Lifeboat Foundation

Here is an interview concerning the current AI and generative AI waves, and their relation to neuroscience. We propose solutions based on new technology from neuroAI – which includes humans ability for reasoning, thought, logic, mathematics, proof etc. – and are therefore poorly modeled by data analysis on its own. Some of our work – also with scholars – has been published, while more is to come in a spin-off setting.

“Engineering the brain”. There was no intelligent design, and as a result, body organs do not resemble machines. Once we start building machines like body organs — with utility functions, self-organization and cells as building blocks, we can mesh engineering and evolutionary principles to arrive at better organisms.

We present a novel model of neuroplasticity in the form of a horizontal-vertical integration model. The horizontal plane consists of a network of neurons connected by adaptive transmission links. This fits with standard computational neuroscience approaches. Each individual neuron also has a vertical dimension with internal parameters steering the external membrane-expressed parameters. These determine neural transmission.

In a paper titled, “Multimodal MRI reveals brainstem connections that sustain wakefulness in human consciousness,” published today in Science Translational Medicine, a group of researchers at Massachusetts General Hospital, a founding member of the Mass General Brigham healthcare system, and Boston Children’s Hospital, created a connectivity map of a brain network that they propose is critical to human consciousness.

The study involved high-resolution scans that enabled the researchers to visualize brain connections at submillimeter spatial resolution. This technical advance allowed them to identify previously unseen pathways connecting the brainstem, thalamus, hypothalamus, basal forebrain, and cerebral cortex.

Together, these pathways form a “default ascending arousal network” that sustains wakefulness in the resting, conscious human brain. The concept of a “default” network is based on the idea that specific networks within the brain are most functionally active when the brain is in a resting state of consciousness. In contrast, other networks are more active when the brain is performing goal-directed tasks.

Summary: Researchers developed a groundbreaking model called Brain Language Model (BrainLM) using generative artificial intelligence to map brain activity and its implications for behavior and disease. BrainLM leverages 80,000 scans from 40,000 subjects to create a foundational model that captures the dynamics of brain activity without the need for specific disease-related data.

This model significantly reduces the cost and scale of data required for traditional brain studies, offering a robust framework that can predict conditions like depression, anxiety, and PTSD more effectively than other tools. The BrainLM demonstrates a potent application in clinical trials, potentially halving the costs by identifying patients most likely to benefit from new treatments.

New research reveals the potential link between memory formation and elemental interactions in the mind.

Depression and cardiovascular disease (CVD) are serious concerns for public health. Approximately 280 million people worldwide have depression, while 620 million people have CVD.

It has been known since the 1990s that the two diseases are somehow related. For example, people with depression run a greater risk of CVD, while effective early treatment for depression cuts the risk of subsequently developing CVD by half. Conversely, people with CVD tend to have depression as well. For these reasons, the American Heart Association (AHA) advises to monitor teenagers with depression for CVD.

What wasn’t yet known is what causes this apparent relatedness between the two diseases. Part of the answer probably lies in lifestyle factors common in patients with depression and which increase the risk of CVD, such as smoking, alcohol abuse, lack of exercise, and a poor diet. But it’s also possible that both diseases might be related at a deeper level, through shared developmental pathways.

What influences mental health, academic achievement, and cognitive growth? A recent review published in De Gruyter’s Reviews in the Neurosciences indicates that poverty and low socioeconomic status (SES) are significant contributing factors. While previous research has explored the individual impacts of poverty on the brain and behavior, this review introduces the first integrated framework. It synthesizes evidence from various studies to directly connect brain alterations caused by low SES with behavioral, pathological, and developmental outcomes.

SES refers to the social standing of an individual or family, and involves factors such as wealth, occupation, educational attainment, and living conditions. As well as affecting day-to-day life, perhaps surprisingly SES can also have far-reaching consequences for our brains that begin in childhood and persist into adulthood.

So, how can poverty and low SES change the brain? The review examines the negative effects of poor nutrition, chronic stress, and environmental hazards (such as pollution and inadequate housing conditions), which are more likely to affect low-SES families. These factors can impair the brain development of children, which in turn can influence their language skills, educational attainment, and risk of psychiatric illness.

A study focusing on childhood maltreatment in Australia has uncovered its alarming impact, estimating it causes up to 40 percent of common, life-long mental health conditions.

The mental health conditions examined were anxiety, depression, harmful alcohol and drug use, self-harm, and suicide attempts. Childhood maltreatment is classified as physical, sexual, and emotional abuse, and emotional or physical neglect before the age of 18. Childhood maltreatment was found to account for 41 percent of suicide attempts in Australia, 35 percent for cases of self-harm, and 21 percent for depression.

The analysis, published in JAMA Psychiatry is the first study to provide estimates of the proportion of mental health conditions in Australia that arise from childhood maltreatment. The researchers said the results are a wake-up call for childhood abuse and neglect to be treated as a national public health priority.