In real life scenarios, the way brain generates cognition is complex and cognitive domains and subdomains are highly interrelated. Moreover, brain processes are intrinsically multidimensional, since they operate across time, frequency, and space domains. These processes involve the intricate interaction and collaboration of widely distributed brain regions through the activation and deactivation of specific networks. Depending on the specific brain imaging technique used and the analysis methods adopted, different aspects of brain functioning can be explored. This PhD work was focused on the design and implementation of EEG-based methods to investigate human brain functions during the performance of complex cognitive tasks, aiming to reliably replicate real-life cognitive processes. Specifically, two EEG dataset were acquired during the real-life simulations of a software programming task and visuo-motor integration task. This work started from data acquisition, for which two ad-hoc experimental paradigms were successfully designed and implemented. For the software production case, a dataset of continuous EEG data during a real software production task on fifteen experienced programmers was acquired. A second dataset of continuous EEG was acquired during the visuo-motor integration task Nine Hole Peg test on 45 healthy right-handed volunteers. This dataset was also acquired in order to evaluate the effect of three weeks of action observation therapy on healthy subjects delivered before sleep hours. The present thesis is organized as the collection of three research studies, based on the analysis the two EEG dataset acquired. The first study investigated brain mechanisms during software programming, revealing adaptive responses in the Theta network topology. Connectivity and graph theoretical analysis (GTA) results showed that programming tasks are supported by the Theta frontoparietal network that dynamic adapts to task demands. Moreover, a central role of parietal nodes emerged. The second study evaluated action observation therapy effects during a visuo-motor integration task. Spectral analysis in Mu and Beta bands showed increased frontal and parietal activation after therapy before sleep, correlating with improved motor performance. The study suggested that therapy associated with sleep enhances motor plasticity and generates motor memory. In the third study, we investigated the re-configurations of functional brain networks triggered by the execution of a visuo-motor integration task using both the dominant and non-dominant hands. Obtained results showed that connectivity analysis associated with GTA is able to shed light over the main brain networks frequency-dependent reorganization strategies supporting visuo-motor processes with the two sides of the body. Three functional subnetworks were identified: Default Mode Network, Sensorimotor Network, and Attention Network, revealing frequency-dependent reorganization strategies supporting visuo-motor processes. From a methodological point of view, the main result of the entire PhD work was the identification and implementation of a pipeline for continuous EEG data analysis and the extraction of meaningful descriptors of brain functioning. Particular attention was focused on the identification of proper methodologies for the manipulation of brain connectivity matrices, and their consequent visualization, description and interpretation. The obtained pipeline is organized in sequential modules of data analysis which can be easily adapted to the specific protocol, dataset available and to the research question. Given its modular and adaptable structure, the present pipeline was adjusted according to the specific needs of the three research studied presented.
Nella vita quotidiana, i processi cognitivi sono generati dai meccanismi cerebrali complessi ancora non completamente compresi. Tali processi sono intrinsecamente multidimensionali, poiché operano attraverso domini temporali, di frequenza e spaziali. Essi prevedono, inoltre, la collaborazione di regioni cerebrali ampiamente distribuite che avviene attraverso l'attivazione e la disattivazione di reti specifiche. A seconda della tecnica specifica di imaging cerebrale utilizzata e dei metodi di analisi adottati, è possibile esplorare diversi aspetti del funzionamento cerebrale. Il presente lavoro di dottorato è stato focalizzato sulla progettazione e implementazione di metodi per l’investigazione delle funzioni cerebrali umane durante l'esecuzione di compiti cognitivi complessi a partire da segnali elettroencefalografici (EEG). In particolare, sono stati acquisiti due dataset EEG durante la simulazione di: i) un compito di programmazione software e ii) di un compito di integrazione visuo-motoria. La prima fase del lavoro si è concentrata sulla raccolta dati, per la quale sono stati progettati e implementati con successo due protocolli sperimentali. Nel caso della produzione di software, é stato acquisito un dataset di EEG continuo durante l’esecuzione di un vero compito di produzione software su 15 programmatori esperti. Un secondo set di dati di EEG continuo è stato acquisito durante l’esecuzione del Nine Hole Peg Test su 45 volontari sani destrimani. Questo set di dati è stato anche acquisito per valutare l'effetto di tre settimane della Action Observation Therapy (AOT) su soggetti sani, somministrata prima delle ore di sonno. La presente tesi è organizzata come la raccolta di tre studi di ricerca, basati sull'analisi dei due dataset acquisiti. Il primo studio aveva lo scopo di identificare i principali meccanismi cerebrali innescati durante la programmazione software e ha rivelato la presenza di risposte adattive nella topologia di rete nella banda Theta. I risultati dell'analisi di connettività associata all’analisi dei grafi (GTA) hanno mostrato che i compiti di programmazione sono supportati dalla rete fronto-parietale in Theta, in grado di adattarsi dinamicamente in funzione del compito cognitivo. Inoltre, è emerso un ruolo centrale dei nodi parietali. Il secondo studio ha valutato gli effetti dell’AOT durante un compito di integrazione visuo-motoria. L'analisi spettrale nelle bande Mu e Beta ha mostrato un aumento dell'attivazione frontale e parietale dopo la terapia somministrata prima del sonno, la quale risulta essere correlata a un miglioramento delle prestazioni motorie. In generale, i risultati dello studio suggeriscono che la terapia associata al sonno potenzia la plasticità motoria e genera una memoria motoria. Nel terzo studio, sono state indagate le riconfigurazioni delle reti cerebrali funzionali scatenate dall'esecuzione di un compito di integrazione visuo-motoria utilizzando entrambe le mani (dominante e non dominante). I risultati ottenuti hanno mostrato che l'analisi di connettività associata a GTA è in grado di discriminare in funzione della frequenza le strategie di riorganizzazione delle reti cerebrali che supportano i processi visuo-motori eseguiti con entrambi i lati del corpo. Dal punto di vista metodologico, il risultato principale dell'intero lavoro di dottorato si basa sull'identificazione e l'implementazione di una sequenza di procedure per l'analisi dei dati EEG continui e sull'estrazione di descrittori del funzionamento delle reti cerebrali. Particolare attenzione è stata dedicata all'identificazione di metodologie adeguate per la manipolazione delle matrici di connettività e alla loro successiva visualizzazione, descrizione e interpretazione. La sequenza di procedure ottenuta è organizzata in moduli sequenziali di analisi, i quali possono essere facilmente adattati al protocollo specifico, al set di dati disponibile e alla domanda di ricerca. Data la sua struttura modulare e adattabile, la presente sequenza è stata applicata in base alle esigenze specifiche dei tre studi di ricerca presentati.
EEG-based characterization of human brain networks in cognition
Calcagno, Alessandra
2023/2024
Abstract
In real life scenarios, the way brain generates cognition is complex and cognitive domains and subdomains are highly interrelated. Moreover, brain processes are intrinsically multidimensional, since they operate across time, frequency, and space domains. These processes involve the intricate interaction and collaboration of widely distributed brain regions through the activation and deactivation of specific networks. Depending on the specific brain imaging technique used and the analysis methods adopted, different aspects of brain functioning can be explored. This PhD work was focused on the design and implementation of EEG-based methods to investigate human brain functions during the performance of complex cognitive tasks, aiming to reliably replicate real-life cognitive processes. Specifically, two EEG dataset were acquired during the real-life simulations of a software programming task and visuo-motor integration task. This work started from data acquisition, for which two ad-hoc experimental paradigms were successfully designed and implemented. For the software production case, a dataset of continuous EEG data during a real software production task on fifteen experienced programmers was acquired. A second dataset of continuous EEG was acquired during the visuo-motor integration task Nine Hole Peg test on 45 healthy right-handed volunteers. This dataset was also acquired in order to evaluate the effect of three weeks of action observation therapy on healthy subjects delivered before sleep hours. The present thesis is organized as the collection of three research studies, based on the analysis the two EEG dataset acquired. The first study investigated brain mechanisms during software programming, revealing adaptive responses in the Theta network topology. Connectivity and graph theoretical analysis (GTA) results showed that programming tasks are supported by the Theta frontoparietal network that dynamic adapts to task demands. Moreover, a central role of parietal nodes emerged. The second study evaluated action observation therapy effects during a visuo-motor integration task. Spectral analysis in Mu and Beta bands showed increased frontal and parietal activation after therapy before sleep, correlating with improved motor performance. The study suggested that therapy associated with sleep enhances motor plasticity and generates motor memory. In the third study, we investigated the re-configurations of functional brain networks triggered by the execution of a visuo-motor integration task using both the dominant and non-dominant hands. Obtained results showed that connectivity analysis associated with GTA is able to shed light over the main brain networks frequency-dependent reorganization strategies supporting visuo-motor processes with the two sides of the body. Three functional subnetworks were identified: Default Mode Network, Sensorimotor Network, and Attention Network, revealing frequency-dependent reorganization strategies supporting visuo-motor processes. From a methodological point of view, the main result of the entire PhD work was the identification and implementation of a pipeline for continuous EEG data analysis and the extraction of meaningful descriptors of brain functioning. Particular attention was focused on the identification of proper methodologies for the manipulation of brain connectivity matrices, and their consequent visualization, description and interpretation. The obtained pipeline is organized in sequential modules of data analysis which can be easily adapted to the specific protocol, dataset available and to the research question. Given its modular and adaptable structure, the present pipeline was adjusted according to the specific needs of the three research studied presented.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/217076