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November 28, 2016
New finding about a protein that enables our brains and muscles to talk, provides new insight into muscular dystrophy
By Toni Baker, Medical College of Georgia, Augusta University
A huge colony of receptors must be optimally positioned and functioning on our muscle cells for our brains to talk with our bodies so we can walk and breathe.
Now scientists have found that a protein believed to help anchor that city of receptors also helps ensure their formation and function and slow their degradation.
The finding provides new insight into how diseases, such as muscular dystrophy, that disconnect brain and body occur, as it points to novel treatment targets, said neuroscientist Dr. Lin Mei. Mei is chairman of the Department of Neuroscience and Regenerative Medicine at the Medical College of Georgia at Augusta University, Georgia Research Alliance Eminent Scholar in Neuroscience and corresponding author of the study in the journal Neuron.
The protein is rapsyn, and the receptors are for acetylcholine, a neurotransmitter that motor neurons release to activate our muscle cells. Rapsyn is made by our muscle cells and considered a sort of biological anchor that interacts with the acetylcholine receptors to ensure that they are optimally positioned for our muscles to receive orders from our brain.
“For precise, efficient synapse function, the receptors have to be extremely highly concentrated at exactly the right place,” Mei said.
The connection, or synapse, the cells form is called the neuromuscular juncture. During development, neurons in the spinal cord reach out to muscle cells to form this direct line of communication. To make that connection, neurons release the protein agrin, which reaches out to LRP4, a protein on the muscle cell surface. This activates MuSK, an enzyme that supports the clustering of receptors on the muscle cell surface that will enable communication.
November 21, 2016
By Toni Baker, Medical College of Georgia, Augusta University
Our brains have a basic algorithm that enables us to not just recognize a traditional Thanksgiving meal, but the intelligence to ponder the broader implications of a bountiful harvest as well as good family and friends.
“A relatively simple mathematical logic underlies our complex brain computations,” said Dr. Joe Z. Tsien, neuroscientist at the Medical College of Georgia at Augusta University, co-director of the Augusta University Brain and Behavior Discovery Institute and Georgia Research Alliance Eminent Scholar in Cognitive and Systems Neurobiology.
Tsien is talking about his Theory of Connectivity, a fundamental principle for how our billions of neurons assemble and align not just to acquire knowledge, but to generalize and draw conclusions from it.
“Intelligence is really about dealing with uncertainty and infinite possibilities,” Tsien said. It appears to be enabled when a group of similar neurons form a variety of cliques to handle each basic like recognizing food, shelter, friends and foes. Groups of cliques then cluster into functional connectivity motifs, or FCMs, to handle every possibility in each of these basics like extrapolating that rice is part of an important food group that might be a good side dish at your meaningful Thanksgiving gathering. The more complex the thought, the more cliques join in.
That means, for example, we cannot only recognize an office chair, but an office when we see one and know that the chair is where we sit in that office.
“You know an office is an office whether it’s at your house or the White House,” Tsien said of the ability to conceptualize knowledge, one of many things that distinguishes us from computers.
Tsien first published his theory in a 1,000-word essay in October 2015 in the journal Trends in Neurosciences. Now he and his colleagues have documented the algorithm at work in seven different brain regions involved with those basics like food and fear in mice and hamsters. Their documentation is published in the journal Frontiers in Systems Neuroscience.
“For it to be a universal principle, it needs to be operating in many neural circuits, so we selected seven different brain regions and, surprisingly, we indeed saw this principle operating in all these regions,” he said.
Intricate organization seems plausible, even essential, in a human brain, which has about 86 billion neurons and where each neuron can have tens of thousands of synapses, putting potential connections and communications between neurons into the trillions. On top of the seemingly endless connections is the reality of the infinite things each of us can presumably experience and learn.
Neuroscientists as well as computer experts have long been curious about how the brain is able to not only hold specific information, like a computer, but – unlike even the most sophisticated technology – to also categorize and generalize the information into abstract knowledge and concepts.
“Many people have long speculated that there has to be a basic design principle from which intelligence originates and the brain evolves, like how the double helix of DNA and genetic codes are universal for every organism,” Tsien said. “We present evidence that the brain may operate on an amazingly simple mathematical logic.”
“In my view, Joe Tsien proposes an interesting idea that proposes a simple organizational principle of the brain, and that is supported by intriguing and suggestive evidence,” said Dr. Thomas C. Südhof, Avram Goldstein Professor in the Stanford University School of Medicine, neuroscientist studying synapse formation and function and a winner of the 2013 Nobel Prize in Physiology or Medicine.
“This idea is very much worth testing further,” said Südhof, a sentiment echoed by Tsien and his colleagues and needed in additional neural circuits as well as other animal species and artificial intelligence systems.
At the heart of Tsien’s Theory of Connectivity is the algorithm, n=2ⁱ-1, which defines how many cliques are needed for an FCM and which enabled the scientists to predict the number of cliques needed to recognize food options, for example, in their testing of the theory.
N is the number of neural cliques connected in different possible ways; 2 means the neurons in those cliques are receiving the input or not; i is the information they are receiving; and -1 is just part of the math that enables you to account for all possibilities, Tsien explained.
To test the theory, they placed electrodes in the areas of the brain so they could “listen” to the response of neurons, or their action potential, and examine the unique waveforms resulting from each.
They gave the animals, for example, different combinations of four different foods, such as usual rodent biscuits as well as sugar pellets, rice and milk, and as the Theory of Connectivity would predict, the scientists could identify all 15 different cliques, or groupings of neurons, that responded to the potential variety of food combinations.
The neuronal cliques appear prewired during brain development because they showed up immediately when the food choices did. The fundamental mathematical rule even remained largely intact when the NMDA receptor, a master switch for learning and memory, was disabled after the brain matured.
The scientists also learned that size does mostly matter, because while the human and animal brain both have a six-layered cerebral cortex – the lumpy outer layer of the brain that plays a key role in higher brain functions like learning and memory – the extra longitudinal length of the human cortex provides more room for cliques and FCMs, Tsien said. And while the overall girth of the elephant brain is definitely larger than the human brain, for example, most of its neurons reside in the cerebellum with far less in their super-sized cerebral cortex. The cerebellum is more involved in muscle coordination, which may help explain the agility of the huge mammal, particularly its trunk.
Tsien noted exceptions to the brain’s mathematical rule, such as in the reward circuits where the dopamine neurons reside. These cells tend to be more binary where we judge, for example, something as either good or bad, Tsien said.
The project grew out of Tsien’s early work in the creation of smart mouse Doogie 17 years ago while on faculty at Princeton University, in studying how changes in neuronal connections lay down memories in the brain.
The research was funded by the National Institutes of Health, a GRA equipment grant, the Yunnan Science Commission and the Chinese Natural Science Foundation. Collaborators include scientists from the University of Georgia, BanNa Biomedical Research Institute in Yunnan Province and Tsinghua University in Beijing, China.
November 18, 2016
By Holly Korschun, Emory University
New eye-tracking measures show that young children with autism do not avoid eye contact on purpose. Instead, they miss the significance of social information that is in others' eyes.
While reduced eye contact is a well-known symptom of autism used in early screeners and diagnostic instruments, why children with autism look less at other people's eyes has not been known. A new study helps answer that question.
"This is important because we're disentangling very different understandings of autism," says Jennifer Moriuchi, a graduate student at Emory University. "Depending on why you think children with autism are making less eye contact, you might have different approaches to treatment and different ideas about the brain basis of autism.
"Drug treatments and behavioral interventions are already being developed and tested on the basis of these different explanations. By clarifying which explanation is correct, we can make sure that we're addressing the correct underlying concern."
Two explanations for reduced eye contact have been proposed. One explanation holds that children with autism avoid eye contact because they find it stressful and negative. The other explanation holds that children with autism look less at other people's eyes because the social cues from the eyes are not perceived as particularly meaningful or important.
The new research, conducted on the day when children were first diagnosed, shows that young children with autism do not actively avoid eye contact, and it confirms that other people's eyes are not aversive to young children with autism. Instead, young children with autism look less at the eyes because they appear to miss the social significance of eye contact.
For the study, published in the American Journal of Psychiatry, researchers looked at how 86 two-year-old children with and without autism paid attention to other people's eyes. Children with autism watched a series of carefully made videos.
"Before each video, we flashed a small picture to capture the child's attention, and when they looked to where the picture had been, they found that they were either looking directly at another person's eyes or looking away from the eyes," Moriuchi says. "When we did this repeatedly, we found that young children with autism continued to look straight at the eyes. Like their peers without autism, they didn't look away from the eyes or try to avoid the eyes in any way."
However, when varying levels of socially meaningful eye contact were presented, children with autism looked less at other people's eyes than their peers without autism.
"These results go against the idea that young children with autism actively avoid eye contact," says coauthor Warren Jones, director of Research at the Marcus Autism Center and faculty in the pediatrics department. "They're looking less at the eyes not because of an aversion to making eye contact, but because they don't appear to understand the social significance of eye contact." Eye gaze responses in young children with autism were studied at the time of their initial diagnosis in order to have clearer evidence about the initial underlying reasons for reduced eye contact. Some adults and older children with autism have reported feeling anxious in response to eye contact.
"Our results aren't meant to contradict these personal experiences," Jones says. "For children with autism, social signals can be confusing. And as children grow up to be adults, those signals can become even more challenging to understand. This research highlights the opportunity to target the right underlying concerns as early as possible."
"Studies like this one help advance our understanding of autism and improve the way scientists and clinicians develop new treatments," says Lisa Gilotty, Chief of the Research Program on Autism Spectrum Disorders at the National Institute of Mental Health, one of the agencies that funded the study. Additional support was given by the Autism Science Foundation, the Marcus Foundation, the Whitehead Foundation, and the Georgia Research Alliance.