URI | http://purl.tuc.gr/dl/dias/D83DB06D-D54B-4D39-9158-34E3D83BA364 | - |
Αναγνωριστικό | https://doi.org/10.1007/s12021-022-09615-1 | - |
Αναγνωριστικό | https://link.springer.com/article/10.1007/s12021-022-09615-1 | - |
Γλώσσα | en | - |
Μέγεθος | 16 pages | en |
Τίτλος | Chronic mild Traumatic Brain Injury: aberrant static and dynamic connectomic features identified through machine learning model fusion | en |
Δημιουργός | Simos Nikolaos-Ioannis | en |
Δημιουργός | Σιμος Νικολαος-Ιωαννης | el |
Δημιουργός | Manolitsi Katina | en |
Δημιουργός | Luppi Andrea I. | en |
Δημιουργός | Kagialis Antonios | en |
Δημιουργός | Antonakakis Marios | en |
Δημιουργός | Αντωνακακης Μαριος | el |
Δημιουργός | Zervakis Michail | en |
Δημιουργός | Ζερβακης Μιχαηλ | el |
Δημιουργός | Antypa Despina | en |
Δημιουργός | Kavroulakis Eleftherios | en |
Δημιουργός | Maris Thomas G. | en |
Δημιουργός | Vakis Antonios | en |
Δημιουργός | Stamatakis Emmanuel A. | en |
Δημιουργός | Papadaki Efrosini | en |
Εκδότης | Springer | en |
Περίληψη | Traumatic Brain Injury (TBI) is a frequently occurring condition and approximately 90% of TBI cases are classified as mild (mTBI). However, conventional MRI has limited diagnostic and prognostic value, thus warranting the utilization of additional imaging modalities and analysis procedures. The functional connectomic approach using resting-state functional MRI (rs-fMRI) has shown great potential and promising diagnostic capabilities across multiple clinical scenarios, including mTBI. Additionally, there is increasing recognition of a fundamental role of brain dynamics in healthy and pathological cognition. Here, we undertake an in-depth investigation of mTBI-related connectomic disturbances and their emotional and cognitive correlates. We leveraged machine learning and graph theory to combine static and dynamic functional connectivity (FC) with regional entropy values, achieving classification accuracy up to 75% (77, 74 and 76% precision, sensitivity and specificity, respectively). As compared to healthy controls, the mTBI group displayed hypoconnectivity in the temporal poles, which correlated positively with semantic (r = 0.43, p < 0.008) and phonemic verbal fluency (r = 0.46, p < 0.004), while hypoconnectivity in the right dorsal posterior cingulate correlated positively with depression symptom severity (r = 0.54, p < 0.0006). These results highlight the importance of residual FC in these regions for preserved cognitive and emotional function in mTBI. Conversely, hyperconnectivity was observed in the right precentral and supramarginal gyri, which correlated negatively with semantic verbal fluency (r=-0.47, p < 0.003), indicating a potential ineffective compensatory mechanism. These novel results are promising toward understanding the pathophysiology of mTBI and explaining some of its most lingering emotional and cognitive symptoms. | en |
Τύπος | Peer-Reviewed Journal Publication | en |
Τύπος | Δημοσίευση σε Περιοδικό με Κριτές | el |
Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
Ημερομηνία | 2024-03-04 | - |
Ημερομηνία Δημοσίευσης | 2023 | - |
Θεματική Κατηγορία | Traumatic Brain Injury | en |
Θεματική Κατηγορία | fMRI | en |
Θεματική Κατηγορία | Depression | en |
Θεματική Κατηγορία | Verbal Fluency | en |
Θεματική Κατηγορία | Functional Connectivity | en |
Βιβλιογραφική Αναφορά | N. J. Simos, K. Manolitsi, A. I. Luppi, A. Kagialis, M. Antonakakis, M. Zervakis, D. Antypa, E. Kavroulakis, T. G. Maris, A. Vakis, E. A. Stamatakis and E. Papadaki “Chronic mild Traumatic Brain Injury: aberrant static and dynamic connectomic features identified through machine learning model fusion,” Neuroinform., vol. 21, no. 2, pp. 427–442, Apr. 2023, doi: 10.1007/s12021-022-09615-1. | en |