Graph-based analysis of brain resting-state fMRI data in nocturnal frontal lobe epileptic patients

Il lavoro che ho sviluppato presso l'unità di RM funzionale del Policlinico S.Orsola-Malpighi, DIBINEM, è incentrato sull'analisi dati di resting state - functional Magnetic Resonance Imaging (rs-fMRI) mediante l'utilizzo della graph theory, con lo scopo di valutare eventuali differenze in termini di connettività cerebrale funzionale tra un campione di pazienti affetti da Nocturnal Frontal Lobe Epilepsy (NFLE) ed uno di controlli sani. L'epilessia frontale notturna è una peculiare forma di epilessia caratterizzata da crisi che si verificano quasi esclusivamente durante il sonno notturno. Queste sono contraddistinte da comportamenti motori, prevalentemente distonici, spesso complessi, e talora a semiologia bizzarra. L'fMRI è una metodica di neuroimaging avanzata che permette di misurare indirettamente l'attività neuronale. Tutti i soggetti sono stati studiati in condizioni di resting-state, ossia di veglia rilassata. In particolare mi sono occupato di analizzare i dati fMRI con un approccio innovativo in campo clinico-neurologico, rappresentato dalla graph theory. I grafi sono definiti come strutture matematiche costituite da nodi e links, che trovano applicazione in molti campi di studio per la modellizzazione di strutture di diverso tipo. La costruzione di un grafo cerebrale per ogni partecipante allo studio ha rappresentato la parte centrale di questo lavoro. L'obiettivo è stato quello di definire le connessioni funzionali tra le diverse aree del cervello mediante l'utilizzo di un network. Il processo di modellizzazione ha permesso di valutare i grafi neurali mediante il calcolo di parametri topologici che ne caratterizzano struttura ed organizzazione. Le misure calcolate in questa analisi preliminare non hanno evidenziato differenze nelle proprietà globali tra i grafi dei pazienti e quelli dei controlli. Alterazioni locali sono state invece riscontrate nei pazienti, rispetto ai controlli, in aree della sostanza grigia profonda, del sistema limbico e delle regioni frontali, le quali rientrano tra quelle ipotizzate essere coinvolte nella fisiopatologia di questa peculiare forma di epilessia.

The Effects of Hibernation on Immunological Functions in Female Big Brown Bats (Eptesicus fuscus)

The emerging disease White-Nose Syndrome in hibernating bat populations across the United States has increased the need to understand the physiological benefits and consequences of hibernation and the effects on immunological responsiveness. Hibernation has been well-documented in many mammalian species, yet few studies have examined hibernation immunology in bats, particularly with respect to normal immunological patterns. In order to characterize the levels of circulating leukocytes and plasma immunoglobulins in euthermic and hibernating female big brown bats (Eptesicus fuscus), blood smear differential leukocyte counts and total immunoglobulin assays were performed for each group using blood samples from the active and hibernation seasons. Hibernation patterns – torpor and arousals from torpor – were determined by placing temperature-sensitive dataloggers on the backs of bats assigned to the hibernating group during the hibernation season. Data indicate that the ratio of circulating neutrophils to lymphocytes is lower in bats assigned to the euthermic group during the hibernation season than in bats assigned to the hibernation group during the hibernation period, but that relative immunoglobulin levels do not differ during the hibernation season, regardless of whether bats were active or hibernating. Neither bats assigned to the hibernation group nor bats assigned to the euthermic group demonstrate a significant change in the ratio of circulating neutrophils and lymphocytes between their active and hibernating seasons. Bats assigned to the hibernation group were also observed to arouse from torpor somewhat synchronously. These results suggest that innate and adaptive cell levels are maintained, at best, in hibernating bats that are not immunologically challenged and that bats that remain euthermic during the hibernation season are able to continually regulate their levels of neutrophils and lymphocytes and therefore their innate and adaptive immune system responses.

Brain areas involved in medial temporal lobe seizures: a principal component analysis of ictal SPECT data

The study describes brain areas involved in medial temporal lobe (mTL) seizures of 12 patients. All patients showed so-called oro-alimentary behavior within the first 20 s of clinical seizure manifestation characteristic of mTL seizures. Single photon emission computed tomography (SPECT) images of regional cerebral blood flow (rCBF) were acquired from the patients in ictal and interictal phases and from normal volunteers. Image analysis employed categorical comparisons with statistical parametric mapping and principal component analysis (PCA) to assess functional connectivity. PCA supplemented the findings of the categorical analysis by decomposing the covariance matrix containing images of patients and healthy subjects into distinct component images of independent variance, including areas not identified by the categorical analysis. Two principal components (PCs) discriminated the subject groups: patients with right or left mTL seizures and normal volunteers, indicating distinct neuronal networks implicated by the seizure. Both PCs were correlated with seizure duration, one positively and the other negatively, confirming their physiological significance. The independence of the two PCs yielded a clear clustering of subject groups. The local pattern within the temporal lobe describes critical relay nodes which are the counterpart of oro-alimentary behavior: (1) right mesial temporal zone and ipsilateral anterior insula in right mTL seizures, and (2) temporal poles on both sides that are densely interconnected by the anterior commissure. Regions remote from the temporal lobe may be related to seizure propagation and include positively and negatively loaded areas. These patterns, the covarying areas of the temporal pole and occipito-basal visual association cortices, for example, are related to known anatomic paths.

A BAYESIAN HIERARCHICAL FRAMEWORK FOR SPATIAL MODELING OF fMRI DATA

Functional neuroimaging techniques enable investigations into the neural basis of human cognition, emotions, and behaviors. In practice, applications of functional magnetic resonance imaging (fMRI) have provided novel insights into the neuropathophysiology of major psychiatric,neurological, and substance abuse disorders, as well as into the neural responses to their treatments. Modern activation studies often compare localized task-induced changes in brain activity between experimental groups. One may also extend voxel-level analyses by simultaneously considering the ensemble of voxels constituting an anatomically defined region of interest (ROI) or by considering means or quantiles of the ROI. In this work we present a Bayesian extension of voxel-level analyses that offers several notable benefits. First, it combines whole-brain voxel-by-voxel modeling and ROI analyses within a unified framework. Secondly, an unstructured variance/covariance for regional mean parameters allows for the study of inter-regional functional connectivity, provided enough subjects are available to allow for accurate estimation. Finally, an exchangeable correlation structure within regions allows for the consideration of intra-regional functional connectivity. We perform estimation for our model using Markov Chain Monte Carlo (MCMC) techniques implemented via Gibbs sampling which, despite the high throughput nature of the data, can be executed quickly (less than 30 minutes). We apply our Bayesian hierarchical model to two novel fMRI data sets: one considering inhibitory control in cocaine-dependent men and the second considering verbal memory in subjects at high risk for Alzheimer’s disease. The unifying hierarchical model presented in this manuscript is shown to enhance the interpretation content of these data sets.

Brain connectivity at different time-scales measured with EEG

We present an overview of different methods for decomposing a multichannel spontaneous electroencephalogram (EEG) into sets of temporal patterns and topographic distributions. All of the methods presented here consider the scalp electric field as the basic analysis entity in space. In time, the resolution of the methods is between milliseconds (time-domain analysis), subseconds (time- and frequency-domain analysis) and seconds (frequency-domain analysis). For any of these methods, we show that large parts of the data can be explained by a small number of topographic distributions. Physically, this implies that the brain regions that generated one of those topographies must have been active with a common phase. If several brain regions are producing EEG signals at the same time and frequency, they have a strong tendency to do this in a synchronized mode. This view is illustrated by several examples (including combined EEG and functional magnetic resonance imaging (fMRI)) and a selective review of the literature. The findings are discussed in terms of short-lasting binding between different brain regions through synchronized oscillations, which could constitute a mechanism to form transient, functional neurocognitive networks.

Linking brain connectivity across different time scales with electroencephalogram, functional magnetic resonance imaging, and diffusion tensor imaging

Structural and functional connectivity are intrinsic properties of the human brain and represent the amount of cognitive capacities of individual subjects. These connections are modulated due to development, learning, and disease. Momentary adaptations in functional connectivity alter the structural connections, which in turn affect the functional connectivity. Thus, structural and functional connectivity interact on a broad timescale. In this study, we aimed to explore distinct measures of connectivity assessed by functional magnetic resonance imaging and diffusion tensor imaging and their association to the dominant electroencephalogram oscillatory property at rest: the individual alpha frequency (IAF). We found that in 21 healthy young subjects, small intraindividual temporal IAF fluctuations were correlated to increased blood oxygenation level-dependent signal in brain areas associated to working memory functions and to the modulation of attention. These areas colocalized with functionally connected networks supporting the respective functions. Furthermore, subjects with higher IAF show increased fractional anisotropy values in fascicles connecting the above-mentioned areas and networks. Hence, due to a multimodal approach a consistent functionally and structurally connected network related to IAF was observed.

Landscape connectivity, habitat structure and activity of bat guilds in farmland-dominated matrices

Agricultural intensification has caused a decline in structural elements in European farmland, where natural habitats are increasingly fragmented. The loss of habitat structures has a detrimental effect on biodiversity and affects bat species that depend on vegetation structures for foraging and commuting. We investigated the impact of connectivity and configuration of structural landscape elements on flight activity, species richness and diversity of insectivorous bats and distinguished three bat guilds according to species-specific bioacoustic characteristics. We tested whether bats with shorter-range echolocation were more sensitive to habitat fragmentation than bats with longer-range echolocation. We expected to find different connectivity thresholds for the three guilds and hypothesized that bats prefer linear over patchy landscape elements. Bat activity was quantified using repeated acoustic monitoring in 225 locations at 15 study plots distributed across the Swiss Central Plateau, where connectivity and the shape of landscape elements were determined by spatial analysis (GIS). Spectrograms of bat calls were assigned to species with the software batit by means of image recognition and statistical classification algorithms. Bat activity was significantly higher around landscape elements compared to open control areas. Short- and long-range echolocating bats were more active in well-connected landscapes, but optimal connectivity levels differed between the guilds. Species richness increased significantly with connectivity, while species diversity did not (Shannon's diversity index). Total bat activity was unaffected by the shape of landscape elements. Synthesis and applications. This study highlights the importance of connectivity in farmland landscapes for bats, with shorter-range echolocating bats being particularly sensitive to habitat fragmentation. More structurally diverse landscape elements are likely to reduce population declines of bats and could improve conditions for other declining species, including birds. Activity was highest around optimal values of connectivity, which must be evaluated for the different guilds and spatially targeted for a region's habitat configuration. In a multi-species approach, we recommend the reintroduction of structural elements to increase habitat heterogeneity should become part of agri-environment schemes.

Symptoms of endocrine treatment and outcome in the BIG 1-98 study

There may be a relationship between the incidence of vasomotor and arthralgia/myalgia symptoms and treatment outcomes for postmenopausal breast cancer patients with endocrine-responsive disease who received adjuvant letrozole or tamoxifen. Data on patients randomized into the monotherapy arms of the BIG 1-98 clinical trial who did not have either vasomotor or arthralgia/myalgia/carpal tunnel (AMC) symptoms reported at baseline, started protocol treatment and were alive and disease-free at the 3-month landmark (n = 4,798) and at the 12-month landmark (n = 4,682) were used for this report. Cohorts of patients with vasomotor symptoms, AMC symptoms, neither, or both were defined at both 3 and 12 months from randomization. Landmark analyses were performed for disease-free survival (DFS) and for breast cancer free interval (BCFI), using regression analysis to estimate hazard ratios (HR) and 95 % confidence intervals (CI). Median follow-up was 7.0 years. Reporting of AMC symptoms was associated with better outcome for both the 3- and 12-month landmark analyses [e.g., 12-month landmark, HR (95 % CI) for DFS = 0.65 (0.49–0.87), and for BCFI = 0.70 (0.49–0.99)]. By contrast, reporting of vasomotor symptoms was less clearly associated with DFS [12-month DFS HR (95 % CI) = 0.82 (0.70–0.96)] and BCFI (12-month DFS HR (95 % CI) = 0.97 (0.80–1.18). Interaction tests indicated no effect of treatment group on associations between symptoms and outcomes. While reporting of AMC symptoms was clearly associated with better DFS and BCFI, the association between vasomotor symptoms and outcome was less clear, especially with respect to breast cancer-related events.

BRAIN ACTIVATION AND CONNECTIVITY IN NON-DISABLED MULTIPLE SCLEROSIS PATIENTS

Multiple sclerosis (MS) is the most common demyelinating disease affecting the central nervous system. There is no cure for MS and current therapies have limited efficacy. While the majority of individuals with MS develop significant clinical disability, a subset experiences a disease course with minimal impairment even in the presence of significant apparent tissue damage on magnetic resonance imaging (MRI). The current studies combined functional MRI and diffusion tensor imaging (DTI) to elucidate brain mechanisms associated with lack of clinical disability in patients with MS. Recent evidence has implicated cortical reorganization as a mechanism to limit the clinical manifestation of the disease. Functional MRI was used to test the hypothesis that non-disabled MS patients (Expanded Disability Status Scale ≤ 1.5) show increased recruitment of cognitive control regions (dorsolateral prefrontal and anterior cingulate cortex) while performing sensory, motor and cognitive tasks. Compared to matched healthy controls, patients increased activation of cognitive control brain regions when performing non-dominant hand movements and the 2-back working memory task. Using dynamic causal modeling, we tested whether increased cognitive control recruitment is associated with alterations in connectivity in the working memory functional network. Patients exhibited similar network connectivity to that of control subjects when performing working memory tasks. We subsequently investigated the integrity of major white matter tracts to assess structural connectivity and its relation to activation and functional integration of the cognitive control system. Patients showed substantial alterations in callosal, inferior and posterior white matter tracts and less pronounced involvement of the corticospinal tracts and superior longitudinal fasciculi (SLF). Decreased structural integrity within the right SLF in patients was associated with decreased performance, and decreased activation and connectivity of the cognitive control system when performing working memory tasks. These studies suggest that patient with MS without clinical disability increase cognitive control system recruitment across functional domains and rely on preserved functional and structural connectivity of brain regions associated with this network. Moreover, the current studies show the usefulness of combining brain activation data from functional MRI and structural connectivity data from DTI to improve our understanding of brain adaptation mechanisms to neurological disease.

Virtual Infrastructures as a Service enabling Converged Optical Networks and Data Centres

Abstract Cloud computing service emerged as an essential component of the Enterprise {IT} infrastructure. Migration towards a full range and large-scale convergence of Cloud and network services has become the current trend for addressing requirements of the Cloud environment. Our approach takes the infrastructure as a service paradigm to build converged virtual infrastructures, which allow offering tailored performance and enable multi-tenancy over a common physical infrastructure. Thanks to virtualization, new exploitation activities of the physical infrastructures may arise for both transport network and Data Centres services. This approach makes network and Data Centres’ resources dedicated to Cloud Computing to converge on the same flexible and scalable level. The work presented here is based on the automation of the virtual infrastructure provisioning service. On top of the virtual infrastructures, a coordinated operation and control of the different resources is performed with the objective of automatically tailoring connectivity services to the Cloud service dynamics. Furthermore, in order to support elasticity of the Cloud services through the optical network, dynamic re-planning features have been provided to the virtual infrastructure service, which allows scaling up or down existing virtual infrastructures to optimize resource utilisation and dynamically adapt to users’ demands. Thus, the dynamic re-planning of the service becomes key component for the coordination of Cloud and optical network resource in an optimal way in terms of resource utilisation. The presented work is complemented with a use case of the virtual infrastructure service being adopted in a distributed Enterprise Information System, that scales up and down as a function of the application requests.

Validation of network communicability metrics for the analysis of brain structural networks.

Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

Explaining car drivers' intention to prevent road-traffic noise: An application of the Norm Activation Model

Strengthening car drivers’ intention to prevent road-traffic noise is a first step toward noise abatement through voluntary change of behavior. We analyzed predictors of this intention based on the norm activation model (i.e., personal norm, problem awareness, awareness of consequences, social norm, and value orientations). Moreover, we studied the effects of noise exposure, noise sensitivity, and noise annoyance on problem awareness. Data came from 1,002 car drivers who participated in a two-wave longitudinal survey over 4 months. Personal norm had a large prospective effect on intention, even when the previous level of intention was controlled for, and mediated the effect of all other variables on intention. Almost 60% of variance in personal norm was explained by problem awareness, social norm, and biospheric value orientation. The effects of noise sensitivity and noise exposure on problem awareness were small and mediated by noise annoyance. We propose four communication strategies for strengthening the intention to prevent road-traffic noise in car drivers.

Car Design and Road Crossing Behaviour

Humans possess a highly developed sensitivity for facial features. This sensitivity is also deployed to non-human beings and inanimate objects such as cars. In the present study we aimed to investigate whether car design has a bearing on the behaviour of pedestrians. Methods: An immersive virtual reality environment with a zebra crossing was used to determine a) whether the minimum accepted distance for crossing the street is bigger for cars with dominant appearance than for cars with friendly appearance (Block 1) and b) whether the speed of dominant cars are overestimated compared to friendly cars (Block 2). In Block 1, the participant's task was to cross the road in front of an approaching car at the latest moment. The point of time when entering and leaving the street was measured. In Block 2 they were asked to estimate the speed of each passing car. An independent sample rated dominant cars as being more dominant, angry and hostile than friendly cars. Results: None of the predictions regarding the car design was confirmed. Instead, there was an effect of starting position: From the centre island, participants entered the road significantly later (smaller accepted distance) and left the road later than when starting from the pavement. Consistently, the speed of the cars was estimated significantly lower when standing on the centre island compared to the pavement. When entering the visual size of the cars as factor (instead of dominance), we found that participants started to cross the road significantly later in front of small cars compared to big cars and that the speed of smaller cars was overestimated compared to big cars (size-speed bias). Conclusions: Car size and starting position, not car design seem to have an influence on road crossing behaviour.

A high-resolution map of direct and indirect connectivity of erosion risk areas to surface waters in Switzerland: A risk assessment tool for planning and policy-making

Off-site effects of soil erosion are becoming increasingly important, particularly the pollution of surface waters. In order to develop environmentally efficient and cost effective mitigation options it is essential to identify areas that bear both a high erosion risk and high connectivity to surface waters. This paper introduces a simple risk assessment tool that allows the delineation of potential critical source areas (CSA) of sediment input into surface waters concerning the agricultural areas of Switzerland. The basis are the erosion risk map with a 2 m resolution (ERM2) and the drainage network, which is extended by drained roads, farm tracks, and slope depressions. The probability of hydrological and sedimentological connectivity is assessed by combining soil erosion risk and extended drainage network with flow distance calculation. A GIS-environment with multiple-flow accumulation algorithms is used for routing runoff generation and flow pathways. The result is a high resolution connectivity map of the agricultural area of Switzerland (888,050 ha). Fifty-five percent of the computed agricultural area is potentially connected with surface waters, 45% is not connected. Surprisingly, the larger part of 34% (62% of the connected area) is indirectly connected with surface waters through drained roads, and only 21% are directly connected. The reason is the topographic complexity and patchiness of the landscape due to a dense road and drainage network. A total of 24% of the connected area and 13% of the computed agricultural area, respectively, are rated with a high connectivity probability. On these CSA an adapted land use is recommended, supported by vegetated buffer strips preventing sediment load. Even areas that are far away from open water bodies can be indirectly connected and need to be included in planning of mitigation measures. Thus, the connectivity map presented is an important decision-making tool for policy-makers and extension services. The map is published on the web and thus available for application.

Risk of severe hypoglycemia in sulfonylurea-treated patients from diabetes centers in Germany/Austria: how big is the problem? which patients are at risk?

BACKGROUND We investigated the rate of severe hypoglycemic events and confounding factors in patients with type-2-diabetes treated with sulfonylurea (SU) at specialized diabetes centers, documented in the German/Austrian DPV-Wiss-database. METHODS Data from 29,485 SU-treated patients were analyzed (median[IQR] age 70.8[62.2-77.8]yrs, diabetes-duration 8.2[4.3-12.8]yrs). The primary objective was to estimate the event-rate of severe hypoglycemia (requiring external help, causing unconsciousness/coma/convulsion and/or emergency.hospitalization). Secondary objectives included exploration of confounding risk-factors through group-comparison and Poisson-regression. RESULTS Severe hypoglycemic events were reported in 826(2.8%) of all patients during their most recent year of SU-treatment. Of these, n = 531(1.8%) had coma, n = 501(1.7%) were hospitalized at least once. The adjusted event-rate of severe hypoglycemia [95%CI] was 3.9[3.7-4.2] events/100 patient-years (coma: 1.9[1.8-2.1]; hospitalization: 1.6[1.5-1.8]). Adjusted event-rates by diabetes-treatment were 6.7 (SU + insulin), 4.9 (SU + insulin + other OAD), 3.1 (SU + other OAD), and 3.8 (SU only). Patients with ≥1 severe event were older (p < 0.001) and had longer diabetes-duration (p = 0.020) than patients without severe events. Participation in educational diabetes-programs and indirect measures of insulin-resistance (increased BMI, plasma-triglycerides) were associated with fewer events (all p < 0.001). Impaired renal function was common (N = 3,113 eGFR ≤30 mL/min) and associated with an increased rate of severe events (≤30 mL/min: 7.7; 30-60 mL/min: 4.8; >60 mL/min: 3.9). CONCLUSIONS These real-life data showed a rate of severe hypoglycemia of 3.9/100 patient-years in SU-treated patients from specialized diabetes centers. Higher risk was associated with known risk-factors including lack of diabetes-education, older age, and decreased eGFR, but also with lower BMI and lower triglyceride-levels, suggesting that SU-treatment in those patients should be considered with caution. This article is protected by copyright. All rights reserved.