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Development Of Neocortical Complexity. Synaptogenesis Is Related To The Transformation Of Wolfram Asymmetry Graph #30 To #110

Über Development Of Neocortical Complexity. Synaptogenesis Is Related To The Transformation Of Wolfram Asymmetry Graph #30 To #110

Scientific Study from the year 2016 in the subject Mathematics - Miscellaneous, , language: English, abstract: A heuristic approach relates the self-organization of the fetal neo-cortex to transformation of random information flow in Wolfram asymmetry graph #30 into the controlled and complex information flow in Wolfram asymmetry graph #110. Random spindle bursts transmitted through gap junctions affect developing neuron trans-membrane potentials, Vmem. A scale-free, Vmem-dependent, negative-feedback homeostatic mechanism controls network connectivity via neuron paring, and alteration of the ratios of excitatory and inhibitory synapses so that random information flow becomes organized and capable of complex calculations. This model allows the formation of synaptic complexity with a minimal amount of DNA information.

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  • Sprache:
  • Englisch
  • ISBN:
  • 9783668420328
  • Einband:
  • Taschenbuch
  • Seitenzahl:
  • 24
  • Veröffentlicht:
  • 26. April 2017
  • Ausgabe:
  • 17002
  • Abmessungen:
  • 148x3x210 mm.
  • Gewicht:
  • 51 g.
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Beschreibung von Development Of Neocortical Complexity. Synaptogenesis Is Related To The Transformation Of Wolfram Asymmetry Graph #30 To #110

Scientific Study from the year 2016 in the subject Mathematics - Miscellaneous, , language: English, abstract: A heuristic approach relates the self-organization of the fetal neo-cortex to transformation of random information flow in Wolfram asymmetry graph #30 into the controlled and complex information flow in Wolfram asymmetry graph #110.

Random spindle bursts transmitted through gap junctions affect developing neuron trans-membrane potentials, Vmem. A scale-free, Vmem-dependent, negative-feedback homeostatic mechanism controls network connectivity via neuron paring, and alteration of the ratios of excitatory and inhibitory synapses so that random information flow becomes organized and capable of complex calculations.

This model allows the formation of synaptic complexity with a minimal amount of DNA information.

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