Lifeboat Foundation

Researchers show how Stable Diffusion can read minds. The method reconstructs images from fMRI scans with amazing accuracy.

Researchers have been using AI models to decode information from the human brain for years. At their core, most methods involve using pre-recorded fMRI images as input to a generative AI model for text or images.

In early 2018, for example, a group of researchers from Japan demonstrated how a neural network reconstructed images from fMRI recordings. In 2019, a group reconstructed images from monkey neurons, and Meta’s research group, led by Jean-Remi King, has published new work that derives text from fMRI data, for example.

Neuralace™ is a glimpse of what’s possible in the future of BCI.

This patent pending concept technology is the start of Blackrock’s journey toward whole-brain data capture–with transformative potential for the way neurological disorders are treated. With over 10,000 channels and a flexible lace structure that seamlessly conforms to the brain, Neuralace has potential applications in vision and memory restoration, performance prediction, and the treatment of mental health disorders like depression.

Continue reading “Neuralace™ | The next-generation of BCI and whole-brain data capture” »

Blackrock’s long-tested NeuroPort® Array, widely considered the gold standard of high-channel neural interfacing, has been used in human BCIs since 2004 and powered many of the field’s most significant milestones. In clinical trials, patients using Blackrock’s BCI have regained tactile function, movement of their own limbs and prosthetics, and the ability to control digital devices, despite diagnoses of paralysis and other neurological disorders.

While Blackrock’s BCI enables patients to execute sophisticated functions without reliance on assistive technologies, next-generation BCIs for areas such as vision and memory restoration, performance prediction, and treatment of mental health disorders like depression will need to interface with more neurons.

Neuralace is designed to capitalize on this need; with 10,000+ channels and the entire scalable system integrated on an extremely flexible lace-structured chip, it could capture data that is orders of magnitude greater than existing electrodes, allowing for an exponential increase in capability and intuitiveness.

Peptidomics employs techniques of genomics, modern proteomics, state-of-the-art analytical chemistry and computational biology. In this Primer, Hellinger et al. describe the techniques and workflows required for peptide discovery and characterization and give an overview of biological and clinical applications of peptidomics.

A book talk by:

Robert Stickgold, PhD

Continue reading “When Brains Dream: Exploring the Science and Mystery of Sleep” »

AI is spreading beyond the tech giants into all aspects of life and work. One of its most impactful roles will be to help nuclear medicine save the lives of many thousands of cancer patients.

A recent study has suggested that transcriptomes may be the best method for classifying different types of brain disease.

Brains are like puzzles, requiring many nested and co-dependent pieces to function well. The brain is divided into areas, each containing many millions of neurons connected across thousands of synapses. These synapses, which enable communication between neurons, depend on even smaller structures: message-sending boutons (swollen bulbs at the branch-like tips of neurons), message-receiving dendrites (complementary branch-like structures for receiving bouton messages), and power-generating mitochondria. To create a cohesive brain, all these pieces must be accounted for.

However, in the aging brain, these pieces can get lost or altered, and no longer fit in the greater brain puzzle. A research team has now published a study in Frontiers in Aging Neuroscience on this topic.

“Fifty percent of people experience loss of working memory with old age, meaning their ability to hold and manipulate information in the short-term decreases,” says co-first author Courtney Glavis-Bloom, a senior staff scientist in Salk Institute Professor John Reynolds’s lab. “We set out to understand why some individuals maintain healthy working memory as they age, while others do not. In the process, we discovered a novel mechanism for the synaptic basis of cognitive impairment.”

Functional movement/conversion disorder (FMD), part of the spectrum of Functional Neurological Disorder (FND), is a neuropsychiatric condition marked by a range of neurological symptoms, including tremors, muscular spasms and cognitive difficulties. Despite being the second-most common cause of referrals to neurology outpatient clinics after headache, scientists have struggled to pin down the disorder’s root cause. Female sex and a history of childhood trauma are factors associated with higher risk of developing FMD, but it’s been unclear why.

A new study from investigators of the Brigham and Women’s Hospital, in collaboration with researchers at the National Institute of Neurological Disorders and Stroke, demonstrated that FMD is characterized by epigenetic changes, and that women and childhood abuse survivors with FMD have different epigenetic profiles linked to this condition. Their study, which examined the genomes of over 100 individuals and was recently published in Progress in Neuro-Psychopharmacology and Biological Psychiatry, is the first to demonstrate the occurrence of epigenetic changes in FMD.

“This study finally takes FMD out of a cloud of confusion and provides a neuroscientifically grounded explanation for why childhood trauma and female sex are associated with this disorder,” said lead author Primavera A. Spagnolo, MD, Ph.D., scientific director of the Mary Horrigan Connors Center for Women’s Health and Gender Biology and assistant professor of psychiatry at HMS.