Formation of Neural Circuits in an Expanded Version of Darwin's Theory: Effects of DNAs in Extra Dimensions and within the Earth's Core on Neural Networks

Open Access Maced J Med Sci. 2019 Sep 10;7(18):3113-3117. doi: 10.3889/oamjms.2019.769. eCollection 2019 Sep 30.

Abstract

Aim: In this paper, inspiring Darwin's theory, we propose a model which connects evolutions of neural circuits with evolutions of cosmos. In this model, in the beginning, there are some closed strings which decay into two groups of open strings.

Methods: First group couple to our universe from one side and produce matters like some genes of DNAs and couple to an anti-universe from another side with opposite sign and create anti-matters like some anti-genes of anti-DNAs. Second group couple to the star and planet's cores like the earth's core from one side and produce anti-matters like stringy black anti-DNA and couple to outer layers of stars and planets like the earth from other side and produce matters like some genes of DNAs on the earth. Each DNA or anti-DNA contains some genetic circuits which act like the circuits of receiver or sender of radio waves. To transfer waves of these circuits, some neurons emerge which some of them are related to genetic circuits of anti-DNAs in anti-universe, and some are related to genetic circuits of stringy black anti-DNA within the earth's core. A collection of these neural circuits forms the little brain on the heart at first and main brain after some time.

Results: To examine the model, we remove effects of matters in outer layers of earth in the conditions of microgravity and consider radiated signals of neural circuits in a chick embryo. We observe that in microgravity, more signals are emitted by neural circuits respect to normal conditions. This is a signature of exchanged waves between neural circuits and structures within the earth's core.

Conclusion: These communications help some animals to predict the time and place of an earthquake.

Keywords: DNAs; Darwin; Earth; Earthquake; Extra dimensions; Neural network.