a little from that.