Pre<fbno>: Hu: I need to consider and maybe research how the brain experiences visual input also has build a system that force replicated that, then make the metrics match industry standards. 11:03 PM: The current generation of live video streaming either 1) stops, and does not auto-restart, permanus, unless it’s hard-netted to a television, which is not on the internet, or it burns 50% of your resources, and is itself a miracle, like Zoom.
MIC.ch-42,H4S2: The lateral geniculate nucleus <LGN>
Koeppen, Stanton <a-r>: <pg-123> Posterior to the optic chiasm, the axons of retinal ganglion cells pass through the optic tracts and synapse in nuclei of the brain. The main visual pathway in humans is through the lateral geniculate nucleus <LGN> of the thalamus. This nucleus projects through the visual radiation to the visual cortex: MIC: The LGN is the relay point of eye -> brain, directional passages of neural signals # Koeppen, Stanton <a-r>: pg-135: The LGN is a layered | structure. The first two layers, which contain large | neurons, are called magnocellular | layers. The other four layers are the parvocellular layers. There is a point-to-point projection from the retina to the LGN. The LGN thus has a retinotopic | map. MIC: The visual system is not the only sensory | system that contains a point-to-point topographic | map <Kaas, 1997>; the somatosensory system, famously, in the cortical homunculus, also represents and processes information from different parts of the body separately. Kaas, 1997: Most notably, topographic representations permit interconnections between appropriate sets of neurons to be made in a highly efficient manner. Topographic maps provide an especially suitable | substrate for the common spatiotemporal computations for neural circuits. Finally, aspects of perception suggest the functional | importance of topographic maps. MIC: Topographic representations are hardly used in computer science in visual, auditory, and somatosensory | processing, and this may explain why computers continue to lag behind in sensory processing; in fact, this seems to be the only arena in which even a toddler | human can, consistently, outwit the world’s top supercomputers. There may be deeper insights in the fact that the body represents 3-D space in its linear | neural wiring, much like the linear string of amino acids folds, in order to form the 3-D configuration that permits protein function; without this 3-D configuration, a polypeptide may have the same amino identity as a fully formed protein, but without the ability to perform the necessary | functions. However, as Kaas points out, topographic representations also permits the brain an advantage in computational efficiency, which indicates that 1) the third dimension in itself may be, instead of, or in addition to, an extrapolation of 2-D space, but also a reduction of it, as folding into 3-Dimensions brings certain parts of the 2-Dimensions that were further apart in a flat plane closer together <r: Wormholes, protein subunits> and 2) the structure of the brain co-evolved with the physical world around it, mirroring its own structure physically, and is thus an adapted | computer, as well as a general | computer. #np-10s. Fin-v3. MIC: As we predicted in ch-20 H2S3 H3S6, ch-8 H2S7 H3S3, and ch-42 H2S3 H3S4 H4S6
Hu: Before information enters my browser to enter my brain, it must first be captured by my opponent’s web-cam, and relayed into my browser, across the internet, in packets, since the internet is a packet.switched-Network<Anki 11/22>. Ideally, being as these augment my | brain, the input will align with my mental | processing upon several | vectors: 1) the visual.hierarchy-distribution; where the relevant | focals 2) the rhythm of input | delivery, with some | alignment, on a valid q.tum–note,interval<MIC.clarinet-gallery>3) a relevant max-red //
The brain processes visual input on several vectors 1) when light strikes the retina, it is translated from photon–encoded to binary, encoded by a-p, which is an electrical | signal 2) the signal will travel through optic | nerves, some distance, and arrive, first at the 3) LGN, an intermediate processing center, not quite conscious, 4) the visual | cortex. This means that any given time, there will be, ideally , 4 | frame-payloads<#n.p-dirty!> in the brain at any given time; one at the retina, one at the chiasm, one at the LGN, and one at the cortex<Turing>; the electrical | computer interface extends this, where a 5th payload will be found at the user’s browser, a 6th, in TURN, or missing, if a TURN is missing, a 6th in any servers, or a 6th, in the enemy’s | browser, you get the idea. The distance, time-encoded, between each of these, in the augmentation | layer, should be the same as the inter–brain | distance; fortunately, a-ps in the brain travel quite slowly, almost, mapping onto earth distance, to allow for light.speed-relaying; the brain is made the simulate an earth.sized-object.
Realistically, the speed of a myelinated | a-p is about 40.m/s, on average, and let’s say the total distance traveled from 1) to 4) is 20-cm, 0.2-m, then 1/80th of a s will be required to travel that distance. In 1/80-s, light can travel 300-mn<Google>*(1/80) = 3,750,000 meters; the circumference<since ocean-wires don’t cut through the core>of the Earth is 40-mn meters. Ideally, the time-distance<#n-p> is not greater than 1/4 of 4-mn meters, so the distance between the 2 cli-sers<Turing> should be no greater than 1-mn meters, or 1/40 of the Earth’s circumference. There are 360 longitude | lines, and 1/40 of 360 is 9. For reference, the longitude of Buffalo, NY is 78.8784° W, +9 from this, approximately, at 87.6298° W, is Chicago, Illinois. Note that this distance includes time to reroute through the TURN, if applicable.
Training the render–forward | component: the extent to which incoming video is predictable to the human brain will determine, to a larger extent than latency, the satisfaction of the consumption | experience. Fin.v-1
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