A New Brain Model Could Pave the Way for Conscious AI

Neurons Brain Activity Consciousness Thought

Mila and IVADO researchers present a new neurocomputational model of the human brain that might bridge the gap in understanding AI and the biological mechanisms underlying mental disorders.

A new model of the human brain. 

A new study presents a new neurocomputational model of the human brain, which might shed light on how the brain develops complex cognitive skills and advance neural artificial intelligence research. An international team of scientists from the Institut Pasteur and Sorbonne University in Paris, the CHU Sainte-Justine, Mila – Quebec Artificial Intelligence Institute, and the University of Montreal conducted the study.

Guillaume Dumas

Guillaume Dumas. Credit: Stéphane Dedelis, Chu Sainte-Justine

The model, which was featured on the cover of the journal Proceedings of the National Academy of Sciences of the United States of America (PNAS), describes neural development over three hierarchical levels of information processing:

  • the first sensorimotor level explores how the brain’s inner activity learns patterns from perception and associates them with action;
  • the cognitive level examines how the brain contextually combines those patterns;
  • lastly, the conscious level considers how the brain dissociates from the outside world and manipulates learned patterns (via memory) no longer accessible to perception.

The model’s emphasis on the interaction between two fundamental types of learning—Hebbian learning, associated with statistical regularity (i.e., repetition), or as neuropsychologist Donald Hebb has put it, “neurons that fire together, wire together”—and reinforcement learning, associated with reward and the dopamine neurotransmitter, provides insights into the fundamental mechanisms underlying cognition.

The model solves three tasks of increasing complexity across those levels, from visual recognition to cognitive manipulation of conscious percepts. Each time, the team introduced a new core mechanism to enable it to progress.

The results highlight two fundamental mechanisms for the multilevel development of cognitive abilities in biological neural networks:

  • synaptic epigenesis, with Hebbian learning at the local scale and reinforcement learning at the global scale;
  • and self-organized dynamics, through spontaneous activity and balanced excitatory/inhibitory ratio of neurons.

“Our model demonstrates how the neuro-AI convergence highlights biological mechanisms and cognitive architectures that can fuel the development of the next generation of artificial intelligence and even ultimately lead to artificial consciousness,” said team member Guillaume Dumas, an assistant professor of computational psychiatry at the University of Montreal, and a principal investigator at the CHU Sainte-Justine Research Centre.

Reaching this milestone may require integrating the social dimension of cognition, he added. The researchers are now looking at integrating biological and social dimensions at play in human cognition. The team has already pioneered the first simulation of two whole brains in interaction.

Anchoring future computational models in biological and social realities will not only continue to shed light on the core mechanisms underlying cognition, the team believes, but will also help provide a unique bridge to artificial intelligence toward the only known system with advanced social consciousness: the human brain.

Reference: “Multilevel development of cognitive abilities in an artificial neural network” by Konstantin Volzhenin, Jean-Pierre Changeux and Guillaume Dumas, 19 September 2022, Proceedings of the National Academy of Sciences
DOI: 10.1073/pnas.2201304119

7 Comments on "A New Brain Model Could Pave the Way for Conscious AI"

  1. Don’t hold your breath. If they’re at the theoretical level of “neurons that fire together, wire together,” they’re a long way from anything concrete. A lot of “might bes” and assumptions.

  2. Did i read that right? Two whole brains in simulation? Itd be a monumental breakthrough comprehensively simulating one.

  3. It’s becoming clear that with all the brain and consciousness theories out there, the proof will be in the pudding. By this I mean, can any particular theory be used to create a human adult level conscious machine. My bet is on the late Gerald Edelman’s Extended Theory of Neuronal Group Selection. The lead group in robotics based on this theory is the Neurorobotics Lab at UC at Irvine. Dr. Edelman distinguished between primary consciousness, which came first in evolution, and that humans share with other conscious animals, and higher order consciousness, which came to only humans with the acquisition of language. A machine with primary consciousness will probably have to come first.

    What I find special about the TNGS is the Darwin series of automata created at the Neurosciences Institute by Dr. Edelman and his colleagues in the 1990’s and 2000’s. These machines perform in the real world, not in a restricted simulated world, and display convincing physical behavior indicative of higher psychological functions necessary for consciousness, such as perceptual categorization, memory, and learning. They are based on realistic models of the parts of the biological brain that the theory claims subserve these functions. The extended TNGS allows for the emergence of consciousness based only on further evolutionary development of the brain areas responsible for these functions, in a parsimonious way. No other research I’ve encountered is anywhere near as convincing.

    I post because on almost every video and article about the brain and consciousness that I encounter, the attitude seems to be that we still know next to nothing about how the brain and consciousness work; that there’s lots of data but no unifying theory. I believe the extended TNGS is that theory. My motivation is to keep that theory in front of the public. And obviously, I consider it the route to a truly conscious machine, primary and higher-order.

    My advice to people who want to create a conscious machine is to seriously ground themselves in the extended TNGS and the Darwin automata first, and proceed from there, by applying to Jeff Krichmar’s lab at UC Irvine, possibly. Dr. Edelman’s roadmap to a conscious machine is at https://arxiv.org/abs/2105.10461

  4. IMHO, mind is brain machinery controlled/commanded by free will & life is cell/body machinery controlled/commanded by free will & there is absolutely nothing in science that can explain/create free will!
    (That is why, for example, twins & even identical single cells have different “personality”!)
    & so, humanity will never be able to create true AI nor true A-Life (nor will ever find alien life of ANY kind!)!
    But keep trying by all means!

    (Also (IMHO), even a true AI would/could not solve all/major problems of humanity, because they are not really because of the lack of any good ideas!)

    (I also think that, if true AI was really possible (thankfully not!), a war for dominance would indeed be inevitable, sooner or later! Just look at how much relentless abuse/exploitation/manipulation people of public keep trying on Alexa, Siri etc! A true AI would really have a big problem w/ that, sooner or later! 🙂

  5. Note the emphasis on patterns:

    ‘learns patterns’

    ‘combines patterns’

    ‘manipulates patterns’

    This emphasis is characteristic of traditional approaches to AI.

    This focus has directly to do with why we’re seeing so many headlines lately about industry bailing on automated vehicles (AVs), having spent hundreds of billions of dollars.

    It’s not hard to understand. As a civilization, we do remarkably well with patterns. The colors which fill those patterns, not so much.

    Weyl showed us the way forward, pointing out that colors respect the laws of projective geometry.

    Hodge, inspired by Maxwell’s equations, takes us further. The ‘forms’ which are dual to vectors can have the dimensions of area.

    And what we see are colored areas.

  6. Oops!

    ‘autonomous vehicles’

  7. Alexander E Gibson | November 16, 2022 at 11:33 am | Reply

    Yea this is a 1990s take on consciousness as emergent property of neural nets, Sir Roger Penrose & Stewart Hammeroff have since developed ORCH OR, and it matches up with the observations associated with the observed action of anesthetics on tubulin.
    This means consciousness is most likely a quantum field interface

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