Lifeboat Foundation: Safeguarding Humanity
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Category: neuroscience – Page 301

About six years ago, scientists discovered a new type of more powerful neural network model known as a transformer. These models can achieve unprecedented performance, such as by generating text from prompts with near-human-like accuracy. A transformer underlies AI systems such as ChatGPT and Bard, for example. While incredibly effective, transformers are also mysterious: Unlike with other -inspired neural network models, it hasn’t been clear how to build them using biological components.

Now, researchers from MIT, the MIT-IBM Watson AI Lab, and Harvard Medical School have produced a hypothesis that may explain how a transformer could be built using biological elements in the brain. They suggest that a biological network composed of neurons and other called astrocytes could perform the same core computation as a transformer.

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We often believe computers are more efficient than humans. After all, computers can complete a complex math equation in a moment and can also recall the name of that one actor we keep forgetting. However, human brains can process complicated layers of information quickly, accurately, and with almost no energy input: recognizing a face after only seeing it once or instantly knowing the difference between a mountain and the ocean. These simple human tasks require enormous processing and energy input from computers, and even then, with varying degrees of accuracy.

Creating brain-like computers with minimal energy requirements would revolutionize nearly every aspect of modern life. Funded by the Department of Energy, Quantum Materials for Energy Efficient Neuromorphic Computing (Q-MEEN-C) — a nationwide consortium led by the University of California San Diego — has been at the forefront of this research.

UC San Diego Assistant Professor of Physics Alex Frañó is co-director of Q-MEEN-C and thinks of the center’s work in phases. In the first phase, he worked closely with President Emeritus of University of California and Professor of Physics Robert Dynes, as well as Rutgers Professor of Engineering Shriram Ramanathan. Together, their teams were successful in finding ways to create or mimic the properties of a single brain element (such as a neuron or synapse) in a quantum material.

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A protein involved in wound healing can improve learning and memory in ageing mice1.

Platelet factor 4 (PF4) has long been known for its role in promoting blood clotting and sealing broken blood vessels. Now, researchers are wondering whether this signalling molecule could be used to treat age-related cognitive disorders such as Alzheimer’s disease.

“The therapeutic possibilities are very exciting,” says geneticist and anti-ageing scientist David Sinclair at Harvard University in Boston, Massachusetts, who was not involved in the research. The study was published on 16 August in Nature.

Young blood, old brains.

A platelet factor joins the list of blood components that might have anti-ageing effects.

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Free will?

Neuroscientists and psychologists have been trying for decades to better understand how humans make decisions, in the hope to devise more effective interventions to promote healthy and beneficial lifestyle choices. Two brain regions that have been linked to decision-making are the orbitofrontal cortex (OFC) and the anterior cingulate cortex (ACC).

Researchers at University of California, Berkeley (UC Berkeley), have been conducting extensive research focusing on these two areas of the brain and exploring their involvement in . In a recent paper published in Nature Neuroscience, they presented interesting new findings that could shed light on the through which the brain prepares to make choices.

“We previously used neural recordings to determine what was going on during decision-making,” Joni Wallis, one of the researchers who carried out the study, told Medical Xpress. “We showed that OFC neurons represent the value of the options under consideration and flip-flopping them back and forth representing the value of each option in turn, as though the OFC is weighing up the two options. This flip-flopping predicts decision making: the more flip-flopping, the more likely the subject is to make a suboptimal choice or to take a long time over their decision.”

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This is a significant development that brings hope to the one billion individuals with obesity worldwide. Researchers led by Director C. Justin LEE from the Center for Cognition and Sociality (CCS) within the Institute for Basic Science (IBS) have discovered new insights into the regulation of fat metabolism. The focus of their study lies within the star-shaped non-neuronal cells in the brain, known as ‘astrocytes’. Furthermore, the group announced successful animal experiments using the newly developed drug ‘KDS2010’, which allowed the mice to successfully achieve weight loss without resorting to dietary restrictions.

The complex balance between food intake and energy expenditure is overseen by the hypothalamus in the brain. While it has been known that the neurons in the lateral hypothalamus are connected to fat tissue and are involved in fat metabolism, their exact role in fat metabolism regulation has remained a mystery. The researchers discovered a cluster of neurons in the hypothalamus that specifically express the receptor for the inhibitory neurotransmitter ‘GABA (Gamma-Aminobutyric Acid)’. This cluster has been found to be associated with the α5 subunit of the GABAA receptor and was hence named the GABRA5 cluster.

In a diet-induced obese mouse model, the researchers observed significant slowing in the pacemaker firing of the GABRA5 neurons. Researchers continued with the study by attempting to inhibit the activity of these GABRA5 neurons using chemogenetic methods. This in turn caused a reduction in heat production (energy consumption) in the brown fat tissue, leading to fat accumulation and weight gain. On the other hand, when the GABRA5 neurons in the hypothalamus were activated, the mice were able to achieve a successful weight reduction. This suggests that the GABRA5 neurons may act as a switch for weight regulation.

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A paper published in Nature Communications shows that when neurons are given information about the changing world around them (task-related sensory input) it changes how they behave, putting them on edge so that tiny inputs can then set off ‘avalanches’ of brain activity, supporting a theory known as the critical brain hypothesis.

The researchers, from Cortical Labs and The University of Melbourne, used DishBrain – a collection of 800,000 human neural cells learning to play Pong.

It is the strongest evidence to date in support of a controversial theory of how the human brain processes information.

DishBrain reveals how human neurons work together to process information.

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In a study of brains from contact sport players who died before reaching 30, more than 40% had chronic traumatic encephalopathy, oXavier?

The findings confirm that CTE can occur even in young people, but more work is needed to determine how CTE relates to clinical symptoms.

Millions of people worldwide get repetitive head impacts through various activities. These can lead to chronic traumatic encephalopathy (CTE), a progressive neurodegenerative disease that causes brain damage similar to that seen in Alzheimer’s disease. CTE has been reported in people as young as 17. The incidence of CTE in young people, however, is unknown.

An NIH-funded research team, led by Dr. Ann McKee at Boston University and VA Boston Health Care, analyzed 152 brains (141 male and 11 female) that were donated to a brain bank. The brain donors had a history of repetitive head impacts from playing contact sports and were younger than 30 years old when they died. Researchers examined the brains and surveyed the donors’ next of kin about clinical symptoms. Results were published in JAMA Neurology on August 28, 2023.

More than 40% of the donors (63 out of 152) had CTE based on established criteria. Nearly all cases of CTE were mild (stages 1 or 2 out of 4). Donors with CTE tended to be older than those without the disease. The most common cause of death among the donors was suicide, followed by unintentional drug overdose. The causes of death did not differ between those with and without CTE. Most of the donors with CTE were male, but one was female–a collegiate soccer player.

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Now, scientists have a mathematical model that closely matches how the human brain processes visual information.

Scientists have confirmed that human brains are naturally wired to perform advanced calculations, much like a high-powered computer, to make sense of the world through a process known as Bayesian inference.

In a study published in the journal Nature Communications, researchers from the University of Sydney, University of Queensland and University of Cambridge developed a specific mathematical model that closely matches how human brains work when it comes to reading vision. The model contained everything needed to carry out Bayesian inference.

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Researchers from the Netherlands Institute for Neuroscience have, for the first time, witnessed nerve plasticity in the axon in motion.

Our nerve cells communicate through rapid transmission of electrical signals known as action potentials. All action potentials in the brain start in one unique small area of the cell: the axon initial segment (AIS). This is the very first part of the axon, the long, thin extension of a nerve cell that transmits signals or impulses from one nerve cell to another. It acts as a control center where it is decided when an action potential is initiated before traveling further along the axon.

Previously, researchers made the surprising observation that plasticity also occurs at the AIS. Plasticity refers to the brain’s ability to create new connections and structures in order to scale the amount of electrical activity, which is crucial for learning and memory. AIS plasticity occurs during changes in brain network activity. The segment’s length can become shorter with excessive activity or longer with low activity. But how does this structure change, and how quickly does it happen? Amélie Fréal and Nora Jamann in the lab of Maarten Kole have, for the first time, observed in real-time how this adaptability functions within the axon and identified the molecular mechanisms behind this process.

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