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Edwin van Dellen

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4 papers

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YNICL Journal 2025 Journal Article

Quantitative electroencephalography characteristics in delirium with various etiologies: A multicenter study

Julia van der A
Robert Fleischmann
Annerose Mengel
Lisette Vernooij
Cornelis Stam
Sophie Leroy
Pauline Schneider
Johannes Ehler

AIM: Delirium is a manifestation of acute encephalopathy, which has a heterogeneous etiology. This study aimed to investigate whether quantitative electroencephalography (qEEG) characteristics of delirium differ among etiology-based delirium subtypes or converge on common neurophysiological patterns. METHODS: In this multicenter observational study, we analyzed qEEG data from 377 patients (173 delirious, 204 non-delirious) consecutively enrolled across three sites. Etiology-based delirium subtypes included post-stroke, medical and postoperative delirium diagnosed by staff physicians based on the Diagnostic and Statistical Manual of Mental Disorders-IV or 5 criteria. We compared peak frequency, relative power, and phase lag index (PLI) between delirious and non-delirious patients across different etiologies using standardized mean differences (SMDs) with 95% confidence intervals (CI). RESULTS: Among spectral qEEG measures, there were no differences between subgroups. The peak frequency showed a consistent decrease between all delirium groups and non-delirious controls (SMD = -0.81, CI:-1.50 to -0.13), relative delta power increased (SMD = 1.44, CI:0.61 to 2.26), and relative beta power decreased (SMD = -1.72, CI:-2.46 to -0.97). Effect sizes differences in PLI between delirious and non-delirious controls were small and not consistent across subtypes. CONCLUSIONS: Our findings demonstrate consistent patterns in spectral qEEG characteristics across delirium subtypes, suggesting a common neurophysiological pathway of global EEG slowing in delirium regardless of etiology. By contrast, differences in PLI did not converge across subtypes. Multicenter studies should harmonize data collection to disentangle the shared and distinct neurophysiological changes associated with delirium of varying etiologies, in order to advance our understanding of potentially convergent mechanisms across subtypes.

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YNICL Journal 2018 Journal Article

Resting-state fMRI reveals network disintegration during delirium

Simone J.T. van Montfort
Edwin van Dellen
Aletta M.R. van den Bosch
Willem M. Otte
Maya J.L. Schutte
Soo-Hee Choi
Tae-Sub Chung
Sunghyon Kyeong

Delirium is characterized by inattention and other cognitive deficits, symptoms that have been associated with disturbed interactions between remote brain regions. Recent EEG studies confirm that disturbed global network topology may underlie the syndrome, but lack an anatomical basis. The aim of this study was to increase our understanding of the global organization of functional connectivity during delirium and to localize possible alterations. Resting-state fMRI data from 44 subjects were analyzed, and motion-free data were available in nine delirious patients, seven post delirium patients and thirteen non-delirious clinical controls. We focused on the functional network backbones using the minimum spanning tree, which allows unbiased network comparisons. During delirium a longer diameter (mean (M) = 0. 30, standard deviation (SD) = 0. 05, P =. 024) and a lower leaf fraction (M = 0. 32, SD = 0. 03, P =. 027) was found compared to the control group (M = 0. 28, SD = 0. 04 respectively M = 0. 35, SD = 0. 03), suggesting reduced functional network integration and efficiency. Delirium duration was strongly related to loss of network hierarchy (rho = −0. 92, P =. 001). Connectivity strength was decreased in the post delirium group (M = 0. 16, SD = 0. 01) compared to the delirium group (M = 0. 17, SD = 0. 03, P =. 024) and the control group (M = 0. 19, SD = 0. 02, P =. 001). Permutation tests revealed a decreased degree of the right posterior cingulate cortex during delirium and complex regional alterations after delirium. These findings indicate that delirium reflects disintegration of functional interactions between remote brain areas and suggest long-term impact after the syndrome resolves.

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YNIMG Journal 2017 Journal Article

Meditation is associated with increased brain network integration

Remko van Lutterveld
Edwin van Dellen
Prasanta Pal
Hua Yang
Cornelis Jan Stam
Judson Brewer

Introduction This study aims to identify novel quantitative EEG measures associated with mindfulness meditation. As there is some evidence that meditation is associated with higher integration of brain networks, we focused on EEG measures of network integration. Methods Sixteen novice meditators and sixteen experienced meditators participated in the study. Novice meditators performed a basic meditation practice that supported effortless awareness, which is an important quality of experience related to mindfulness practices, while their EEG was recorded. Experienced meditators performed a self-selected meditation practice that supported effortless awareness. Network integration was analyzed with maximum betweenness centrality and leaf fraction (which both correlate positively with network integration) as well as with diameter and average eccentricity (which both correlate negatively with network integration), based on a phase-lag index (PLI) and minimum spanning tree (MST) approach. Differences between groups were assessed using repeated-measures ANOVA for the theta (4–8 Hz), alpha (8–13 Hz) and lower beta (13–20 Hz) frequency bands. Results Maximum betweenness centrality was significantly higher in experienced meditators than in novices (P = 0. 012) in the alpha band. In the same frequency band, leaf fraction showed a trend toward being significantly higher in experienced meditators than in novices (P = 0. 056), while diameter and average eccentricity were significantly lower in experienced meditators than in novices (P = 0. 016 and P = 0. 028 respectively). No significant differences between groups were observed for the theta and beta frequency bands. Conclusion These results show that alpha band functional network topology is better integrated in experienced meditators than in novice meditators during meditation. This novel finding provides the rationale to investigate the temporal relation between measures of functional connectivity network integration and meditation quality, for example using neurophenomenology experiments.

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YNIMG Journal 2014 Journal Article

Epilepsy surgery outcome and functional network alterations in longitudinal MEG: A minimum spanning tree analysis

Edwin van Dellen
Linda Douw
Arjan Hillebrand
Philip C. de Witt Hamer
Johannes C. Baayen
Jan J. Heimans
Jaap C. Reijneveld
Cornelis J. Stam

Seizure freedom after resective epilepsy surgery is not obtained in a substantial number of patients with medically intractable epilepsy. Functional neural network analysis is a promising technique for more accurate identification of the target areas for epilepsy surgery, but a better understanding of the correlations between changes in functional network organization due to surgery and postoperative seizure status is required. We explored these correlations in longitudinal magnetoencephalography (MEG) recordings of 20 lesional epilepsy patients. Resting-state MEG recordings were obtained at baseline (preoperatively; T0) and at 3–7 (T1) and 9–15months after resection (T2). We assessed frequency-specific functional connectivity and performed a minimum spanning tree (MST) network analysis. The MST captures the most important connections in the network. We found a significant positive correlation between functional connectivity in the lower alpha band and seizure frequency at T0, especially in regions where lesions were located. MST leaf fraction, a measure of integration of information in the network, was significantly increased between T0 and T2, only for the seizure-free patients. This is in line with previous work, which showed that lower functional network integration in lesional epilepsy patients is related to higher epilepsy burden. Finally, eccentricity and betweenness centrality, which are measures of hub-status, decreased between T0 and T2 in seizure free patients, also in regions that were anatomically close to resection cavities. Our results increase insight into functional network changes in successful epilepsy surgery and might eventually be utilized for optimization of neurosurgical approaches.

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