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Factors affecting the cerebral network in brain tumor patients.

Heimans JJ, Reijneveld JC - J. Neurooncol. (2012)

Bottom Line: The effect of a brain tumor on cerebral functioning is often more global than should be expected on the basis of the local character of the disease, and this is thought to be a consequence of disturbance of the cerebral network as a whole.Functional MRI, electroencephalography and especially magnetoencephalography are used to measure brain function and the signals that are being registered with these techniques can be analyzed with respect to network characteristics such as "synchronization" and "clustering".Evidence accumulates that loss of optimal neural network architecture negatively impacts complex cerebral functioning and also decreases the threshold to develop epileptic seizures.

View Article: PubMed Central - PubMed

Affiliation: Department of Neurology, VU University Medical Center, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands. j.heimans@vumc.nl

ABSTRACT
Brain functions, including cognitive functions, are frequently disturbed in brain tumor patients. These disturbances may result from the tumor itself, but also from the treatment directed against the tumor. Surgery, radiotherapy and chemotherapy all may affect cerebral functioning, both in a positive as well as in a negative way. Apart from the anti-tumor treatment, glioma patients often receive glucocorticoids and anti-epileptic drugs, which both also have influence on brain functioning. The effect of a brain tumor on cerebral functioning is often more global than should be expected on the basis of the local character of the disease, and this is thought to be a consequence of disturbance of the cerebral network as a whole. Any network, whether it be a neural, a social or an electronic network, can be described in parameters assessing the topological characteristics of that particular network. Repeated assessment of neural network characteristics in brain tumor patients during their disease course enables study of the dynamics of neural networks and provides more insight into the plasticity of the diseased brain. Functional MRI, electroencephalography and especially magnetoencephalography are used to measure brain function and the signals that are being registered with these techniques can be analyzed with respect to network characteristics such as "synchronization" and "clustering". Evidence accumulates that loss of optimal neural network architecture negatively impacts complex cerebral functioning and also decreases the threshold to develop epileptic seizures. Future research should be focused on both plasticity of neural networks and the factors that have impact on that plasticity as well as the possible role of assessment of neural network characteristics in the determination of cerebral function during the disease course.

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Part of a 151-channel MEG recording. Synchronization of signals from different regions of the brain is a measure of connectivity of these regions
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Fig2: Part of a 151-channel MEG recording. Synchronization of signals from different regions of the brain is a measure of connectivity of these regions

Mentions: A fundamental conception for the study of brain dynamics is “synchronization” or “functional connectivity”. The basic assumption of functional connectivity is that statistical interdependencies between time series of brain activity at separate areas reflect functional interactions between these brain regions [34]. This functional connectivity can be calculated on the basis of the amount of synchrony of brain activity measured in two different areas. The conception is that multiple local networks are maintained by long-distance patterns of functional connectivity and this results in higher and complex brain functions, such as planning, memory, and executive functioning [35–38]. Functional connectivity between brain areas may thus be used to construct graphs of the brain (see Fig. 2 for an example in an MEG recording). The two prerequisites of local segregation, referring to local specialization in specific tasks, and integration, combining information from lower-level networks at a higher and more global level, are thought to be crucial for optimal brain functioning [39–41]. The small-world network is a highly adequate model of organization in the brain, because it supports both segregated as well as integrated information processing [42]. Brain tumors may interfere with neuronal structures and the resulting disturbances of anatomical connectivity may lead to alterations of functional connectivity patterns [43, 44].Fig. 2


Factors affecting the cerebral network in brain tumor patients.

Heimans JJ, Reijneveld JC - J. Neurooncol. (2012)

Part of a 151-channel MEG recording. Synchronization of signals from different regions of the brain is a measure of connectivity of these regions
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3351596&req=5

Fig2: Part of a 151-channel MEG recording. Synchronization of signals from different regions of the brain is a measure of connectivity of these regions
Mentions: A fundamental conception for the study of brain dynamics is “synchronization” or “functional connectivity”. The basic assumption of functional connectivity is that statistical interdependencies between time series of brain activity at separate areas reflect functional interactions between these brain regions [34]. This functional connectivity can be calculated on the basis of the amount of synchrony of brain activity measured in two different areas. The conception is that multiple local networks are maintained by long-distance patterns of functional connectivity and this results in higher and complex brain functions, such as planning, memory, and executive functioning [35–38]. Functional connectivity between brain areas may thus be used to construct graphs of the brain (see Fig. 2 for an example in an MEG recording). The two prerequisites of local segregation, referring to local specialization in specific tasks, and integration, combining information from lower-level networks at a higher and more global level, are thought to be crucial for optimal brain functioning [39–41]. The small-world network is a highly adequate model of organization in the brain, because it supports both segregated as well as integrated information processing [42]. Brain tumors may interfere with neuronal structures and the resulting disturbances of anatomical connectivity may lead to alterations of functional connectivity patterns [43, 44].Fig. 2

Bottom Line: The effect of a brain tumor on cerebral functioning is often more global than should be expected on the basis of the local character of the disease, and this is thought to be a consequence of disturbance of the cerebral network as a whole.Functional MRI, electroencephalography and especially magnetoencephalography are used to measure brain function and the signals that are being registered with these techniques can be analyzed with respect to network characteristics such as "synchronization" and "clustering".Evidence accumulates that loss of optimal neural network architecture negatively impacts complex cerebral functioning and also decreases the threshold to develop epileptic seizures.

View Article: PubMed Central - PubMed

Affiliation: Department of Neurology, VU University Medical Center, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands. j.heimans@vumc.nl

ABSTRACT
Brain functions, including cognitive functions, are frequently disturbed in brain tumor patients. These disturbances may result from the tumor itself, but also from the treatment directed against the tumor. Surgery, radiotherapy and chemotherapy all may affect cerebral functioning, both in a positive as well as in a negative way. Apart from the anti-tumor treatment, glioma patients often receive glucocorticoids and anti-epileptic drugs, which both also have influence on brain functioning. The effect of a brain tumor on cerebral functioning is often more global than should be expected on the basis of the local character of the disease, and this is thought to be a consequence of disturbance of the cerebral network as a whole. Any network, whether it be a neural, a social or an electronic network, can be described in parameters assessing the topological characteristics of that particular network. Repeated assessment of neural network characteristics in brain tumor patients during their disease course enables study of the dynamics of neural networks and provides more insight into the plasticity of the diseased brain. Functional MRI, electroencephalography and especially magnetoencephalography are used to measure brain function and the signals that are being registered with these techniques can be analyzed with respect to network characteristics such as "synchronization" and "clustering". Evidence accumulates that loss of optimal neural network architecture negatively impacts complex cerebral functioning and also decreases the threshold to develop epileptic seizures. Future research should be focused on both plasticity of neural networks and the factors that have impact on that plasticity as well as the possible role of assessment of neural network characteristics in the determination of cerebral function during the disease course.

Show MeSH
Related in: MedlinePlus