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  • On-line (Sign-up required): 48th CiNet Monthly Seminar: Vincenzo Romei “Enhancing brain connectivity and testing its functional significance through manipulation of Hebbian-like plasticity of targeted networks”

On-line (Sign-up required): 48th CiNet Monthly Seminar: Vincenzo Romei “Enhancing brain connectivity and testing its functional significance through manipulation of Hebbian-like plasticity of targeted networks”

 

CiNet Monthly Seminar

December 17, 2020
16:00-18:00
(On-line)
Apply for participation from here.
You will be notified of participation details by e-mail on Dec. 16.

“Enhancing brain connectivity and testing its functional significance through manipulation of Hebbian-like plasticity of targeted networks”

Vincenzo Romei
Associate Professor
University of Bologna

Host : Masamichi Hayashi (Amano G)

Abstract:
In this talk I will introduce a novel neurostimulation protocol, namelycortico-cortical Paired Associative Stimulation (ccPAS). It uses repeated paired-pulses of Transcranial Magnetic Stimulation (TMS) of multiple sites at critical temporal delays to induce Hebbian-like plasticity of targeted networks. It can lead to enhanced functional connectivity, ultimately driving specific cognitive functions. Here I will present a set of experiments showing how, for example, ccPAS to the V5-to-V1 network enhances sensitivity to coherent motion perception and how it is possible to implement functional specificity of this network in a state-dependent manner. Moreover, I will show that ccPAS to the IPS-to-V1 network boosts the level of perceived confidence to coherent motion perception, without impacting coherent motion sensitivity per se, thus dissociating functional networks controlling for perceptual confidence vs. perceptual accuracy. Finally, I will show that it is possible to implement oscillatory-informed ccPAS protocols to modulate oscillatory properties of functional connections shaping both behavioural outcome and EEG oscillatory activity in expected directions during a visuo-spatial working memory task.