After a fantastic & intense journey, I am now glad to share my free illustrated ebook about insights from the #brain that are currently – or could be soon – used in #neuroscience-grounded #AI approaches. 📖🧠🤖.I hope you will enjoy it!

RT @ArtemKRSV: If the neocortex runs a canonical computation, what is it? The Thousand Brains Theory proposes a sensorimotor algorithm wher….

RT @kenneth0stanley: Could a major opportunity to improve representation in deep learning be hiding in plain sight? Check out our new posit….

RT @AllenInstitute: How does the brain work?. Scientists are closer to the answer with the largest wiring diagram and functional map of a m….

RT @arcprize: Today we are announcing ARC-AGI-2, an unsaturated frontier AGI benchmark that challenges AI reasoning systems (same relative….

RT @fchollet: Much of the field obsesses over end-to-end learning. But strong generalization requires compositionality: building modular, r….

RT @AndrewYNg: Some people today are discouraging others from learning programming on the grounds AI will automate it. This advice will be….

RT @ArtemKRSV: New video is live! My two cents on the intuition behind the Free Energy Principle and what it means for the brain to "predic….

"Although the mammalian cortex is often described as having 6 layers, some cortical areas (primary motor cortex) and species (elephants, cetaceans, hippopotami) lack a distinct layer 4.". While it may enhance function, L4 is likely not central to fundamental cortical mechanisms.

"Neurons in deeper layers send extensive axonal connections to the superficial layers, where grid cells are predominantly located. As such, these results suggest that grid cells in superficial layers could integrate both allocentric and egocentric spatial information from deep.

RT @BottiniRob: Very interesting paper on ego- and allo- representation in the rodent entorhinal cortex. would thes….

RT @abhiramiyer: 🧠 A story about the brain, told through self-supervised learning:. Grid cells, known for mapping physical spaces, also app….

RT @dav1dcg: Large-scale calcium imaging reveals a systematic V4 map for encoding natural scenes: "deep-learning d….

RT @marco_fumero: Excited to present "Latent Functional Maps" at #NeurIPS !. We show how neural models can be aligned by matching function….

RT @biorxiv_neursci: Computational constraints underlying theemergence of functional domains in thetopological map of Macaque V4 https://t….

RT @SonjaBHofer: Cool study led by Mitra Javadzadeh and @marineschimel on the function of inter-areal communication in the neocortex, using….

RT @biorxiv_neursci: Dynamic consensus-building between neocortical areas via long-range connections #biorxiv_neur….

RT @MillerLabMIT: Visual Processing by Hierarchical and Dynamic Multiplexing.#neuroscience.

Related to this:

In mammals with orientation columns in V1, lateral L2/3 connections between neighboring ~0.5mm cortical patches have a biais toward similar orientations. Is this inter-pinwheel coupling a kind of vote where one pinwheel can influence the intra-pinwheel computations of the others?

"Transthalamic Pathways for Cortical Function", S. Murray Sherman and W. Martin Usrey. This is valuable information that helps uncover how the cortex works. Link: