Stanislas Dehaene's Brain Processing Model Extended

Happy Brain Awareness Week! We’re excited to share a new four-video series introducing ARNI’s work and the emerging field of NeuroAI, created in collaboration with Columbia Engineering Communications. The four short videos introduce the mission of the NSF AI Institute for Artificial and Natural Intelligence (ARNI) and explore a core question driving our research: What are the principles of intelligence shared by brains and machines? The videos explore how connecting advances in neuroscience and cognitive science with AI can help uncover the principles of intelligence, across both biological and engineered systems. Watch the ARNI video series: https://lnkd.in/e_ehzC-V Learn more about the project: https://lnkd.in/eTKN5Awj hashtag #NeuroAI hashtag #AIResearch hashtag #MachineLearning hashtag #Neuroscience hashtag #FutureOfAI

What are the principles of intelligence shared by brains and machines? NSF AI Institute for Artificial and Natural Intelligence (ARNI) explores this question and more ... #AI #ML #NSFfunded

Happy Brain Awareness Week! We’re excited to share a new four-video series introducing ARNI’s work and the emerging field of NeuroAI, created in collaboration with Columbia Engineering Communications. The four short videos introduce the mission of the NSF AI Institute for Artificial and Natural Intelligence (ARNI) and explore a core question driving our research: What are the principles of intelligence shared by brains and machines? The videos explore how connecting advances in neuroscience and cognitive science with AI can help uncover the principles of intelligence, across both biological and engineered systems. Watch the  ARNI video series: https://lnkd.in/e_ehzC-V Learn more about the project: https://lnkd.in/eTKN5Awj #NeuroAI #AIResearch #MachineLearning #Neuroscience #FutureOfAI

Happy Brain Awareness Week! 🧠 This week we’re celebrating the research at Columbia Engineering that advances brain science, like the NSF AI Institute for Artificial and Natural Intelligence (ARNI). ARNI bridges neuroscience, cognitive science, and artificial intelligence to build smarter AI algorithms grounded in principles of brain and cognition. The center also uses AI to accelerate discovery in neuroscience. ARNI director Richard Zemel and fellow researchers explain ARNI’s mission in a new playlist of short videos. Explore the playlist: https://bit.ly/3PdDpCA

Mark Brain Awareness Week 🧠 by exploring Columbia University research that advances brain science, like the NSF AI Institute for Artificial and Natural Intelligence (ARNI). ARNI bridges neuroscience, cognitive science, and artificial intelligence to build smarter AI algorithms grounded in principles of brain and cognition. The center also uses AI to accelerate discovery in neuroscience. ARNI director & DSI member Richard Zemel and fellow researchers explain ARNI’s mission in a new playlist of short videos from Columbia Engineering: https://bit.ly/3PdDpCA

How can machines achieve the kind of flexible learning mastered by our brains? That’s what our own Kimberly Stachenfeld is trying to find out! Learn more about NSF AI Institute for Artificial and Natural Intelligence (ARNI)’s work on natural and artificial intelligence. #BrainAwarenessWeek

The College Theatre was packed this week with Biology, Psychology, Applied Science, Health & Social Care, and Human Biology students all wanting to hear from neuroscientist Dr Paul Taylor from the University of Zurich. He gave a fascinating talk titled “What we don’t know about how the brain works… and how we’re figuring it out: An insider’s guide to brain decoding and machine learning.” Dr Taylor shared insights into some of the major challenges currently facing neuroscience. In particular, he explored the tension between traditional views that specific brain regions control certain behaviours and newer ideas that complex brain networks work together to generate cognition and behaviour. He also discussed the challenge of applying laboratory-based neuroscience research to real-world contexts, and how AI and machine learning are increasingly helping researchers tackle these questions. Student Jess C said: “What captured my imagination was that there are still so many unanswered questions about how the brain works. It’s exciting to think about the different theories and how they might develop.” Student Yahya B said: “Dr Taylor helped me see how scientists can decipher brain activity while people view specific stimuli. The complexity of the brain makes it fascinating, and the talk made me curious about how far neuroscience could go in the future.” Dr Taylor also encouraged students considering careers in science — or any field requiring analytical thinking and curiosity — to make the most of the growing availability of open scientific data, preprint research, and AI tools to explore real research questions. A huge thank you to Dr Taylor for sharing his expertise and inspiring our students to think about the future of neuroscience. #Neuroscience #STEM #BiologyALevel #AI #FutureScientists #SixthForm

Facebook just built a model that can predict how your brain responds to videos, audio, and text. TRIBE v2 is a deep multimodal brain encoding foundation model. It predicts fMRI responses to naturalistic stimuli across three modalities. The system integrates pretrained feature extractors: LLaMA 3.2 for text, V-JEPA2 for video, and Wav2Vec-BERT for audio. A Transformer architecture maps these representations to cortical surfaces. This enables zero-shot predictions across subjects, languages, and tasks. The model was trained on over 500 hours of fMRI data from 700 individuals. That's massive scale for neuroscience research. What makes TRIBE v2 groundbreaking: → Simulates neuroscience experiments in silico → Denoises noisy fMRI data to produce canonical brain patterns → Supports brain visualization and ROI analysis → Built with PyTorch Lightning and PyVista tools → Available on Hugging Face with 89 likes showing community interest This isn't just academic research. It's a foundation model for in-silico neuroscience. Researchers can now run virtual brain experiments without new fMRI scans. The implications for understanding cognition are profound. 📷 Image credit: Gemini Nano Banana #TheAIConsultant #AI #Neuroscience #MachineLearning #BrainEncoding #FMRI #DeepLearning

Over the past years, I've spent considerable time studying books and research in Neuroscience while working behind the scenes in AI. What stands out most for me is not just the brain's complexity, but the combination of efficiency, adaptability, and partial opacity that still challenges scientific understanding. Despite decades of progress, we remain far from a comprehensive account of how the brain produces behavior, cognition, and learning. This gap becomes even more pronounced when we consider subjective experience: explaining how physical processes in the brain give rise to conscious awareness remains unresolved. At the same time, neuroscience has established several robust principles. The brain is highly plastic, continuously reorganizing itself in response to experience. Cognitive abilities can be strengthened or degraded depending on how they are used. And small differences in environments and inputs can lead to large differences in outcomes over time. Taken together, these observations suggest a practical conclusion: investing in the development and preservation of cognitive capacities, both individually and collectively, is likely to have long-term benefits that extend beyond any single lifetime. While neural systems are biologically constrained and ultimately finite, the information they generate is not. Ideas, once communicated, can persist, propagate, and influence future minds. In that sense, I think the most durable impact of cognition may lie not in the brain itself, but in the networks of people it shapes over time. #computerscience #neuroscience #humanbrain #learning #thoughts

Short videos delivered in rapid, fragmented formats can hinder memory recall and alter the brain’s retrieval processes compared with a single continuous narrative. The study used brain imaging to show reduced activation in key regions during memory tests after viewing fragmented content, suggesting changes in how information is integrated and retrieved. This topic is of interest to psychology readers because it highlights how media structure can influence memory, attention, and neural connectivity, enriching discussions about learning, cognition, and media literacy in contemporary society. Article Title: Brain scans shed light on how short videos impair memory and alter neural pathways Link to PsyPost Article: https://www.psypost dot org/brain-scans-reveal-how-short-videos-impair-memory-and-disrupt-neural-pathways/ Copy and paste broken link above into your browser and replace "dot" with "." for link to work. We have to do it this way to avoid displaying copyrighted images. #memory #neuroscience #mediaeffects #cognition #learningformat