Brain Connectivity Lab

Responsabile: Vecchio Fabrizio
Staff: Miraglia Francesca, Pappalettera Chiara, Nucci Lorenzo, Cacciotti Alessia

Focuses on the assessment of brain networks for the study of brain complexity and functional, structural and effective connectivity. The Laboratory’s activity is specifically aimed at the evaluation of modulations of brain networks, studied through connectivity and complexity, due to neurodegenerative and non-neurodegenerative diseases (such as in Alzheimer’s patients, epilepsy, sclerosis, Parkinson’s, Stroke, …) as well as therapeutic treatment and motor or cognitive rehabilitation (such as in Alzheimer’s, Stroke, …). The acquisition methods used are: electroencephalographic (EEG) data, magnetic resonance imaging (MRI) data, simultaneous recordings of electroencephalographic data and electrical and magnetic stimulation (EEG-TMS, EEG-tDCS, EEG-tACS).

The major innovations made by our research are first of all in the multimodal approach to pathology and in the integration of data from different origins, such as those already listed, but also as data from neuropsychological and clinical tests that allow correlation with neurophysiological assessments to follow the patient during disease progression or functional and cognitive recovery through new rehabilitation approaches such as those related to cognitive tasks and magnetic and electrical stimulation aimed at specific cognitive recovery of specific brain areas.

Interessi di Ricerca

  • Neurophysiological methods of predicting/programming functional recovery
  • Methods of analysis (including artificial intelligence) of electroencephalographic signal
  • New uses of non-invasive brain stimulation methods for neuromotor and cognitive rehabilitation
  • Evaluation of brain network modulations due to neurodegenerative and non-neurodegenerative diseases (such as in patients with Alzheimer’s disease, epilepsy, sclerosis, Parkinson’s disease, Stroke, …) as well as therapeutic treatment and motor or cognitive rehabilitation (such as in Alzheimer’s, Stroke, …) and physiological aging.


  1. Vecchio F , Miraglia F, Alù F, Judica E, Cotelli M, Pellicciari MC, Rossini PM. Human brain networks in physiological and pathological aging: reproducibility of EEG graph theoretical analysis in cortical connectivity. Brain Connect. 2022 Feb;12(1):41-51. doi: 10.1089/brain.2020.0824. Epub 2021 Dec 24. PMID: 33797981.
  1. Costa C, Vecchio F, Romoli M, Miraglia F, Nardi Cesarini E, Alù F, Calabresi P, Rossini PM. Cognitive Decline Risk Stratification in People with Late-Onset Epilepsy of Unknown Etiology: An Electroencephalographic Connectivity and Graph Theory Pilot Study. J Alzheimers Dis. 2022;88(3):893-901. doi: 10.3233/JAD-210350. PMID: 34842184.
  1. Vecchio F , Quaranta D, Miraglia F, Pappalettera C, Di Iorio R, L’Abbate F, Cotelli M, Marra C, Rossini PM. Neuronavigated Magnetic Stimulation combined with cognitive training for Alzheimer’s patients: an EEG graph study. Geroscience. 2022 Feb;44(1):159-172. doi: 10.1007/s11357-021-00508-w. Epub 2021 Dec 31. PMID: 34970718; PMCID: PMC8811083.
  1. Miraglia F, Vecchio F, Pellicciari MC, Cespon J, Rossini PM. Brain Networks Modulation in Young and Old Subjects During Transcranial Direct Current Stimulation Applied on Prefrontal and Parietal Cortex. Int J Neural Syst. 2022 Jan;32(1):2150056. doi: 10.1142/S0129065721500568. Epub 2021 Oct 15. PMID: 34651550.
  1. Rossini PM, Miraglia F, Vecchio F, Di Iorio R, Iodice F, Cotelli M. General principles of brain electromagnetic rhythmic oscillations and implications for neuroplasticity. Handb Clin Neurol. 2022;184:221-237. doi: 10.1016/B978-0-12-819410-2.00012-6. PMID: 35034737. Book Chapter
  1. Rossini PM, Miraglia F, Judica E, Cotelli M, Alù F, Vecchio F . Methods Used in Brain Connectivity: Focus on Electrophysiological Measures, Editor(s): Sergio Della Sala, Encyclopedia of Behavioral Neuroscience, 2nd edition (Second Edition), Elsevier, 2022, 1-3:155-162, ISBN 9780128216361, Book Chapter
  1. Rossini PM, Miraglia F, Orlando B, Iodice F, Ferreri F, Cotelli M, Judica E, Vecchio F . Chapter 8 – Noninvasive electrical and magnetic brain stimulation (with insights on the effects of cellular phone emissions): basic principles and procedures for clinical application, Editor(s): Alexander M. Tishin, In Woodhead Publishing Series in Electronic and Optical Materials, Magnetic Materials and Technologies for Medical Applications, Woodhead Publishing, 2022, 227-262, ISBN 9780128225325, Book Chapter
  1. Longo V, Barbati SA, King A, Paciello F, Bolla M, Rinaudo M, Miraglia F, Alù F, Di Donna MG, Vecchio F, Rossini PM, Podda MV, Grassi C. Transcranial Direct Current Stimulation Enhances Neuroplasticity and Accelerates Motor Recovery in a Stroke Mouse Model. Stroke. 2022 May;53(5):1746-1758. doi: 10.1161/STROKEAHA.121.034200. Epub 2022 Mar 16. PMID: 35291824
  1. Miraglia F, Vecchio F, Pappalettera C, Nucci L, Cotelli M, Judica E, Ferreri F, Rossini PM. Brain Connectivity and Graph Theory Analysis in Alzheimer’s and Parkinson’s Disease: The Contribution of Electrophysiological Techniques. Brain Sci. 2022 Mar 18;12(3):402. doi: 10.3390/brainsci12030402. PMID: 35326358.
  1. Pappalettera C, Miraglia F, Cotelli M, Rossini PM, Vecchio F . Analysis of complexity in the EEG activity of Parkinson’s disease patients by means of approximate entropy. Geroscience. 2022 Jun;44(3):1599-1607. doi: 10.1007/s11357-022-00552-0. Epub 2022 Mar 28. PMID: 35344121; PMCID: PMC9213590.
  1. Gourdeau D, Potvin O, Archambault P, Chartrand-Lefebvre C, Dieumegarde L, Forghani R, Gagné C, Hains A, Hornstein D, Le H, Lemieux S, Lévesque MH, Martin D, Rosenbloom L, Tang A, Vecchio F, Yang I, Duchesne N, Duchesne S. Tracking and predicting COVID-19 radiological trajectory on chest X-rays using deep learning. Sci Rep. 2022 Apr 4;12(1):5616. doi: 10.1038/s41598-022-09356-w. PMID: 35379856.
  1. Rossini PM, Miraglia F, Vecchio F . Early dementia diagnosis, MCI-to-dementia risk prediction, and the role of machine learning methods for feature extraction from integrated biomarkers, in particular for EEG signal analysis. Alzheimers Dement. 2022 Dec;18(12):2699-2706. doi: 10.1002/alz.12645. Epub 2022 Apr 7. PMID: 35388959.
  1. Vecchio F , Alù F, Orticoni A, Miraglia F, Judica E, Cotelli M, Rossini PM. Performance prediction in a visuomotor task: the contribution of EEG analysis. Cogn Neurodyn. 2022 Apr;16(2):297-308. doi: 10.1007/s11571-021-09713-x. Epub 2021 Sep 11. PMID: 35401869; PMCID: PMC8934791.
  1. Porcaro C, Vecchio F, Miraglia F, Zito G, Rossini PM. Dynamics of the “Cognitive” Brain Wave P3b at Rest for Alzheimer Dementia Prediction in Mild Cognitive Impairment. Int J Neural Syst. 2022 May;32(5):2250022. doi: 10.1142/S0129065722500228. Epub 2022 Apr 18. PMID: 35435134.
  1. Old F . Cognitive training and neuromodulation for Alzheimer’s treatment. Aging (Albany NY). 2022 Apr 27;14(9):3722-3723. doi: 10.18632/aging.204044. Epub 2022 Apr 27. PMID: 35478169; PMCID: PMC9134967.
  1. Ferreri F, Miraglia F, Vecchio F, Manzo N, Cotelli M, Judica E, Rossini PM. Electroencephalographic hallmarks of Alzheimer’s disease. Int J Psychophysiol. 2022 Nov;181:85-94. doi: 10.1016/j.ijpsycho.2022.08.005. Epub 2022 Aug 31. PMID: 36055410.
  1. Vecchio F , Nucci L, Pappalettera C, Miraglia F, Iacoviello D, Rossini PM. Time-frequency analysis of brain activity in response to directional and non-directional visual stimuli: an event-related spectral perturbations (ERSP) study. J Neural Eng. 2022 Nov 9;19(6). doi: 10.1088/1741-2552/ac9c96. PMID: 36270505.
  2. Vecchio F , Pappalettera C, Miraglia F, Deinite G, Manenti R, Judica E, Caliandro P, Rossini PM. Prognostic Role of Hemispherical Functional Connectivity in Stroke: A Study via Graph Theory Versus Coherence of Electroencephalography Rhythms. Stroke. 2023 Feb;54(2):499-508. doi: 10.1161/STROKEAHA.122.040747. Epub 2022 Nov 23. PMID: 36416129.
  1. Pappalettera C, Cacciotti A, Nucci L, Miraglia F, Rossini PM, Vecchio F . Approximate entropy analysis across electroencephalographic rhythmic frequency bands during physiological aging of human brain. Geroscience. 2023 Apr;45(2):1131-1145. doi: 10.1007/s11357-022-00710-4. Epub 2022 Dec 20. PMID: 36538178; PMCID: PMC9886767.
  1. Rossini PM, Miraglia F, Vecchio F . Commentary on Comparison of Machine Learning-based Approaches to Predict the Conversion to Alzheimer’s Disease from Mild Cognitive Impairment. Neuroscience. 2023 Mar 15;514:141-142. doi: 10.1016/j.neuroscience.2022.12.018. Epub 2022 Dec 30. PMID: 36592944.
  1. Miraglia F, Pappalettera C, Guglielmi V, Cacciotti A, Manenti R, Judica E, Vecchio F, Rossini PM. The combination of hyperventilation test and graph theory parameters to characterize EEG changes in mild cognitive impairment (MCI) condition. Geroscience. 2023 Jan 24. doi: 10.1007/s11357-023-00733-5. Epub ahead of print. PMID: 36692591.
  1. Miraglia F, Pappalettera C, Di Ienno S, Nucci L, Cacciotti A, Manenti R, Judica E, Rossini PM, Vecchio F . The Effects of Directional and Non-Directional Stimuli during a Visuomotor Task and Their Correlation with Reaction Time: An ERP Study. Sensors (Basel). 2023 Mar 15;23(6):3143. doi: 10.3390/s23063143. PMID: 36991853; PMCID: PMC10058543.
  1. Nucci L, Miraglia F, Alù F, Pappalettera, C, Judica E, Manenti R, Rossini PM, Vecchio F . Reaction time and cognitive strategies: The role of education in task performance. Learning and Motivation. 2023; 82, 101884. doi:10.1016/j.lmot.2023.101884
  1. Cacciotti A, Pappalettera C, Miraglia F, Valeriani L, Judica E, Rossini PM, Vecchio F . Complexity Analysis from EEG data in Congestive Heart Failure: a study via Approximate Entropy. Acta Physiol (Oxf). 2023 Jun;238(2):e13979. doi: 10.1111/apha.13979. Epub 2023 Apr 30. PMID: 37070962.

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