Posts tagged brain networks
Articles and news from the latest research reports.
Speedier scans reveal new distinctions in resting and active brain
A boost in the speed of brain scans is unveiling new insights into how brain regions work with each other in cooperative groups called networks.
Scientists at Washington University School of Medicine in St. Louis and the Institute of Technology and Advanced Biomedical Imaging at the University of Chieti, Italy, used the quicker scans to track brain activity in volunteers at rest and while they watched a movie.
“Brain activity occurs in waves that repeat as slowly as once every 10 seconds or as rapidly as once every 50 milliseconds,” said senior researcher Maurizio Corbetta, MD, the Norman J. Stupp Professor of Neurology. “This is our first look at these networks where we could sample activity every 50 milliseconds, as well as track slower activity fluctuations that are more similar to those observed with functional magnetic resonance imaging (fMRI). This analysis performed at rest and while watching a movie provides some interesting and novel insights into how these networks are configured in resting and active brains.”
Understanding how brain networks function is important for better diagnosis and treatment of brain injuries, according to Corbetta.
The study appears online in Neuron.
Researchers know of several resting-state brain networks, which are groups of different brain regions whose activity levels rise and fall in sync when the brain is at rest. Scientists used fMRI to locate and characterize these networks, but the relative slowness of this approach limited their observations to activity that changes every 10 seconds or so. A surprising result from fMRI was that the spatial pattern of activity (or topography) of these brain networks is similar at rest and during tasks.
In contrast, a faster technology called magnetoencephalography (MEG) can detect activity at the millisecond level, letting scientists examine waves of activity in frequencies from slow (0.1-4 cycles per second) to fast (greater than 50 cycles per second).
“Interestingly, even when we looked at much higher temporal resolution, brain networks appear to fluctuate on a relatively slow time scale,” said first author Viviana Betti, PhD, a postdoctoral researcher at Chieti. “However, when the subjects went from resting to watching a movie, the networks appeared to shift the frequency channels in which they operate, suggesting that the brain uses different frequencies for rest and task, much like a radio.”
In the study, the scientists asked one group of volunteers to either rest or watch the movie during brain scans. A second group was asked to watch the movie and look for event boundaries, moments when the plot or characters or other elements of the story changed. They pushed a button when they noticed these changes.
As in previous studies, most subjects recognized similar event boundaries in the movie. The MEG scans showed that the communication between regions in the visual cortex was altered near the movie boundaries, especially in networks in the visual cortex.
“This gives us a hint of how cognitive activity dynamically changes the resting-state networks,” Corbetta said. “Activity locks and unlocks in these networks depending on how the task unfolds. Future studies will need to track resting-state networks in different tasks to see how correlated activity is dynamically coordinated across the brain.”
(Source: news.wustl.edu)
Daydreaming simulated by computer model
Scientists have created a virtual model of the brain that daydreams like humans do.
Researchers created the computer model based on the dynamics of brain cells and the many connections those cells make with their neighbors and with cells in other brain regions. They hope the model will help them understand why certain portions of the brain work together when a person daydreams or is mentally idle. This, in turn, may one day help doctors better diagnose and treat brain injuries.
“We can give our model lesions like those we see in stroke or brain cancer, disabling groups of virtual cells to see how brain function is affected,” said senior author Maurizio Corbetta, MD, the Norman J. Stupp Professor of Neurology at Washington University School of Medicine in St. Louis. “We can also test ways to push the patterns of activity back to normal.”
The study is now available online in The Journal of Neuroscience.
The model was developed and tested by scientists at Washington University School of Medicine in St. Louis, Universitat Pompeu Fabra in Barcelona, Spain, and several other European universities including ETH Zurich, Switzerland; University of Oxford, United Kingdom; Institute of Advanced Biomedical Technologies, Chieti, Italy; and University of Lausanne, Switzerland.
Scientists first recognized in the late 1990s and early 2000s that the brain stays busy even when it’s not engaged in mental tasks. Researchers have identified several “resting state” brain networks, which are groups of different brain regions that have activity levels that rise and fall in sync when the brain is at rest. They have also linked disruptions in networks associated with brain injury and disease to cognitive problems in memory, attention, movement and speech.
The new model was developed to help scientists learn how the brain’s anatomical structure contributes to the creation and maintenance of resting state networks. The researchers began with a process for simulating small groups of neurons, including factors that decrease or increase the likelihood that a group of cells will send a signal.
“In a way, we treated small regions of the brain like cognitive units: not as individual cells but as groups of cells,” said Gustavo Deco, PhD, professor and head of the Computational Neuroscience Group in Barcelona. “The activity of these cognitive units sends out excitatory signals to the other units through anatomical connections. This makes the connected units more or less likely to synchronize their signals.”
Based on data from brain scans, researchers assembled 66 cognitive units in each hemisphere, and interconnected them in anatomical patterns similar to the connections present in the brain.
Scientists set up the model so that the individual units went through the signaling process at random low frequencies that had previously been observed in brain cells in culture and in recordings of resting brain activity.
Next, researchers let the model run, slowly changing the coupling, or the strength of the connections between units. At a specific coupling value, the interconnections between units sending impulses soon began to create coordinated patterns of activity.
“Even though we started the cognitive units with random low activity levels, the connections allowed the units to synchronize,” Deco said. “The spatial pattern of synchronization that we eventually observed approximates very well—about 70 percent—to the patterns we see in scans of resting human brains.”
Using the model to simulate 20 minutes of human brain activity took a cluster of powerful computers 26 hours. But researchers were able to simplify the mathematics to make it possible to run the model on a typical computer.
“This simpler whole brain model allows us to test a number of different hypotheses on how the structural connections generate dynamics of brain function at rest and during tasks, and how brain damage affects brain dynamics and cognitive function,” Corbetta said.
Has evolution given humans unique brain structures?
Humans have at least two functional networks in their cerebral cortex not found in rhesus monkeys. This means that new brain networks were likely added in the course of evolution from primate ancestor to human. These findings, based on an analysis of functional brain scans, were published in a study by neurophysiologist Wim Vanduffel (KU Leuven and Harvard Medical School) in collaboration with a team of Italian and American researchers.
Our ancestors evolutionarily split from those of rhesus monkeys about 25 million years ago. Since then, brain areas have been added, have disappeared or have changed in function. This raises the question, ‘Has evolution given humans unique brain structures?’. Scientists have entertained the idea before but conclusive evidence was lacking. By combining different research methods, we now have a first piece of evidence that could prove that humans have unique cortical brain networks.
Professor Vanduffel explains: “We did functional brain scans in humans and rhesus monkeys at rest and while watching a movie to compare both the place and the function of cortical brain networks. Even at rest, the brain is very active. Different brain areas that are active simultaneously during rest form so-called ‘resting state’ networks. For the most part, these resting state networks in humans and monkeys are surprisingly similar, but we found two networks unique to humans and one unique network in the monkey.”
“When watching a movie, the cortex processes an enormous amount of visual and auditory information. The human-specific resting state networks react to this stimulation in a totally different way than any part of the monkey brain. This means that they also have a different function than any of the resting state networks found in the monkey. In other words, brain structures that are unique in humans are anatomically absent in the monkey and there no other brain structures in the monkey that have an analogous function. Our unique brain areas are primarily located high at the back and at the front of the cortex and are probably related to specific human cognitive abilities, such as human-specific intelligence.”
The study used fMRI (functional Magnetic Resonance Imaging) scans to visualise brain activity. fMRI scans map functional activity in the brain by detecting changes in blood flow. The oxygen content and the amount of blood in a given brain area vary according to a particular task, thus allowing activity to be tracked.
Neuroscientists are trying to work out why the brain does so much when it seems to be doing nothing at all.
For volunteers, a brain-scanning experiment can be pretty demanding. Researchers generally ask participants to do something — solve mathematics problems, search a scene for faces or think about their favoured political leaders — while their brains are being imaged.
But over the past few years, some researchers have been adding a bit of down time to their study protocols. While subjects are still lying in the functional magnetic resonance imaging (fMRI) scanners, the researchers ask them to try to empty their minds. The aim is to find out what happens when the brain simply idles. And the answer is: quite a lot.
Alzheimer’s breaks brain networks’ coordination
Scientists at Washington University School of Medicine in St. Louis have taken one of the first detailed looks into how Alzheimer’s disease disrupts coordination among several of the brain’s networks. The results, reported in The Journal of Neuroscience, include some of the earliest assessments of Alzheimer’s effects on networks that are active when the brain is at rest.
“Until now, most research into Alzheimer’s effects on brain networks has either focused on the networks that become active during a mental task, or the default mode network, the primary network that activates when a person is daydreaming or letting the mind wander,” says senior author Beau Ances, MD, assistant professor of neurology. “There are, however, a number of additional networks besides the default mode network that become active when the brain is idling and could tell us important things about Alzheimer’s effects.”
Ances and his colleagues analyzed brain scans of 559 subjects. Some of these subjects were cognitively normal, while others were in the early stages of very mild to mild Alzheimer’s disease. Scientists found that all of the networks they studied eventually became impaired during the initial stages of Alzheimer’s.
“Communications within and between networks are disrupted, but it doesn’t happen all at once,” Ances says. “There’s even one network that has a momentary surge of improved connections before it starts dropping again. That’s the salience network, which helps you determine what in your environment you need to pay attention to.”
Other networks studied by the researchers included:
- the dorsal attention network, which directs attention toward things in the environment that are salient;
- the control network, believed to be active in consciousness and decision-making; and
- the sensory-motor network, which integrates the brain’s control of body movements with sensory feedback (e.g., did the finger that just moved strike the right piano key?).
Scientists also examined Alzheimer’s effects on a brain networking property known as anti-correlations. Researchers identify networks by determining which brain areas frequently become active at the same time, but anti-correlated networks are noteworthy for the way their activities fluctuate: when one network is active, the other network is quiet. This ability to switch back-and-forth between networks is significantly diminished in participants with mild to moderate Alzheimer’s disease.
The default mode network, previously identified as one of the first networks to be impaired by Alzheimer’s, is a partner in two of the three pairs of anti-correlated networks scientist studied.
“While we can’t prove this yet, one hypothesis is that as things go wrong in the processing of information in the default mode network, that mishandled data is passed on to other networks, where it creates additional problems,” Ances says.
It’s not practical to use these network breakdowns to clinically diagnose Alzheimer’s disease, Ances notes, but they may help track the development of the disease and aid efforts to better understand its spread through the brain.
Ances plans to look at other markers for Alzheimer’s disease in the same subjects, such as levels in the cerebrospinal fluid of amyloid beta, a major component of Alzheimer’s plaques.
(Source: news.wustl.edu)