The complexity of our brains can be described as a multilayer network, from neurons, to the neural agglomerates, to lobes. Neurological diseases are often related to malfunctions in the brain network. We propose a conceptual model of the brain, where the disease can be modeled as the result of an operator affecting and disrupting the brain-network organization, called “K-operator” (from “Krankheit,” German for “disease”). In our approach, the network channel model is adapted from telecommunications, where the action of the K-operator corresponds to an alteration of the healthy communication-structure between neu- ronal agglomerates. The potential of this novel approach is tested by quantitatively modelling the operator with real-data considering the Parkinson disease. We use data from the dataset of Parkinson’s Progression Markers Initiative (PPMI) upon concession by the University of Southern California. The networks are re- constructed from fMRI analysis, resulting in a matrix acting on the healthy brain and giving as output the diseased brain. We finally decompose the K-operator into the tensor product of its submatrices and we are able to assess its action on each one of the regions of interest (ROI) characterizing the brain for the specific considered samples. More interestingly, this application confirms the feasibility of the proposed analytic technique. Further research development can compare operators for different patients and for different diseases, looking for commonalities and aiming to develop a comprehensive theoretical approach. This research was funded by Next Generation EU - Age-It (PE0000015).

An Operator Acting on the Brain Network and Provoking Disease: A Conceptual Model and a First Data- Based Application

Mannone M
;
2024

Abstract

The complexity of our brains can be described as a multilayer network, from neurons, to the neural agglomerates, to lobes. Neurological diseases are often related to malfunctions in the brain network. We propose a conceptual model of the brain, where the disease can be modeled as the result of an operator affecting and disrupting the brain-network organization, called “K-operator” (from “Krankheit,” German for “disease”). In our approach, the network channel model is adapted from telecommunications, where the action of the K-operator corresponds to an alteration of the healthy communication-structure between neu- ronal agglomerates. The potential of this novel approach is tested by quantitatively modelling the operator with real-data considering the Parkinson disease. We use data from the dataset of Parkinson’s Progression Markers Initiative (PPMI) upon concession by the University of Southern California. The networks are re- constructed from fMRI analysis, resulting in a matrix acting on the healthy brain and giving as output the diseased brain. We finally decompose the K-operator into the tensor product of its submatrices and we are able to assess its action on each one of the regions of interest (ROI) characterizing the brain for the specific considered samples. More interestingly, this application confirms the feasibility of the proposed analytic technique. Further research development can compare operators for different patients and for different diseases, looking for commonalities and aiming to develop a comprehensive theoretical approach. This research was funded by Next Generation EU - Age-It (PE0000015).
2024
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR - Sede Secondaria Palermo
neurodegenerative disease
operators
theoretical physics
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/511775
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