Lifeboat Foundation

Psychoses like schizophrenia cost billions of dollars annually and derail the lives of people struggling with the disease. Now Monash University researchers have modeled how the effects of psychosis spread through the brain, allowing them to isolate areas where these changes may originate from and which could be targeted by therapies designed to reduce the disease’s progression.

Scientists have revealed the molecular structure of a type of receptor that’s crucial to brain development and function.

Known as Type A GABA receptors, these receptors are already targeted by pharmaceutical anesthetics, sedatives and antidepressants because of their important role in brain function. The discovery, published today in the journal Nature, reveals the dominant assemblies and states of the GABA receptor, a finding that could enable the development of new compounds that more specifically target a range of medical disorders.

“It is the main player that balances excitation and inhibition in the brain,” said lead author Chang Sun, Ph.D., a postdoctoral researcher in the Vollum Institute at Oregon Health & Science University. “It affects all aspects of brain function, from motor function, to memory and learning, and also emotion and anxiety.”

New research from the University of Missouri School of Medicine suggests there may be another way to treat cigarette cravings. Researchers found that theta-burst transcranial magnetic stimulation (TBS)—strong, rapidly fluctuating magnetic field pulses that can affect brain activity—can lead to improved self-control, reduced cravings and as a result, less smoking.

People with nicotine dependence tend to have significant structural and functional differences in the brain, compared to healthy non-smokers. Smoking cigarettes has been shown to be associated with less gray matter, which means they have less neurons and other cells in the brain.

Research suggests these differences may affect inhibitory control (IC), which is our control over automatic urges and response to stimuli—what enables humans to stop an impulsive reaction to something.

The opioid epidemic in the United States has exacted an incalculable toll on individuals and communities, creating an urgent need for alternative painkillers. The search for non-opioid treatments is crucial, not only to mitigate the risks of addiction and overdose, but also to develop pain management tools that remain effective without inducing tolerance and other challenging side effects in patients.

New research from the University of Chicago identified an alternative signaling pathway in the brain of mice that relieves pain, even in animals that have developed tolerance to opioids.

The study, titled “A Cholinergic Circuit That Relieves Pain, Despite Opioid Tolerance” and published in Neuron, also showed that pain relief through this route did not induce tolerance, did not create withdrawals symptoms after treatment was stopped, and did not activate reward systems, limiting risk for addiction and making it a viable path to developing effective, non-opioid pain relief.

You’re looking at a truck. You’re with a young child and he follows your gaze. He’s interested in the object you’re looking at without you pointing at it. This is called joint attention and it is one of the primary ways children learn to connect words with objects and acquire language.

Lack of joint attention is a core feature of autism. Until now, it was thought that stimulating joint attention in people with autism would help them express themselves verbally. But a meta-analysis of 71 studies on autism challenges this assumption and suggests that people with autism spectrum disorders may acquire language differently.

The study—by Laurent Mottron, a professor in the Department of Psychiatry and Addiction at Université de Montréal and a psychiatrist at the Hôpital en santé mentale Rivière-des-Prairies of the CIUSSS du Nord-de-l’Île-de-Montréal; Mikhail Kissine, a professor of linguistics at Université Libre de Bruxelles; and Ariane St-Denis, a medical student at McGill University—is published in Neuroscience & Biobehavioral Reviews.

Fresh from solving the protein structure challenge, Google’s deep-learning outfit is moving on to the human genome.

Google DeepMind researchers recently developed a technique to improve math ability in AI language models like ChatGPT by using other AI models to improve prompting—the written instructions that tell the AI model what to do. It found that using human-style encouragement improved math skills dramatically, in line with earlier results.

In a paper called “Large Language Models as Optimizers” listed this month on arXiv, DeepMind scientists introduced Optimization by PROmpting (OPRO), a method to improve the performance of large language models (LLMs) such as OpenAI’s ChatGPT and Google’s PaLM 2. This new approach sidesteps the limitations of traditional math-based optimizers by using natural language to guide LLMs in problem-solving. “Natural language” is a fancy way of saying everyday human speech.

A team of researchers in Japan claims to have figured out a way to translate the clucking of chickens with the use of artificial intelligence.

As detailed in a yet-to-be-peer-reviewed preprint, the team led by University of Tokyo professor Adrian David Cheok — who has previously studied sex robots — came up with a “system capable of interpreting various emotional states in chickens, including hunger, fear, anger, contentment, excitement, and distress” by using “cutting-edge AI technique we call Deep Emotional Analysis Learning.”

They say the technique is “rooted in complex mathematical algorithms” and can even be used to adapt to the ever-changing vocal patterns of chickens, meaning that it only gets better at deciphering “chicken vocalizations” over time.

With advanced technology and proper medical care, one can live without pancreas and lead a normal lifestyle.