Posts tagged diffusion tensor imaging

Newcastle University scientists have discovered that as the brain re-organises connections throughout our life, the process begins earlier in girls which may explain why they mature faster during the teenage years.

As we grow older, our brains undergo a major reorganisation reducing the connections in the brain. Studying people up to the age of 40, scientists led by Dr Marcus Kaiser and Ms Sol Lim at Newcastle University found that while overall connections in the brain get streamlined, long-distance connections that are crucial for integrating information are preserved.

The researchers suspect this newly-discovered selective process might explain why brain function does not deteriorate – and indeed improves –during this pruning of the network. Interestingly, they also found that these changes occurred earlier in females than in males.

Explaining the work which is being published in Cerebral Cortex, Dr Kaiser, Reader in Neuroinformatics at Newcastle University, says: “Long-distance connections are difficult to establish and maintain but are crucial for fast and efficient processing. If you think about a social network, nearby friends might give you very similar information – you might hear the same news from different people. People from different cities or countries are more likely to give you novel information. In the same way, some information flow within a brain module might be redundant whereas information from other modules, say integrating the optical information about a face with the acoustic information of a voice is vital in making sense of the outside world.”

Brain “pruned”

The researchers at Newcastle, Glasgow and Seoul Universities evaluated the scans of 121 healthy participants between the ages of 4 and 40 years as this is where the major connectivity changes can be seen during this period of maturation and improvement in the brain. The work is part of the EPSRC-funded Human Green Brain project which examines human brain development.

Using a non-invasive technique called diffusion tensor imaging – a special measurement protocol for Magnetic Resonance Imaging (MRI) scanners – they demonstrated that fibres are overall getting pruned that period.

However, they found that not all projections (long-range connections) between brain regions are affected to the same extent; changes were influenced differently depending on the types of connections.
Projections that are preserved were short-cuts that quickly link different processing modules, e.g. for vision and sound, and allow fast information transfer and synchronous processing. Changes in these connections have been found in many developmental brain disorders including autism, epilepsy and schizophrenia.

The researchers have demonstrated for the first time that the loss of white matter fibres between brain regions is a highly selective process – a phenomenon they call preferential detachment. They show that connections between distant brain regions, between brain hemispheres, and between processing modules lose fewer nerve fibres during brain maturation than expected. The researchers say this may explain how we retain a stable brain network during brain maturation.

Commenting on the fact that these changes occurred earlier in females than males, Ms Sol Lim explains: “The loss of connectivity during brain development can actually help to improve brain function by reorganizing the network more efficiently. Say instead of talking to many people at random, asking a couple of people who have lived in the area for a long time is the most efficient way to know your way. In a similar way, reducing some projections in the brain helps to focus on essential information.”

(Source: ncl.ac.uk)

People who carry a high-risk gene for Alzheimer’s disease show changes in their brains beginning in childhood, decades before the illness appears, new research from the Centre for Addiction and Mental Health (CAMH) suggests.

The gene, called SORL1, is one of a number of genes linked to an increased risk of late-onset Alzheimer’s disease, the most common form of the illness. SORL1 carries the gene code for the sortilin-like receptor, which is involved in recycling some molecules in the brain before they develop into beta-amyloid a toxic Alzheimer protein. SORL1 is also involved in lipid metabolism, putting it at the heart of the vascular risk pathway for Alzheimer’s disease as well.

“We need to understand where, when and how these Alzheimer’s risk genes affect the brain, by studying the biological pathways through which they work,” says Dr. Aristotle Voineskos, head of the Kimel Family Translational Imaging-Genetics Laboratory at CAMH, who led the study. “Through this knowledge, we can begin to design interventions at the right time, for the right people.” The study was recently published online in Molecular Psychiatry with Dr. Voineskos’s graduate student, Daniel Felsky as first author, and was a collaborative effort with the Zucker Hillside Hospital/Feinstein Institute in New York and the Rush Alzheimer’s Disease Center in Chicago.

To understand SORL1’s effects across the lifespan, the researchers studied individuals both with and without Alzheimer’s disease. Their approach was to identify genetic differences in SORL1, and see if there was a link to Alzheimer’s-related changes in the brain, using imaging as well as post-mortem tissue analysis.

In each approach, a link was confirmed.

In the first group of healthy individuals, aged eight to 86, researchers used a brain imaging technique called diffusion tensor imaging (DTI). Even among the youngest participants in the study, those with a specific copy of SORL1 showed a reduction in white matter connections in the brain important for memory performance and executive function. 

The second sample included post-mortem brain tissue from 189 individuals less than a year old to 92 years, without Alzheimer’s disease. Among those with that same copy of the SORL1 gene, the brain tissue showed a disruption in the process by which the gene translated its code to become the sortilin-like receptor.

Finally, the third set of post-mortem brains came from 710 individuals, aged 66 to 108, of whom the majority had mild cognitive impairment or Alzheimer’s. In this case, the SORL1 risk gene was linked with the presence of amyloid-beta, a protein found in Alzheimer’s disease. 

Dr. Voineskos notes that risk for Alzheimer’s disease results from a combination of factors – unhealthy diet, lack of exercise, smoking, high blood pressure combined with a person’s genetic profile – which all contribute to the development of the illness. “The gene has a relatively small effect, but the changes are reliable, and may represent one ‘hit’, among a pathway of hits required to develop Alzheimer’s disease later in life”.

While it’s too early to provide interventions that may target these changes, “individuals can take measures in their own lifestyle to reduce the risk of late-onset Alzheimer’s disease.” Determining whether there is an interaction with this risk gene and lifestyle factors will be one important next step.

In order to develop genetically-based interventions to prevent Alzheimer’s disease, the biological pathways of other risk genes also need to be systematically analyzed, the researchers note.

This research does, however, build on a previous CAMH imaging-genetics study on another gene related to Alzheimer’s disease. That study showed that a genetic variation of brain-derived neurotrophic factor (BDNF) affected brain structures in Alzheimer’s.

“The interesting connection is that BDNF may have important therapeutic value. But there is data to suggest that the effects of BDNF won’t work unless SORL1 is present, so there is the possibility that if you boost the activity of one gene, the other will increase,” says Dr. Voineskos, adding that BDNF therapeutics are in development. A next stage in the research, he says, is to look at the interaction of BDNF and SORL1.

(Source: camh.ca)

For the first time scientists have identified how a pathway in the brain which is unique to humans allows us to learn new words.

The average adult’s vocabulary consists of about 30,000 words. This ability seems unique to humans as even the species closest to us - chimps - manage to learn no more than 100. 

It has long been believed that language learning depends on the integration of hearing and repeating words but the neural mechanisms behind learning new words remained unclear. Previous studies have shown that this may be related to a pathway in the brain only found in humans and that humans can learn only words that they can articulate. 

Now researchers from King’s College London Institute of Psychiatry, in collaboration with Bellvitge Biomedical Research Institute (IDIBELL) and the University of Barcelona, have mapped the neural pathways involved in word learning among humans. They found that the arcuate fasciculus, a collection of nerve fibres connecting auditory regions at the temporal lobe with the motor area located at the frontal lobe in the left hemisphere of the brain, allows the ‘sound’ of a word to be connected to the regions responsible for its articulation. Differences in the development of these auditory-motor connections may explain differences in people’s ability to learn words. 

The results of the study are published in the journal Proceedings of the National Academy of Sciences (PNAS).

Dr Marco Catani, co-author from the NatBrainLab at King’s College London Institute of Psychiatry said: “Often humans take their ability to learn words for granted. This research sheds new light on the unique ability of humans to learn a language, as this pathway is not present in other species. The implications of our findings could be wide ranging – from how language is taught in schools and rehabilitation from injury, to early detection of language disorders such as dyslexia. In addition these findings could have implications for other disorders where language is affected such as autism and schizophrenia.”

The study involved 27 healthy volunteers. Researchers used diffusion tensor imaging to image the structure of the brain before a word learning task and functional MRI, to  detect the regions in the brain that were most active during the task. They found a strong relationship between the ability to remember words and the structure of arcuate fasciculus, which connects two brain areas: the territory of Wernicke, related to auditory language decoding, and Broca’s area, which coordinates the movements associated with speech and the language processing.

In participants able to learn words more successfully their arcuate fasciculus was more myelinated i.e. the nervous tissue facilitated faster conduction of the electrical signal. In addition the activity between the two regions was more co-ordinated in these participants.

Dr Catani concludes, “Now we understand that this is how we learn new words, our concern is that children will have less vocabulary as much of their interaction is via screen, text and email rather than using their external prosthetic memory. This research reinforces the need for us to maintain the oral tradition of talking to our children.”

(Source: kcl.ac.uk)

Pioneering experiments back in 1982 by Tasaki and Iwasa at the NIH revealed that action potentials in neurons are more than just the electrical blips that physiologists readily amplify and record. These so-called “spikes” are in fact multi-modal signalling packages that include mechanical and thermal disturbances propagating down the axon at their own rates. Nobel Laureate Francis Crick published a paper that same year, in which he postulated potential mechanisms that would explain twitching in dendritic spines, adding to an emerging picture of a brain more vibrant and motile than had been previously imagined. More recently, researchers have developed diffusion-based MRI methods, like diffusion tensor imaging (DTI), to trace the trajectories of axons, and perhaps more intriguingly, determine their directional polarity. Working at the EPFL in Switzerland, Denis Le Bihan and his co-workers have been using diffusional MRI in slightly different way. They now appear to be able to directly measure neuronal activity from the subtle movements of membranes, the water within them, and in the extracellular space around them. Their work, just published in PNAS, provides a much needed conceptual shift away from currently established, but typically nebulous, ideas regarding neurovascular coupling of brain activity to blood flow.

Present-day imaging methods, like blood oxygen level-dependent (BOLD) MRI, are only indirectly and remotely related to the cortical activity they often claim to measure. In 2006, Le Bihan reported a water “phase transition” response that preceded the neurovascular response normally detected by functional MRI. He attributed the changes in water diffusion to previously established effects involving membrane expansion and cell swelling secondary to activity. At the biophysical level, interpreting action potentials as phase transitions is a little off the beaten path from traditional neurobiology, but it can be an informative approach when to trying to understand what might be going on when cells fire.

As biophysicist Gerald Pollack has previously pointed out, spikes may involve the propagation of the line of transition of water from the ordered phase, (as patterned by hydrophic interactions nucleated at the surfaces of membranes and proteins) to a disordered phase.
Traditionally, the so-called bound surface water only extends out a only a couple of molecules from the surface of nondiffusable features. That idea may need to be revisited in light of more recent understanding when attempting to account for the diffusion of water in axons. A decrease in water diffusion as measured by MRI may be in part explained by a decrease in extracellular space, and that has been suggested from experiments measuring intrinsic optical effects. The larger picture of water diffusion, however, is likely a bit more complicated than this.

In his new study, Le Bihan stimulated the forepaw of a rat and looked at responses in the somatosensory cortex. The key experiment was to infuse nitroprusside in attempt to inhibit neurovascular coupling. It is a tricky alteration because nitroprusside apparently has many diffuse effects. It can induce potent vasodilation, particularly on the vascular end (mainly the smaller venules), after it breaks down to produce nitric oxide. It is also a diamagnetic molecule, and each molecule releases five cyanide ions, which are presumably detoxified by the mitochondrial enzyme rhodanese. The experiments were done under isoflurane anesthesia, which also introduces a few uncertainties, particularly with regard to responses to different frequencies of forepaw stimulation.

If nitroprusside is indeed a realistic experimental proxy for neurovascular uncoupling, then the results of Le Bihan appear to show that the diffusion response is not of vascular origin, and that it is closely linked to neural activation. He found that the standard BOLD MRI responses were completely quenched under nitroprusside, whereas the diffusion MRI responses were only slightly suppressed. Local field potentials were also simultaneously measured and suggested at least, that the neuronal responses were also intact.

The work of Le Bihan indicates that diffusion-based MRI can be used to infer neural activity directly from the structural changes that affect the molecular displacements of water. The ability to use shape changes in neurons, astrocytes, or even spines, raises the question of whether these kinds of techniques might eventually be of use in creating larger scale, and more detailed, Brain Activity Maps (BAMs). I asked Konrad Kording, author on the recent theoretical paper which discussed the theoretical limits to MRI and other activity recording methods, whether methods that probe water movements might be applied to this end.

Kording observed that the spatial resolution of standard MRI is ultimately limited by the diffusion of water, but more importantly perhaps, the temporal resolution of all known MRI methods is nowhere near that required to create spike maps. None-the-less, detecting mechanical responses in the brain could provide many unique insights into function. For example, experiments using agents that dissolve the extracellular matrix, like the clot-busting drug TPA, result in more twitching, or vibration if you will, in dendritic spines. Other studies have shown that the greater the electrical drive on a spine, the less it tends to twitch or change size, particularly during periods of rapid development.

Similarly, sensory deprivations appear to increase these kinds of movements as neurons grow and reorganize connections. While these effects are far below that which could be detected by any large external method of MRI, new tools may permit us to access these newly-revealed activities. Diffusional MRI in particular, can be done with a little modification of the standard MRI procedure. For example, to determine directional diffusion parameters, or diffusion tensors, typically six gradients are used to measure three directional vectors. As these capabilities become more common, hopefully the results of Le Bihan can be further explored and verified.

The distribution of white matter brain abnormalities in some patients after mild traumatic brain injury (MTBI) closely resembles that found in early Alzheimer’s dementia, according to a new study published online in the journal Radiology.

“Findings of MTBI bear a striking resemblance to those seen in early Alzheimer’s dementia,” said the study’s lead author, Saeed Fakhran, M.D., assistant professor of radiology in the Division of Neuroradiology at the University of Pittsburgh School of Medicine. “Additional research may help further elucidate a link between these two disease processes.”

MTBI, or concussion, affects more than 1.7 million people in the United States annually. Despite the name, these injuries are by no means mild, with approximately 15 percent of concussion patients suffering persistent neurological symptoms.

“Sleep-wake disturbances are among the earliest findings of Alzheimer’s patients, and are also seen in a subset of MTBI patients,” Dr. Fakhran said. “Furthermore, after concussion, many patients have difficulty filtering out white noise and concentrating on the important sounds, making it hard for them to understand the world around them. Hearing problems are not only an independent risk factor for developing Alzheimer’s disease, but the same type of hearing problem seen in MTBI patients has been found to predict which patients with memory problems will go on to develop Alzheimer’s disease.”

For the study, Dr. Fakhran and colleagues set out to determine if there was a relationship between white matter injury patterns and severity of post-concussion symptoms in MTBI patients with normal findings on conventional magnetic resonance imaging (MRI) exams. The researchers studied data from imaging exams performed on 64 MTBI patients and 15 control patients, using an advanced MRI technique called diffusion tensor imaging, which identifies microscopic changes in the brain’s white matter.

The brain’s white matter is composed of millions of nerve fibers called axons that act like communication cables connecting various regions of the brain. Diffusion tensor imaging produces a measurement, called fractional anisotropy, of the movement of water molecules along axons. In healthy white matter, the direction of water movement is fairly uniform and measures high in fractional anisotropy. When water movement is more random, fractional anisotropy values decrease.

Of the MTBI patients, 42 (65.6 percent) were men, and the mean age was 17. Sports injury was the reason for concussion in two-thirds of the patients. All patients underwent neurocognitive evaluation with Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT). The researchers analyzed correlation between fractional anisotropy values, the ImPACT total symptom score, and findings of sleep-wake disturbances.

Sleep-wake disturbances are among the most disabling post-concussive symptoms, directly decreasing quality of life and productivity and magnifying post-concussion memory and social dysfunction.

The results showed a significant correlation between high ImPACT total symptom score and reduced fractional anisotropy at the gray-white junction, most prominently in the auditory cortex. Significantly decreased fractional anisotropy was found in patients with sleep-wake disturbances in the parahippocampal gyri relative to patients without sleep-wake disturbances.

“When we sleep, the brain organizes our experiences into memories, storing them so that we can later find them,” Dr. Fakhran said. “The parahippocampus is important for this process, and involvement of the parahippocampus may, in part, explain the memory problems that occur in many patients after concussion.”

According to Dr. Fakhran, the results suggest that the true problem facing concussion patients may not be the injury itself, but rather the brain’s response to that injury.

“Traditionally, it has been believed that patients with MTBI have symptoms because of abnormalities secondary to direct injury,” he said. “Simply put, they hit their head, damaged their brain at the point of trauma and thus have symptoms from that direct damage. Our preliminary findings suggest that the initial traumatic event that caused the concussion acts as a trigger for a sequence of degenerative changes in the brain that results in patient symptoms and that may be potentially prevented. Furthermore, these neurodegenerative changes are very similar to those seen in early Alzheimer’s dementia.”

The researchers hope that these findings may lead to improved treatments in the future.

“The first step in developing a treatment for any disease is understanding what causes it,” Dr. Fakhran said. “If we can prove a link, or even a common pathway, between MTBI and Alzheimer’s, this could potentially lead to treatment strategies that would be potentially efficacious in treating both diseases.”

(Source: prweb.com)

A new University of Florida study suggests a promising brain-imaging technique has the potential to improve diagnoses for the millions of people with movement disorders such as Parkinson’s disease.

Utilizing the diffusion tensor imaging technique, as it is known, could allow clinicians to assess people earlier, leading to improved treatment interventions and therapies for patients.

The three-year study looked at 72 patients, each with a clinically defined movement disorder diagnosis. Using a technique called diffusion tensor imaging, the researchers successfully separated the patients into disorder groups with a high degree of accuracy.

The study is being published in the journal Movement Disorders.

“The purpose of this study is to identify markers in the brain that differentiate movement disorders which have clinical symptoms that overlap, making [the disorders] difficult to distinguish,” said David Vaillancourt, associate professor in the department of applied physiology and kinesiology and the study’s principal investigator.

“No other imaging, cerebrospinal fluid or blood marker has been this successful at differentiating these disorders,” he said. “The results are very promising.”

Movement disorders such as Parkinson’s disease, essential tremor, multiple system atrophy and progressive supranuclear palsy exhibit similar symptoms in the early stages, which can make it challenging to assign a specific diagnosis. Often, the original diagnosis changes as the disease progresses, Vaillancourt said.

Diffusion tensor imaging, known as DTI, is a non-invasive method that examines the diffusion of water molecules within the brain and can identify key areas that have been affected as a result of damage to gray matter and white matter in the brain. Vaillancourt and his team measured areas of the basal ganglia and cerebellum in individuals, and used a statistical approach to predict group classification. By asking different questions within the data and comparing different groups to one another, they were able to show distinct separation among disorders.

“Our goal was to use these measures to accurately predict the original disease classification,” Vaillancourt said. “The idea being that if a new patient came in with an unknown diagnosis, you might be able to apply this algorithm to that individual.

He compared the process to a cholesterol test.

“If you have high cholesterol, it raises your chances of developing heart disease in the future,” he said. “There are tests like those that give a probability or likelihood scenario of a particular disease group. We’re going a step further and trying to utilize information to predict the classification of specific tremor and Parkinsonian diseases.”

(Source: news.ufl.edu)