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Psilocybin has antidepressant-like effects and can improve cognitive function in a rat model of depression induced by chronic stress, according to new research published in Psychedelic Medicine. The findings provide new insights into the potential therapeutic applications of psychedelic substances and highlight the need for further research in this area to fully comprehend the underlying mechanisms.

Psilocybin is a naturally occurring psychedelic compound found in certain species of mushrooms, often referred to as “magic mushrooms” or “shrooms.” In recent years, there has been a growing interest in studying psilocybin and other psychedelics for their potential therapeutic effects. Psychedelics have shown promising rapid and persistent antidepressant effects in humans and animals. However, the exact mechanism behind these effects is not fully understood.

To investigate the cellular and molecular mechanisms responsible for the antidepressant effects of psychedelics, the researchers used an appropriate animal model of depression. They chose a chronic stress-based model for greater translational value, as chronic stress is known to be a significant factor in depression. They specifically focused on female rats, as women are more susceptible to depression than men.

New research sheds light on a tricky idea of consciousness: There’s a difference between what the brain takes in and what we’re consciously aware of taking in.

Scientists now think they’ve pinpointed the brain region where that conscious awareness is managed.

The team, from the Hebrew University of Jerusalem in Israel and the University of California, Berkeley (UC Berkeley), in the US, found sustained brain activity in the occipitotemporal area of the visual cortex in the back of the brain.

Neurons are the cells that constitute neural circuits and use chemicals and electricity to receive and send messages that allow the body to do everything, including thinking, sensing, moving, and more. Neurons have a long fiber called an axon that sends information to the subsequent neurons. Information from axons is received by branch-like structures that fan out from the cell body, called dendrites.

Dendritic refinement is an important part of early postnatal brain development during which dendrites are tailored to make specific connections with appropriate axons. In a recently published paper, researchers present evidence showing how a mechanism within the neurons of a rodent involving the Golgi apparatus initiates dendritic refinement with the help of the neuronal activity received by a receptor of a neurotransmitter called N-methyl-D-aspartate-type glutamate receptor (NMDAR).

The paper was published in Cell Reports on July 28.

How is ongoing visual experience represented neurally? Vishne et al. decode images lasting different durations from intracranial electrophysiology, uncovering distinct representation dynamics across the human brain: sustained and stable in occipitotemporal cortex and transient in frontoparietal areas. This sheds light on the spatiotemporal correlates of experience encoding by the brain.

UCLA Health researchers have published the largest-ever study of families with at least two children with autism, uncovering new risk genes and providing new insights into how genetics influence whether someone develops autism spectrum disorder.

The new study, published July 28 in the Proceedings of the National Academy of Sciences, also provides genetic evidence that language delay and dysfunction should be reconsidered as a core component of autism.

Most genetic studies of autism have focused on families with one child affected by the neurodevelopmental disorder, sometimes excluding families with multiple affected children. As a result, few studies have examined the role of rare inherited variation or its interaction with the combined effect of multiple common genetic variations that contribute to the risk of developing autism.

The STAR party’s vision for Canada includes the research and development of self sustainable Mobile Airborne Cities; or Airborne Arcologies. Being an obviously semi-long term goal, the objective would be to at first, allocate budgeting towards research and development of components to build this project in a phased manner… and the scaling of the project as technology allows for it.

Phase I: research and development of scalable micro-prototypes.

Phase II: multiple prototype development / testing stages.

Phase III: Final modifications, and testing of Finished Model.

Phase IV: aircity one digital-testing / infrastructure development.

Phase V: aircity production facility development.

Phase VI:… More

Researchers from the Tokyo University of Science recently published a study in the journal Artificial Life and Robotics where they explored how machine learning can help detect deception.

Machine learning is a subset of artificial intelligence (AI) that involves the use of algorithms and statistical models to enable computers to learn and improve from experience without being explicitly programmed. In other words, it is a method of teaching computers to perform specific tasks by learning from data, patterns, and examples, rather than relying on pre-defined rules.

Detecting deception can be important in various situations, like questioning crime victims or suspects and interviewing patients with mental health issues. Sometimes, human interviewers might struggle to ask the right questions or spot deception accurately.

The biological roots of autism continue to perplex researchers, despite a growing body of studies looking at an increasing array of genetic, cellular and microbial data. Recently, scientists have homed in on a new and promising area of focus: the microbiome. This collection of microbes that inhabit the human gut has been shown to play a role in autism, but the mechanics of this link have remained awash in ambiguity.

Taking a fresh computational approach to the problem, a study published today, June 26, in Nature Neuroscience sheds new light on the relationship between the microbiome and . This research—which originated at the Simons Foundation’s Autism Research Initiative (SFARI) and involved an innovative reanalysis of dozens of previously published datasets—aligns with a recent, long-term study of autistic individuals that centered on a microbiome-focused treatment intervention. These findings also underscore the importance of longitudinal studies in elucidating the interplay between the microbiome and complex conditions such as autism.

“We were able to harmonize seemingly disparate data from different studies and find a common language with which to unite them. With this, we were able to identify a microbial signature that distinguishes autistic from neurotypical individuals across many studies,” says Jamie Morton, one of the study’s corresponding authors, who began this work while a postdoctoral researcher at the Simons Foundation and is now an independent consultant. “But the bigger point is that going forward, we need robust long-term studies that look at as many datasets as possible and understand how they change when there is a [therapeutic] intervention.”