Posts tagged neuronal activity
Articles and news from the latest research reports.
How chronic pain disrupts short term memory
A group of Portuguese researchers from IBMC and FMUP at the University of Porto has found the reason why patients with chronic pain often suffer from impaired short –term memory. The study, to be published in the Journal of Neuroscience, shows how persistent pain disrupts the flow of information between two brain regions crucial to retain temporary memories.
Chronic pain suffers often complain of short term memory’s problems. The neural mechanisms why this occurs are however not understood. Recent studies in animals showed that pain can disturb several cognitive processes as well as change the brain pathways for how we think and feel. Of the many cognitive disturbances observed the most important include problems in spatial memory, recognition memory, attention and even emotional and non-emotional decisions.
In the new article the team of researchers from the University of Porto led by Vasco Gallardo describes in a rat model of neuropathic pain how a neuronal circuit crucial for the processing of short-term memory is affected by pain. The circuit, established between the prefrontal cortex and the hippocampus, is essential for encoding and retaining temporary memories on spatial information. The researchers used multi-electrodes implanted in the brain to record neuronal activity during a behaviour dependent of spatial memory - the animals were trained in a maze where they had to choose between two alternative paths and then asked to recall their chosen path.
The results show that after a painful injury there is a significant reduction in the amount of information that passes through the circuit. This could mean a loss of ability to process information on spatial localization memory, or that those regions critical to memory are now “overwhelmed” by the painful stimuli disrupting the flow of information for memory.
According to Vasco Gallardo, the team ” has already demonstrated that peripheral nerve injury induces an instability in the spatial coding capacity of hippocampus neurons “, where is seen “a clear reduction in their capacity to encode information on the location of the animal.”
So to the author “this new work contributes to the demonstration that chronic pain induces alterations in the function of brain circuits that are not directly connected to tactile or painful processes”. So as a result of chronic pain it is seen that “are also affected neuronal circuits linked to the processing of memories and emotions, what might mean a need for larger and more integrative strategies in the treatment of painful pathologies”, says the researcher.
Astrocytes Identified as Target for New Depression Therapy
Neuroscience researchers from Tufts University have found that our star-shaped brain cells, called astrocytes, may be responsible for the rapid improvement in mood in depressed patients after acute sleep deprivation. This in vivo study, published in the current issue of Translational Psychiatry, identified how astrocytes regulate a neurotransmitter involved in sleep. The researchers report that the findings may help lead to the development of effective and fast-acting drugs to treat depression, particularly in psychiatric emergencies.
Drugs are widely used to treat depression, but often take weeks to work effectively. Sleep deprivation, however, has been shown to be effective immediately in approximately 60% of patients with major depressive disorders. Although widely-recognized as helpful, it is not always ideal because it can be uncomfortable for patients, and the effects are not long-lasting.
During the 1970s, research verified the effectiveness of acute sleep deprivation for treating depression, particularly deprivation of rapid eye movement sleep, but the underlying brain mechanisms were not known.
Most of what we understand of the brain has come from research on neurons, but another type of largely-ignored cell, called glia, are their partners. Although historically thought of as a support cell for neurons, the Phil Haydon group at Tufts University School of Medicine has shown in animal models that a type of glia, called astrocytes, affect behavior.
Haydon’s team had established previously that astrocytes regulate responses to sleep deprivation by releasing neurotransmitters that regulate neurons. This regulation of neuronal activity affects the sleep-wake cycle. Specifically, astrocytes act on adenosine receptors on neurons. Adenosine is a chemical known to have sleep-inducing effects.
During our waking hours, adenosine accumulates and increases the urge to sleep, known as sleep pressure. Chemicals, such as caffeine, are adenosine receptor antagonists and promote wakefulness. In contrast, an adenosine receptor agonist creates sleepiness.
“In this study, we administered three doses of an adenosine receptor agonist to mice over the course of a night that caused the equivalent of sleep deprivation. The mice slept as normal, but the sleep did not reduce adenosine levels sufficiently, mimicking the effects of sleep deprivation. After only 12 hours, we observed that mice had decreased depressive-like symptoms and increased levels of adenosine in the brain, and these results were sustained for 48 hours,” said first author Dustin Hines, Ph.D., a post-doctoral fellow in the department of neuroscience at Tufts University School of Medicine (TUSM).
“By manipulating astrocytes we were able to mimic the effects of sleep deprivation on depressive-like symptoms, causing a rapid and sustained improvement in behavior,” continued Hines.
“Further understanding of astrocytic signaling and the role of adenosine is important for research and development of anti-depressant drugs. Potentially, new drugs that target this mechanism may provide rapid relief for psychiatric emergencies, as well as long-term alleviation of chronic depressive symptoms,” said Naomi Rosenberg, Ph.D., dean of the Sackler School of Graduate Biomedical Sciences and vice dean for research at Tufts University School of Medicine. “The team’s next step is to further understand the other receptors in this system and see if they, too, can be affected.”
(Image: Paul De Koninck)
Newly found ‘volume control’ in the brain promotes learning, memory
Scientists have long wondered how nerve cell activity in the brain’s hippocampus, the epicenter for learning and memory, is controlled — too much synaptic communication between neurons can trigger a seizure, and too little impairs information processing, promoting neurodegeneration. Researchers at Georgetown University Medical Center say they now have an answer. In the January 10 issue of Neuron, they report that synapses that link two different groups of nerve cells in the hippocampus serve as a kind of “volume control,” keeping neuronal activity throughout that region at a steady, optimal level.
"Think of these special synapses like the fingers of God and man touching in Michelangelo’s famous fresco in the Sistine Chapel," says the study’s senior investigator, Daniel Pak, PhD, an associate professor of pharmacology. "Now substitute the figures for two different groups of neurons that need to perform smoothly. The touching of the fingers, or synapses, controls activity levels of neurons within the hippocampus."
The hippocampus is a processing unit that receives input from the cortex and consolidates that information in terms of learning and memory. Neurons known as granule cells, located in the hippocampus’ dentate gyrus, receive transmissions from the cortex. Those granule cells then pass that information to the other set of neurons (those in the CA3 region of the hippocampus, in this study) via the synaptic fingers.
Those fingers dial up, or dial down, the volume of neurotransmission from the granule cells to the CA3 region to keep neurotransmission in the learning and memory areas of the hippocampus at an optimal flow — a concept known as homeostatic plasticity. “If granule cells try to transmit too much activity, we found, the synaptic junction tamps down the volume of transmission by weakening their connections, allowing the proper amount of information to travel to CA3 neurons,” says Pak. “If there is not enough activity being transmitted by the granule cells, the synapses become stronger, pumping up the volume to CA3 so that information flow remains constant.”
There are many such touching fingers in the hippocampus, connecting the so-called “mossy fibers” of the granule cells to neurons in the CA3 region. But importantly, not every one of the billions of neurons in the hippocampus needs to set its own level of transmission from one nerve cell to the other, says Pak.
To explain, he uses another analogy. “It had previously been thought that neurons act separately like cars, each working to keep their speed at a constant level even though signal traffic may be fast or slow. But we wondered how these neurons could process learning and memory information efficiently, while also regulating the speed by which they process and communicate that information.
"We believe, based on our study, that only the mossy fiber synapses on the CA3 neurons control the level of activity for the hippocampus — they are like the engine on a train that sets the speed for all the other cars, or neurons, attached to it," Pak says. "That frees up the other neurons to do the job they are tasked with doing — processing and encoding information in the forms of learning and memory."
Not only does the study offer a new model for how homeostatic plasticity in the hippocampus can co-exist with learning and memory, it also suggests a new therapeutic avenue to help patients with uncontrollable seizures, he says.
"The CA3 region is highly susceptible to seizures, so if we understand how homeostasis is maintained in these neurons, we could potentially manipulate the system. When there is an excessive level of CA3 neuronal activity in a patient, we could learn how to therapeutically turn it down."
(Source: eurekalert.org)
How Neuroscientists Observe Brains Watching Movies
Unless you have been deaf and blind to the world over the past decade, you know that functional magnetic resonance brain imaging (fMRI) can look inside the skull of volunteers lying still inside the claustrophobic, coffinlike confines of a loud, banging magnetic scanner. The technique relies on a fortuitous property of the blood supply to reveal regional activity. Active synapses and neurons consume power and therefore need more oxygen, which is delivered by the hemoglobin molecules inside the circulating red blood cells. When these molecules give off their oxygen to the surrounding tissue, they not only change color—from arterial red to venous blue—but also turn slightly magnetic.
(Image: Todd Davidson/Stock Illustration Source)
Activity in neural tissue causes an increase in the volume and flow of fresh blood. This change in the blood supply, called the hemodynamic signal, is tracked by sending radio waves into the skull and carefully listening to their return echoes. FMRI does not directly measure synaptic and neuronal activity, which occurs over the course of milliseconds; instead it uses a relatively sluggish proxy—changes in the blood supply—that rises and falls in seconds. The spatial resolution of fMRI is currently limited to a volume element (voxel) the size of a pea, encompassing about one million nerve cells.
Neuroscientists routinely exploit fMRI to infer what volunteers are seeing, imagining or intending to do. It is really a primitive form of mind reading. Now a team has taken that reading to a new, startling level.
A number of groups have deduced the identity of pictures viewed by volunteers while lying in the magnet scanner from the slew of maplike representations found in primary, secondary and higher-order visual cortical regions underneath the bump on the back of the head.
Jack L. Gallant of the University of California, Berkeley, is the acknowledged master of these techniques, which proceed in two stages. First, a volunteer looks at a couple of thousand images while lying in a magnet. The response of a few hundred voxels in the visual cortex to each image is carefully registered. These data are then used to train an algorithm to predict the magnitude of the fMRI response for each voxel. Second, this procedure is inverted. That is, for a given magnitude of hemodynamic response, a probabilistic technique called Bayesian decoding infers the most likely image that gave rise to the observed response in that particular volunteer (human brains differ substantially, so it is difficult to use one brain to predict the responses of another).
The best of these techniques exploit preexisting, or prior, knowledge about pictures that could have been seen before. The number of mathematically possible images is vast, but the types of actual scenes that are encountered in a world populated by people, animals, trees, buildings and other objects encompass a tiny fraction of all possible images. Appropriately enough, the images that we usually encounter are called natural images. Using a database of six million natural images, Gallant’s group showed in 2009 how brain responses of volunteers to photographs they had not previously encountered could be reconstructed.
(Source: scientificamerican.com)
Brain study provides new insight into why haste makes waste
Why do our brains make more mistakes when we act quickly?
A new study demonstrates how the brain follows Ben Franklin’s famous dictum, “Take time for all things: great haste makes great waste.”
The research – conducted by Research Assistant Professor Richard Heitz and Jeffrey Schall, Ingram Professor of Neuroscience, at Vanderbilt University – has found that the brain actually switches into a special mode when pushed to make rapid decisions.
The study was published Nov. 7 in the journal Neuron.
A glance at the brain’s circuit diagram
The human brain accomplishes its remarkable feats through the interplay of an unimaginable number of neurons that are interconnected in complex networks. A team of scientists from the Max Planck Institute for Dynamics and Self-Organization, the University of Göttingen and the Bernstein Center for Computational Neuroscience Göttingen has now developed a method for decoding neural circuit diagrams. Using measurements of total neuronal activity, they can determine the probability that two neurons are connected with each other.