Do brain networks evolve by maximizing their information flow capacity?

We propose a working hypothesis supported by numerical simulations that brain networks evolve based on the principle of the maximization of their internal information flow capacity. We find that synchronous behavior and capacity of information flow of the evolved networks reproduce well the same behaviors observed in the brain dynamical networks of Caenorhabditis elegans and humans, networks of Hindmarsh-Rose neurons with graphs given by these brain networks. We make a strong case to verify our hypothesis by showing that the neural networks with the closest graph distance to the brain networks of Caenorhabditis elegans and humans are the Hindmarsh-Rose neural networks evolved with coupling strengths that maximize information flow capacity. Surprisingly, we find that global neural synchronization levels decrease during brain evolution, reflecting on an underlying global no Hebbian-like evolution process, which is driven by no Hebbian-like learning behaviors for some of the clusters during evolution, and Hebbian-like learning rules for clusters where neurons increase their synchronization

Measuring Baryon Acoustic Oscillations along the line of sight with photometric redshifs: the PAU survey

Baryon Acoustic Oscillations (BAO) provide a standard ruler of known physical length, making it a promising probe of the nature of dark energy. The detection of BAO requires measuring galaxy positions and redshifts. "Transversal" (angular distance) BAO measure the angular size of this scale, while "line-of-sight" (or "radial") BAO require precise redshifts, but provide a direct measurement of the Hubble parameter at different redshifts, a more sensitive probe of dark energy. The main goal of this paper is to show that a precision of sigma_z ~0.003(1 + z) is sufficient to measure BAO in the radial direction. This precision can be achieved for bright, red galaxies, by using a filter system comprising about 40 filters, each with a width of ~100 A, from ~ 4000 A to ~ 8000 A, supplemented by two broad-band filters. We describe a practical implementation, a new galaxy survey, PAU, to be carried out with a telescope/camera combination with an etendue of about 20 m^2deg^2, and covering 8000 sq. deg. in the sky in four years. We expect to measure positions and redshifts for over 14 million red, early-type galaxies with L > L* and i_AB < 22.5 in the interval 0.1 < z < 0.9, with sigma_z < 0.003(1 + z). This population has a number density n > 10^-3 Mpc^-3 h^3 within the 9 (Gpc/h)^3 volume of the survey, ensuring that the error in the determination of the BAO scale is not limited by shot-noise. By itself, such a survey will deliver precisions of order 5% in the dark-energy equation of state parameter w, if assumed constant, and can determine its time derivative when combined with future CMB measurements. In addition, PAU will yield high-quality redshift and low-resolution spectroscopy for hundreds of millions of other galaxies.Comment: 56 pages, 18 figures. Version 4 fixes figures 5 and 9 to 14 that had been erroneously uploaded in v2 and v3. The figures were however correct in version