Researchers led by UCLA have developed an adversarial AI framework that may help explain how consciousness breaks down after brain injury — and how it might one day be restored. Published in Nature Neuroscience, the study used deep neural networks trained on more than 680,000 neuroelectrophysiology samples and validated findings across 565 patients, healthy volunteers, and animals. The model identified specific circuit-level disruptions linked to disorders of consciousness, including the basal ganglia indirect pathway and altered inhibitory cortical wiring.
What makes this so important is that it pushes consciousness research closer to mechanism. Instead of only asking what consciousness is, this kind of work asks: what specific brain circuitry fails when consciousness is lost, and can that failure be targeted? The study also identified high-frequency stimulation of the subthalamic nucleus as a promising intervention, supported by human electrophysiological data. This is the kind of neuroscience that makes consciousness feel less like pure philosophy — and more like something we may eventually model, test, and repair.
Abstract: Nature Neuroscience Adversarial AI reveals mechanisms and treatments for disorders of consciousness.
Toker et al. present an AI framework that identifies mechanisms of consciousness. The model predicts new drivers of unconsciousness and identifies subthalamic nucleus stimulation as a potential therapy for disorders of consciousness.
To get the best out of AI, some users tell it to provide answers as if it were an expert. Others ask it to adopt a persona, such as a safety monitor, to guide its responses. However, this approach can sometimes hurt performance, according to a study available on the arXiv preprint server.
To see how well large language models (LLMs) behave when they are told to be someone else, researchers from the University of California ran a huge test using 12 different personas across six language models. These included experts in fields like math, coding and STEM (science, technology, engineering and mathematics) as well as general roles such as creative writer or safety monitor.
The team found that adopting a persona was something of a double-edged sword. While it makes AI sound more professional and keeps it safer (more likely to follow rules and less likely to generate harmful content), it sometimes performs worse at recalling facts.
GitHub is adopting AI-based scanning for its Code Security tool to expand vulnerability detections beyond the CodeQL static analysis and cover more languages and frameworks.
The developer collaboration platform says that the move is meant to uncover security issues “in areas that are difficult to support with traditional static analysis alone.”
CodeQL will continue to provide deep semantic analysis for supported languages, while AI detections will provide broader coverage for Shell/Bash, Dockerfiles, Terraform, PHP, and other ecosystems.
Neurotechnology pioneers @gcourtine and @jocelynebloch are redefining what recovery looks like for people with spinal cord injuries. With a combination of neurosurgery, innovative engineering and AI,…
Self-driving laboratories (SDLs) powered by artificial intelligence (AI) are rapidly accelerating materials discovery, but can they also explain their results? Researchers from the Theory Department of the Fritz Haber Institute, in collaboration with BASF, and BasCat—UniCat BASF JointLab, show that they can.
Their new AI-driven strategy works hand-in-hand with SDLs to identify better catalysts while revealing the chemistry behind their performance. The approach was validated on the industrially crucial conversion of propane into propylene.
An SDL integrates an AI doing the experiment planning with lab automation and robotics. In the race to develop better materials, AI and SDLs are often celebrated for one main reason: speed.
A fascination with fish gills has led researchers at Cornell to develop a bio-inspired approach to mixing heat and molecules in fluids—findings that could inform future biomedical devices, heat exchangers and soft robotics.
Moving heat and mass efficiently through flowing liquids is central to technologies ranging from dialysis machines to industrial cooling systems, yet many of those technologies rely on rigid components to get the job done.
Looking for an alternative, Yicong Fu, a mechanical engineering doctoral student, turned to fish gills—soft, porous tissue that constantly stirs water to keep gases and ions flowing. Working with Sunghwan “Sunny” Jung, professor of biological and environmental engineering in the College of Agriculture and Life Sciences, Fu designed a gill-like thermal dispenser that is providing new insights into fluid-structure interactions.
PhD student in Computer Science at Stanford University.
After activation, these NLRs form multi-protein complexes—called resistosomes—that carry out the immune response. Studies have shown that certain resistosomes are pentameric (e.g., ZAR1 and Sr35), whereas others are hexameric (e.g., NRC2 and NRC4). These complexes initiate immune responses by triggering calcium (Ca2+) influx into the cytoplasm. However, the G10 type of CC-NLR (CCG10-NLR) immune receptors constitutes a unique clade among CC-NLRs and its activation mechanism has remained poorly understood.
Now, in a study published in Cell, a research team has revealed a novel octameric resistosome formed by an activated wheat CCG10-NLR immune receptor, which induces Ca2+ influx and immune responses through a unique channel architecture.
The researchers identified the Wheat Autoimmunity 3 (WAI3) gene, which encodes a CCG10-NLR protein. Subsequent analysis revealed that a gain-of-function (GOF) single amino acid mutation in the leucine-rich repeat (LRR) domain leads to autoactivation, providing an opportunity to study the activation mechanism of CCG10-NLR.
After expressing the WAI3 proteins in Nicotiana benthamiana, the researchers used cryo-electron microscopy to resolve the octameric structure of the activated WAI3 resistosome—marking the first time an octameric resistosome has been identified in plants.
The CCG10-NLR WAI3 resistosome differs from known resistosomes both in the number of monomers and in its conformation, representing a novel assembly mechanism for plant NLR resistosomes.
Using Nicotiana benthamiana and animal cell expression systems, the researchers also demonstrated that the WAI3 resistosome induces Ca2+ influx in plants but is not effective in animal cells. ScienceMission sciencenewshighlights.