Posts tagged neuronal networks
Articles and news from the latest research reports.
Common gene known to cause inherited autism now linked to specific behaviors
The genetic malady known as Fragile X syndrome is the most common cause of inherited autism and intellectual disability. Brain scientists know the gene defect that causes the syndrome and understand the damage it does in misshaping the brain’s synapses — the connections between neurons. But how this abnormal shaping of synapses translates into abnormal behavior is unclear.
Now, researchers at UCLA believe they know. Using a mouse model of Fragile X syndrome (FXS), they recorded the activity of networks of neurons in a living mouse brain while the animal was awake and asleep. They found that during both sleep and quiet wakefulness, these neuronal networks showed too much activity, firing too often and in sync, much more than a normal brain.
This neuronal excitability, the researchers said, may be the basis for symptoms in children with FXS, which can include disrupted sleep, seizures or learning disabilities. The findings may lead to treatments that could quiet the excessive activity and allow for more normal behavior.
The study results are published in the June 2 online edition of the journal Nature Neuroscience.
According to the National Fragile X Foundation, approximately one in every 3,600 to 4,000 males has the disorder, as does one in 4,000 to 6,000 females. FXS is caused by a mutation in the gene FMR1, which encodes the fragile X mental retardation protein, or FMRP. That protein is believed to be important for the formation and regulation of synapses. Mice that lack the FMR1 gene — and therefore lack the FMRP protein — show some of the same symptoms of human FXS, including seizures, impaired sleep, abnormal social relationships and learning defects.
"We wanted to find the link between the abnormal structure of synapses in the FXS mouse and the behavioral abnormalities at the level of brain circuits. That had not been previously established," said senior author Dr. Carlos Portera-Cailliau, an associate professor in the departments of neurology and neurobiology at UCLA. " So we tested the signaling between different neurons in Fragile X mice and indeed found there was abnormally high firing of action potentials — the signals between neurons — and also abnormally high synchrony — that is, too many neurons fired together. That’s a feature that is common in early brain development, but not in the adult."
"In essence, this points to a relative immaturity of brain circuits in FXS," added Tiago Gonçalves, a former postdoctoral researcher in Portera-Cailliau’s laboratory and the first author of the study.
The researchers used two-photon calcium imaging and patch-clamp electrophysiology — two sophisticated technologies that allowed them to record the signals from individual brain cells. Abnormally high firing and network synchrony, said Portera-Cailliau, is evidence of the fact that neuronal circuits are overexcitable in FXS.
"That likely leads to aberrant brain function or impairments in the normal computations of the brain," he said. "For example, high synchrony could lead to seizures; more neurons firing together could cause entire portions of the brain to fire synchronously, which is the basis of seizures."
And epilepsy, Portera-Cailliau said, is seen in up to 20 percent of children with FXS. High firing rates could also impair the ability of the brain to decode sensory stimuli by causing an overwhelming response to even simple sensory stimuli; this could lead to autism and the withdrawal from social interactions, he noted.
"Interestingly, we found that the high firing and synchrony were especially apparent at times when the animals were asleep," said Portera-Cailliau. "This is curious because a prominent symptom of FXS is disrupted sleep and frequent awakenings."
And, he noted, since sleep is important for encoding memories and consolidating learning, this hyperexcitability of brain networks in FXS may interfere with the process of laying down new memories, and perhaps explain the learning disability in children with FXS.
"Because brain scientists know a lot about the factors that regulate neuronal excitability, including inhibitory neurons, they can now try to use a variety of strategies to dampen neuronal excitation," he said. "Hopefully, this may be helpful to treat symptoms of FXS."
The next step, said Portera-Cailliau, is to explore whether Fragile X mice indeed exhibit exaggerated responses to sensory stimuli.
"An overwhelming reaction to a slight sound or caress, or hyperarousal to sensory stimuli, could be common to different types of autism and not just FXS," he said. "If hyperexcitability is the brain-network basis for these symptoms, then reducing neuronal excitability with certain drugs that modulate inhibition could be of therapeutic value in these devastating neurodevelopmental disorders."
How the brain forms categories
Neurobiologists at the Research Institute of Molecular Pathology (IMP) in Vienna investigated how the brain is able to group external stimuli into stable categories. They found the answer in the discrete dynamics of neuronal circuits. The journal Neuron publishes the results in its current issue.
How do we manage to recognize a friend’s face, regardless of the light conditions, the person’s hairstyle or make-up? Why do we always hear the same words, whether they are spoken by a man or woman, in a loud or soft voice? It is due to the amazing skill of our brain to turn a wealth of sensory information into a number of defined categories and objects. The ability to create constants in a changing world feels natural and effortless to a human, but it is extremely difficult to train a computer to perform the task.
At the IMP in Vienna, neurobiologist Simon Rumpel and his post-doc Brice Bathellier have been able to show that certain properties of neuronal networks in the brain are responsible for the formation of categories. In experiments with mice, the researchers produced an array of sounds and monitored the activity of nerve cell-clusters in the auditory cortex. They found that groups of 50 to 100 neurons displayed only a limited number of different activity-patterns in response to the different sounds.
The scientists then selected two basis sounds that produced different response patterns and constructed linear mixtures from them. When the mixture ratio was varied continuously, the answer was not a continuous change in the activity patters of the nerve cells, but rather an abrupt transition. Such dynamic behavior is reminiscent of the behavior of artificial attractor-networks that have been suggested by computer scientists as a solution to the categorization problem.
The findings in the activity patters of neurons were backed up by behavioral experiments with mice. The animals were trained to discriminate between two sounds. They were then exposed to a third sound and their reaction was tracked. Whether the answer to the third tone was more like the reaction to the first or the second one, was used as an indicator of the similarity of perception. By looking at the activity patters in the auditory cortex, the scientists were able to predict the reaction of the mice.
The new findings that are published in the current issue of the journal Neuron, demonstrate that discrete network states provide a substrate for category formation in brain circuits. The authors suggest that the hierarchical structure of discrete representations might be essential for elaborate cognitive functions such as language processing.
(Source: alphagalileo.org)
Specific regions of the hippocampus connected to discrete steps of task mastery, study finds
In a study published in Nature Neuroscience, neurobiologists from the Friedrich Miescher Institute for Biomedical Research have been linking synapse formation in the hippocampus to distinct learning steps. They show how different regions of the hippocampus have specific and sequential functions in the mastery of a complex task.
The setup is natural. The mouse finds herself in the water and is looking for a dry place. But how does she solve this task? And what happens if she finds herself in the same situation again? Here is what the scientists observed: At the beginning, the mouse swims all around the little pool, randomly searching for the platform. After two days, there is a change in search approach: The mouse has learned where about the platform is and will start to search right away in the area of the platform. Finally, after another five days, the mouse knows exactly where the platform is and swims directly for it. What is astonishing is that every mouse behaves same way and all the mice learn to find the platform in about the same time, through the same trial and error search strategy stages.
Pico Caroni, senior group leader at the Friedrich Miescher Institute for Biomedical Research, and his team not only described for the first time how mice learn to master such a complex task step by step, but they have also been able to show how one region of the brain, the hippocampus, is engaged in these learning processes. The hippocampus is the region of the brain that is the relay station for a lot of sensory information. In this function, the hippocampus is extremely important for learning and the consolidation of memory. The hippocampus can be divided into three areas termed ventral (vH), intermediate (iH) and dorsal hippocampus (dH). Even though the composition of the neuronal networks in each area is comparable, they differ in gene expression, connectivity, tuning and function.
Caroni and his team could now show that this difference has functional implications in learning. It has been known that during learning new synapses are formed in the hippocampus by so called mossy fibers. In their study published in Nature Neuroscience the scientists show that each search strategy, each level of learning, is associated with a different region of the hippocampus. First, mossy fiber synapses are formed in vH. With the first change in search strategy, mossy fiber formation moves to iH. The mice now have a clear understanding of the relative position of the platform, e.g. distance from the pool wall. Finally, synapse formation moves to dH. By now the mouse has a clear map of the pool, the platform and her position in these surroundings. From now on the mouse will always know where the platform is and will directly head for it.
"We believe that many complex learning tasks are achieved through sub-tasks and that the three areas of the hippocampus are involved in similar ways," comments Caroni. "Our experiments indicate further that this approach is innate, which indicates that similar processes may play as we learn to bike or become proficient in playing tennis."
(Source: medicalxpress.com)