Aging in Down Syndrome: A Model for Preclinical Alzheimer's Disease
N. Virji-Babul (DSRF), A. Moiseev (DSRF), A. Babul (Physics and Astronomy, UVIC) , R. deSousa (Physics and Astronomy, UVIC), R. Edwards (Mathematics and Statistics, UVIC), I. Lott (UCI), R. Haier (UCI)

As science and medicine extend life expectancy, there is a growing concern regarding the quality of life of the aged. According to the Canadian Study of Health and Aging (CSHA), 8% of Canadians aged 65 and older suffer from dementia. The proportion rises to 35% among those over 85 years of age. Alzheimer’s disease (AD) is the most common form of dementia characterized by a gradual onset and progressive deterioration of cognitive function leading to devastating consequences for the individual and the family. Thus far, there are no drug interventions that can reverse the neuropathological changes of AD. Still there is growing evidence that treatment initiated early in the course of the disease can significantly delay the decline in cognition. A major challenge in diagnosing AD however is that the early pathological changes can appear many years in advance of clinical symptoms. As a result, it may take up to 2 years between the onset of recognizable symptoms and a formal diagnosis. Identifying markers of pre-symptomatic AD is critical not only to begin early drug treatment, but also for identify individuals at risk for developing AD and to trial approaches for prevention in the at risk population.

In recent years, advances in the analysis of neuroimaging data are making it possible to detect subtle changes in brain function. Brain imaging studies are moving beyond examining localized brain functions to look at functional interactions between brain regions and neural networks of the whole brain. Characterizing these changes has the potential of identifying changes in the underlying brain processes and networks.

Postmortem studies show that at 40 years of age, almost all subjects with DS have neuropathological changes that meet the pathological criteria for AD. These changes include extensive cerebral atrophy, accumulation of ßamyloid, extracellular senile plaques and intracellular neurofibrillary tangles in the hippocampus and frontal and temporal cortices. DS is therefore an extremely useful model to study the preclinical stages of AD as middle aged individuals can be identified prior to any clinical signs of dementia.  Our goal for this project is to use MEG data to compute measures of functional connectivity that may be useful in predicting the onset of dementia.

Mirrors in the Brain
N. Virji-Babul, A. Moiseev, T. Cheung, D. Cheyne, U. Ribary, D. Weeks

Humans have a remarkable ability to understand the actions and intentions of other people, and to imitate these same actions. How we understand and interpret the actions and an emotion of others has been a central question in neuroscience. Advances in neuroscience in the last decade have led to the discovery of new class of brain cells called mirror neurons. These cells not only fire when we perform an action but also when we watch someone else performing the same action. This discovery has generated tremendous excitement as some scientists speculate that the mirror neuron system may form the basis of our social behaviour, our ability to imitate, acquire language and show empathy. The question we asked is whether this system is intact in individuals with Down syndrome. Preliminary results from this work indicates that although there is a link between perception and action in individuals with DS, the mirror neuron system may not function in the same way as in typical individuals.

See poster

Can Mirror Neurons be Used to Improve Motor Control?
N. Virji-Babul, A. Moiseev

Two of the characteristic features of voluntary movements in DS are slowness of movement and difficulties with motor coordination. Many studies have shown that individuals with DS have longer reaction times, longer movement times and clumsy or uncoordinated motion.. The hypothesis that there may be a functional link between perception and action suggests that it might be possible to use movement observation of specific motor actions to facilitate activity in the mirror neuron system and thereby cause a change in motor coordination. We are now in the process of designing research studies to investigate whether targeted “observation intervention” can cause changes in the underlying activation patterns in the brain.

Perception of Motion and Emotion
N. Virji-Babul, A. Moiseev, F. Beg. S. Shuo, U. Ribary

Social behavior depends upon inferences that are based on the perception and interpretation of other people’s actions and emotions. Given the fundamental importance of accurately perceiving socially relevant information, we are studying how children and adults (with and without DS) perceive this information. We present short video clips showing animations of people performing different actions or portraying a variety of emotional expressions in the movement of their bodies. We are currently investigating how the underlying patterns of brain activity are modulated by the emotional content of the actions.

Brain Rhythms and the Control of Visual Attention
S. Doesburg, L. Ward, A. Herdman

A wealth of recent evidence has suggested that the synchronization of brain rhythms helps to quickly reorganize networks in order to support the varied and ever changing mental acts we perform.  We are investigating how brain rhythms become synchronized when visual attention is shifted to particular areas.  Preliminary evidence suggest that synchronization of alpha-band (8 – 12 Hz) rhythms helps to inhibit information in ignored areas of space and promotes the transfer of information in attended areas to higher-order brain regions.

Figure: Alpha-band activation (colours; blue bars) and occipital-parietal synchronization (black line) and desynchronization (white line) as a subject attends to the right visual field.  Note that alpha activation is greater in the right hemisphere (inhibition), whereas occipital-parietal synchronization is greater in the left hemisphere (functional integration).

Cortical Processing in Children Born Very Preterm
S. Doesburg, U. Ribary, A. Herdman, T. Cheung, A. Moiseev, H. Weinberg, M Liotti, D. Weeks, R. E. Grunau

Children born very preterm often have problems with learning and attention, leading to academic difficulties.  Little is known, however, about what alterations in brain activity underlie these problems.  We are comparing brain activation in children born very preterm, now 7½ years old, during a short-term memory task to that of age-matched control children.  Preliminary results suggest that children born very preterm show difficulty recruiting task-relevant cortical networks. This project is funded by a grant to REG from the National Institutes of Health (NIH), USA.

Figure: Alpha-band (8-12 Hz) activation(colours) and synchronization (black lines) and desynchronization (white lines) between brain areas during a short-term memory task."

Children's Brain Activity While Reading Letters
A.Herdman

These are brain images at 25 ms intervals from 75 ms to 550ms for typically developing children (8-12 years old) reading letters. These activation maps show that reading letters first activates the primary visual centers in the back of the brain that then travel  forward to areas responsible for sound association in the temporal areas and then for motor planning in frontal areas. Current research in Dr. Herdman's Human Brain Research Lab at the DSRF/SFU is using brain imaging (EEG and MEG) to untangle how these areas develop into brain networks for reading letters and words and how such networks are disrupted by specific brain-dependent deficits, such as dyslexia.

Leakage Correction Procedure for Improving Beamformer Spatial Resolution
A. Moiseev.

No matter what we do or even when we seem to do nothing hundreds of thousands of neurons in the brain keep working, resulting in tiny electrical currents running in various parts of our heads. These currents could tell researchers and clinicians a lot about what is going on, but we cannot measure them directly. However, each electric current generates magnetic field that is not stopped by the brain tissue and gets outside. A MEG system installed at DSRF can detect these magnetic fields using 151 extremely sensitive detectors which are placed close to the subject’s scalp.

Now, when the magnetic field outside the head is known, the next step is to figure out which neurons generated it and where exactly they are located. This is a difficult problem. One of the methods (called beamforming)regards the detector array as an antenna. By combining signals from all the 151 sensors in a special way the antenna can be steered so that its output yields a signal from a certain spot in the brain. In practice that can’t be done with perfect spatial resolution. A signal from one spot will “leak” into other locations in the brain, resulting in somewhat blurred map of the brain activity. In the research conducted at DSRF, we developed a technique that deals with the leakage problem and improves the beamformer spatial resolution. The idea is to remove the blur so that “true” underlying sources could be uncovered. Such an improvement in spatial resolution may be important for scientific research and especially for clinical applications.

The picture demonstrates how the method works when there is a single known brain source. The vertical and horizontal axes show distances along X and Y directions in cm at some horizontal section of the brain volume Color denotes the source strength, from weak (blue) to strong (red). The black cross shows the true source position. We see rather smooth and blurry source distribution obtained by the uncorrected beamformer, and a sharp source image after the correction is applied.

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