Parameter-free extraction of the functional network topology from intracranial EEG recordings: a time-resolved study of graph properties in focal onset seizures

Rationale: Focal onset epileptic seizures are due to abnormal interactions between distributed brain areas. By estimating the cross-correlation matrix of multi-site intra-cerebral EEG recordings (iEEG), one can quantify these interactions. To assess the topology of the underlying functional network, the binary connectivity matrix has to be derived from the cross-correlation matrix by use of a threshold. Classically, a unique threshold is used that constrains the topology [1]. Our method aims to set the threshold in a data-driven way by separating genuine from random cross-correlation. We compare our approach to the fixed threshold method and study the dynamics of the functional topology. Methods: We investigate the iEEG of patients suffering from focal onset seizures who underwent evaluation for the possibility of surgery. The equal-time cross-correlation matrices are evaluated using a sliding time window. We then compare 3 approaches assessing the corresponding binary networks. For each time window: * Our parameter-free method derives from the cross-correlation strength matrix (CCS)[2]. It aims at disentangling genuine from random correlations (due to finite length and varying frequency content of the signals). In practice, a threshold is evaluated for each pair of channels independently, in a data-driven way. * The fixed mean degree (FMD) uses a unique threshold on the whole connectivity matrix so as to ensure a user defined mean degree. * The varying mean degree (VMD) uses the mean degree of the CCS network to set a unique threshold for the entire connectivity matrix. * Finally, the connectivity (c), connectedness (given by k, the number of disconnected sub-networks), mean global and local efficiencies (Eg, El, resp.) are computed from FMD, CCS, VMD, and their corresponding random and lattice networks. Results: Compared to FMD and VMD, CCS networks present: *topologies that are different in terms of c, k, Eg and El. *from the pre-ictal to the ictal and then post-ictal period, topological features time courses that are more stable within a period, and more contrasted from one period to the next. For CCS, pre-ictal connectivity is low, increases to a high level during the seizure, then decreases at offset. k shows a ‘‘U-curve’’ underlining the synchronization of all electrodes during the seizure. Eg and El time courses fluctuate between the corresponding random and lattice networks values in a reproducible manner. Conclusions: The definition of a data-driven threshold provides new insights into the topology of the epileptic functional networks.

Identification of glacial meltwater runoff in a karstic environment and its implication for present and future water availability

Glaciers all over the world are expected to continue to retreat due to the global warming throughout the 21st century. Consequently, future seasonal water availability might become scarce once glacier areas have declined below a certain threshold affecting future water management strategies. Particular attention should be paid to glaciers located in a karstic environment, as parts of the meltwater can be drained by underlying karst systems, making it difficult to assess water availability. In this study tracer experiments, karst modeling and glacier melt modeling are combined in order to identify flow paths in a high alpine, glacierized, karstic environment (Glacier de la Plaine Morte, Switzerland) and to investigate current and predict future downstream water availability. Flow paths through the karst underground were determined with natural and fluorescent tracers. Subsequently, geologic information and the findings from tracer experiments were assembled in a karst model. Finally, glacier melt projections driven with a climate scenario were performed to discuss future water availability in the area surrounding the glacier. The results suggest that during late summer glacier meltwater is rapidly drained through well-developed channels at the glacier bottom to the north of the glacier, while during low flow season meltwater enters into the karst and is drained to the south. Climate change projections with the glacier melt model reveal that by the end of the century glacier melt will be significantly reduced in the summer, jeopardizing water availability in glacier-fed karst springs.

Chronology of Lake El'gygytgyn sediments – a combined magnetostratigraphic, palaeoclimatic and orbital tuning study based on multi-parameter analyses

A 318-metre-long sedimentary profile drilled by the International Continental Scientific Drilling Program (ICDP) at Site 5011-1 in Lake El’gygytgyn, Far East Russian Arctic, has been analysed for its sedimentologic response to global climate modes by chronostratigraphic methods. The 12 km wide lake is sited off-centre in an 18 km large crater that was created by the impact of a meteorite 3.58 Ma ago. Since then sediments have been continuously deposited. For establishing their chronology, major reversals of the earth’s magnetic field provided initial tie points for the age model, confirming that the impact occurred in the earliest geomagnetic Gauss chron. Various stratigraphic parameters, reflecting redox conditions at the lake floor and climatic conditions in the catchment were tuned synchronously to Northern Hemisphere insolation variations and the marine oxygen isotope stack, respectively. Thus, a robust age model comprising more than 600 tie points could be defined. It could be shown that deposition of sediments in Lake El’gygytgyn occurred in concert with global climatic cycles. The upper �160m of sediments represent the past 3.3 Ma, equivalent to sedimentation rates of 4 to 5 cm ka−1, whereas the lower 160m represent just the first 0.3 Ma after the impact, equivalent to sedimentation rates in the order of 45 cm ka−1. This study also provides orbitally tuned ages for a total of 8 tephras deposited in Lake El’gygytgyn.

Characterization of microcirculation in multiple sclerosis lesions by dynamic texture parameter analysis (DTPA)

OBJECTIVE Texture analysis is an alternative method to quantitatively assess MR-images. In this study, we introduce dynamic texture parameter analysis (DTPA), a novel technique to investigate the temporal evolution of texture parameters using dynamic susceptibility contrast enhanced (DSCE) imaging. Here, we aim to introduce the method and its application on enhancing lesions (EL), non-enhancing lesions (NEL) and normal appearing white matter (NAWM) in multiple sclerosis (MS). METHODS We investigated 18 patients with MS and clinical isolated syndrome (CIS), according to the 2010 McDonald's criteria using DSCE imaging at different field strengths (1.5 and 3 Tesla). Tissues of interest (TOIs) were defined within 27 EL, 29 NEL and 37 NAWM areas after normalization and eight histogram-based texture parameter maps (TPMs) were computed. TPMs quantify the heterogeneity of the TOI. For every TOI, the average, variance, skewness, kurtosis and variance-of-the-variance statistical parameters were calculated. These TOI parameters were further analyzed using one-way ANOVA followed by multiple Wilcoxon sum rank testing corrected for multiple comparisons. RESULTS Tissue- and time-dependent differences were observed in the dynamics of computed texture parameters. Sixteen parameters discriminated between EL, NEL and NAWM (pAVG = 0.0005). Significant differences in the DTPA texture maps were found during inflow (52 parameters), outflow (40 parameters) and reperfusion (62 parameters). The strongest discriminators among the TPMs were observed in the variance-related parameters, while skewness and kurtosis TPMs were in general less sensitive to detect differences between the tissues. CONCLUSION DTPA of DSCE image time series revealed characteristic time responses for ELs, NELs and NAWM. This may be further used for a refined quantitative grading of MS lesions during their evolution from acute to chronic state. DTPA discriminates lesions beyond features of enhancement or T2-hypersignal, on a numeric scale allowing for a more subtle grading of MS-lesions.