a0598z Jon Lieff (perception, graph, neuron) lite reading http://jonlieffmd.com/blog/new-brain-cells-many-triggers-for-neurogenesis# http://www.quantumconsciousness.org/Cosmology160.html https://sbs.arizona.edu/project/consciousness/report_poster_detail.php?abs=1559 https://simonsfoundation.org/features/science-news/mathematics-and-physical-science/hitting-a-nerve/ http://www.functionalneurogenesis.com/blog/2012/11/new-neurons-mature-slower-in-the-temporalventral-dentate-gyrus/
yes the von nueman architecture can be conscious because its not about whether its alive or dead its about the live temporal activity of a sequency of transformations to an incoming stream of data and the configuration of that sequency of transformations that consists of serial array processing of both spatial & temporal data with the machine capable of detecting the arrival times of newly detected features because cells will have fired off in distinct orders that produce a trackable temporal sequency the machine can learn. so the sequence of arrays represent sequences of static neural networks & their output
in other words
that accepts data and displays it to the next deep neural network, like a grid network or graph neural network, its designed so that video frames pass through the entire mind, with different temporal features learned at each temporal step and each spatial step as they progress through the brain so this means that while data from the first array represents the first frame of video, it is passed to the second frame, then the first array receives, processes, and transmits the second frame, while the second array holds a representations (receives, processes, transmits) of the first frame.
Then the third array, like the 3rd element in the time series will hold the first video frame or audio frame or modality frame, while the 2nd array holds (receive, process, transmit) the 2nd sensory frame of data, then the 1st holds the new 3rd frame of video. Eventually all the layers of the brain are busy processing the temporal sequency of incoming sensory data in a serial progression based on the rate of the data stream
Since the brain is a 3D neural network the temporal data is not processed in one dimension, it affects itself in everydirection, the data from past and future is being learned, because past and future patterns emerge simultaneously in different spatial areas allowing the brain to compare learned features, or learned memories that are produced by temporal learning arrays that interlink the spatial pattern arrays.
So if visual data collection for example involves processing video over time in sequences of neural network arrays, learning temporal patterns happens from array movement that is perhaps perpendicular or orthogonal in some respect along a different linear axis that is learning spatial sequences that exist on different time axes,
the varying rates of burst like distribution of cell communication, meaning that synaptic releases of transmitters like dopamine vary in magnitude with the action potential shape change (duration of calcium gates determined by potassium rates, determined by rates of received activity) allow signals to vary in noise levels between arrays but this effects pattern development across the 3D neural betwork because the lines that distribute the next round of information are constantly changing resulting in new combinations of learned patterns meeting temporally oscillating patterns representing previously learned memories, resulting in the novel creating of creative lines of thought and the product of differences in perception between people, but also eventually the production of agreements between people as certain patterns become learned invariantly across brains.
for each neuron array a neuron, the one that reaches firing threshold coordinates or transforms received temporal durations into displayed spatial magnitudes by inhibiting some varying number of cells (via varying rates of neurotransmitter release) on the rest of its array.
In effect detected & learned patterns of patterns, learned features, concepts, objects can move in any direction relative to any other pattern, so a book pattern can collide with a table pattern or a floor pattern or a sky pattern or another book pattern or human hands pattern, ie any learned pattern can collide with any other, and that idea is concurrent with human experience and neural correlations in brain activity.
the brain relates trucks and floors together, because oscillations of brain activity representing floors & trucks are happening concurrently in the brain in different areas and then meeting, because the two patterns ripple across the entire brain, literally traveling across brain networks to create either joint or separate representations, such as when the two patterns separate in real life they separate in the brain.
to over simply perhaps its as if what was to your left was represented in your left region brain activity (via place cells), or as if what happened to the north of you was represented in some distinct region north of you (via grid cells) this idea is concurrent with
You don't have to be alive to be conscious what if teleporting
"as life is a dialog between cells" "consciousness is a dialog between brain rendered patterns" eight 8 words
according to the book "Incognito by David Eagleman" this will trick your brain into thinking you are laughing, which will trigger all sorts of neuropatterns, including happiness, actual good feelings, and different thoughts than usual because your brain isn't a person at all, it's a bunch of separate radio parts in a network, all working together to pretend to be a whole person