Principal Investigator Associate Professor of Psychobiology and Physiological Psychology
Viviana Betti is an associate professor of Functional Neuroanatomy and Cognitive Neuroimaging at the Department of Psychology, Sapienza University of Rome. She is the Director of the Cognitive and System neuroscience lab (Cosynclab) based at IRCCS Fondazione Santa Lucia and the Department of Psychology. She is PI of International and national research projects and authors of high impact peer-review publications addressing how cognitive, visual, and motor tasks reorganize the intrinsic connections of the brain. Prof. Betti is also a junior research fellow at the Sapienza School for Advanced Studies (Ssas) and part of the board member of the Italian Society of psychophysiology and cognitive neuroimaging.
Marco is a Physiotherapist with a Ph.D. in Human Movement and Sport Sciences. He has expertise in dynamic balance assessment and treating patients with vestibular and neurological disorders. He is studying the neurophysiological correlates in patients with balance and gait disorders during dynamic tasks. At Cosynclab, he manages the patients’ recruitment for the clinical trials and is the key person for the instrumental evaluation.
Matteo is a Psychologist with a PhD in Neuroscience. He has a background in Virtual Reality (VR) and expertise on embodiment, presence, ownership, and agency. He is now working in combining VR with electrophysiological techniques such as EEG, EMG, and GSR.
Ottavia received her Ph.D. in Psychology, Linguistic and Cognitive Neuroscience from the University of Milano-Bicocca where she specialized in non-invasive brain stimulation techniques (e.g., Transcranial Magnetic Stimulation and Transcranial Direct Current Stimulation) investigating Hebbian-like plasticity mechanisms. At Cosynclab she works with Hd-EEG and MEG data. Her current research aims to investigate how brain architecture during spontaneous activity predicts the topology of task-evoked activity.
Daniele received his master's degree in Biomedical Engineering from the Sapienza University of Roma. His research activity is focused on computational methods of fMRI data analysis to study the human brain function in resting-state. His skills include preprocessing fMRI data, statistical analysis models, univariate and multivariate methods of analysis, brain connectivity, and machine learning. He is able to program in Matlab, Python, and in Unix systems (Bash).
Simona received her master’s degree in Cognitive Neuroscience and Psychological Rehabilitation from the Sapienza University of Rome. She did a traineeship at CosyncLab where she is gaining experience in EEG, fMRI and virtual reality. She has a research grant in Fast Project and she has previous experience with ECG signals in people affected by major depression disorder.
Gabriele received his master's degree in Biomedical Engineering from the Sapienza University of Roma. He is an expert in EEG. He gained his experience working in companies specialising in neuroscience. His skills include preprocessing data and mounting EEG configurations for experiments. He is able to program in Matlab.
Cristina received her master’s degree in Cognitive Neuroscience and Psychological Rehabilitation from the Sapienza University of Roma. She is currently a PhD student in Morphogenesis and Tissue Engineering taking part at the ERC-funded project HANDmade. Her research is focused on resting state Hd-EEG data and MEG functional connectivity.
Teresa received her master’s degree in Clinical Psychology from the University of Padua. She is currently a PhD student in Cognitive, Computational and Social Neurosciencesat the IMT School for Advanced Studies Lucca. Her research focuses on the hand representation in the resting state activity.
Aurelia received her master's degree in Applied Experimental Psychological Sciences from Bicocca University of Milan. She is currently a Phd student in Psychology and Cognitive Sciences at Sapienza. Her research is focused on integration of tactile and motor system, studying behavioral and electrophysiological data.