Arturo Tozzi

The paper develops a simulation framework using engineering energy metrics to quantify mitochondrial bioenergetics changes in tumors and immune cells after mitochondrial transfer.

This paper applies Takens' theorem to EEG data to reveal regional differences in brain dynamics across frontal, sensorimotor, and occipital regions.

This paper models how neonatal skin scratching may drive immune imprinting through localized inflammation and antigen exposure.

This study shows that bacterial stiffness influences spatial organization and mechanical responses in the gut, suggesting mechanical properties can shape microbial localization and persistence.

This study shows that a closed-hand posture improves heat retention and blood flow, potentially reducing Raynaud's Phenomenon symptoms through biomechanical and thermodynamic mechanisms.

This paper introduces a multi-valued logic model of T cell activation and cytokine response, showing that cytokine output scales with activating inputs and is modulated by inhibitory signals in a graded manner.

This paper applies Wedderburn's Theorem to model non-commutative biological and evolutionary systems by decomposing them into irreducible components that capture sequence-dependent functionality.

This paper uses a Linear Logic framework to model prebiotic biochemical pathways, showing RNA synthesis is sensitive to environmental changes while DNA formation is more resilient.

This paper develops an optimal transport model to quantify gas migration in pneumatosis intestinalis, showing how gas spreads from the lumen to deeper gut layers through diffusion and trapping mechanisms.

This study uses advanced mathematical methods to analyze EEG signals from high- and low-IQ individuals, finding differences in cortical organization related to intelligence.

This study applies topological methods to cerebral angiography to analyze vascular network structure, identifying potential biomarkers for cerebrovascular diseases.

This study analyzes the topological structure of a star jasmine bush using computational methods to show how it balances local constraints with global connectivity for efficient resource distribution.

The paper applies Poincare duality to analyze cortical structures in Macaca mulatta, revealing topological relationships between dense neuronal clusters and sparse integration regions.

The paper identifies Levy flight-like patterns in the cortical architecture of Macaca mulatta using histological data, showing heavy-tailed step-length distributions and small-world network properties.

This study analyzes nonlinear locomotion patterns in the Egyptian Locust using mathematical and computational methods, revealing structured and predictable movement dynamics.

This study uses Monte Carlo simulations to predict EEG patterns and identifies neural differences between high and low IQ groups, showing higher predictability in low-IQ individuals.

This paper extends Stokes' theorem to spiral paths, applying it to analyze rotational flows in plant stems and flowers of Trachelospermum jasminoides.

The paper explores mapping three-dimensional EEG data to a four-dimensional hypersphere using quaternion projections to analyze neural activity patterns.

The paper applies the hairy ball theorem to EEG data, identifying zero-points in electric wave fronts and suggesting their use in improving transcranial magnetic stimulation for drug-resistant epilepsy.

The paper proposes that brain activity resembles Belousov-Zhabotinsky (BZ) reactions, showing that spontaneous neural activity matches BZ dynamics in cortical subareas.

The paper uses computational topology to analyze rs-fMRI data, identifying persistent BOLD signal structures called cortical lag threads and visualizing them as persistent barcodes.

This study uses a reaction-diffusion model to show that neuronal density patterns in Hirschsprung’s disease match Turing-like predictions, enabling precise surgical resection length calculations.

The paper investigates if the real part of the modular j-function can be observed in human EEG data, finding a high match between j-function trajectories and EEG patterns.

The paper shows that variations in Renyi entropy correlate with changes in the scaling slope of brain scale-free dynamics, suggesting potential applications in mind reading and transcranial stimulation.

The paper proposes a topological framework showing that all brain activities are dual and interconnected across different spatiotemporal scales and cortical regions.

The paper measures information entropy in fMRI data and finds higher entropy in associative brain regions compared to primary sensory areas, suggesting the brain operates in higher dimensions than the environment.

The paper proposes a model of cortical microcolumns as fullerene-like lattices where neural activity is represented as barcodes of neuron activation patterns, enabling artificial networks with robustness and plasticity.

The paper introduces a novel fMRI analysis method, maximal nucleus clustering, to detect hidden temporal patterns of entropy in brain activity, suggesting evidence for a fourth spatial dimension in the brain.

The paper uses first-order predicate logic to evaluate whether mind is a function of brain activity, if mental faculties can be reduced, and if cognition and emotion are distinct.

This paper proposes a mathematical framework combining Borsuk's theory of shape and the Borsuk-Ulam theorem to model perception as a topological and ecological process.