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Student Name: Francesco Di Ciò

Institute of Cognitive Neuroscience, Division of Psychology and Language Sciences, Faculty of Brain Science
UBEL Pathway: Psychology
Supervisor: Prof. Antonia F. de C. Hamilton
Contact details: francesco.cio'.20@ucl.ac.uk
Social Media: https://twitter.com/CioFrancesco
About Me:

I’m a Cognitive Neuroscience PhD candidate at the Social Neuroscience Lab. I earned my undergrad degree in Medical Diagnostic Imaging and Radiotherapy from the University of Rome Tor Vergata, and my MRes in Cognitive Neuroscience from UCL. During my academic journey, I completed a
year-long internship in Neuroimaging analysis at Tor Vergata University’s Medical Physics section, where I was also awarded with a six-month research bursary. I am interested in studying verbal and non-verbal behaviours in natural conversations. Beyond academics, I enjoy traveling and learning new languages.

My Research:

My research delves into the neural and computational mechanisms that underlie joint attention during naturalistic conversations. As a part of my PhD program, I will design innovative experimental paradigms aimed at inducing states of joint attention within everyday conversational contexts. These paradigms will be complemented by the use of fNIRS hyperscanning, physiological data and advanced statistical and mathematical modelling techniques. My work will emphasize the development of novel cognitive models to better understand the underlying mechanisms.

 
Impact of My Research:

Joint attention is a fundamental social and cognitive skill that carries significant implications for interpersonal relationships, communication, and cognitive development. My research endeavours to deepen our comprehension of the neural and cognitive mechanisms underpinning joint attention. This understanding will not only shed light on the intricate processes involved but also serve as a valuable tool for probing neural processes in neuroatypical individuals in the future.

I will also work on improving and developing new methods for the integration of multimodal data, encompassing behavioural, physiological, and neural data.