TED Conversations

Brian Johnson

Scientist at Intel Corporation 1987-2008

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Models for the human brain need to reflect the biological details of the brain and the computer is inadequate for this.

In thinking about the human brain , as well as brains other mammal species, analogies to computers have been proposed. I would argue that digital computing as we know it today gives an overly simplified model to the "wetware" of brains which leads to simplistic mechanistic views. Neurons have been thought to function like transistor switches ; being connected in circuits and having discrete firing pulses across their synapses. New scientific data suggest much more complicated functioning [ several examples are described in "Rhythms of the Brian" by Gyorgy Buzsaki ]. All regions of a neuron cell surface have been found to be subject to stimulation from the intracellular and intercellular medium, ion channels have voltage dependence driven by intercellular oscillatory waves and most importantly all parts of a neuron can function like a resonator-oscillator leading to potential waves being transmitted across large regions of cells as well as leading to neural firing. This enables regions of the brain to become synchronized. As an aside this functioning is likely to be the basis for alpha,theta ... voltage waves that can be measured with EEG. This operating mechanism of oscillation also enables very fast communication across large regions of the brain [ neuron firing is actually very slow ( tens of msecs ). In contrast transistors are either on ( high current) or off ( low current) and only their connections through circuits lead to information processing. The extreme power of computing hardware is the speed in which billions of transistors can operate. The extreme power of the brain is likely to be driven by the enormous complexity of interactions of neurons with their cellular environment and their synchronization by oscillations, as well as the signal processing of vast interconnections of neurons though pulse firing at synapses.

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      Jan 20 2014: Brendan - Thank you for your response and the detailed level of information. Why evolution led to two hemisphere brains in humans and all mammals is a very interesting question. It appears that there is both duplication and asymmetry. But of course the basic body structure has symmetry : eyes, ears etc . I would suppose one aspect of this is increased about of neural tissue and thus capability that comes with two hemispheres. Asymmetry allows specialization of functions. I suspect there is a great amount of current research on this. I am not very knowledgeable with this work.

      However what I find the most interesting is whether our consciousness is related to having two hemispheres. Is there a dialogue between them ?
  • Jan 19 2014: When I was at the university I read about this idea: The human mind is the adition of the neurons electric activity plus the micro-electromagnetic field they generate all over and in the nervous system. That will imply that to know more about the mind we need to elaborate the spacial model of that quantum field. Taking that as a valid hipothesis (it seems to me) the endeavour we face to modeling a single brain is huge.
  • Jan 18 2014: Current computers can never truly approach the human brain in its complexity or have any chance at all of producing something like consciousness. I would say that a fly, that has a rudimentary brain, is far superior to any computer ever built. Consider also that if say the computer maintenance people all went on strike one day, all the computers would start to fail in a relatively short time, no inbuilt immune system nor any kind of independence from humans.

    All computers, other than some neural networks, require programming instructions to function. These must be written by a human being. Nothing creative going on here among the circuits. Every time a new technology has arisen people have claimed that the brain is a this or that, e.g. first it was a telephone exchange, next an analogue computer, then a digital one, then a parallel one, then a neural network and now maybe a quantum computer. I believe that there is a very long way to go before a true understanding of the brain will be forthcoming. Before such an understanding becomes possible no computer can be built to simulate it.
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    Jan 12 2014: Very interesting topic, thank you. I agree with you that digital computing and brain functions are not comparable truly. The degrees of freedom of 'firing' of a neuron at synapses are vastly more in case of brains because it has multiple input channels. Moreover, at the basic synaptic connection electrons are possibly quantum indeterminately moving so a classical reduction seems inappropriate.
    If it needs to be compared with computing at all - it should be quantum computing.
    There is an outside chance that the 'rich internal life' is something brain conjures up. Despite being vastly complex it is too frugal on energy consumption.
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      Jan 13 2014: Pabitra- Thanks for your thoughts on this question. My knowledge of quantum computing is very limited but I believe that quantum computing is probabilistic whereas digital computing is deterministic. This becomes a fundamental difference. We both agree that neurons have a large complex set of inputs which lead to the postsynaptic pulse , actually a train of pulses, that travel along the axon to other synapses. I would argue this mechanism is still deterministic since there is either conduction across the synapse or not. What Gyorgy Buzsaki describes in the "Rhythms of the Brain" are mechanisms by which communication occurs not through the neural network but by resonance behavior through the cellular medium or between circuits of neurons acting as oscillators. The oscillations can resonate and become synchronized. Think of it as voltage waves propagating through whole regions of the brain. What I find so intriguing about Buzsaki's findings is that they may provide a way to thinking about how the brain "integrates" sensory data with memory data. We experience consciousness as an integrated, simultaneous awareness of many things in a moment of time. That "moment" is likely to be on the order of milliseconds. Integrating information over milliseconds is like oscillatory events at kilohertz cycles. EEG measurements show waves from tens of cycles to thousands of cycles.