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Elshahabi, A.

Publications and source records attributed to Elshahabi, A..

2 recordsLinked to original sources

Linking neuronal and hemodynamic network signatures in the resting human brain

Despite several studies investigating the relationship between blood-oxygen-level-dependent functional MRI (BOLD-fMRI) and neuroelectric activity, our understanding is rather incomplete. For instance, the canonical hemodynamic response function (HRF) is commonly used, regardless of brain region, frequency of electric activity and functional networks. We studied this relationship between BOLD-fMRI and electroencephalography (EEG) signal of the human brain in detail using simultaneous fMRI and EEG in healthy awake human subjects at rest. Signals from EEG sensors were filtered into different frequency bands and reconstructed it in the three-dimensional source space. The correlation of the time courses of the two modalities were quantified on a voxel-by-voxel basis on full-brain level as well as separately for each resting state network, with different temporal shifts and EEG frequency bands. We found highly significant correlations between the BOLD-fMRI signal and simultaneously measured EEG, yet with varying time-lags for different frequency bands and different resting state networks. Additionally, we found significant negative correlations with a much longer delay in the fMRI BOLD signal. The positive correlations were mostly around 6-8 seconds delayed in the BOLD time course while the negative correlations were noticed with a BOLD delay of around 20 to 26 seconds. These positive and negative correlation patterns included the commonly reported alpha and gamma bands but also extend in other frequency bands giving characteristic profiles for different resting state networks. Our results confirm recent works that suggest that the relationship between the two modalities is rather brain region / network-specific than a global function and suggest that applying a global canonical HRF for electrophysiological data is probably insufficient to account for the different spatial and temporal dynamics of different brain networks. Moreover, our results suggest that the HRF also varies in different frequency bands giving way to further studies investigating cross-frequency coupling and its interplay with resting state networks.

neuroscience↗

Functional dynamics underlying near-threshold perception of facial emotions: a magnetoencephalography investigation.

Conscious perception of emotional valence of faces has been proposed to involve top-down and bottom-up information processing. Yet, the underlying neuronal mechanisms of these two processes and the implementation of their cooperation is still unclear. We hypothesized that the networks activated during the interaction of top-down and bottom-up processes are the key substrates responsible for perception. We assessed the participation of neural networks involved in conscious perception of emotional stimuli near the perceptual threshold using a visual-backward-masking paradigm in 12 healthy individuals using magnetoencephalography. Providing visual stimulation near the perceptual threshold enabled us to compare correctly and incorrectly recognized facial emotions and assess differences in top-down modulation for these stimuli using coherence analysis. We found a fronto-parietal network oscillating in the lower gamma band and exerting top-down control as determined by the causality measure of phase slope index. We demonstrated that correct recognition of facial emotions involved high-beta and low-gamma activity in parietal networks, Incorrect recognition was associated with enhanced coupling in the gamma band between left frontal and right parietal regions. Our results indicate that fronto-parietal control of the perception of emotional face stimuli relies on the right-hemispheric dominance of synchronized gamma band activity.

neuroscience↗