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Category: neuroscience – Page 333

Lifespan Increases in Mice when Specific Brain Cells are Activated, study finds

In recent years, research has begun to reveal that the lines of communication between the body’s organs are key regulators of aging. When these lines are open, the body’s organs and systems work well together. But with age, communication lines deteriorate, and organs don’t get the molecular and electrical messages they need to function properly.

A new study from Washington University School of Medicine in St. Louis identifies, in mice, a critical communication pathway connecting the brain and the body’s fat tissue in a feedback loop that appears central to energy production throughout the body. The research suggests that the gradual deterioration of this feedback loop contributes to the increasing health problems that are typical of natural aging.

The study—published in the journal Cell Metabolism—has implications for developing future interventions that could maintain the feedback loop longer and slow the effects of advancing age.

Quantum Approaches to Consciousness

It is widely accepted that consciousness or, more generally, mental activity is in some way correlated to the behavior of the material brain. Since quantum theory is the most fundamental theory of matter that is currently available, it is a legitimate question to ask whether quantum theory can help us to understand consciousness. Several approaches answering this question affirmatively, proposed in recent decades, will be surveyed. There are three basic types of corresponding approaches: consciousness is a manifestation of quantum processes in the brain, quantum concepts are used to understand consciousness without referring to brain activity, and matter and consciousness are regarded as dual aspects of one underlying reality. Major contemporary variants of these quantum-inspired approaches will be discussed.

Ultimate Computing: Biomolecular Consciousness and NanoTechnology

The possibility of direct interfacing between biological and technological information devices could result in a merger of mind and machine — Ultimate Computing. This book, a thorough consideration of this idea, involves a number of disciplines, including biochemistry, cognitive science, computer science, engineering, mathematics, microbiology, molecular biology, pharmacology, philosophy, physics, physiology, and psychology.

Ion-tunable antiambipolarity in mixed ion–electron conducting polymers enables biorealistic organic electrochemical neurons

Silicon-based complementary metal-oxide semiconductors or negative differential resistance device circuits can emulate neural features, yet are complicated to fabricate and not biocompatible. Here, the authors report an ion-modulated antiambipolarity in mixed ion–electron conducting polymers demonstrating capability of sensing, spiking, emulating the most critical biological neural features, and stimulating biological nerves in vivo.

Brain Waves Reveal Layered Activity Patterns Across Species

Summary: Researchers discovered that different layers of the brain’s cortex exhibit distinct electrical activity patterns, with rapid gamma waves in the upper layers and slower alpha and beta waves in the deeper layers. This pattern is consistent across various brain regions and species, including humans, suggesting a fundamental role in cortical function.

The research indicates that imbalances in these oscillations might be linked to neurological disorders like ADHD. This study not only deepens our understanding of brain function but also opens new possibilities for diagnosing and treating neuropsychiatric disorders.

A breakthrough way to train neuromorphic chips

Using a biosensor to detect cystic fibrosis as the test case, TU/e researchers have devised an innovative way to train neuromorphic chips as presented in a new paper in Nature Electronics.

Neuromorphic computers—which are based on the structure of the human brain—could revolutionize our future health care devices. However, their widespread use is hindered by the need to train neuromorphic computers using external training software, which can be time-consuming and energy inefficient.

Researchers from Eindhoven University of Technology and Northwestern University in the U.S. have developed a new neuromorphic biosensor capable of on-chip learning that doesn’t need external training. As a proof-of-concept, the researchers used the biosensor to diagnose based on sweat samples.