Search

Resting-state connectivity has been widely studied in the healthy and pathological brain. Less well-characterized are the brain networks altered during pharmacological interventions and their possible interaction with vigilance. In the hopes of finding new biomarkers which can be used to identify cortical activity and cognitive processes linked to the effects of drugs to treat neurodegenerative diseases such as Alzheimer's disease, the analysis of networks altered by medication would be particularly interesting. Eleven healthy subjects were recruited in the context of the European Innovative Medicines Initiative 'PharmaCog'. Each underwent five sessions of simultaneous EEG-fMRI in order to investigate the effects of donepezil and memantine before and after sleep deprivation (SD). The SD approach has been previously proposed as a model for cognitive impairment in healthy subjects. By applying network based statistics (NBS), we observed altered brain networks significantly linked to donepezil intake and sleep deprivation. Taking into account the sleep stages extracted from the EEG data we revealed that a network linked to sleep is interacting with sleep deprivation but not with medication intake. We successfully extracted the functional resting-state networks modified by donepezil intake, sleep and SD. We observed donepezil induced whole brain connectivity alterations forming a network separated from the changes induced by sleep and SD, a result which shows the utility of this approach to check for the validity of pharmacological resting-state analysis of the tested medications without the need of taking into account the subject specific vigilance.

For the first time in research in humans, we used simultaneous icEEG-fMRI to examine the link between connectivity in haemodynamic signals during the resting-state (rs) and connectivity derived from electrophysiological activity in terms of the inter-modal connectivity correlation (IMCC). We quantified IMCC in nine patients with drug-resistant epilepsy (i) within brain networks in 'healthy' non-involved cortical zones (NIZ) and (ii) within brain networks involved in generating seizures and interictal spikes (IZ1) or solely spikes (IZ2). Functional connectivity (h 2 ) estimates for 10 min of resting-state data were obtained between each pair of electrodes within each clinical zone for both icEEG and fMRI. A sliding window approach allowed us to quantify the variability over time of h 2 (vh 2 ) as an indicator of connectivity dynamics. We observe significant positive IMCC for h 2 and vh 2 , for multiple bands in the NIZ only, with the strongest effect in the lower icEEG frequencies. Similarly, intra-modal h 2 and vh 2 were found to be differently modified as a function of different epileptic processes: compared to NIZ, [Formula: see text] was higher in IZ1, but lower in IZ2, while [Formula: see text] showed the inverse pattern. This corroborates previous observations of inter-modal connectivity discrepancies in pathological cortices, while providing the first direct invasive and simultaneous comparison in humans. We also studied time-resolved FC variability multimodally for the first time, finding that IZ1 shows both elevated internal [Formula: see text] and less rich dynamical variability, suggesting that its chronic role in epileptogenesis may be linked to greater homogeneity in self-sustaining pathological oscillatory states.