C J Stam

Publications of C J Stam

• Disrupted modular brain dynamics reflect cognitive dysfunction in Alzheimer's disease.

  Authors: W de Haan, W M van der Flier, T Koene, L L Smits, P Scheltens, C J Stam

  NeuroImage. 11/2011; 59(4):3085-93.

  The relation between pathology and cognitive dysfunction in dementia is still poorly understood, although disturbed communication between different brain regions is almost certainly involved. In thisThe relation between pathology and cognitive dysfunction in dementia is still poorly understood, although disturbed communication between different brain regions is almost certainly involved. In this study we combine magneto-encephalography (MEG) and network analysis to investigate the role of functional sub-networks (modules) in the brain with regard to cognitive failure in Alzheimer's disease. Whole-head resting-state (MEG) was performed in 18 Alzheimer patients (age 67±9, 6 females, MMSE 23±5) and 18 healthy controls (age 66±9, 11 females, MMSE 29±1). We constructed functional brain networks based on interregional synchronization measurements, and performed graph theoretical analysis with a focus on modular organization. The overall modular strength and the number of modules changed significantly in Alzheimer patients. The parietal cortex was the most highly connected network area, but showed the strongest intramodular losses. Nonetheless, weakening of intermodular connectivity was even more outspoken, and more strongly related to cognitive impairment. The results of this study demonstrate that particularly the loss of communication between different functional brain regions reflects cognitive decline in Alzheimer's disease. These findings imply the relevance of regarding dementia as a functional network disorder.

• Cognition is related to resting-state small-world network topology: an magnetoencephalographic study.

  Authors: L Douw, M M Schoonheim, D Landi, M L van der Meer, J J G Geurts, J C Reijneveld, M Klein, C J Stam

  Neuroscience. 02/2011; 175:169-77.

  Brain networks and cognition have recently begun to attract attention: studies suggest that more efficiently wired resting-state brain networks are indeed correlated with better cognitiveBrain networks and cognition have recently begun to attract attention: studies suggest that more efficiently wired resting-state brain networks are indeed correlated with better cognitive performance. "Small-world" brain networks combine local segregation with global integration, hereby subserving information processing. Furthermore, recent studies implicate that gender effects may be present in both network dynamics and its correlations with cognition. This study reports on the relation between resting-state functional brain topology with overall and domain-specific cognitive performance in healthy participants and possible gender differences herein. Healthy participants underwent neuropsychological tests, of which individual scores were converted to z-scores. Network analysis was performed on resting-state, eyes-closed magnetoencephalography (MEG) data, after determining functional connectivity between each pair of sensors. The clustering coefficient (local specialization), average path length (overall integration and efficiency) and "small-world index" (i.e. ratio between clustering and path length) were calculated in six frequency bands. 14 male and 14 female participants were included. Better total cognitive performance was related to increased local connectivity in the theta band, higher clustering coefficient (in delta and theta bands) and higher small-worldness (in theta and lower gamma bands). Women showed less clustering and shorter path length in the delta band. There were no significant correlations between network topology and cognitive functioning in females. In contrast, higher cognitive scores in men were associated with increased theta band clustering and small-worldness. These results provide further evidence for the value of functional brain network topology for cognitive functioning and suggest that gender is an important factor in this respect.

• Feasibility of online seizure detection with continuous EEG monitoring in the intensive care unit.

  Authors: S C Ponten, H E Ronner, R L M Strijers, M C Visser, S M Peerdeman, W P Vandertop, A Beishuizen, A R J Girbes, C J Stam

  Seizure : the journal of the British Epilepsy Association. 09/2010; 19(9):580-6.

  Continuous EEG (cEEG) is of great interest in view of the reported high prevalence of non-convulsive seizures on intensive care units (ICUs). Here, we describe our experiences applying a seizureContinuous EEG (cEEG) is of great interest in view of the reported high prevalence of non-convulsive seizures on intensive care units (ICUs). Here, we describe our experiences applying a seizure warning system using cEEG monitoring. Fifty comatose ICU patients were included prospectively and monitored. Twenty-eight patients had post-anoxic encephalopathy (PAE) and 22 had focal brain lesions. A measure of neuronal interactions, synchronization likelihood, was calculated online over 10s EEG epochs and instances when the synchronization likelihood exceeded a threshold where marked as seizures. Five patients developed seizures. Our method detected seizures in three patients, in the other patients seizures were missed because of they were non-convulsive and had a focal character. The average false positive rate was 0.676/h. This is our first attempt to implement online seizure detection in the ICU. Despite problems with artifacts and that we missed focally oriented seizures, we succeeded in monitoring patients online. Given the relatively high occurrence of seizures, online seizure detection with cEEG merits further development for use in ICUs.

• Characterization of anatomical and functional connectivity in the brain: a complex networks perspective.

  Authors: C J Stam

  International journal of psychophysiology : official journal of the International Organization of Psychophysiology. 09/2010; 77(3):186-94.

  A central question in modern neuroscience is how anatomical and functional connections between brain areas are organized to allow optimal information processing. In particular, both segregation andA central question in modern neuroscience is how anatomical and functional connections between brain areas are organized to allow optimal information processing. In particular, both segregation and integration of information have to be dealt with in a single architecture of brain networks. There is strong evidence that synchronization of neural activity, both locally and between distant regions is a crucial code for functional interactions. However, a powerful theoretical framework to describe the structural and functional topology of system-wide brain networks has only become available with the discovery of 'small-world' and 'scale-free' networks in 1998 and 1999. There is now strong evidence that brain networks, ranging from simple nets of interconnected neurons up to macroscopic networks of brain areas display the typical features of complex systems: high clustering, short path lengths (both typical of 'small-world' networks), skewed degree distributions, presence of hubs, assortative mixing and the presence of modules. This has been demonstrated for anatomical and functional networks using neuroanatomical techniques, EEG, MEG and structural and functional MRI, in organisms ranging from C. elegans to man. In addition, network topology has been shown to be highly heritable, and very predictive of cognitive functioning. A short path length, which implies that from any area in the brain any other area can be reached in a small number of steps, is strongly correlated with IQ. Computational models are now beginning to reveal how the complex structure of adult brain networks could arise during development.

• Effect of tumor resection on the characteristics of functional brain networks.

  Authors: H Wang, L Douw, J M Hernández, J C Reijneveld, C J Stam, P Van Mieghem

  Physical review. E, Statistical, nonlinear, and soft matter physics. 08/2010; 82(2 Pt 1):021924.

  Brain functioning such as cognitive performance depends on the functional interactions between brain areas, namely, the functional brain networks. The functional brain networks of a group of patientsBrain functioning such as cognitive performance depends on the functional interactions between brain areas, namely, the functional brain networks. The functional brain networks of a group of patients with brain tumors are measured before and after tumor resection. In this work, we perform a weighted network analysis to understand the effect of neurosurgery on the characteristics of functional brain networks. Statistically significant changes in network features have been discovered in the beta (13-30 Hz) band after neurosurgery: the link weight correlation around nodes and within triangles increases which implies improvement in local efficiency of information transfer and robustness; the clustering of high link weights in a subgraph becomes stronger, which enhances the global transport capability; and the decrease in the synchronization or virus spreading threshold, revealed by the increase in the largest eigenvalue of the adjacency matrix, which suggests again the improvement of information dissemination.

• Use of magnetoencephalography (MEG) to study functional brain networks in neurodegenerative disorders.

  Authors: C J Stam

  Journal of the neurological sciences. 10/2009;

  The pathophysiological mechanisms underlying clinical symptoms in neurodegenerative disorders such as Parkinson's disease (PD) and Alzheimer's disease (AD) are incompletely understood.The pathophysiological mechanisms underlying clinical symptoms in neurodegenerative disorders such as Parkinson's disease (PD) and Alzheimer's disease (AD) are incompletely understood. Magnetoencephalography (MEG) is a relatively new functional neuroimaging technique, which allows the simultaneous recording of the brain's magnetic activity from large arrays of sensors covering the whole head. MEG studies in PD and AD have identified characteristic patterns of abnormal oscillatory activity in different frequency bands. Furthermore, MEG studies aimed at the characterization of distributed functional networks have demonstrated distinct patterns of abnormal connectivity in demented and non-demented PD, as well as in AD. In PD abnormal oscillatory activity and disturbed connectivity may respond differently to dopaminergic treatment. Further studies in this field could benefit from new technological developments such as ultra low field MRI and from the application of a well-defined theoretical framework such as graph theory to the study of disturbed brain networks.

• The relationship between structural and functional connectivity: Graph theoretical analysis of an EEG neural mass model.

  Authors: S C Ponten, A Daffertshofer, A Hillebrand, C J Stam

  NeuroImage. 10/2009;

  We investigated the relationship between structural network properties and both synchronization strength and functional characteristics in a combined neural mass and graph theoretical model of theWe investigated the relationship between structural network properties and both synchronization strength and functional characteristics in a combined neural mass and graph theoretical model of the electroencephalogram (EEG). Thirty-two neural mass models (NMMs), each representing the lump activity of reasonably large groups of interacting excitatory and inhibitory neurons, were reciprocally and excitatory coupled using random rewiring as described by Watts and Strogatz. Numerical analysis of the network revealed an abrupt transition towards a synchronized state as a function of increasing coupling strength alpha. Synchronization increased with increasing degree and decreasing regularity of the network. Parameters of the functional network showed a diverse dependency on structural connectivity: normalized clustering coefficient gamma and path length lambda increased with increasing alpha. For sufficiently large alpha, however, gamma decreased with increasing rewiring probability p, while lambda increased. Hence, a structured functional network exists despite the randomness of the underlying structural network. That is, patterns of functional connectivity are influenced by patterns of the corresponding structural level but do not necessarily agree with those.

• Cholinergic modulation of MEG resting-state oscillatory activity in Parkinson's disease related dementia.

  Authors: J L W Bosboom, D Stoffers, C J Stam, H W Berendse, E Ch Wolters

  Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology. 05/2009;

  OBJECTIVE: EEG and MEG studies in Parkinson's disease (PD) related dementia (PDD) have shown a slowing of resting-state, oscillatory activity compared to non demented PD. Aim of the present MEG studyOBJECTIVE: EEG and MEG studies in Parkinson's disease (PD) related dementia (PDD) have shown a slowing of resting-state, oscillatory activity compared to non demented PD. Aim of the present MEG study was to determine whether treatment with the cholinesterase inhibitor rivastigmine would reverse this slowing of resting-state activity in PDD patients. METHODS: In eight PDD patients, whole head MEG was recorded in a resting-state condition before and after treatment with rivastigmine. Relative spectral power was calculated in the delta, theta, alpha, beta and gamma frequency bands in fronto-central, parieto-occipital and temporal regions. RESULTS: After treatment with rivastigmine, PDD patients demonstrated an increase in relative power in the alpha range in parieto-occipital and temporal regions together with a diffuse increase in beta power. Furthermore, a decrease of delta power in fronto-central and parieto-occipital regions was found. CONCLUSIONS: Treatment with the cholinesterase inhibitor rivastigmine at least partly counteracts the slowing of resting-state brain activity that is known to occur in PD related dementia. SIGNIFICANCE: Our observations emphasize the prominent role of degeneration of the cholinergic system in the pathophysiology of dementia in PD. In the future, MEG might contribute to the selection of PD patients who may optimally benefit from cholinergic treatment.

• Indications for network regularization during absence seizures: Weighted and unweighted graph theoretical analysis.

  Authors: S C Ponten, L Douw, F Bartolomei, J C Reijneveld, C J Stam

  Experimental neurology. 03/2009;

  Previous studies with intracranial recordings suggested that a more random spatial structure of functional brain networks could be related to seizure generation. Here, we studied whether similarPrevious studies with intracranial recordings suggested that a more random spatial structure of functional brain networks could be related to seizure generation. Here, we studied whether similar network changes in weighted and unweighted networks can be found in generalized absence seizures recorded with surface EEG. We retrospectively selected EEG recordings of eleven children with absence seizures. The functional neural networks were characterized by calculating both coherence and synchronization likelihood (SL) between 21 EEG signals that were either broad band filtered (1-48 Hz) or filtered in different frequency bands. From both weighted and unweighted networks the clustering coefficient (C) and path length (L) were computed and compared to 500 random networks. We compared the ictal with the pre-ictal network structure. During absence seizures there was an increase of synchronization in all frequency bands, seen most clearly in the SL-based networks, and the functional network topology changed towards a more ordered pattern, with an increase of C/C-s and L/L-s. This study supports the hypothesis of functional neural network changes during absence seizures. The network became more regularized in weighted and unweighted analyses, when compared to the more randomized pre-ictal network configuration.

• Associations between Patterns of EEG Abnormalities and Diagnosis in a Large Memory Clinic Cohort.

  Authors: M Liedorp, W M van der Flier, E L J Hoogervorst, P Scheltens, C J Stam

  Dementia and geriatric cognitive disorders. 01/2009; 27(1):18-23.

  Aim: To describe associations of abnormalities in the electroencephalogram (EEG) with the most prevalent diagnoses in a memory clinic cohort. Methods: Associations between visual EEG findings andAim: To describe associations of abnormalities in the electroencephalogram (EEG) with the most prevalent diagnoses in a memory clinic cohort. Methods: Associations between visual EEG findings and diagnoses in 1,116 consecutive patients [382 Alzheimer's disease (AD), 274 subjective complaints, 190 mild cognitive impairment (MCI), 118 psychiatric disorder, 61 frontotemporal lobar degeneration, 53 vascular dementia (VaD), 38 dementia with Lewy bodies (DLB)] were determined by prevalence ratio (PR). Results: Diagnoses of subjective complaints [PR = 1.6; 95% confidence interval (CI) = 1.4-1.9] and psychiatric disorder (1.4; 95% CI = 1.1-1.9) were associated with a normal EEG, while subjects with both focal and diffuse EEG disturbances were more likely to have DLB (3.5; 95% CI = 2.1-5.6), VaD (2.3; 95% CI = 1.4-3.6) or AD (1.5; 95% CI = 1.3-1.8). Subjects with only diffuse EEG abnormalities were more likely to have AD (PR = 1.5; 95% CI = 1.3-1.9). The prevalence of MCI was higher among those with only focal EEG abnormalities (PR = 1.3; 95% CI = 1.0-1.7). Conclusions: A normal EEG argues for subjective complaints or psychiatric diagnosis. An EEG with only focal abnormalities supports MCI. An EEG with only diffuse abnormalities argues for AD. An EEG with both focal and diffuse abnormalities argues for DLB, VaD or AD.

• Inter-observer variability of the EEG diagnosis of seizures in comatose patients.

  Authors: H E Ronner, S C Ponten, C J Stam, B M J Uitdehaag

  Seizure : the journal of the British Epilepsy Association. 12/2008;

  OBJECTIVE: To assess the inter-observer agreement of the electroencephalogram (EEG) diagnosis of (non-convulsive) seizures in comatose patients. DESIGN/SETTING/PATIENTS: Nine clinicians withOBJECTIVE: To assess the inter-observer agreement of the electroencephalogram (EEG) diagnosis of (non-convulsive) seizures in comatose patients. DESIGN/SETTING/PATIENTS: Nine clinicians with different levels of experience in clinical neurophysiology were asked to evaluate in a strictly controlled way 90 epochs (10s each) of 30 EEG's of 23 comatose patients admitted to the intensive care unit (ICU). For each EEG clinicians had to decide whether there was an electrographic seizure or not. Furthermore, Young's EEG criteria for (non-convulsive) seizures were scored in detail for all EEG's. Agreement was determined by calculating kappa values. RESULTS: The inter-observer agreement of an EEG diagnosis of seizure was limited. The overall kappa score for the five experienced raters was 0.5, and the kappa score for less experienced raters was 0.29. Kappa values for the individual Young's criteria were highly variable, indicating discrepancies in the interpretation of specific phenomena. Especially, some types of periodic discharges gave rise to different interpretations. CONCLUSIONS: The EEG diagnosis of (non-convulsive) seizures in ICU patients is not very reliable, even when strict criteria such as proposed by Young are applied. There is a need for less ambiguous EEG criteria for (non-convulsive) seizures and status epilepticus.

• Graph theoretical analysis of magnetoencephalographic functional connectivity in Alzheimer's disease.

  Authors: C J Stam, W de Haan, A Daffertshofer, B F Jones, I Manshanden, A M van Cappellen van Walsum, T Montez, J P A Verbunt, J C de Munck, B W van Dijk, H W Berendse, P Scheltens

  Brain : a journal of neurology. 11/2008;

  In this study we examined changes in the large-scale structure of resting-state brain networks in patients with Alzheimer's disease compared with non-demented controls, using concepts from graphIn this study we examined changes in the large-scale structure of resting-state brain networks in patients with Alzheimer's disease compared with non-demented controls, using concepts from graph theory. Magneto-encephalograms (MEG) were recorded in 18 Alzheimer's disease patients and 18 non-demented control subjects in a no-task, eyes-closed condition. For the main frequency bands, synchronization between all pairs of MEG channels was assessed using a phase lag index (PLI, a synchronization measure insensitive to volume conduction). PLI-weighted connectivity networks were calculated, and characterized by a mean clustering coefficient and path length. Alzheimer's disease patients showed a decrease of mean PLI in the lower alpha and beta band. In the lower alpha band, the clustering coefficient and path length were both decreased in Alzheimer's disease patients. Network changes in the lower alpha band were better explained by a 'Targeted Attack' model than by a 'Random Failure' model. Thus, Alzheimer's disease patients display a loss of resting-state functional connectivity in lower alpha and beta bands even when a measure insensitive to volume conduction effects is used. Moreover, the large-scale structure of lower alpha band functional networks in Alzheimer's disease is more random. The modelling results suggest that highly connected neural network 'hubs' may be especially at risk in Alzheimer's disease.

• Reduced resting-state brain activity in the "default network" in normal aging.

  Authors: J S Damoiseaux, C F Beckmann, E J Sanz Arigita, F Barkhof, Ph Scheltens, C J Stam, S M Smith, S A R B Rombouts

  Cerebral cortex (New York, N.Y. : 1991). 09/2008; 18(8):1856-64.

  Normal aging is associated with cognitive decline. Functions such as attention, information processing, and working memory are compromised. It has been hypothesized that not only regional changes,Normal aging is associated with cognitive decline. Functions such as attention, information processing, and working memory are compromised. It has been hypothesized that not only regional changes, but also alterations in the integration of regional brain activity (functional brain connectivity) underlie the observed age-related deficits. Here, we examined the functional properties of brain networks based on spontaneous fluctuations within brain systems using functional magnetic resonance imaging. We hypothesized that functional connectivity of intrinsic brain activity in the "default-mode" network (DMN) is affected by normal aging and that this relates to cognitive function. Ten younger and 22 older subjects were scanned at "rest," that is, lying awake with eyes closed. Our results show decreased activity in older versus younger subjects in 2 resting-state networks (RSNs) resembling the previously described DMN, containing the superior and middle frontal gyrus, posterior cingulate, middle temporal gyrus, and the superior parietal region. These results remain significant after correction for RSN-specific gray matter volume. The relevance of these findings is illustrated by the correlation between reduced activity of one of these RSNs and less effective executive functioning/processing speed in the older group.

• Increased cortico-cortical functional connectivity in early-stage Parkinson's disease: an MEG study.

  Authors: D Stoffers, J L W Bosboom, J B Deijen, E Ch Wolters, C J Stam, H W Berendse

  NeuroImage. 07/2008; 41(2):212-22.

  We set out to determine whether changes in resting-state cortico-cortical functional connectivity are a feature of early-stage Parkinson's disease (PD), explore how functional coupling might evolveWe set out to determine whether changes in resting-state cortico-cortical functional connectivity are a feature of early-stage Parkinson's disease (PD), explore how functional coupling might evolve over the course of the disease and establish its relationship with clinical deficits. Whole-head magnetoencephalography was performed in an eyes-closed resting-state condition in 70 PD patients with varying disease duration (including 18 recently diagnosed, drug-naive patients) in an "OFF" medication state and 21 controls. Neuropsychological testing was performed in all subjects. Data analysis involved calculation of three synchronization likelihood (SL, a general measure of linear and non-linear temporal correlations between time series) measures which reflect functional connectivity within (local) and between (intrahemispheric and interhemispheric) ten major cortical regions in five frequency bands. Recently diagnosed, drug-naive patients showed an overall increase in alpha1 SL relative to controls. Cross-sectional analysis in all patients revealed that disease duration was positively associated with alpha2 and beta SL measures, while severity of parkinsonism was positively associated with theta and beta SL measures. Moderately advanced patients had increases in theta, alpha1, alpha2 and beta SL, particularly with regard to local SL. In recently diagnosed patients, cognitive perseveration was associated with increased interhemispheric alpha1 SL. Increased resting-state cortico-cortical functional connectivity in the 8-10 Hz alpha range is a feature of PD from the earliest clinical stages onward. With disease progression, neighboring frequency bands become increasingly involved. These findings suggest that changes in functional coupling over the course of PD may be linked to the topographical progression of pathology over the brain.

• The influence of low-grade glioma on resting state oscillatory brain activity: a magnetoencephalography study.

  Authors: I Bosma, C J Stam, L Douw, F Bartolomei, J J Heimans, B W van Dijk, T J Postma, M Klein, J C Reijneveld

  Journal of neuro-oncology. 06/2008; 88(1):77-85.

  PURPOSE: In the present MEG-study, power spectral analysis of oscillatory brain activity was used to compare resting state brain activity in both low-grade glioma (LGG) patients and healthy controls.PURPOSE: In the present MEG-study, power spectral analysis of oscillatory brain activity was used to compare resting state brain activity in both low-grade glioma (LGG) patients and healthy controls. We hypothesized that LGG patients show local as well as diffuse slowing of resting state brain activity compared to healthy controls and that particularly global slowing correlates with neurocognitive dysfunction. PATIENT AND METHODS: Resting state MEG recordings were obtained from 17 LGG patients and 17 age-, sex-, and education-matched healthy controls. Relative spectral power was calculated in the delta, theta, upper and lower alpha, beta, and gamma frequency band. A battery of standardized neurocognitive tests measuring 6 neurocognitive domains was administered. RESULTS: LGG patients showed a slowing of the resting state brain activity when compared to healthy controls. Decrease in relative power was mainly found in the gamma frequency band in the bilateral frontocentral MEG regions, whereas an increase in relative power was found in the theta frequency band in the left parietal region. An increase of the relative power in the theta and lower alpha band correlated with impaired executive functioning, information processing, and working memory. CONCLUSION: LGG patients are characterized by global slowing of their resting state brain activity and this slowing phenomenon correlates with the observed neurocognitive deficits.

• Global dynamical analysis of the EEG in Alzheimer's disease: frequency-specific changes of functional interactions.

  Authors: B Jelles, Ph Scheltens, W M van der Flier, E J Jonkman, F H Lopes da Silva, C J Stam

  Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology. 05/2008; 119(4):837-41.

  OBJECTIVE: EEG coherence is decreased in Alzheimer's disease (AD), suggesting decreased interaction between brain areas. Nonlinear EEG analysis in AD points to decreased complexity of brain dynamics,OBJECTIVE: EEG coherence is decreased in Alzheimer's disease (AD), suggesting decreased interaction between brain areas. Nonlinear EEG analysis in AD points to decreased complexity of brain dynamics, implicating increased interaction. To clarify these apparently paradoxical findings from linear and nonlinear analysis, we calculated global coherence and global correlation dimension (D2), a nonlinear measure, in the EEG of patients with probable AD and controls. Our hypothesis is that these measures are related to each other when calculated in a comparable way. METHODS: From 15 patients with probable AD (mean age 63.1 years; SD 6.3) and 21 age-matched controls with subjective memory complaints (mean age 62.8; SD 12.0), band filtered EEG data were analysed in six frequency bands. For each frequency band average coherence and multichannel D2 were determined. RESULTS: ANOVA for repeated measures showed for D2 an interaction between band and group, but not for coherence. In the beta band and upper alpha band, D2 was higher in patients with probable AD compared to controls, while global coherence tended to be lower in these frequency bands in patients with probable AD. In the frequency range from theta to beta, coherence and D2 were inversely correlated without group differences. CONCLUSIONS: When calculated in comparable ways, global correlation dimension and coherence are related measures. In AD, these measures change especially in the higher frequency ranges, both pointing to decreased functional cortical connectivity. SIGNIFICANCE: Both global coherence and global correlation dimension seem to measure global connectivity, but nonlinear measures may be more sensitive. In AD, connectivity measures are not equally impaired in all frequency ranges, possibly reflecting differentiated affection of the dynamical processes responsible for the different frequency bands.

• The use of EEG in the diagnosis of dementia with Lewy bodies.

  Authors: G Roks, E S C Korf, W M van der Flier, P Scheltens, C J Stam

  Journal of neurology, neurosurgery, and psychiatry. 04/2008; 79(4):377-80.

  Although reports on EEG in dementia with Lewy bodies (DLB) are conflicting, the recent diagnostic guidelines define EEG abnormalities as being supportive for the diagnosis. We examined EEGAlthough reports on EEG in dementia with Lewy bodies (DLB) are conflicting, the recent diagnostic guidelines define EEG abnormalities as being supportive for the diagnosis. We examined EEG abnormalities in 18 patients with DLB, 34 patients with Alzheimer's disease (AD) and 36 patients with subjective memory complaints (SMC) using the Grand Total EEG (GTE) score. There was a difference in median GTE score of DLB (11.0), AD (4.8) and SMC (2.5) (p<0.001). Patients with DLB had higher scores than patients with AD. ROC analyses revealed that patients with DLB could be distinguished from those with AD with a sensitivity of 72% and a specificity of 85% at a GTE cut-off of 9.5. The association between GTE and DLB was independent of age, gender, Mini Mental State Examination and medication use. Frontal intermittent rhythmic delta activity (FIRDA) was found in 2.9% of the patients with AD and in 33.3% of the patients with DLB. The GTE is a simple EEG scoring method that can be helpful in the differential diagnosis between DLB and AD with good sensitivity and specificity.

• Slowing of oscillatory brain activity is a stable characteristic of Parkinson's disease without dementia.

  Authors: D Stoffers, J L W Bosboom, J B Deijen, E C Wolters, H W Berendse, C J Stam

  Brain : a journal of neurology. 08/2007; 130(Pt 7):1847-60.

  Extensive changes in resting-state oscillatory brain activity have recently been demonstrated using magnetoencephalography (MEG) in moderately advanced, non-demented Parkinson's disease patientsExtensive changes in resting-state oscillatory brain activity have recently been demonstrated using magnetoencephalography (MEG) in moderately advanced, non-demented Parkinson's disease patients relative to age-matched controls. The aim of the present study was to determine the onset and evolution of these changes over the disease course and their relationship with clinical parameters. In addition, we evaluated the effects of dopaminomimetics on resting-state oscillatory brain activity in levodopa-treated patients. MEG background oscillatory activity was studied in a group of 70 Parkinson's disease patients with varying disease duration and severity (including 18 de novo patients) as well as in 21 controls that were age-matched to the de novo patients. Whole head 151-channel MEG recordings were obtained in an eyes-closed resting-state condition. Levodopa-treated patients (N = 37) were examined both in a practically defined 'OFF' as well as in the 'ON' state. Relative spectral power was calculated for delta, theta, low alpha, high alpha, beta and gamma frequency bands and averaged for 10 cortical regions of interest (ROIs). Additionally, extensive clinical and neuropsychological testing was performed in all subjects. De novo Parkinson's disease patients showed widespread slowing of background MEG activity relative to controls. Changes included a widespread increase in theta and low alpha power, as well as a loss of beta power over all but the frontal ROIs and a loss of gamma power over all but the right occipital ROI. Neuropsychological assessment revealed abnormal perseveration in de novo patients, which was associated with increased low alpha power in centroparietal ROIs. In the whole group of Parkinson's disease patients, longer disease duration was associated with reduced low alpha power in the right temporal and right occipital ROI, but not with any other spectral power measure. No association was found between spectral power and disease stage, disease severity or dose of dopaminomimetics. In patients on levodopa therapy, a change from the 'OFF' to the 'ON' state was associated with decreases in right frontal theta, left occipital beta and left temporal gamma power and an increase in right parietal gamma power. Widespread slowing of oscillatory brain activity is a characteristic of non-demented Parkinson's disease patients from the earliest clinical stages onwards that is (largely) independent of disease duration, stage and severity and hardly influenced by dopaminomimetic treatment. Some early cognitive deficits in Parkinson's disease appear to be associated with increased low alpha power. We postulate a role for hypofunctional non-dopaminergic ascending neurotransmitter systems in spectral power changes in non-demented Parkinson's disease patients.

• Motor evoked potential: a reliable and objective measure to document the functional consequences of multiple sclerosis? Relation to disability and MRI.

  Authors: N F Kalkers, R L M Strijers, M M S Jasperse, V Neacsu, J J G Geurts, F Barkhof, C H Polman, C J Stam

  Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology. 06/2007; 118(6):1332-40.

  In an attempt to analyze whether MEP can serve as a valid measure for evaluating neurological dysfunction in multiple sclerosis (MS), we related MEP to clinical and MRI measures. TranscranialIn an attempt to analyze whether MEP can serve as a valid measure for evaluating neurological dysfunction in multiple sclerosis (MS), we related MEP to clinical and MRI measures. Transcranial magnetic stimulation was applied in 52 MS patients to determine the central motor conduction time (CMCT) to the extremities. We calculated Z-scores for each CMCT (Zcmct) corrected for height. All patients underwent two clinical measurements and a MRI scan, of which T1 and T2 brain lesion volumes, brain volume, spinal cord volume and the number of T2 spinal cord lesions were derived. The clinical measurements correlated significantly with various Zcmct (Spearman correlation coefficients ranged from 0.29 to 0.53; p<0.05). The number of spinal cord lesions, brain T1 and T2 lesion volume and spinal cord volume correlated with various Zcmct (r=0.31-0.53; p<0.05). Linear regression analysis revealed that the clinical measurements were explained by Zcmct left leg and T1 lesion volume (adjusted R(2)=0.38). For one clinical measurement the number of spinal cord lesions was also included (adjusted R(2)=0.43). We found a relation between MEP, brain and spinal cord MRI measures, and two clinical measures. Moreover, a model for explaining disability in MS revealed that MEP measures provide information in addition to MRI measures. This study suggests that MEP is a measure that might adequately reflect pathology and neurological dysfunction in MS.

• Small-world networks and epilepsy: graph theoretical analysis of intracerebrally recorded mesial temporal lobe seizures.

  Authors: S C Ponten, F Bartolomei, C J Stam

  Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology. 05/2007; 118(4):918-27.

  OBJECTIVE: Neuronal networks with a so-called "small-world" topography (characterized by strong clustering in combination with short path lengths) are known to facilitate synchronization, andOBJECTIVE: Neuronal networks with a so-called "small-world" topography (characterized by strong clustering in combination with short path lengths) are known to facilitate synchronization, and possibly seizure generation. We tested the hypothesis that real functional brain networks during seizures display small-world features, using intracerebral recordings of mesial temporal lobe seizures. METHODS: We used synchronization likelihood (SL) to characterize synchronization patterns in intracerebral EEG recordings of 7 patients for 5 periods of interest: interictal, before-, during- and after rapid discharges (in which the last two periods are ictal) and postictal. For each period, graphs (abstract network representations) were reconstructed from the synchronization matrix and characterized by a clustering coefficient C (measure of local connectedness) and a shortest path length L (measure of overall network integration). Results were also compared with those obtained from random networks. RESULTS: The neuronal network changed during seizure activity, with an increase of C and L most prominent in the alpha, theta and delta frequency bands during and after the seizure. CONCLUSIONS: During seizures, the neuronal network moves in the direction of a more ordered configuration (higher C combined with a slightly, but significantly, higher L) compared to the more randomly organized interictal network, even after correcting for changes in synchronization strength. SIGNIFICANCE: Analysis of neuronal networks during seizures may provide insight into seizure genesis and development.