neuronfire2019

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https://neurosciencenews.com/cognition-amyloid-neurodegeneration-15370/Objective subtle cognitive difficulties predict amyloid accumulation and neurodegeneration

Amyloid accumulation occurs faster in those who have objectively-defined cognitive difficulties than older people who are consideredto be cognitively normal. Mild cognitive impairment is also associated with faster hippocampal and entorhinal cortex atrophy.

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An issue with reading academic writing is that it has all these footnotes containing other texts they’re referencing and I always go ‘oh shit… that sounds good… I gotta read that’ and I’m just never done with stuff I gotta read, one article soon turns into a masterlist of 100 articles which, like decapitating a hydra, increases instead of decreases as each one is read

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Gut bacteria may control movement

A new study puts a fresh spin on what it means to “go with your gut.” The findings, published in Nature, suggest that gut bacteria may control movement in fruit flies and identify the neurons involved in this response. The study was supported by the National Institute of Neurological Disorders and Stroke (NINDS), part of the National Institutes of Health.

“This study provides additional evidence for a connection between the gut and the brain, and in particular outlines how gut bacteria may influence behavior, including movement,” said Margaret Sutherland, Ph.D., program director at NINDS.

Researchers led by Sarkis K. Mazmanian, Ph.D., professor of microbiology at the California Institute of Technology in Pasadena, and graduate student Catherine E. Schretter, observed that germ-free flies, which did not carry bacteria, were hyperactive. For instance, they walked faster, over greater distances, and took shorter rests than flies that had normal levels of microbes. Dr. Mazmanian and his team investigated ways in which gut bacteria may affect behavior in fruit flies.

“Locomotion is important for a number of activities such as mating and searching for food. It turns out that gut bacteria may be critical for fundamental behaviors in animals,” said Dr. Mazmanian.

Fruit flies carry between five and 20 different species of bacteria and Dr. Mazmanian’s team treated the germ-free animals with individual strains of those microbes. When the flies received Lactobacillus brevis, their movements slowed down to normal speed. L. brevis was one of only two species of bacteria that restored normal behavior in the germ-free flies.

Dr. Mazmanian’s group also discovered that the molecule xylose isomerase (Xi), a protein that breaks down sugar and is found in L. brevis, may be critical to this process. Isolating the molecule and treating germ-free flies with it was sufficient to slow down the speedwalkers.

Additional experiments showed that Xi may regulate movement by fine-tuning levels of certain carbohydrates, such as trehalose, which is the main sugar found in flies and is similar to mammalian glucose. Flies that were given Xi had lower levels of trehalose than did untreated germ-free flies. When Xi-treated flies, which showed normal behavior, were given trehalose alone, they resumed fast movements suggesting that the sugar was able to reverse the effects of Xi.

Next, the researchers looked into the flies’ nervous system to see what cells were involved in bacteria-directed movement. When Dr. Mazmanian’s team turned on neurons that produce the chemical octopamine, that activation canceled out the effect of L. brevis on the germ-free flies. As a result, the flies, which had previously slowed down after receiving the bacterium or Xi, resumed their speedwalking behavior. Turning on octopamine-producing nerve cells in flies with normal levels of bacteria also caused them to move faster. However, activating neurons that produce other brain chemicals did not influence the flies’ movements.

According to Dr. Mazmanian, Schretter and their colleagues, Xi may be monitoring the flies’ metabolic state, including levels of nutrients, and then signaling to octopamine neurons whether they should turn on or off, resulting in changes in behavior.

Instead of octopamine, mammals produce a comparable chemical called noradrenaline, which has been shown to control movement.

“Gut bacteria may play a similar role in mammalian locomotion, and even in movement disorders such as Parkinson’s disease,” said Dr. Mazmanian.

More research is needed to see whether bacteria control movement in other species, including mammals. In addition, future studies will further investigate how Xi is involved in these behaviors.

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‘Ecstasy’ shows promise for post-traumatic stress treatment

MDMA shows promise for the treatment of post-traumatic stress disorder. Combining the use of Ecstasy with psychotherapy treatments resulted in a reduction of PTSD symptoms after just one session. 54% of the study participants no longer met the PTSD criteria after two sessions. Patients also reported improvements in depression symptoms.

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It’s Not Your Fault, Your Brain is Self-Centered

https://neurosciencenews.com/short-term-memory-self-centered-10891/

Testing self-referential bias in working memory, researchers report people automatically self prioritize. This may form the basis for egocentric bias when it comes to decision making.

“Automatic Prioritization of Self-Referential Stimuli in Working Memory,” Shouhang Yin, Jie Sui, yu-Chin Chiu, Antao Chen and Tobias Egner. Psychological Science, March 1, 2019. DOI:10.1177/0956797618818483

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Obese Mice Lose Anxiety When ‘Zombie Cells’ Exit the Brain

Obesity increases the level of “zombie” or senescent cells in the brain, and that those cells, in turn, are linked to anxiety.

The research is in Cell Metabolism. (full open access)

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Prediction method developed for epileptic seizures

System to predict epileptic seizures developed by Dr Omid Kavehei designed to give 30-minute warning using data from a non-surgical device and is based on latest artificial intelligence and machine learning.

Proof of concept for seizure prediction

Epileptic seizures strike with little warning and nearly one third of people living with epilepsy are resistant to treatment that controls these attacks. More than 250,000 Australians and 65 million people worldwide are living with epilepsy.

Now researchers at the University of Sydney have used advanced artificial intelligence and machine learning to develop a generalised method to predict when seizures will strike that will not require surgical implants.

Dr Omid Kavehei from the Faculty of Engineering and IT and the University of Sydney Nano Institute said: “We are on track to develop an affordable, portable and non-surgical device that will give reliable prediction of seizures for people living with treatment-resistant epilepsy.”

In a paper published in Neural Networks, Dr Kavehei and his team have proposed a generalised, patient-specific, seizure-prediction method that can alert epilepsy sufferers within 30 minutes of the likelihood of a seizure.

Dr Kavehei said there had been remarkable advances in artificial intelligence as well as micro- and nano-electronics that have allowed the development of such systems.

“Just four years ago, you couldn’t process sophisticated AI through small electronic chips. Now it is completely accessible. In five years, the possibilities will be enormous,” Dr Kavehei said.

The study uses three data sets from Europe and the United States. Using that data, the team has developed a predictive algorithm with sensitivity of up to 81.4 percent and false prediction rate as low as 0.06 an hour.

“While this still leaves some uncertainty, we expect that as our access to seizure data increases, our sensitivity rates will improve,” Dr Kavehei said.

Carol Ireland, chief executive of Epilepsy Action Australia, said: “Living with constant uncertainty significantly contributes to increased anxiety in people with epilepsy and their families, never knowing when the next seizure may occur.

“Even people with well controlled epilepsy have expressed their constant concern, not knowing if or when they will experience a seizure at work, school, travelling or out with friends.

“Any progress toward reliable seizure prediction will significantly impact the quality of life and freedom of choice for people living with epilepsy.”

Dr Kavehei and lead author of the study, Nhan Duy Truong, used deep machine learning and data-mining techniques to develop a dynamic analytical tool that can read a patient’s electroencephalogram, or EEG, data from a wearable cap or other portable device to gather EEG data.

Wearable technology could be attached to an affordable device based on the readily available Raspberry Pi technology that could give a patient a 30-minute warning and percentage likelihood of a seizure.

Dr Kavehei said an advantage of their system is that is unlikely to require regulatory approval, and could easily work with existing implanted systems or medical treatments.

The algorithm that Dr Kavehei and team have developed can generate optimised features for each patient. They do this using what is known as a ‘convolutional neural network’, that is highly attuned to noticing changes in brain activity based on EEG readings.

Other technologies being developed typically require surgical implants or rely on high levels of feature engineering for each patient. Such engineering requires an expert to develop optimised features for each prediction task.

An advantage of Dr Kavehei’s methodology is that the system learns as brain patterns change, requiring minimum feature engineering. This allows for faster and more frequent updates of the information, giving patients maximum benefit from the seizure prediction algorithm.

The next step for the team is to apply the neural networks across much larger data sets of seizure information, improving sensitivity. They are also planning to develop a physical prototype to test the system clinically with partners at the University of Sydney’s Westmead medical campus.

An alarm would be triggered between 30 and five minutes before a seizure onset, giving patients time to find a safe place, reduce stress or initiate an intervention strategy to prevent or control the seizure.

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Art and science in beautiful conversation!

Here’s a 30-something Santiago Ramón y Cajal hanging out in his library:

For more, check out this article or visit the Weisman Art Museum in Minnesota before May 21.

Images courtesy of Instituto Cajal del Consjo Superior de Investigaciones Científicas, Madrid

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Brainbow is the process by which individual neurons in the brain can be distinguished from neighboring neurons using fluorescent proteins. By randomly expressing different ratios of red, green, and blue derivatives of green fluorescent protein in individual neurons, it is possible to flag each neuron with a distinctive color. This process has been a major contribution to the field of connectomics; the study of neural connections in the brain.

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This picture shows the architecture of white matter in your brain.

The nervous system is made up of two types of matter; white and grey. They get their colour from when the axons are covered in a fatty white coloured substance called myelin. Essentially, the grey matter is composed of the neuron’s cell bodies whilst white matter is composed of the myelinated axons which connects areas of grey matter together. It can be compared to a computer network; the grey matter as the computers, whereas the white matter represents the network cables connecting the computers together.

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And the best headline of the year goes to….

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Overheard from another faculty office down the hall: “All right, who am I and what am I doing here?”

Later, from still another office: “Do not talk to me about my own research! I have GIVEN UP.”

It’s that time of the semester.

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sure i guess sex is okay but have you ever closed a dozen tabs after finishing an academic paper

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when you find an academic source that’s perfect for your paper but it’s behind a pay wall

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Your body is an incredibly bizarre machine.

“What you see is a myosin protein dragging an endorphin along a filament to the inner part of the brain’s parietal cortex which creates happiness. Happiness. You’re looking at happiness.”