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Jonathan Mason: on 7/3/20 at 10:15am UTC, wrote Abstract: We seek to model the human cortex with 1B to 10B neurones...
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Steve Dufourny: "there is something of very relevant for the actions coupled in matters and..." in Is Causality Fundamental?
Steve Dufourny: "I have utilised this general method for the quantum gravitation and oddly I..." in Is Causality Fundamental?
Jim Snowdon: "Hi Steve, The Earth`s rotational motion is the physical mechanism..." in The Nature of Time
Steve Dufourny: "Hi Mr Snowdon, I beleive indeed that there is a link with the rotations of..." in The Nature of Time
Steve Dufourny: "I repeat this simple general intuitive idea, what are your thoughts? .... ..." in Undecidability,...
Steve Dufourny: "You know Tejinder, I don t want to destroy the works of strings theorists,..." in Undecidability,...
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click titles to read articles
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Grounded physicists are exploring the use of online and virtual-reality conferencing, and AI-controlled experiments, to maintain social distancing. Post-pandemic, these positive innovations could make science more accessible and environmentally-friendly.
Is Causality Fundamental?
Untangling how the human perception of cause-and-effect might arise from quantum physics, may help us understand the limits and the potential of AI.
Building Agency in the Biology Lab
Physicists are using optogenetics techniques to make a rudimentary agent, from cellular components, which can convert measurements into actions using light.
Think Quantum to Build Better AI
Investigating how quantum memory storage could aid machine learning and how quantum interactions with the environment may have played a role in evolution.
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August 5, 2020
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TOPIC: Large scale simulations of information processing within the human cortex: what “inner life” occurs? by Peter Grindrod [refresh]
TOPIC: Large scale simulations of information processing within the human cortex: what “inner life” occurs? by Peter Grindrod [refresh]
Abstract: We seek to model the human cortex with 1B to 10B neurones arranged in a directed and highly modular network (a network of networks); with the tightly coupled modules (each containing 10,000 neurones or so) representing the cortical “columns”. Each neurone has an excitable and refectory dynamic and the neurone-to-neurone connections incur individual time delays. Thus the whole is a massive set of modular delay-differential equations (expensive to solve on a binary computer, but easily implemented within 1.5kg of neural wet-ware). Our early work has shown why evolution has resulted in such a design to ensure optimal use of the limited space and energy available. Indeed we can show that if the time delays were all integers rather than reals then much of the potential behaviour (dynamical degrees of freedom) would be lost.
Simulating a 1B neurone directed graph produces its own big data challenge. We focus on the inner life of these complex dynamical system, and show that the dynamical responses to external stimuli result in distinct, latent (internal), dynamic “states" or modes. These inner subjective and private states govern the immediate dynamical responses to further incoming stimuli. Hence they are candidates for internal “feelings”. So, what is it like to be a human? A human brain must also possess such inertial dynamical states, and a human brain can experience being within them: they are natural and necessary byproducts of the system's architecture and dynamics, and they suggest that the "hard problem of consciousness” is mainly explicable, and can be anticipated, in terms of network science and dynamical systems theory.
The numerical simulation at such large scales requires a special computing platform, such as SpiNNaker (at the University of Manchester). We will set out the methodology to be deployed in (i) defining such complex systems; (ii) in simulating the spiking behaviour being passed around when such a system is subject to various stimuli; and (iii) the post processing -reverse engineering -of the whole system performance, to demonstrate that internal states/modes exist. We cannot reverse engineer a real human brain at the neurone-to-neurone level, but we can do so for such ambitious simulations.
Keywords: #Models of consciousness #human cortex simulations #Inner feelings, modes #SpiNNaker
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Simulating a 1B neurone directed graph produces its own big data challenge. We focus on the inner life of these complex dynamical system, and show that the dynamical responses to external stimuli result in distinct, latent (internal), dynamic “states" or modes. These inner subjective and private states govern the immediate dynamical responses to further incoming stimuli. Hence they are candidates for internal “feelings”. So, what is it like to be a human? A human brain must also possess such inertial dynamical states, and a human brain can experience being within them: they are natural and necessary byproducts of the system's architecture and dynamics, and they suggest that the "hard problem of consciousness” is mainly explicable, and can be anticipated, in terms of network science and dynamical systems theory.
The numerical simulation at such large scales requires a special computing platform, such as SpiNNaker (at the University of Manchester). We will set out the methodology to be deployed in (i) defining such complex systems; (ii) in simulating the spiking behaviour being passed around when such a system is subject to various stimuli; and (iii) the post processing -reverse engineering -of the whole system performance, to demonstrate that internal states/modes exist. We cannot reverse engineer a real human brain at the neurone-to-neurone level, but we can do so for such ambitious simulations.
Keywords: #Models of consciousness #human cortex simulations #Inner feelings, modes #SpiNNaker
This forum thread is open to the public.
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