Join Durham International School for Discovery Day: Exploring The Illusive Brain with Dr Dan Adams

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! 🧠 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

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

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

How do you go from the AI winter to building biologically realistic models of the visual cortex… and then to vision restoration? In our latest Pathways interview, Jan Antolik reflects on that journey, and on what it really takes to connect neural activity to perception. A few themes that stood out to me: • Taking biology seriously is not a constraint, it is the point • We still lack a mechanistic understanding of something as “basic” as phosphenes • Bridging stimulation, circuit dynamics, and percept remains one of the central challenges for visual prosthetics Jan also shares how this thinking shapes his work within REVICAN, a Marie Skłodowska-Curie Actions program bringing together neuroscience, engineering, and clinical research across Europe and the US. 👉 Read the full interview: https://lnkd.in/gnaCkuFW Thanks, Jan, for taking the time to share your perspective. #BionicVision #ComputationalNeuroscience #Neurotechnology #BCI

Listening in on the brain's electrical conversations with better tools by Rachel Bedford, University of Oregon The human brain contains more connections between neurons than there are stars in the Milky Way. Decoding the electrical activity behind all those cells is the massive task that excites neural engineers like Felix Deku, who are working to build better tools for recording brain activity. "We're at the intersection of engineering and neuroscience," says Deku, the Betsy and Greg Hatton Assistant Professor in Neuroengineering at the Phil and Penny Knight Campus for Accelerating Scientific Impact. "The brain is incredibly complex, and our ability to understand it has been limited by the tools we have available." New research from Deku's lab, published in the Journal of Neural Engineering, introduces a new tool for recording brain activity known as a neural interface that can record the activity of hundreds of neurons simultaneously. https://lnkd.in/gcuAk3ik

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

I am pleased to share my recent review article: A Review on Stanislas Dehaene’s Model of How the Brain Thinks and Hierarchical Model of Conscious Processing and Metacognition In this paper, I examine Stanislas Dehaene’s Global Neuronal Workspace theory and propose a hierarchical extension in which metacognition is modeled as a higher-level regulatory layer. The model introduces a computational interpretation of conscious processing using a UNet-like autoencoder architecture combined with a top-level metacognitive autoencoder that can evaluate, refine, and modify lower-level representations. This framework aims to connect cognitive neuroscience, predictive coding, and modern deep learning architectures in order to simulate reflective and ethical aspects of human cognition. The article has been published in Advances Brain Research and Neuroscience. I would be happy to receive comments, feedback, or suggestions from researchers working in neuroscience, cognitive science, artificial intelligence, and philosophy of mind. #Neuroscience #Consciousness #Metacognition #ArtificialIntelligence #CognitiveScience #DeepLearning