Posts tagged neural synchrony

Posts tagged neural synchrony
A 350-year-old mathematical mystery could lead toward a better understanding of medical conditions like epilepsy or even the behavior of predator-prey systems in the wild, University of Pittsburgh researchers report.
The mystery dates back to 1665, when Dutch mathematician, astronomer, and physicist Christiaan Huygens, inventor of the pendulum clock, first observed that two pendulum clocks mounted together could swing in opposite directions. The cause was tiny vibrations in the beam caused by both clocks, affecting their motions.
The effect, now referred to by scientists as “indirect coupling,” was not mathematically analyzed until nearly 350 years later, and deriving a formula that explains it remains a challenge to mathematicians still. Now, Pitt professors apply this principle to measure the interaction of “units”—such as neurons, for example—that turn “off” and “on” repeatedly. Their findings are highlighted in the latest issue of Physical Review Letters.
“We have developed a mathematical approach to better understanding the ‘ingredients’ in a system that affect synchrony in a number of medical and ecological conditions,” said Jonathan E. Rubin, coauthor of the study and professor in Pitt’s Department of Mathematics within the Kenneth P. Dietrich School of Arts and Sciences. “Researchers can use our ideas to generate predictions that can be tested through experiments.”
More specifically, the researchers believe the formula could lead toward a better understanding of conditions like epilepsy, in which neurons become overly active and fail to turn off, ultimately leading to seizures. Likewise, it could have applications in other areas of biology, such as understanding how bacteria use external cues to synchronize growth.
Together with G. Bard Ermentrout, University Professor of Computational Biology and professor in Pitt’s Department of Mathematics, and Jonathan J. Rubin, an undergraduate mathematics major, Jonathan E. Rubin examined these forms of indirect communication that are not typically included in most mathematical studies owing to their complicated elements. In addition to studying neurons, the Pitt researchers applied their methods to a model of artificial gene networks in bacteria, which are used by experimentalists to better understand how genes function.
“In the model we studied, the genes turn off and on rhythmically. While on, they lead to production of proteins and a substance called an autoinducer, which promotes the genes turning on,” said Jonathan E. Rubin. “Past research claimed that this rhythm would occur simultaneously in all the cells. But we show that, depending on the speed of communication, the cells will either go together or become completely out of synch with each another.”
To apply their formula to an epilepsy model, the team assumed that neurons oscillate, or turn off and on in a regular fashion. Ermentrout compares this to Southeast Asian fireflies that flash rhythmically, encouraging synchronization.
“For neurons, we have shown that the slow nature of these interactions encouraged ‘asynchrony,’ or firing at different parts of the cycle,” Ermentrout said. “In these seizure-like states, the slow dynamics that couple the neurons together are such that they encourage the neurons to fire all out of phase with each other.”
The Pitt researchers believe this approach may extend beyond medical applications into ecology—for example, a situation in which two independent animal groups in a common environment communicate indirectly. Jonathan E. Rubin illustrates the idea by using a predator-prey system, such as rabbits and foxes.
“With an increase in rabbits will come an increase in foxes, as they’ll have plenty of prey,” said Jonathan E. Rubin. “More rabbits will get eaten, but eventually the foxes won’t have enough to eat and will die off, allowing the rabbit numbers to surge again. Voila, it’s an oscillation. So, if we have a fox-rabbit oscillation and a wolf-sheep oscillation in the same field, the two oscillations could affect each other indirectly because now rabbits and sheep are both competing for the same grass to eat.”
(Source: news.pitt.edu)

Neuroscience Research Project Examines Neural Synchronization Patterns During Addiction
A cross-disciplinary collaboration of researchers in the School of Science at Indiana University-Purdue University Indianapolis (IUPUI) explores the neural synchrony between circuits in the brain and their behavior under simulated drug addiction. The two-year study could have broad implications for treating addiction and understanding brain function in conditions such as Parkinson’s disease.
Advanced mathematical models coupled with extensive laboratory testing revealed recurrent stimulant injections in rodents resulted in neural circuits that could easily synchronize but were more likely to become unstable. In other words, the introduction and restriction of drugs over time caused neurons to lose their ability to engage supervisory control over brain function and behavior. Researchers noticed these short periods of desynchronization were much more prevalent and caused changes in neurobiology and behavior.
“A better understanding of the dynamics of neural synchrony could have very important implications for understanding the addicted brain and may provide a physiological target to understand persistent neural changes that contribute to the probability of relapse,” said Christopher Lapish, Ph.D., assistant professor of psychology at IUPUI.
Lapish, with expertise in neurophysiology and addiction, and Leonid Rubchinsky, Ph.D., associate professor of mathematical sciences, collaborated on the project with support from the IUPUI Institute for Mathematical Modeling and Computational Science. Rubchinsky is an applied mathematician and neuroscientist who has extensively studied the neurophysiology of Parkinson’s disease.
Sungwoo Ahn, Ph.D., a post-doctoral fellow in mathematical sciences, also co-authored the study, recently published in the Cerebral Cortex scientific journal.
The research was patterned after the various stages of drug addiction: the first introduction of amphetamines, periods of abstinence that model withdrawal and then relapse.
The neural synchrony patterns of models injected with a stimulant were compared to those injected with a saline solution. Short periods of desychronization were prevalent in both groups, but the drug-affected group displayed a marked connection between synchrony and brain function. Synchrony has long been considered to play an important role in how the brain processes data, so any disruption of this pattern could hold significant research value, according to the published study.
“Through these long and progressive experimental examinations, we were able to explore the different areas of the brain and how they are connected to each other,” Rubchinsky said. “In addition to understanding, monitoring, diagnosing and treating addiction, this type of study is helpful in better understanding how the normal brain works.”
This collaboration moves scientists closer to understanding brain function and disruptions, Rubchinsky said, by incorporating mathematical models that recreate events and reactions in the brain over time. Lapish agreed, saying computational science ultimately will drive the growth and success of future neuroscience research.
“Neuroscience is an inherently data-rich science and, by combining experimentalists with theorists, there is a tremendous potential for discovery,” Lapish. “The interactive effects of this collaboration are certainly greater than the sum of its parts. We’re able to create a fully dynamic picture of this process that would not be possible without combining these two areas of expertise.”
Moving forward, the team will continue to seek funding to advance their research methods and better understand the role of synchrony in brain function. By doing so, scientists could map the progress and deterioration of neural circuits in various scenarios.
New research sheds light on how the brain encodes objects with multiple features, a fundamental task for the perceptual system. The study, published in Psychological Science, a journal of the Association for Psychological Science, suggests that we have limited ability to perceive mixed color-shape associations among objects that exist in several locations.
Research suggests that neurons that encode a certain feature — shape or color, for example — fire in synchrony with neurons that encode other features of the same object. Psychological scientists Liat Goldfarb of the University of Haifa and Anne Treisman of Princeton University hypothesized that if this neural-synchrony explanation were true, then synchrony would be impossible in situations in which the same features are paired differently in different objects.
Say, for example, a person sees a string of letters, “XOOX,” and the letters are printed in alternating colors, red and green. Both letter shape and letter color need to be encoded, but the associations between letter shape and letter color are mixed (i.e., the first X is red, while the second X is green), which should make neural synchrony impossible.
“The perceptual system can either know how many Xs there are or how many reds there are, but it cannot know both at the same time,” Goldfarb and Treisman explain.
The researchers investigated their hypothesis in two experiments, in which they presented participants with strings of green and red Xs and Os and asked them to compare the number of Xs with the number of red letters (i.e., more Xs, more reds, or the same).
Participants’ responses to unique color-shape associations were significantly faster and more accurate than were their responses to displays with mixed color-shape associations.
The results show that relevant color and shape dimensions could be synchronized when the pairings between color and shape were unique, but not when the pairings were mixed.
These findings demonstrate a new behavioral principle that governs object representation. When shapes are repeated in several locations and have mixed color-shape associations, they are hard to perceive.
This research expands on Anne Treisman’s groundbreaking research on feature integration in visual perception, which shows that humans can encode characteristics such as color, form, and orientation, even in the absence of spatial attention.
Treisman is one of 12 scientists who received the National Medal of Science at the White House on February 1, 2013. The National Medal of Science, along with the National Medal of Technology and Innovation, is the highest honor that the US government grants to scientists, engineers, and inventors.