Kim T E Olde Dubbelink

Publications (5)14.81 Total impact

• Source

  Available from: Arjan Hillebrand

  Article: Resting-state functional connectivity as a marker of disease progression in Parkinson's disease: A longitudinal MEG study ☆

  Kim T E Olde Dubbelink, Diederick Stoffers, Jan Berend Deijen, Jos W R Twisk, Cornelis J Stam, Arjan Hillebrand, Henk W Berendse
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  ABSTRACT: The assessment of resting-state functional connectivity has become an important tool in studying brain disease mechanisms. Here we use magnetoencephalography to longitudinally evaluate functional connectiv-ity changes in relation to clinical measures of disease progression in Parkinson's disease (PD). Using a source-space based approach with detailed anatomical mapping, functional connectivity was assessed for temporal, prefrontal and high order sensory association areas known to show neuropathological changes in early clinical disease stages. At baseline, early stage, untreated PD patients (n = 12) had lower parahippocampal and temporal delta band connectivity and higher temporal alpha1 band connectivity compared to controls. Longitudinal analyses over a 4-year period in a larger patient group (n = 43) revealed decreases in alpha1 and alpha2 band connectivity for multiple seed regions that were associated with motor or cognitive deterioration. In the earliest clinical stages of PD, delta and alpha1 band resting-state functional connectivity is altered in temporal cortical regions. With disease progression, a reversal of the initial changes in alpha1 and additional decreases in alpha2 band connectivity evolving in a more widespread cortical pattern. These changes in functional connectivity appear to reflect clinically relevant phenomena and therefore hold promise as a marker of disease progression, with potential predictive value for clinical outcome.
  NeuroImage: Clinical. 04/2013; 2:612-619.
• Article: Complexity Analysis of Resting-State MEG Activity in Early-Stage Parkinson’s Disease Patients

  Carlos Gómez, Kim T. E. Olde Dubbelink, Cornelis J. Stam, Daniel Abásolo, Henk W. Berendse, Roberto Hornero
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  ABSTRACT: The aim of the present study was to analyze resting-state brain activity in patients with Parkinson’s disease (PD), a degenerative disorder of the nervous system. Magnetoencephalography (MEG) signals were recorded with a 151-channel whole-head radial gradiometer MEG system in 18 early-stage untreated PD patients and 20 age-matched control subjects. Artifact-free epochs of 4s (1250 samples) were analyzed with Lempel–Ziv complexity (LZC), applying two- and three-symbol sequence conversion methods. The results showed that MEG signals from PD patients are less complex than control subjects’ recordings. We found significant group differences (p-values <0.01) for the 10 major cortical areas analyzed (e.g., bilateral frontal, central, temporal, parietal, and occipital regions). In addition, using receiver-operating characteristic curves with a leave-one-out cross-validation procedure, a classification accuracy of 81.58% was obtained. In order to investigate the best combination of LZC results for classification purposes, a forward stepwise linear discriminant analysis with leave-one out cross-validation was employed. LZC results (three-symbol sequence conversion) from right parietal and temporal brain regions were automatically selected by the model. With this procedure, an accuracy of 84.21% (77.78% sensitivity, 90.0% specificity) was achieved. Our findings demonstrate the usefulness of LZC to detect an abnormal type of dynamics associated with PD. KeywordsParkinson’s disease–Lempel–Ziv complexity–Magnetoencephalography (MEG)–ROC curves–Linear discriminant analysis
  Annals of Biomedical Engineering 04/2012; 39(12):2935-2944. · 2.37 Impact Factor
• Article: Cognitive decline in Parkinson's disease is associated with slowing of resting-state brain activity: a longitudinal study.

  Kim T E Olde Dubbelink, Diederick Stoffers, Jan Berend Deijen, Jos W R Twisk, Cornelis J Stam, Henk W Berendse
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  ABSTRACT: The pathophysiological mechanisms of Parkinson's disease (PD)-related dementia (PDD) are still poorly understood. Previous studies using electroencephalography (EEG) and magnetoencephalography (MEG) have demonstrated widespread slowing of oscillatory brain activity as a neurophysiological characteristic of PD-related dementia. Here, we use MEG to longitudinally study early changes in oscillatory brain activity in initially nondemented PD patients that may be associated with cognitive decline. Using a longitudinal design, resting-state MEG recordings were performed twice at an approximate 4-year interval in 14 healthy controls and 49 PD patients. Changes in peak frequency and in relative spectral power for 10 brain regions were analyzed in relation to clinical measures of cognitive and motor function. In contrast to healthy controls, PD patients showed a slowing of the dominant peak frequency. Furthermore, analysis per frequency band revealed an increase in theta power over time, along with decreases in alpha1 and alpha2 power. In PD patients, decreasing cognitive performance was associated with increases in delta and theta power, as well as decreases in alpha1, alpha2, and gamma power, whereas increasing motor impairment was associated with a theta power increase only. The present longitudinal study revealed widespread progressive slowing of oscillatory brain activity in initially nondemented PD patients, independent of aging effects. The slowing of oscillatory brain activity strongly correlated with cognitive decline and therefore holds promise as an early marker for the development of dementia in PD.
  Neurobiology of aging 04/2012; · 5.94 Impact Factor
• Article: Complexity analysis of resting-state MEG activity in early-stage Parkinson's disease patients.

  Carlos Gómez, Kim T E Olde Dubbelink, Cornelis J Stam, Daniel Abásolo, Henk W Berendse, Roberto Hornero
  [show abstract] [hide abstract]
  ABSTRACT: The aim of the present study was to analyze resting-state brain activity in patients with Parkinson's disease (PD), a degenerative disorder of the nervous system. Magnetoencephalography (MEG) signals were recorded with a 151-channel whole-head radial gradiometer MEG system in 18 early-stage untreated PD patients and 20 age-matched control subjects. Artifact-free epochs of 4 s (1250 samples) were analyzed with Lempel-Ziv complexity (LZC), applying two- and three-symbol sequence conversion methods. The results showed that MEG signals from PD patients are less complex than control subjects' recordings. We found significant group differences (p-values <0.01) for the 10 major cortical areas analyzed (e.g., bilateral frontal, central, temporal, parietal, and occipital regions). In addition, using receiver-operating characteristic curves with a leave-one-out cross-validation procedure, a classification accuracy of 81.58% was obtained. In order to investigate the best combination of LZC results for classification purposes, a forward stepwise linear discriminant analysis with leave-one out cross-validation was employed. LZC results (three-symbol sequence conversion) from right parietal and temporal brain regions were automatically selected by the model. With this procedure, an accuracy of 84.21% (77.78% sensitivity, 90.0% specificity) was achieved. Our findings demonstrate the usefulness of LZC to detect an abnormal type of dynamics associated with PD.
  Annals of biomedical engineering 12/2011; 39(12):2935-44. · 2.41 Impact Factor
• Source

  Available from: Henk W Berendse

  Article: Increased resting-state functional connectivity in obese adolescents; a magnetoencephalographic pilot study.

  Kim T E Olde Dubbelink, Abraham Felius, Jeroen P A Verbunt, Bob W van Dijk, Henk W Berendse, Cornelis J Stam, Henriette A Delemarre-van de Waal
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  ABSTRACT: Obesity is not only associated with metabolic abnormalities, but also with cognitive dysfunction and changes in the central nervous system. The present pilot study was carried out to investigate functional connectivity in obese and non-obese adolescents using magnetoencephalography (MEG). Magnetoencephalographic recordings were performed in 11 obese (mean BMI 38.8+/-4.6 kg/m(2)) and 8 lean (mean BMI 21.0+/-1.5 kg/m(2)) female adolescents (age 12-19 years) during an eyes-closed resting-state condition. From these recordings, the synchronization likelihood (SL), a common method that estimates both linear and non-linear interdependencies between MEG signals, was calculated within and between brain regions, and within standard frequency bands (delta, theta, alpha1, alpha2, beta and gamma). The obese adolescents had increased synchronization in delta (0.5-4 Hz) and beta (13-30 Hz) frequency bands compared to lean controls (P(delta total) = 0.001; P(beta total) = 0.002). This study identified increased resting-state functional connectivity in severe obese adolescents. Considering the importance of functional coupling between brain areas for cognitive functioning, the present findings strengthen the hypothesis that obesity may have a major impact on human brain function. The cause of the observed excessive synchronization is unknown, but might be related to disturbed motivational pathways, the recently demonstrated increase in white matter volume in obese subjects or altered metabolic processes like hyperinsulinemia. The question arises whether the changes in brain structure and communication are a dynamic process due to weight gain and whether these effects are reversible or not.
  PLoS ONE 02/2008; 3(7):e2827. · 4.09 Impact Factor