Brain Chemical Ratios Help Predict Developmental Delays in Preterm Infants

Researchers have identified a potential biomarker for predicting whether a premature infant is at high risk for motor development problems, according to a study published online in the journal Radiology.

"We are living in an era in which survival of premature birth is more common," said Giles S. Kendall, Ph.D., consultant for the neonatal intensive care unit at University College London Hospitals NHS Foundation Trust and honorary senior lecturer of neonatal neuroimaging and neuroprotection at the University College London. "However, these infants continue to be at risk for neurodevelopmental problems."

Patients in the study included 43 infants (24 male) born at less than 32 weeks gestation and admitted to the neonatal intensive care unit (NICU) at the University College of London between 2007 and 2010. Dr. Kendall and his research team performed magnetic resonance imaging (MRI) and MR spectroscopy (MRS) exams on the infants at their approximate expected due dates (or term-equivalent age). MRS measures chemical levels in the brain.

The imaging studies were focused on the white matter of the brain, which is composed of nerve fibers that connect the functional centers of the brain.

"The white matter is especially fragile in the newborn and at risk for injury," Dr. Kendall explained.

One year later, 40 of the 43 infants were evaluated using the Bayley Scales of Infant and Toddler Development, which assess fine motor, gross motor and communication abilities. Of the 40 infants evaluated, 15 (38 percent) had abnormal composite motor scores and four (10 percent) showed cognitive impairment.

Statistical analysis of the MRS results and Bayley Scales scores revealed that the presence of two chemical ratios—increased choline/creatine (Cho/Cr) and decreased N-acetylaspartate/choline (NAA/Cho)—at birth were significantly correlated with developmental delays one year later.

"Low N-acetylaspartate/choline and rising choline/creatine observed during MRS at the baby’s expected due date predicted with 70 percent certainty which babies were at high risk for motor development problems at one year," Dr. Kendall said.

Dr. Kendall said a tool to predict the likelihood of a premature baby having neurodevelopmental problems would be useful in determining which infants should receive intensive interventions and in testing the effectiveness of those therapies.

"Physiotherapy interventions are available but are very expensive, and the vast majority of premature babies don’t need them," Dr. Kendall said. "Our hope is to find a robust biomarker that we can use as an outcome measure so that we don’t have to wait five or six years to see if an intervention has worked."

Dr. Kendall said severe disability associated with premature births has decreased over the past two decades as a result of improved care techniques in the NICU. However, many premature infants today have subtle abnormalities that are difficult to detect with conventional MRI.

"There’s a general shift away from simply ensuring the survival of these infants to how to give them the best quality of life," he said. "Our research is part of an effort to improve the outcomes for prematurely born infants and to identify earlier which babies are at greater risk."

Tinnitus discovery opens door to possible new treatment avenues

For tens of millions of Americans, there’s no such thing as the sound of silence. Instead, even in a quiet room, they hear a constant ringing, buzzing, hissing, humming or other noise in their ears that isn’t real. Called tinnitus, it can be debilitating and life-altering.

Now, University of Michigan Medical School researchers report new scientific findings that help explain what is going on inside these unquiet brains.

The discovery reveals an important new target for treating the condition. Already, the U-M team has a patent pending and device in development based on the approach.

The critical findings are published online in the prestigious Journal of Neuroscience. Though the work was done in animals, it provides a science-based, novel approach to treating tinnitus in humans.

Susan Shore, Ph.D., the senior author of the paper, explains that her team has confirmed that a process called stimulus-timing dependent multisensory plasticity is altered in animals with tinnitus – and that this plasticity is “exquisitely sensitive” to the timing of signals coming in to a key area of the brain.

That area, called the dorsal cochlear nucleus, is the first station for signals arriving in the brain from the ear via the auditory nerve. But it’s also a center where “multitasking” neurons integrate other sensory signals, such as touch, together with the hearing information.

Shore, who leads a lab in U-M’s Kresge Hearing Research Institute, is a Professor of Otolaryngology and Molecular and Integrative Physiology at the U-M Medical School, and also Professor of Biomedical Engineering, which spans the Medical School and College of Engineering.

She explains that in tinnitus, some of the input to the brain from the ear’s cochlea is reduced, while signals from the somatosensory nerves of the face and neck, related to touch, are excessively amplified.

“It’s as if the signals are compensating for the lost auditory input, but they overcompensate and end up making everything noisy,” says Shore.

The new findings illuminate the relationship between tinnitus, hearing loss and sensory input and help explain why many tinnitus sufferers can change the volume and pitch of their tinnitus’s sound by clenching their jaw, or moving their head and neck.

But it’s not just the combination of loud noise and overactive somatosensory signals that are involved in tinnitus, the researchers report.

It’s the precise timing of these signals in relation to one another that prompt the changes in the nervous system’s plasticity mechanisms, which may lead to the symptoms known to tinnitus sufferers. 

Shore and her colleagues, including former U-M biomedical engineering graduate student and first author Seth Koehler, Ph.D., hope their findings will eventually help many of the 50 million people in the United States and millions more worldwide who have the condition, according to the American Tinnitus Association. They hope to bring science-based approaches to the treatment of a condition for which there is no cure – and for which many unproven would-be therapies exist.

Tinnitus especially affects baby boomers, who, as they reach an age at which hearing tends to diminish, increasingly experience tinnitus. The condition most commonly occurs with hearing loss, but can also follow head and neck trauma, such as after an auto accident, or dental work.

Loud noises and blast forces experienced by members of the military in war zones also can trigger the condition. Tinnitus is a top cause of disability among members and veterans of the armed forces.

Researchers still don’t understand what protective factors might keep some people from developing tinnitus, while others exposed to the same conditions experience tinnitus.

In this study, only half of the animals receiving a noise-overexposure developed tinnitus. This is similarly the case with humans — not everyone with hearing damage ends up with tinnitus. An important finding in the new paper is that animals that did not get tinnitus showed fewer changes in their multisensory plasticity than those with evidence of tinnitus. In other words, their neurons were not hyperactive.

Shore is now working with other students and postdoctoral fellows to develop a device that uses the new knowledge about the importance of signal timing to alleviate tinnitus. The device will combine sound and electrical stimulation of the face and neck in order to return to normal the neural activity in the auditory pathway.

“If we get the timing right, we believe we can decrease the firing rates of neurons at the tinnitus frequency, and target those with hyperactivity,” says Shore. She and her colleagues are also working to develop pharmacological manipulations that could enhance stimulus timed plasticity by changing specific molecular targets.

But, she notes, any treatment will likely have to be customized to each patient, and delivered on a regular basis. And some patients may be more likely to derive benefit than others.

Alzheimer-substance may be the nanomaterial of tomorrow

It causes brain diseases like Alzheimer’s, Parkinson’s and Creutzfeldt-Jakob’s disease. It is also hard and rigid as steel. Now research at Chalmers University of Technology shows that the amyloid protein carries unique characteristics that may lead to the development of new composite materials for nano processors and data storage of tomorrow and even make objects invisible.

Piotr Hanczyc, PhD student at the department of Chemical and Biological Engineering, shows in an article in Nature Photonics, that the amyloid, a very dense aggregate of protein that causes brain diseases like Alzheimer’s and Parkinson’s, carries unique characteristics. Unlike well-functioning protein the amyloid reacts upon multi photon laser irradiation. This laser may in the future possibly be used for detection of amyloids inside a human brain. This discovery is in itself a breakthrough.

- But you can also create these aggregates in an artificial way in a laboratory and in combination with other materials create unique characteristics, Piotr Hanczyc says.

The amyloid aggregates are as hard and rigid as steel. The difference is that steel is much heavier and has defined material properties whereas amyloids can be tuned for desired purpose. By attaching a material’s molecules to the dense amyloid its characteristics change. This has been known for more than ten years and is already used by scientists.

- What hasn’t been known is that the amyloids react to multi-photon irradiation and this opens up new possibilities to also change the nature of the material attached to the amyloids, Piotr Hanczyc says.

The amyloids are shaped like discs densely piled upon each other.  When a material gets merged with these discs its molecules end up so densely and regularly that they can communicate and exchange information. This means totally new possibilities to change a material’s characteristics.

Multi-photon tests on materials tied to amyloids are yet to be performed, but Piotr sees an opportunity for cooperation with Chalmers material science researchers interested for example in solar cell technology.

And though it may still be science fiction, he also considers that one day scientists may use the material properties of amyloid fibrils in the research of invisible metamaterials.

- An object’s ability to reflect light could be altered so that what’s behind it gets reflected instead of the object itself, in principle changing the index of light refraction, kind of like when light hits the surface of water, Piotr Hanczyc says.

Researchers Study Alcohol Addiction Using Optogenetics

Wake Forest Baptist Medical Center researchers are gaining a better understanding of the neurochemical basis of addiction with a new technology called optogenetics.

In neuroscience research, optogenetics is a newly developed technology that allows researchers to control the activity of specific populations of brain cells, or neurons, using light. And it’s all thanks to understanding how tiny green algae, that give pond scum its distinctive color, detect and use light to grow.

The technology enables researchers like Evgeny A. Budygin, Ph.D., assistant professor of neurobiology and anatomy at Wake Forest Baptist, to address critical questions regarding the role of dopamine in alcohol drinking-related behaviors, using a rodent model.

"With this technique, we’ve basically taken control of specific populations of dopamine cells, using light to make them respond - almost like flipping a light switch," said Budygin. "These data provide us with concrete direction about what kind of patterns of dopamine cell activation might be most effective to target alcohol drinking."

The latest study from Budygin and his team published online in last month’s journal Frontiers in Behavioral Neuroscience. Co-author Jeffrey L. Weiner, Ph.D., professor of physiology and pharmacology at Wake Forest Baptist, said one of the biggest challenges in neuroscience has been to control the activity of brain cells in the same way that the brain actually controls them. With optogenetics, neuroscientists can turn specific neurons on or off at will, proving that those neurons actually govern specific behaviors.

"We have known for many years what areas of the brain are involved in the development of addiction and which neurotransmitters are essential for this process," Weiner said. "We need to know the causal relationship between neurochemical changes in the brain and addictive behaviors, and optogenetics is making that possible now."

The researchers used cutting-edge molecular techniques to express the light-responsive channelrhodopsin protein in a specific population of dopamine cells in the brain-reward system of rodents. They then implanted tiny optical fibers into this brain region and were able to control the activity of these dopamine cells by flashing a blue laser on them.

"You can place an electrode in the brain and apply an electrical current to mimic the way brain cells get excited, but when you do that you’re activating all the cells in that area," Weiner said. "With optogenetics, we were able to selectively control a specific population of dopamine cells in a part of the brain-reward system. Using this technique, we discovered distinct patterns of dopamine cell activation that seemed to be able to disrupt the alcohol-drinking behavior of the rats."

Weiner said there is translational value from the study because “it gives us better insight into how we might want to use something like deep-brain stimulation to treat alcoholism. Doctors are starting to use deep-brain stimulation to treat everything from anxiety to depression, and while it works, there is little scientific understanding behind it, he said.

Budygin agreed and said this kind of project wouldn’t be possible without cross campus collaboration between neurobiology and anatomy, physiology and pharmacology and physics. “Now we are taking the first steps in this direction,” he said. “It was impossible before the optogenetic era.”

The brain’s got rhythm: Extracting temporal patterns from visual input

To understand how the brain recognizes speech, appreciates music and performs other higher-level functions, it is necessary to understand how neural systems process temporal information. Recently, scientists at Beijing Normal University studied a simple but powerful network model by which a neural system can extract long-period (several seconds in duration) external rhythms from visual input. Moreover, the study’s findings suggest that a large neural network with a scale-free topology – that is, a network in which the probability distribution of the number of connections between its nodes follows a power law – is analogous to a repertoire where neural loops and chains form the mechanism by which exogenous rhythms are learned. Importantly, their model suggests that the brain does not necessarily require an internal clock to acquire and memorize these rhythms.

Prof. Si Wu and Prof. Gang Hu discussed the paper that they and their co-authors recently published in Proceedings of the National Academy of Sciences. “The challenge for generating slow oscillation – that is, on the order of seconds – in a neural system is that the dynamics of single neurons and neuronal synapses are too short,” Wu tells Medical Xpress. “In other words, for an unstructured network, a strong input will typically generate a strong transient response, and hence the system is unable to retain slow oscillation.” To solve this problem, the scientists came up with the idea of using the propagation of activity along a long loop of neurons to hold the rhythm information. “Neurons in the loop need to have low-connectivity degrees to avoid inducing synchronous firing of the network,” Hu adds.

Hu also comments on constructing a network model with scale-free structure. “We knew that a scale-free network had the structure we wanted – namely, it consists of a large number of low-degree neurons which can form different sizes of loops and chains, as well as a few hub neurons which can trigger synchronous firing of the network. Furthermore,” he continues, “we didn’t want hub neurons to be easily elicited; otherwise, the network will always get into epileptic firings.” To solve this problem, the researchers required that the neuronal interactions have the proper form to easily activate low-degree neuron while also making it hard to activate hub neurons. Wu point out that biologically plausible electrical synapses and scaled chemical synapses naturally hold this property.

Wu says that the researchers did not develop innovative techniques in this study. “Our main contribution was to propose a simple and yet effective mechanism for a neural system encoding temporal information,” he explains, noting that this mechanism consists of five key points:

1. Hub neurons, through their massive connections to others, induce synchronous firing of the network

2. Loops of low-degree neurons hold rhythm information, with the loop size deciding the rhythm

3. Proper electrical or scaled chemical neuronal synapses ensure that activating a hub neuron is difficult in comparison with a low-degree neuron – and also avoids epileptic network firing, in which periods of rapid spiking are followed by quiescent, silent, periods

4. A large-size scale-free network is like a reservoir, which contains a large number and various sizes of loops and chains formed by low-degree neurons, and hence can encode a broad range of rhythmic information

5. When an external rhythmic input is presented, the network selects a loop from its reservoir, with the loop size matching the input rhythm – and this matching operation can be achieved by a synaptic plasticity rule

The team’s findings imply that in terms of neural information processing, a neural system can use loops and chains of connected neurons to hold the memory trace of input information and, that the latter might serve as the substrate to process temporal events. “These implications for temporal information processing in neural systems have two aspects,” Wu points out. “Firstly, there’s been a long-standing debate on whether the brain has a global clock that counts time and coordinates temporal events. Our study suggests that this is not necessary: By using intrinsic network dynamics, the neural system can process temporal information in a distributed manner.”

Secondly, Wu continues, the brain may not use very complicated strategies to process temporal information, but by fully utilizing its enormous number of neurons, rather simple ones. “Our study suggests that a large size scale-free network has various lengths of loops and chains to hold different rhythms of inputs, making information encoding very simple. This is not economically efficient, but it simplifies computation, which could be crucial for animals responding quickly in a naturally competitive environment.”

In the presence of an external rhythmic input, Wu says that the neural system responds and holds the residual activity as the memory trace of the input for a sufficiently long time. If this input is repetitively presented, neuron pairs which fire together become connected through the biological synaptic plasticity rule, and thereby a loop matching the input rhythm is established.

Hu tells Medical Xpress that the network topology is not required to be perfectly scale-free, but rather that the network consists of a few neurons having many connections and a large number of neurons with few connections. “For the convenience of analysis, we considered a scale-free network in which the distribution of neuronal connections satisfying a power law. However, in practice, we don’t need such a strong condition. Rather, what we really need is a large number of low-degree neurons forming loops and chains, and a few hub neurons triggering synchronous firing. In other words, scale-free topology is the sufficient, but not the necessary, condition for our model to work.” Although the researchers focused on the visual system and have not applied their model to the auditory system, Hi suspects that it can be applied to the latter, where temporal processing is more critical.

Moving forward, the scientists’ next step is to build large networks having a similar structure but with more realistic neurons and synapses. “Based on this model,” Wu concludes, “we can explore how temporal information encoded in the way proposed in our model is involved in higher brain functions.” Moreover, other dynamical systems which generate slow oscillation and need to hold temporal information by network dynamics might benefit from our study.”