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Category: neuroscience – Page 73

A Tiny Peptide Can Freeze Parkinson’s Proteins Before They Turn Toxic

As Parkinson’s disease progresses, harmful protein clumps build up in the brain, blocking communications between neurons and killing them off – but what if we could prevent these clusters from forming?

Researchers led by a team from the University of Bath in the UK have achieved just that in a basic worm model of Parkinson’s. They engineered a peptide, a small amino acid chain, to essentially keep a protein called alpha-synuclein locked in its healthy shape. This prevented the misfolding that leads to clumps.

The potential treatment checks several important boxes: it’s durable, and it can survive inside cells without causing any toxic side effects.

Sean Carroll: Can we ever escape the logic of a clockwork universe?

What if the universe is a machine, and every moment in our past, present, and future is already encoded in the positions of its particles?

Physicist Sean Carroll explores the unsettling implications of classical mechanics, from Newton’s laws to Laplace’s thought experiment, showing how determinism challenges the very idea of free will.

Lab-grown brains with all major cell types support next-generation therapy research

A new 3D human brain tissue platform developed by MIT researchers is the first to integrate all major brain cell types, including neurons, glial cells and the vasculature into a single culture. Grown from individual donors’ induced pluripotent stem cells, these models—dubbed Multicellular Integrated Brains (miBrains)—replicate key features and functions of human brain tissue, are readily customizable through gene editing, and can be produced in quantities that support large-scale research.

Although each unit is smaller than a dime, miBrains may be worth a great deal to researchers and drug developers who need more complex living lab models to better understand brain biology and treat diseases.

“The miBrain is the only in vitro system that contains all six major cell types that are present in the human brain,” said Li-Huei Tsai, Picower Professor, director of The Picower Professor of Learning and Memory, and senior author of the study describing miBrains, published in the Proceedings of the National Academy of Sciences.

Algorithm precisely quantifies flow of information in complex networks

Networks are systems comprised of two or more connected devices, biological organisms or other components, which typically share information with each other. Understanding how information moves between these connected components, also known as nodes, could help to advance research focusing on numerous topics, ranging from artificial intelligence (AI) to neuroscience.

To measure the directional flow of information in systems, scientists typically rely on a mathematical construct known as transfer entropy, which essentially quantifies the rate at which information is transmitted from one node to another. Yet most strategies for calculating transfer entropy developed so far rely on approximations, which significantly limits their accuracy and reliability.

Researchers at AMOLF, a institute in the Netherlands, recently developed a computational algorithm that can precisely quantify transfer entropy in a wide range of complex networks. Their algorithm, introduced in a paper published in Physical Review Letters, opens new exciting possibilities for the study of information transfer in both biological and engineered networks.

‘Wetware’: Scientists use human mini-brains to power computers

Inside a lab in the picturesque Swiss town of Vevey, a scientist gives tiny clumps of human brain cells the nutrient-rich fluid they need to stay alive.

It is vital these remain healthy, because they are serving as rudimentary computer processors—and, unlike your laptop, once they die, they cannot be rebooted.

This new field of research, called biocomputing or “wetware,” aims to harness the evolutionarily honed yet still mysterious computing power of the human brain.

How the auditory cortex syncs with behavior to help the brain become a better listener

When we are engaged in a task, our brain’s auditory system changes how it works. One of the main auditory centers of the brain, the auditory cortex, is filled with neural activity that is not sound-driven—rather, this activity times the task, each neuron ticking at a different moment during task performance.

Researchers at Hebrew University have discovered how this happens. The study published in Science Advances, led by Prof. Israel Nelken from the Edmond and Lily Safra Center for Brain Sciences (ELSC) and the Institute of Life Sciences, is based on the Ph.D. research of Ana Polterovich, with contributions from Alex Kazakov, Maciej M. Jankowski, and Johannes Niediek.

They found that when we are engaged in the task, neurons in the brain’s show large bursts of activity that aren’t caused directly by sounds. Instead, these “” are tied to specific moments in a task, suggesting that the auditory cortex is deeply in sync with behavior.

Deep sleep supports memory via brain fluid and neural rhythms, research finds

Researchers led by Masako Tamaki at the RIKEN Center for Brain Science in Japan report a link between deep sleep and cerebrospinal fluid, the clear liquid that surrounds and supports the brain and spinal cord. Published in Proceedings of the National Academy of Sciences, the study demonstrates how changes in cerebrospinal fluid signals during sleep—as measured by MRI—are time-locked to slow brain waves and other neural events.

These findings offer a clue as to why stable sleep is important for normal brain function, particularly within the brain network that controls learning and memory.

Why do we sleep? Scientists think that sleep is important for consolidating memories and removing waste from the brain that accumulates as a result of brain activity while we are awake.

Surprising gene mutation in brain’s immune cells linked to increased Alzheimer’s risk

In a study published in Neuron, a research team at the Department of Neurology at Massachusetts General Hospital, aimed to understand how immune cells of the brain, called microglia, contribute to Alzheimer’s disease (AD) pathology. It’s known that subtle changes, or mutations, in genes expressed in microglia are associated with an increased risk for developing late-onset AD.

The study focused on one such mutation in the microglial gene TREM2, an essential switch that activates microglia to clean up toxic amyloid plaques (abnormal protein deposits) that build up between in the brain. This mutation, called T96K, is a “gain-of-function” mutation in TREM2, meaning it increases TREM2 activation and allows the gene to remain super active.

The researchers explored how this mutation impacts microglial function to increase risk for AD. The team generated a mutant mouse model carrying the mutation, which was bred with a mouse model of AD to have brain changes consistent with AD. They found that in female AD mice exclusively, the mutation strongly reduced the capability of microglia to respond to toxic amyloid plaques, making these cells less protective against brain aging.

Astrocytes are superstars in the game of long-term memory

Why are we able to recall only some of our past experiences? A new study led by Jun Nagai at the RIKEN Center for Brain Science in Japan has an answer. Surprisingly, it turns out that the brain cells responsible for stabilizing memories aren’t neurons. Rather, they are astrocytes, a type of glial cell that is usually thought of as a role player in the game of learning and memory.

Published in Nature, the study shows how emotionally intense experiences like fear biologically tag small groups of astrocytes for several days so that they can re-engage when a mouse recalls the experience. It is this repeated astrocytic engagement that stabilizes memories.

Astrocytes have traditionally been thought to have a supporting role in the brain, literally. But when it became clear that engrams—the actual traces that exist in neurons—cannot alone account for stabilized, , Nagai and his team turned to astrocytes for a solution.

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