Long-term online behavioural assessment of patients with cortical network impairment
Caspar Goeke (PI), Tobiasz Kaduk
Online assessment of stroke and PD patients with altered network dynamics and, thus, affected cognitive capacities, enables us to better understand the effects found in the lab and generalize them to the overall population. In particular, each tested patient will conduct an online experimental test battery at several different points in time. This online retest scenario will require latest internet technologies, as we aim to measure reaction time on a millisecond time scale, and also precisely control the visual and auditory display parameters of the stimuli provided. Furthermore, we will re-invite /retest the participants without saving their IP-addresses, but solely by asking them for their email address, which will be stored separately not being connected to other (otherwise pseudonymized) data. Having collected that amount of data, we will apply machine learning approaches aiming to investigate correlations between online test results, patients demographics, and neural data from patients recorded in the groups of Christian Gerloff at UKE and Maurizio Corbetta at UNIPD.