Biology subjects

Marecek, R.

Publications and source records attributed to Marecek, R..

3 recordsLinked to original sources

bioRxiv2026

Resting-state EEG alpha-BOLD coupling spatially follows cortical cell-type and receptor gradients

The coupling between electroencephalography (EEG) and blood-oxygen-level-dependent (BOLD) signals has been investigated across numerous studies, but its neurobiological underpinnings remain poorly understood. Resting-state EEG alpha-BOLD coupling follows a characteristic spatial pattern, shifting from negative correlations in sensory regions to positive correlations in association cortices. In this study, we examined neurobiological correlates of resting-state alpha-BOLD coupling. We compared the spatial pattern of the alpha-BOLD coupling map to 82 cortical feature maps, including gene expression profiles of different cell types and receptor subunits as well as structural MRI measures. We identified three statistically significant (q < 0.05 FDR-corrected) maps: the layer 6 VIP interneuron marker, excitatory layer-5 marker, and NMDA receptor subunit GRIN2C. The three significant gene maps, combined in a multiple linear regression model, explained R2 = 0.312 of the spatial variance in alpha-BOLD coupling. Analysis of the spatial mismatch between cortical maps and the alpha-BOLD coupling map revealed that the early auditory cortex is the region that consistently diverges from predictions across gene expression and T1/T2 maps. The spatial correspondence between alpha-BOLD coupling and gene expression profiles of specific receptor subunits, neuronal types, and layer-specific populations identifies these as concrete candidates for future computational and experimental studies of alpha-BOLD coupling. Author SummaryThe brains electrical rhythms and metabolic activity are coupled, yet why this coupling differs across brain regions remains poorly understood. This study shows that resting-state alpha-BOLD coupling, a well-established link between EEG alpha oscillations and fMRI signals, maps onto the brains cellular landscape: regions enriched in specific inhibitory interneurons and NMDA receptor subunits show systematically different coupling strengths. These findings suggest that regional differences in cell-type composition and receptor expression, rather than purely anatomical features, could shape the spatial organization of alpha-BOLD coupling. By identifying candidate cortical features, this work can guide future experimental and computational studies, ultimately helping to establish alpha-BOLD coupling as a relevant biomarker for psychiatric and neurological disorders.

neuroscience↗

bioRxiv2024

Spatial (Mis)match Between EEG and fMRI Signal Patterns Revealed by Spatio-Spectral Source-Space EEG Decomposition

In this work, we aimed to directly compare and integrate EEG whole-brain patterns of neural dynamics with concurrently measured fMRI BOLD data. For that purpose, we set out to derive EEG patterns based on a spatio-spectral decomposition of band-limited EEG power in the source-reconstructed space. On a large data set of 72 subjects resting-state hdEEG-fMRI we showed that the proposed approach is reliable both in terms of the extracted patterns as well as their spatial BOLD signatures. The five most robust EEG spatio-spectral patterns include, but go beyond, the well-known occipital alpha power dynamics. The EEG spatial-spectral patterns show relatively weak, yet statistically significant spatial similarity to their fMRI BOLD signatures, particularly the patterns that show stronger temporal synchronization with BOLD. However, we observed an insignificant relation between the temporal synchronization and spatial overlap of the EEG spatio-spectral patterns and the classical fMRI BOLD resting state networks (as obtained by independent component analysis). This provides evidence that both EEG (frequency-specific) power and BOLD signal capture reproducible spatiotemporal patterns of neural dynamics. Rather than being mutually redundant, these are only partially overlapping, carrying to a large extent complementary information concerning the underlying low-frequency dynamics. Finally, we report and interpret the most stable source space EEG-fMRI patterns, along with the corresponding EEG electrode space patterns better known from the literature.

neuroscience↗

bioRxiv2024

Cortical evidence accumulation for perceptual experience occurs irrespective of reports

Perceptual experience is a multi-faceted, dynamical process, tackled empirically through measures of stimulus detectability and confidence. To assess if stimulus detection and confidence can be explained by evidence accumulation, a form of sequential sampling of sensory evidence, we analyzed high-gamma activity from stereo-electroencephalographic data of 29 participants partaking in 3 pre-registered experiments. In an immediate-response experiment, individual channels and decoded multivariate latent variables in the visual, inferior frontal, and anterior insular cortices displayed functional markers of evidence accumulation. In two further experiments, this signal in the ventral visual cortex differentiated between (1) seen and unseen stimuli in delayed detection, (2) high and low intensity stimuli during passive viewing, and (3) levels of confidence when stimuli were seen. A computational model of leaky evidence accumulation successfully reproduced both behavioral and neural data. Overall, these results indicate that evidence accumulation explains key aspects of perceptual experience, encompassing both conscious access and monitoring.

neuroscience↗