Modeling the Antipodal Connectivity Structure of Neural Communities

Abstract

Recent studies support the theory of the brain being composed of modules and certain nodes establishing connections between the modules [ 1 , 2 , 3 ] . The existence of such connections can only be identified by conducting a detailed investigation with sophisticated tools. Therefore, in this manuscript we provide a new mathematical model to indicate the functional dependency, which supports the idea of information exchange between the neural modules at the highest spatial and hierarchical level of bottom-up processes using EEG (ElectroEncephaloGraphy) [ 4 ] . The developed model is to study the functional dependencies between di erent regions of the cortex is based on the Borsuk-Ulam's antipodal symmetry theorem. It is a mathematical model complemented with an innovative algorithm, called Projection based on Normalized Transformation (PNT), to show the existence of unique neural activity pattern known as the Antipodal Connectivity. For validating of the model, EEG data collected from a total of 50 experiments with the participation of 18 di erent test subjects was used to measure the e ectiveness and accuracy of method. Using the data collected from the subjects in di erent stages (active or resting) of the brain, the Antipodal Hub Neurons (AHNs) were captured and compared to determine the ratio of fluctuation under di erent conditions and whether or not the stimulus has any role in antipodal neural connectivity. Although the preliminary results are not conclusive, we have successfully identified the existence of antipodal behavioral patterns in neural activities.