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An individuals reaction time data to visual stimuli have usually been represented in Experimental Psychology by means of an ex-Gaussian function (EGF). In most previous works, researchers have mainly aimed at finding a meaning for the parameters of the EGF function in relation to psychological phenomena. We will focus on interpreting the reaction times (RTs) of a group of individuals rather than a single persons RT, which is relevant for the different contexts of social sciences. In doing so, the same model as for the Ideal Gases (IG) (an inanimate system of non-interacting particles) emerges from the experimental RT data. Both systems are characterised by a collective parameter which is k_BT in the case of the system of particles and what we have called life span parameter for the system of brains. Similarly, we came across a Maxwell-Boltzmann-type distribution for the system of brains which provides a natural and more complete characterisation of the collective time response than has ever been provided before. Thus, we are able to know about the behaviour of a single individual in relation to the coetaneous group to which they belong and through the application of a physical law. This leads to a new entropy-based methodology for the classification of the individuals forming the system which emerges from the physical law governing the system of brains. To the best of our knowledge, this is the first work in the literature reporting on the emergence of a physical theory (IG) from human RT experimental data.
This paper describes an x-ray microtomographic technique for imaging the three-dimensional structure of the human cerebral cortex. Neurons in the brain constitute a neural circuit as a three-dimensional network. The brain tissue is composed of light
Collective motion is found in various animal systems, active suspensions and robotic or virtual agents. This is often understood using high level models that directly encode selected empirical features, such as co-alignment and cohesion. Can these fe
We analyze the complex networks associated with brain electrical activity. Multichannel EEG measurements are first processed to obtain 3D voxel activations using the tomographic algorithm LORETA. Then, the correlation of the current intensity activat
In cerebrovascular networks, some vertices are more connected to each other than with the rest of the vasculature, defining a community structure. Here, we introduce a class of model networks built by rewiring Random Regular Graphs, which enables to
Despite great progress in neuroscience, there are still fundamental unanswered questions about the brain, including the origin of subjective experience and consciousness. Some answers might rely on new physical mechanisms. Given that biophotons have