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Fabio Giovannelli

Researcher at University of Florence

Publications -  102
Citations -  2284

Fabio Giovannelli is an academic researcher from University of Florence. The author has contributed to research in topics: Transcranial magnetic stimulation & Cognition. The author has an hindex of 24, co-authored 90 publications receiving 1899 citations. Previous affiliations of Fabio Giovannelli include University of Milano-Bicocca & Santa Maria Nuova Hospital.

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Frequency-dependent enhancement of fluid intelligence induced by transcranial oscillatory potentials.

TL;DR: The present finding supports a direct involvement of gamma oscillatory activity in the mechanisms underlying higher-order human cognition, as well as selectively enhanced performance only on more complex trials involving conditional/logical reasoning.
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A real electro-magnetic placebo (REMP) device for sham transcranial magnetic stimulation (TMS)

TL;DR: A new placebo tool is introduced here, called real electro-magnetic placebo (REMP) device, which can simulate the scalp sensation induced by the real TMS, while leaving both the visual impact and acoustic sensation of real T MS unaltered.
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Modulation of interhemispheric inhibition by volitional motor activity: an ipsilateral silent period study

TL;DR: The findings strongly suggest that voluntary M1 activation by real or imagined movement of the contralateral hand increases interhemispheric motor inhibition of the opposite M1.
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Vegetative versus minimally conscious states: a study using TMS-EEG, sensory and event-related potentials.

TL;DR: Electroencephalography recordings suggest that cortical reactivity and connectivity are severely impaired in all VS patients, whereas in most MCS patients, the TEPs are preserved but with abnormal features, which may add valuable information to the current clinical and neurophysiological assessment of chronic consciousness disorders.
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Analysis of facial expressions in parkinson's disease through video-based automatic methods

TL;DR: The results demonstrate that anger and disgust are the two most impaired expressions in PD patients and contactless video-based systems can be important techniques for analyzing facial expressions also in rehabilitation, in particular speech therapy, where patients could get a definite advantage from a real-time feedback about the proper facial expressions/movements to perform.