Physical measurement of brain perception abilities. Foundations of a working methodology for the design of “intelligent” beings

Most of the important properties of the brain (thinking, consciousness, music, etc.) are severely ill-defined. They are not the direct output of biological sensors or their combinations but emerge from complex computations at the network level and are not necessarily represented in the sensory input or the activity of individual cells. They are emergent properties arising from dynamic interactions between neurons in the different relay stations of the sensory pathways where recognition of basic physical properties of incoming stimuli take place. Emergent properties and interactions between them range from physical properties of stimuli to cognitive operations as emotions or consciousness and gradually involve interactions between sensory pathways, associative cortexes, hippocampus, or the amygdala. Here we propose to build neural tissues from embryonic stem cells in “in vitro” controlled environments to determine the way physical inputs are transformed into what humans perceive and measure. We will start with “low complexity” tissues able to perform low level recognition of physical properties, to gradually increase the complexity of the tissue to investigate how the physical characteristics of the incoming stimuli correspond at higher levels to the emergent properties of the system. Mathematical methods based on networks theory, nonlinear dynamics, fractal theory and chaos among other will be used to determine and measure the emergent properties of the nervous tissue at different complexity levels. We expected to provide criteria and methodologies to measure human-like perception variables and use them for the design of future living artifacts (autonomous robots, intelligent sensors, hybrid systems, etc.)