Lucas Remoaldo Trambaiolli, Ph.D.
Affiliations: | 2018- | McLean Hospital - Harvard Medical School |
Area:
affective neuroscience, neuroimaging, brain-computer interfacesGoogle:
"Lucas Trambaiolli"Mean distance: (not calculated yet)
Parents
Sign in to add mentorAndre M. Cravo | grad student | 2012-2018 | |
Joao Ricardo Sato | grad student | 2012-2018 | |
Suzanne Haber | post-doc | 2018- |
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Publications
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Peng X, Trambaiolli LR, Choi EY, et al. (2024) Cross-species striatal hubs: linking anatomy to resting-state connectivity. Neuroimage. 120866 |
Trambaiolli LR, Cassani R, Biazoli CE, et al. (2022) Multimodal resting-state connectivity predicts affective neurofeedback performance. Frontiers in Human Neuroscience. 16: 977776 |
Trambaiolli LR, Peng X, Lehman JF, et al. (2022) Anatomical and functional connectivity support the existence of a salience network node within the caudal ventrolateral prefrontal cortex. Elife. 11 |
Jezzini A, Bromberg-Martin ES, Trambaiolli LR, et al. (2021) A prefrontal network integrates preferences for advance information about uncertain rewards and punishments. Neuron |
Moreno JG, Biazoli CE, Baptista AF, et al. (2021) Closed-loop neurostimulation for affective symptoms and disorders: an overview. Biological Psychology. 108081 |
Trambaiolli LR, Tossato J, Cravo AM, et al. (2021) Subject-independent decoding of affective states using functional near-infrared spectroscopy. Plos One. 16: e0244840 |
Trambaiolli LR, Biazoli CE. (2020) Resting-state global EEG connectivity predicts depression and anxiety severity. Annual International Conference of the Ieee Engineering in Medicine and Biology Society. Ieee Engineering in Medicine and Biology Society. Annual International Conference. 2020: 3707-3710 |
Trambaiolli LR, Biazoli CE, Cravo AM, et al. (2018) Functional near-infrared spectroscopy-based affective neurofeedback: feedback effect, illiteracy phenomena, and whole-connectivity profiles. Neurophotonics. 5: 035009 |
Trambaiolli LR, Biazoli CE, Cravo AM, et al. (2018) Predicting affective valence using cortical hemodynamic signals. Scientific Reports. 8: 5406 |
Trambaiolli LR, Spolaôr N, Lorena AC, et al. (2017) Feature selection before EEG classification supports the diagnosis of Alzheimer's disease. Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology. 128: 2058-2067 |