Highlights • Resting state EEG and MEG recordings are increasingly used for functional connectivity and functional brain network analysis. • We highlight advantages and disadvantages of ...methodological choices throughout the recording and analysis pipeline and how this may affect construction of functional connectivity and networks. • We give several recommendations for subject instructions and data acquisition for resting state neurophysiological research.
Highlights ► The brain can be represented as a complex network with functionally connected units at several levels that changes in neurological and psychiatric disease. ► Existing clinical ...neurophysiology techniques and network models to explain network properties are reviewed. ► In addition to the already established network models, we suggest a heuristic model including hierarchical modularity.
In recent years there has been a shift in focus from the study of local, mostly task-related activation to the exploration of the organization and functioning of large-scale structural and functional ...complex brain networks. Progress in the interdisciplinary field of modern network science has introduced many new concepts, analytical tools and models which allow a systematic interpretation of multivariate data obtained from structural and functional MRI, EEG and MEG. However, progress in this field has been hampered by the absence of a simple, unbiased method to represent the essential features of brain networks, and to compare these across different conditions, behavioural states and neuropsychiatric/neurological diseases. One promising solution to this problem is to represent brain networks by a minimum spanning tree (MST), a unique acyclic subgraph that connects all nodes and maximizes a property of interest such as synchronization between brain areas. We explain how the global and local properties of an MST can be characterized. We then review early and more recent applications of the MST to EEG and MEG in epilepsy, development, schizophrenia, brain tumours, multiple sclerosis and Parkinson's disease, and show how MST characterization performs compared to more conventional graph analysis. Finally, we illustrate how MST characterization allows representation of observed brain networks in a space of all possible tree configurations and discuss how this may simplify the construction of simple generative models of normal and abnormal brain network organization.
•Comparing brain networks is a challenge for modern network science.•The minimum spanning tree (MST) is a unique representation of weighted brain networks.•The MST reflects traffic flow and hierarchy in the underlying system.•MST sensitivity is comparable to classical graph theoretical brain network analysis.
Highlights • MEG activity in AD is slower, more regular, less complex and less well organized compared to healthy controls. • Posterior and temporal areas are the most affected regions. • MEG has ...currently not been used to its full potential.
In cerebral small vessel disease, the core MRI findings include white matter lesions (WML) and lacunar infarcts. While the clinical significance of WML is better understood, the contribution of ...lacunes to the rate of cognitive decline has not been established. This study investigated whether incident lacunes on MRI determine longitudinal cognitive change in elderly subjects with WML.
Within the Leukoaraiosis and Disability Study (LADIS), 387 subjects were evaluated with repeated MRI and neuropsychological assessment at baseline and after 3 years. Predictors of change in global cognitive function and specific cognitive domains over time were analyzed with multivariate linear regression.
After controlling for demographic factors, baseline cognitive performance, baseline lacunar and WML lesion load, and WML progression, the number of new lacunes was related to subtle decrease in compound scores for executive functions (p = 0.021) and speed and motor control (p = 0.045), but not for memory or global cognitive function. Irrespective of lacunes, WML progression was associated with decrease in executive functions score (p = 0.016).
Incident lacunes on MRI parallel a steeper rate of decline in executive functions and psychomotor speed. Accordingly, in addition to WML, lacunes determine longitudinal cognitive impairment in small vessel disease. Although the individual contribution of lacunes on cognition was modest, they cannot be considered benign findings, but indicate a risk of progressive cognitive impairment.
Summary
Objective
In one third of patients, seizures remain after epilepsy surgery, meaning that improved preoperative evaluation methods are needed to identify the epileptogenic zone. A potential ...framework for such a method is network theory, as it can be applied to noninvasive recordings, even in the absence of epileptiform activity. Our aim was to identify the epileptogenic zone on the basis of hub status of local brain areas in interictal magnetoencephalography (MEG) networks.
Methods
Preoperative eyes‐closed resting‐state MEG recordings were retrospectively analyzed in 22 patients with refractory epilepsy, of whom 14 were seizure‐free 1 year after surgery. Beamformer‐based time series were reconstructed for 90 cortical and subcortical automated anatomic labeling (AAL) regions of interest (ROIs). Broadband functional connectivity was estimated using the phase lag index in artifact‐free epochs without interictal epileptiform abnormalities. A minimum spanning tree was generated to represent the network, and the hub status of each ROI was calculated using betweenness centrality, which indicates the centrality of a node in a network. The correspondence of resection cavity to hub values was evaluated on four levels: resection cavity, lobar, hemisphere, and temporal versus extratemporal areas.
Results
Hubs were localized within the resection cavity in 8 of 14 seizure‐free patients and in zero of 8 patients who were not seizure‐free (57% sensitivity, 100% specificity, 73% accuracy). Hubs were localized in the lobe of resection in 9 of 14 seizure‐free patients and in zero of 8 patients who were not seizure‐free (64% sensitivity, 100% specificity, 77% accuracy). For the other two levels, the true negatives are unknown; hence, only sensitivity could be determined: hubs coincided with both the resection hemisphere and the resection location (temporal versus extratemporal) in 11 of 14 seizure‐free patients (79% sensitivity).
Significance
Identifying hubs noninvasively before surgery is a valuable approach with the potential of indicating the epileptogenic zone in patients without interictal abnormalities.
An important problem in systems neuroscience is the relation between complex structural and functional brain networks. Here we use simulations of a simple dynamic process based upon the ...susceptible–infected–susceptible (SIS) model of infection dynamics on an empirical structural brain network to investigate the extent to which the functional interactions between any two brain areas depend upon (i) the presence of a direct structural connection; and (ii) the degree product of the two areas in the structural network.
For the structural brain network, we used a 78×78 matrix representing known anatomical connections between brain regions at the level of the AAL atlas (Gong et al., 2009). On this structural network we simulated brain dynamics using a model derived from the study of epidemic processes on networks. Analogous to the SIS model, each vertex/brain region could be in one of two states (inactive/active) with two parameters β and δ determining the transition probabilities. First, the phase transition between the fully inactive and partially active state was investigated as a function of β and δ. Second, the statistical interdependencies between time series of node states were determined (close to and far away from the critical state) with two measures: (i) functional connectivity based upon the correlation coefficient of integrated activation time series; and (ii) effective connectivity based upon conditional co-activation at different time intervals.
We find a phase transition between an inactive and a partially active state for a critical ratio τ=β/δ of the transition rates in agreement with the theory of SIS models. Slightly above the critical threshold, node activity increases with degree, also in line with epidemic theory. The functional, but not the effective connectivity matrix closely resembled the underlying structural matrix. Both functional connectivity and, to a lesser extent, effective connectivity were higher for connected as compared to disconnected (i.e.: not directly connected) nodes. Effective connectivity scaled with the degree product. For functional connectivity, a weaker scaling relation was only observed for disconnected node pairs. For random networks with the same degree distribution as the original structural network, similar patterns were seen, but the scaling exponent was significantly decreased especially for effective connectivity.
Even with a very simple dynamical model it can be shown that functional relations between nodes of a realistic anatomical network display clear patterns if the system is studied near the critical transition. The detailed nature of these patterns depends on the properties of the functional or effective connectivity measure that is used. While the strength of functional interactions between any two nodes clearly depends upon the presence or absence of a direct connection, this study has shown that the degree product of the nodes also plays a large role in explaining interaction strength, especially for disconnected nodes and in combination with an effective connectivity measure. The influence of degree product on node interaction strength probably reflects the presence of large numbers of indirect connections.
We introduce a directed phase lag index to investigate the spatial and temporal pattern of phase relations of oscillatory activity in a model of macroscopic structural and functional brain networks. ...Direction of information flow was determined with the directed phase lag index (dPLI) defined as the probability that the instantaneous phase of X was smaller than the phase of Y (modulo π). X was said to phase-lead Y if 0.5<dPLIXY<=1. The dPLI was used to characterize the phase relations between simulated EEG time series. The model consisted of 78 brain regions, coupled according to DTI findings in human subjects (Gong et al., 2009). Activity of each brain region was simulated with a neural mass model. Phase patterns were investigated as a function of coupling strength without stimulation, and with stimulation of the primary visual areas. At rest a clear spatial pattern of phase relations emerged with regions belonging to the anterior part of the default mode network leading in phase and regions belonging to the posterior part of the default mode network and surrounding visual areas lagging in phase. Patterns of phase leading and lagging displayed characteristic patterns with time scales from a few hundred milliseconds to 1–2s. Stimulation of the primary visual areas induced a reversal of the global phase pattern with the visual and basal temporal areas leading and the anterior and superior frontal areas lagging in phase. This study shows that the directed phase lag index (dPLI) is an effective measure to characterize spatial temporal patterns of phase relations at rest and during stimulation. Coupling strength and node degree were found to be critical determinants of the direction of information flow. At a timescale of milliseconds to seconds the phase dynamics revealed spontaneous structure that might correspond to previously described “microstates”. Stimulation of two visual areas reversed the global pattern of phase relations.
► The directed phase lag index characterizes patterns of phase leading or lagging ► In a resting-state there is a front to back pattern of phase relations ► Spatial temporal phase patterns show spontaneous fluctuations at sub second scales ► Stimulation of visual areas reverses the front to back pattern of phase relations
Background
White matter hyperintensities (WMH) have an effect on cognition and are increased in severity among individuals with amnestic mild cognitive impairment (aMCI). The influence of WMH on ...progression of aMCI to Alzheimer’s disease (AD) is less clear.
Methods
Data were drawn from a three-year prospective, double blind, placebo controlled clinical trial that examined the effect of donepezil or vitamin E on progression from aMCI to AD. WMH from multiple brain regions were scored on MR images obtained at entry into the trial from a subset of 152 study participants using a standardized visual rating scale. Cox proportional hazards models adjusting for age, education and treatment arm were used to investigate the role of WMH on time to progression.
Results
55 of the 152 (36.2 %) aMCI subjects progressed to AD. Only periventricular hyperintensities (PVH) were related to an increased risk of AD within three years (HR = 1.59, 95 % CI = 1.24 – 2.05, p-value < 0.001). Correcting for medial temporal lobe atrophy or the presence of lacunes did not change statistical significance.
Conclusion
PVH are associated with an increased risk of progression from aMCI to AD. This suggests that PVH, an MRI finding thought to represent cerebrovascular damage, contributes to AD onset in vulnerable individuals independent of Alzheimer pathology.
Current studies suggest an interaction between vascular mechanisms and neurodegenerative processes that leads to late-onset Alzheimer disease (AD). We tested whether AD pathology was associated with ...white matter hyperintensities (WMH) or cerebral infarcts in the oldest old individuals.
Brains from 132 subjects over 85 years old, who came to autopsy from the Vantaa 85+ population-based cohort, were scanned by postmortem MRI and examined for neuropathologic changes. Coronal images were analyzed to determine the degree of frontal and parietal periventricular WMH (PVWMH) and deep WMH (DWMH) and cerebral infarcts. Neuropathologic variables included Consortium to Establish a Registry for Alzheimer's Disease scores for neuritic plaques and Braak staging among subjects in 5 groups: normal aging (NA), borderline with insufficient AD pathology, AD, AD plus other pathology, and other primary degenerative diseases.
Frontal DWMH were detected in >50% of the sample. Both frontal PVWMH and DWMH were significantly more extensive in the AD group compared to the NA group or the NA and borderline groups combined. Frontal PVWMH and DWMH were also associated with increased Braak staging (p = 0.03) and the neuritic plaque load (p = 0.01). Further analysis revealed there were a greater number of cerebral infarcts associated with frontal DWMH (p = 0.03) but not with frontal PVWMH.
Our study showed an association between neurofibrillary pathology and frontal PVWMH and DWMH (rather than parietal), as a surrogate of small vessel disease, particularly in very old community-dwelling individuals.
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