Anorexia nervosa (AN) is a psychiatric disorder involving complex interactions among biological, psychological, and environmental factors. Recent studies suggest that alterations in brain networks may serve as relevant neurobiological markers. This thesis investigates structural brain organization in patients with AN using graph theory-based connectivity analysis. Using high-resolution structural MRI (3D-T1), global and network-specific graph metrics (e.g., local efficiency, average strength) were extracted in a sample including AN patients and healthy controls. These measures were then correlated with clinical variables (BMI, illness duration, age of onset) and neuropsychological indices (EDI-3, WCST, Rey Figure, RMET). Results revealed associations between lower average strength and higher perceived ineffectiveness, as well as between higher BMI and increased local efficiency. Additionally, illness duration was positively associated with somatomotor network efficiency, suggesting adaptive changes linked to chronicity. These findings support the hypothesis of altered brain network architecture in AN and highlight the value of graph theory for investigating structural disconnection and its clinical relevance.
L’anoressia nervosa (AN) è un disturbo psichiatrico caratterizzato da una complessa interazione tra fattori biologici, psicologici e ambientali. Studi recenti suggeriscono che l’alterazione delle reti cerebrali possa rappresentare un marcatore neurobiologico rilevante della patologia. La presente tesi esplora l’organizzazione strutturale del cervello in pazienti con AN attraverso l’analisi della connettività cerebrale basata sulla teoria dei grafi. Mediante risonanza magnetica strutturale (3D-T1), sono state estratte metriche topologiche globali e specifiche di rete (es. efficienza locale, forza media) in un campione composto da pazienti e controlli sani. Tali misure sono state messe in relazione con variabili cliniche (BMI, durata della malattia, età di esordio) e neuropsicologiche (EDI-3, WCST, figura di Rey, RMET). Le analisi hanno evidenziato correlazioni tra un indice di inefficacia percepita e minore forza media della rete, nonché tra BMI più elevati e maggiore efficienza locale. Sono emerse anche associazioni tra durata della malattia ed efficienza della rete somatomotoria, suggerendo adattamenti cerebrali legati alla cronicità. I risultati supportano l’ipotesi di un’alterata architettura delle reti cerebrali nei soggetti con AN, confermando l’utilità della teoria dei grafi per lo studio delle disconnessioni strutturali e per una migliore comprensione dei correlati clinici della patologia.
Alterazioni della connettività cerebrale strutturale nell’Anoressia Nervosa: un’analisi mediante teoria dei grafi
GIOACHIN, VERONICA
2024/2025
Abstract
Anorexia nervosa (AN) is a psychiatric disorder involving complex interactions among biological, psychological, and environmental factors. Recent studies suggest that alterations in brain networks may serve as relevant neurobiological markers. This thesis investigates structural brain organization in patients with AN using graph theory-based connectivity analysis. Using high-resolution structural MRI (3D-T1), global and network-specific graph metrics (e.g., local efficiency, average strength) were extracted in a sample including AN patients and healthy controls. These measures were then correlated with clinical variables (BMI, illness duration, age of onset) and neuropsychological indices (EDI-3, WCST, Rey Figure, RMET). Results revealed associations between lower average strength and higher perceived ineffectiveness, as well as between higher BMI and increased local efficiency. Additionally, illness duration was positively associated with somatomotor network efficiency, suggesting adaptive changes linked to chronicity. These findings support the hypothesis of altered brain network architecture in AN and highlight the value of graph theory for investigating structural disconnection and its clinical relevance.| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/96297