Disturbed functional brain networks and neurocognitive function in low-grade glioma patients: a graph theoretical analysis of resting-state MEG

Bosma, Ingeborg; Reijneveld, Jaap C.; Klein, Martin; Douw, Linda; Dijk, Bob W. van; Heimans, Jan J.; Stam, Cornelis J.

doi:10.1186/1753-4631-3-9

Cited by 125 publications

(135 citation statements)

References 41 publications

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“…Network theory has been used to examine functional and structural brain connectivity over the past several years (20)(21)(22)(23)(24)(25)(26)(27)(28)(29). Examination of MEG data using these techniques has demonstrated that functional brain network organization is a biologically meaningful phenotype being altered in disease states (25) in ways that can be linked to behavioral task performance (60)(61)(62). Moreover, network organization demonstrates temporal variability that can be induced by cognitive remediation strategies (63), task practice (64), learning (41,53,65), or task difficulty (66).…”

Section: Discussionmentioning

confidence: 99%

Dynamic network structure of interhemispheric coordination

Doron

Bassett

Gazzaniga

2012

Proc. Natl. Acad. Sci. U.S.A.

136

146

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Fifty years ago Gazzaniga and coworkers published a seminal article that discussed the separate roles of the cerebral hemispheres in humans. Today, the study of interhemispheric communication is facilitated by a battery of novel data analysis techniques drawn from across disciplinary boundaries, including dynamic systems theory and network theory. These techniques enable the characterization of dynamic changes in the brain's functional connectivity, thereby providing an unprecedented means of decoding interhemispheric communication. Here, we illustrate the use of these techniques to examine interhemispheric coordination in healthy human participants performing a split visual field experiment in which they process lexical stimuli. We find that interhemispheric coordination is greater when lexical information is introduced to the right hemisphere and must subsequently be transferred to the left hemisphere for language processing than when it is directly introduced to the language-dominant (left) hemisphere. Further, we find that putative functional modules defined by coherent interhemispheric coordination come online in a transient manner, highlighting the underlying dynamic nature of brain communication. Our work illustrates that recently developed dynamic, network-based analysis techniques can provide novel and previously unapproachable insights into the role of interhemispheric coordination in cognition.T he field of split-brain research began several decades ago with the use of a drastic surgical solution for intractable epilepsy (1-3): the severing of the corpus callosum. This procedure significantly decreased the connectivity between the hemispheres, thereby irrevocably altering interhemispheric communication. Although a few interhemispheric pathways remained through subcortical structures and the anterior commissure, examination of callosal function using split visual field experiments clearly demonstrated its role in interhemispheric communication (2). The callosal projection plays a particularly crucial role in a variety of sensory-motor integrative functions of the two hemispheres (4), shows changes with age, and demonstrates the potential for dynamic changes with training (5). In fact, experiments in patients with severance of the callosum revealed that it subserves a large range of behaviors and cognitive functions that underlie the varied workings of the mind.Interhemispheric communication has been studied using two basic approaches. The first uses behavioral experiments to examine cognitive phenotypes, and the second uses neuroscientific experiments to examine brain phenotypes. Split-brain research initially focused on the former: Patients demonstrated striking behavioral phenotypes that provided clues regarding the underlying mechanics of brain communication. For example, although most perceptual processing appears to be isolated in each hemisphere following surgery, some attentional and emotional mechanisms initiated in one hemisphere can still be communicated to the other, cortically disconnected,...

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Section: Discussionmentioning

confidence: 99%

Dynamic network structure of interhemispheric coordination

Doron

Bassett

Gazzaniga

2012

Proc. Natl. Acad. Sci. U.S.A.

136

146

View full text Add to dashboard Cite

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“…Network randomization has mainly been found in higher frequency bands (Bartolomei et al, 2006b; Bosma et al, 2009). In lower frequency bands, brain tumors may give rise to abnormal increase in clustering (Bosma et al, 2009). Of interest, the latter observation corresponds to the increase in the normalized clustering coefficient observed after lesions in our model.…”

Section: Discussionmentioning

confidence: 97%

Emergence of modular structure in a large-scale brain network with interactions between dynamics and connectivity

Stam

Hillebrand

Wang

et al. 2010

Front. Comput. Neurosci.

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A network of 32 or 64 connected neural masses, each representing a large population of interacting excitatory and inhibitory neurons and generating an electroencephalography/magnetoencephalography like output signal, was used to demonstrate how an interaction between dynamics and connectivity might explain the emergence of complex network features, in particular modularity. Network evolution was modeled by two processes: (i) synchronization dependent plasticity (SDP) and (ii) growth dependent plasticity (GDP). In the case of SDP, connections between neural masses were strengthened when they were strongly synchronized, and were weakened when they were not. GDP was modeled as a homeostatic process with random, distance dependent outgrowth of new connections between neural masses. GDP alone resulted in stable networks with distance dependent connection strengths, typical small-world features, but no degree correlations and only weak modularity. SDP applied to random networks induced clustering, but no clear modules. Stronger modularity evolved only through an interaction of SDP and GDP, with the number and size of the modules depending on the relative strength of both processes, as well as on the size of the network. Lesioning part of the network, after a stable state was achieved, resulted in a temporary disruption of the network structure. The model gives a possible scenario to explain how modularity can arise in developing brain networks, and makes predictions about the time course of network changes during development and following acute lesions.

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“…These differences in network structure may be directly related to symptoms of PTSD. Reductions in network efficiency have been related to poorer cognitive performance, particularly in areas of processing speed, learning, and memory (Bosma et al, 2009;Douw et al, 2011;Geib et al, 2015;Schedlbauer et al, 2014). Deficits in attention, learning, and memory have previously been demonstrated in individuals with PTSD .…”

Section: Discussionmentioning

confidence: 99%

Contrasting Effects of Posttraumatic Stress Disorder and Mild Traumatic Brain Injury on the Whole-Brain Resting-State Network: A Magnetoencephalography Study

et al. 2017

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The aim of this study was to evaluate alterations in whole-brain resting-state networks associated with posttraumatic stress disorder (PTSD) and mild traumatic brain injury (mTBI). Networks were constructed from locations of peak statistical power on an individual basis from magnetoencephalography (MEG) source series data by applying the weighted phase lag index and surrogate data thresholding procedures. Networks representing activity in the alpha bandwidth as well as wideband activity (DC-80 Hz) were created. Statistical comparisons were adjusted for age and education level. Alpha network results demonstrate reductions in network structure associated with PTSD, but no differences associated with mTBI. Wideband network results demonstrate a shift in connectivity from the alpha to theta bandwidth in both PTSD and mTBI. Also, contrasting alterations in network structure are noted, with increased randomness associated with PTSD and increased structure associated with mTBI. These results demonstrate the potential of the analysis of MEG resting-state networks to differentiate two highly comorbid conditions. The importance of the alpha bandwidth to resting-state connectivity is also highlighted, while demonstrating the necessity of considering activity in other bandwidths during network construction.

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Disturbed functional brain networks and neurocognitive function in low-grade glioma patients: a graph theoretical analysis of resting-state MEG

Abstract: Background: To understand neurophysiological mechanisms underlying cognitive dysfunction in low-grade glioma (LGG) patients by evaluating the spatial structure of 'resting-state' brain networks with graph theory.

Cited by 125 publications

References 41 publications

Dynamic network structure of interhemispheric coordination

Dynamic network structure of interhemispheric coordination

Emergence of modular structure in a large-scale brain network with interactions between dynamics and connectivity

Contrasting Effects of Posttraumatic Stress Disorder and Mild Traumatic Brain Injury on the Whole-Brain Resting-State Network: A Magnetoencephalography Study

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