Blue light may fight fatigue around the clock

Researchers from Brigham and Women’s Hospital (BWH) have found that exposure to short wavelength, or blue light, during the biological day directly and immediately improves alertness and performance. These findings are published in the February issue of Sleep.

"Our previous research has shown that blue light is able to improve alertness during the night, but our new data demonstrates that these effects also extend to daytime light exposure," said Shadab Rahman, PhD, a researcher in BWH’s Division of Sleep Medicine and lead author of this study. "These findings demonstrate that prolonged blue light exposure during the day has an an alerting effect."

In order to determine which wavelengths of light were most effective in warding off fatigue, the BWH researchers teamed with George Brainard, PhD, a professor of neurology at Thomas Jefferson University, who developed the specialized light equipment used in the study. Researcherscompared the effects of blue light with exposure to an equal amount of green light on alertness and performance in 16 study participants for 6.5 hours over a day. Participants then rated how sleepy they felt, had their reaction times measured and wore electrodes to assess changes in brain activity patterns during the light exposure.

The researchers found that participants exposed to blue light consistently rated themselves as less sleepy, had quicker reaction times and fewer lapses of attention during the performance tests compared to those who were exposed to green light. They also showed changes in brain activity patterns that indicated a more alert state.

"These results contribute to our understanding of how light impacts the brain and open up a new range of possibilities for using light to improve human alertness, productivity and safety," explained Steven Lockley, PhD, neuroscientist at BWH and senior investigator of the study. "While helping to improve alertness in night workers has obvious safety benefits, day shift workers may also benefit from better quality lighting that would not only help them see better but also make them more alert."

Researchers note that the next big challenge is to figure out how to deliver better lighting. While natural light is ideal, many people do not have access to daylight in their schools, homes or work places. In addition to improvements in daylight access, the advent of new, more controllable lighting technologies may help enable researchers to develop ‘smart’ lighting systems designed to maximize the beneficial effects of light for human health, productivity and safety.

In the brain, the number of neurons in a network may not matter

Last spring, President Obama established the federal BRAIN Initiative to give scientists the tools they need to get a dynamic picture of the brain in action.

To do so, the initiative’s architects envision simultaneously recording the activity of complete neural networks that consist of thousands or even millions of neurons. However, a new study indicates that it may be possible to accurately characterize these networks by recording the activity of properly selected samples of 50 neurons or less – an alternative that is much easier to realize.

The study was performed by a team of cognitive neuroscientists at Vanderbilt University and reported in a paper published the week of Feb. 3 in the online Early Edition of the Proceedings of the National Academy of Sciences.

The paper describes the results of an ambitious computer simulation that the team designed to understand the behavior of the networks of hundreds of thousands of neurons that initiate different body movements: specifically, how the neurons are coordinated to trigger a movement at a particular point in time, called the response time.

The researchers were surprised to discover that the range of response times produced by the simulated population of neurons did not change with size: A network of 50 simulated neurons responded with the same speed as a network with 1,000 neurons.

For decades, response time has been a core measurement in psychology. “Psychologists have developed powerful models of human responses that explain the variation of response time based on the concept of single accumulators,” said Centennial Professor of Psychology Gordon Logan. In this model, the brain acts as an accumulator that integrates incoming information related to a given task and produces a movement when the amount of information reaches a preset threshold. The model explains random variations in response times by how quickly the brain accumulates the information it needs to act.

Meanwhile, neuroscientists have related response time to measurements of single neurons. “Twenty years ago we discovered that the activity of particular neurons resembles the accumulators of psychology models. We haven’t understood until now how large numbers of these neurons can act collectively to initiate movements,” said Ingram Professor of Neuroscience Jeffrey Schall.

No one really knows the size of the neural networks involved in initiating movements, but researchers estimated that about 100,000 neurons are involved in launching a simple eye movement.

“One of the main questions we addressed is how ensembles of 100,000 neuron accumulators can produce behavior that is also explained by a single accumulator,” Schall said.

“The way that the response time of these ensembles varies with ensemble size clearly depends on the ‘stopping rules’ that they follow,” explained co-author Thomas Palmeri, associate professor of psychology. For example, if an ensemble doesn’t respond until all of its member neurons have accumulated enough activity, then its response time would be slower for larger networks. On the other hand, if the response time is determined by the first neurons that react, then the response time in larger networks would be shorter than those of smaller networks.

Another important factor is the degree to which the ensemble is coordinated. “The more the ensemble is coordinated, the more the collective resembles a single accumulator. What has been unknown is how much coordination is necessary for the ensemble to act in unison, ” said Bram Zandbelt, a post-doctoral fellow and lead author on the paper.

To address this problem, the researchers developed a new type of computer simulation, one that models the collective behavior of different numbers of accumulators given different amounts of variation in the rates of accumulation. The simulation took a tremendous amount of computer power. Even using Vanderbilt’s in-house supercomputer at the Advanced Computing Center for Research & Education, Zandbelt was limited to modeling networks containing 1,000 neurons.

The researchers found that the networks did not produce realistic response times if responses were initiated when only a few or almost all of the simulated neurons finished accumulating, or if the simulated neurons had very different accumulation rates. However, the networks produced realistic response times over a broad range of stopping rules and similarity in accumulation rates, showing that within these broad constraints, size doesn’t matter. “We were surprised to discover that the networks behaved with a remarkable uniformity except under extreme assumptions,” said Schall.

“As far as the response time goes, the bottom line is that we found that the size of the neural network doesn’t matter under a large set of conditions. If this is true for networks ranging from 10 to 1,000 neurons, it should also hold for networks of 10,000 to 100,000 neurons,” Palmeri said.

Making your brain social

In many people with autism and other neurodevelopmental disorders, different parts of the brain don’t talk to each other very well. Scientists have now identified, for the first time, a way in which this decreased functional connectivity can come about. In a study published online today in Nature Neuroscience, scientists at the European Molecular Biology Laboratory (EMBL) in Monterotondo, Italy, and collaborators at the Istituto Italiano di Tecnologia (IIT), in Rovereto, and La Sapienza University in Rome, demonstrate that it can be caused by cells called microglia failing to trim connections between neurons.

“We show that a deficit in microglia during development can have widespread and long-lasting effects on brain wiring and behaviour,” says Cornelius Gross, who led the study. “It leads to weak brain connectivity, decreased social behaviour, and increased repetitive behaviour, all hallmarks of autism.”

The findings indicate that, by trimming surplus connections in the developing brain, microglia allow the remaining links to grow stronger, like high-speed fibre-optic cables carrying strong signals between brain regions. But if these cells fail to do their job at that crucial stage of development, those brain regions are left with a weaker communication network, which in turn has lifelong effects on behaviour.

Yang Zhan, a postdoctoral fellow in Gross’ lab at EMBL, analysed the strength of connections between different areas of brain in mice that were genetically engineered to have fewer microglia during development. Working with Alessandro Gozzi’s lab at IIT and Davide Ragozzino at La Sapienza University, the EMBL scientists combined this approach with high-resolution fMRI (functional Magnetic Resonance Imaging) scans of the mice’s brains, taking full advantage of a novel technique developed at IIT, which enables scientists to obtain detailed, three-dimensional maps of the brain’s functional connections. The team found that mice with fewer microglia had weaker connections between neurons, and less cross-talk between different brain regions. When Rosa Paolicelli, a PhD student in Gross’ lab, studied the mice’s behaviour, she discovered that mice with fewer microglia and decreased connectivity displayed behaviours commonly associated with autism spectrum disorders. These mice spent more time repeatedly grooming themselves, and avoided social interactions.

“This is an exciting time to be studying microglia,” Gross concludes:  “they’re turning out to be major players in how our brain gets wired up.”

Your Brain Is Fine-Tuning Its Wiring Throughout Your Life

The white matter microstructure, the communication pathways of the brain, continues to develop/mature as one ages. Studies link age-related differences in white matter microstructure to specific cognitive abilities in childhood and adulthood.

Most prior studies, however, did not include individuals from the entire life span or evaluated a limited section of white matter tracts. This knowledge gap prompted a new study published this week in Biological Psychiatry.

Dr. Bart Peters, of the Zucker Hillside Hospital, and his colleagues investigated the relationship of age and neurocognitive performance to nine white matter tracts from childhood to late adulthood.

To accomplish this, they recruited 296 healthy volunteers who ranged from 8 to 68 years of age. The participants completed a comprehensive battery of tests designed to measure their cognitive functioning, including speed, attention, memory, and learning. They also underwent a non-invasive diffusion tensor imaging scan, a technology that allowed the researchers to create maps of the 9 major white matter tracts under investigation.

The combination of this data allowed them to identify the neurocognitive correlates of each white matter tract in relation to its unique aging pattern.

They found that, from childhood into early adulthood, differences in fractional anisotropy – a measure of connectivity – of the cingulum were associated with executive functioning, whereas fractional anisotropy of the inferior fronto-occipital fasciculus was associated with visual learning and global cognitive performance via speed of processing.

"Our study identified key brain circuits that develop during adolescence and young adulthood that are associated with the growth of learning, memory and planning abilities. These findings suggest that young people may not have full capacity of these functions until these connections have completed their normal trajectory of maturation beyond adolescence," explained Peters.

"Our brain is changing throughout our lives. These changes underlie the capacities that emerge and are refined through adulthood," commented Dr. John Krystal, Editor of Biological Psychiatry. “There are clues that the steps that we take to preserve our medical health and stimulate our minds also serve to further refine and maintain these connections. For good reasons, attending to brain health is increasingly a focus of healthy aging.”

In addition, many individuals diagnosed with psychiatric disorders suffer with neurocognitive dysfunction as part of their illness, which is particularly difficult to alleviate with currently available treatments. Studies such as this may help to identify specific brain circuits/pathways that could serve as potential targets for treatment interventions.

Autistic Brains Create More Information at Rest

New research from Case Western Reserve University and University of Toronto neuroscientists finds that the brains of autistic children generate more information at rest – a 42% increase on average. The study offers a scientific explanation for the most typical characteristic of autism – withdrawal into one’s own inner world. The excess production of information may explain a child’s detachment from their environment.

Published at the end of December in Frontiers in Neuroinformatics, this study is a follow-up to the authors’ prior finding that brain connections are different in autistic children. This paper determined that the differences account for the increased complexity within their brains.

“Our results suggest that autistic children are not interested in social interactions because their brains generate more information at rest, which we interpret as more introspection in line with early descriptions of the disorder,” said Roberto Fernández Galán, PhD, senior author and associate professor of neurosciences at Case Western Reserve School of Medicine.

The authors quantified information as engineers normally do but instead of applying it to signals in electronic devices, they applied it to brain activity recorded with magnetoencephalography (MEG). They showed that autistic children’s brains at rest generate more information than non-autistic children. This may explain their lack of interest in external stimuli, including interactions with other people.

The researchers also quantified interactions between brain regions, i.e., the brain’s functional connectivity, and determined the inputs to the brain in the resting state allowing them to interpret the children’s introspection level.

“This is a novel interpretation because it is a different attempt to understand the children’s cognition by analyzing their brain activity,” said José L. Pérez Velázquez, PhD, first author and professor of neuroscience at University of Toronto Institute of Medical Science and Department of Pediatrics, Brain and Behavior Center.

“Measuring cognitive processes is not trivial; yet, our findings indicate that this can be done to some extent with well-established mathematical tools from physics and engineering.”

This study provides quantitative support for the relatively new “Intense World Theory” of autism proposed by neuroscientists Henry and Kamila Markram of the Brain Mind Institute in Switzerland, which describes the disorder as the result of hyper-functioning neural circuitry, leading to a state of over-arousal. More generally, the work of Galán and Pérez Velázquez is an initial step in the investigation of how information generation in the brain relates to cognitive/psychological traits and will begin to frame neurophysiological data into psychological aspects. The team now aims to apply a similar approach to patients with schizophrenia.