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.
Highlights
A neural network, which has the property of a modular/colonial structure and controls the information behavior of a human, is governed with a set of organizational principles
Using Projection based on Normalized Transformation (PNT) method, a total of 50 experiments were analyzed to show the existence of Antipodal Hub Neurons (AHNs) network structure in the brain network
Borsuk-Ulams antipodal symmetry theory was adapted to establish the mathematical foundation for the PNT model
Summary
A neural network, which has the property of a modular/colonial structure and controls the information behavior of a human, is governed with a set of organizational principles. Removing some portions of the brain may stop the progression of diseases, the brain loses some of its previous capabilities that were not related to that region, after the surgery This suggests that there is a higher-level hierarchy in decision-making. We assume that storing or sending information between neural populations is an internal cognitive decision-making process that starts at the lowest hierarchical structural level and concludes at the highest level in the hierarchy before any related task is completed. The rationale behind this approach lies at the very foundation of how the brain operates. Such an approach will represent the activity of the neural populations more realistically because of the following reasons: AIMS Neuroscience
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