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- ItemBrain anomaly networks uncover heterogeneous functional reorganization patterns after stroke([Amsterdam u.a.] : Elsevier, 2018) Zou, Yong; Zhao, Zhiyong; Yin, Dazhi; Fan, Mingxia; Small, Michael; Liu, Zonghua; Hilgetag, Claus C.; Kurths, JürgenStroke has a large physical, psychological, and financial burden on patients, their families, and society. Based on functional networks (FNs) constructed from resting state fMRI data, network connectivity after stroke is commonly conjectured to be more randomly reconfigured. We find that this hypothesis depends on the severity of stroke. Head movement-corrected, resting-state fMRI data were acquired from 32 patients after stroke, and 37 healthy volunteers. We constructed anomaly FNs, which combine time series information of a patient with the healthy control group. We propose data-driven techniques to automatically identify regions of interest that are stroke relevant. Graph analysis based on anomaly FNs suggests consistently that strong connections in healthy controls are broken down specifically and characteristically for brain areas that are related to sensorimotor functions and frontoparietal control systems, but new links in stroke patients are rebuilt randomly from all possible areas. Entropic measures of complexity are proposed for characterizing the functional connectivity reorganization patterns, which are correlated with hand and wrist function assessments of stroke patients and show high potential for clinical use.
- ItemApplication of optical coherence tomography for in vivo monitoring of the meningeal lymphatic vessels during opening of blood–brain barrier: mechanisms of brain clearing(Bellingham, Wash. : SPIE, 2017) Semyachkina-Glushkovskaya, Oxana; Abdurashitov, Arkady; Dubrovsky, Alexander; Bragin, Denis; Bragina, Olga; Shushunova, Natalia; Maslyakova, Galina; Navolokin, Nikita; Bucharskaya, Alla; Tuchind, Valery; Kurths, Jürgen; Shirokov, AlexanderThe meningeal lymphatic vessels were discovered 2 years ago as the drainage system involved in the mechanisms underlying the clearance of waste products from the brain. The blood–brain barrier (BBB) is a gatekeeper that strongly controls the movement of different molecules from the blood into the brain. We know the scenarios during the opening of the BBB, but there is extremely limited information on how the brain clears the substances that cross the BBB. Here, using the model of sound-induced opening of the BBB, we clearly show how the brain clears dextran after it crosses the BBB via the meningeal lymphatic vessels. We first demonstrate successful application of optical coherence tomography (OCT) for imaging of the lymphatic vessels in the meninges after opening of the BBB, which might be a new useful strategy for noninvasive analysis of lymphatic drainage in daily clinical practice. Also, we give information about the depth and size of the meningeal lymphatic vessels in mice. These new fundamental data with the applied focus on the OCT shed light on the mechanisms of brain clearance and the role of lymphatic drainage in these processes that could serve as an informative platform for a development of therapy and diagnostics of diseases associated with injuries of the BBB such as stroke, brain trauma, glioma, depression, or Alzheimer disease.
- ItemCoupling between leg muscle activation and EEG during normal walking, intentional stops, and freezing of gait in Parkinson's disease(Lausanne : Frontiers Media, 2019) Günther, Moritz; Bartsch, Ronny P.; Miron-Shahar, Yael; Hassin-Baer, Sharon; Inzelberg, Rivka; Kurths, Jürgen; Plotnik, Meir; Kantelhardt, Jan W.In this paper, we apply novel techniques for characterizing leg muscle activation patterns via electromyograms (EMGs) and for relating them to changes in electroencephalogram (EEG) activity during gait experiments. Specifically, we investigate changes of leg-muscle EMG amplitudes and EMG frequencies during walking, intentional stops, and unintended freezing-of-gait (FOG) episodes. FOG is a frequent paroxysmal gait disturbance occurring in many patients suffering from Parkinson's disease (PD). We find that EMG amplitudes and frequencies do not change significantly during FOG episodes with respect to walking, while drastic changes occur during intentional stops. Phase synchronization between EMG signals is most pronounced during walking in controls and reduced in PD patients. By analyzing cross-correlations between changes in EMG patterns and brain-wave amplitudes (from EEGs), we find an increase in EEG-EMG coupling at the beginning of stop and FOG episodes. Our results may help to better understand the enigmatic pathophysiology of FOG, to differentiate between FOG events and other gait disturbances, and ultimately to improve diagnostic procedures for patients suffering from PD. Copyright © 2019 Günther, Bartsch, Miron-Shahar, Hassin-Baer, Inzelberg, Kurths, Plotnik and Kantelhardt.
- ItemIncreasing Human Performance by Sharing Cognitive Load Using Brain-to-Brain Interface(Lausanne : Frontiers Research Foundation, 2018) Maksimenko, Vladimir A.; Hramov, Alexander E.; Frolov, Nikita S.; Lüttjohann, Annika; Nedaivozov, Vladimir O.; Grubov, Vadim V.; Runnova, Anastasia E.; Makarov, Vladimir V.; Kurths, Jürgen; Pisarchik, Alexander N.Brain-computer interfaces (BCIs) attract a lot of attention because of their ability to improve the brain's efficiency in performing complex tasks using a computer. Furthermore, BCIs can increase human's performance not only due to human-machine interactions, but also thanks to an optimal distribution of cognitive load among all members of a group working on a common task, i.e., due to human-human interaction. The latter is of particular importance when sustained attention and alertness are required. In every day practice, this is a common occurrence, for example, among office workers, pilots of a military or a civil aircraft, power plant operators, etc. Their routinely work includes continuous monitoring of instrument readings and implies a heavy cognitive load due to processing large amounts of visual information. In this paper, we propose a brain-to-brain interface (BBI) which estimates brain states of every participant and distributes a cognitive load among all members of the group accomplishing together a common task. The BBI allows sharing the whole workload between all participants depending on their current cognitive performance estimated from their electrical brain activity. We show that the team efficiency can be increased due to redistribution of the work between participants so that the most difficult workload falls on the operator who exhibits maximum performance. Finally, we demonstrate that the human-to-human interaction is more efficient in the presence of a certain delay determined by brain rhythms. The obtained results are promising for the development of a new generation of communication systems based on neurophysiological brain activity of interacting people. Such BBIs will distribute a common task between all group members according to their individual physical conditions.
- ItemNeural Interactions in a Spatially-Distributed Cortical Network During Perceptual Decision-Making(Lausanne : Frontiers Media, 2019) Maksimenko, Vladimir A.; Frolov, Nikita S.; Hramov, Alexander E.; Runnova, Anastasia E.; Grubov, Vadim V.; Kurths, Jürgen; Pisarchik, Alexander N.Behavioral experiments evidence that attention is not maintained at a constant level, but fluctuates with time. Recent studies associate such fluctuations with dynamics of attention-related cortical networks, however the exact mechanism remains unclear. To address this issue, we consider functional neuronal interactions during the accomplishment of a reaction time (RT) task which requires sustained attention. The participants are subjected to a binary classification of a large number of presented ambiguous visual stimuli with different degrees of ambiguity. Generally, high ambiguity causes high RT and vice versa. However, we demonstrate that RT fluctuates even when the stimulus ambiguity remains unchanged. The analysis of neuronal activity reveals that the subject's behavioral response is preceded by the formation of a distributed functional network in the β-frequency band. This network is characterized by high connectivity in the frontal cortex and supposed to subserve a decision-making process. We show that neither the network structure nor the duration of its formation depend on RT and stimulus ambiguity. In turn, RT is related to the moment of time when the β-band functional network emerges. We hypothesize that RT is affected by the processes preceding the decision-making stage, e.g., encoding visual sensory information and extracting decision-relevant features from raw sensory information. © Copyright © 2019 Maksimenko, Frolov, Hramov, Runnova, Grubov, Kurths and Pisarchik.
- ItemBistable firing pattern in a neural network model(Lausanne : Frontiers Media, 2019) Protachevicz, Paulo R.; Borges, Fernando S.; Lameu, Ewandson L.; Ji, Peng; Iarosz, Kelly C.; Kihara, Alexandre H.; Caldas, Ibere L.; Szezech Jr., Jose D.; Baptista, Murilo S.; Macau, Elbert E.N.; Antonopoulos, Chris G.; Batista, Antonio M.; Kurths, JürgenExcessively high, neural synchronization has been associated with epileptic seizures, one of the most common brain diseases worldwide. A better understanding of neural synchronization mechanisms can thus help control or even treat epilepsy. In this paper, we study neural synchronization in a random network where nodes are neurons with excitatory and inhibitory synapses, and neural activity for each node is provided by the adaptive exponential integrate-and-fire model. In this framework, we verify that the decrease in the influence of inhibition can generate synchronization originating from a pattern of desynchronized spikes. The transition from desynchronous spikes to synchronous bursts of activity, induced by varying the synaptic coupling, emerges in a hysteresis loop due to bistability where abnormal (excessively high synchronous) regimes exist. We verify that, for parameters in the bistability regime, a square current pulse can trigger excessively high (abnormal) synchronization, a process that can reproduce features of epileptic seizures. Then, we show that it is possible to suppress such abnormal synchronization by applying a small-amplitude external current on > 10% of the neurons in the network. Our results demonstrate that external electrical stimulation not only can trigger synchronous behavior, but more importantly, it can be used as a means to reduce abnormal synchronization and thus, control or treat effectively epileptic seizures. © 2019 Protachevicz, Borges, Lameu, Ji, Iarosz, Kihara, Caldas, Szezech, Baptista, Macau, Antonopoulos, Batista and Kurths.
- ItemFood and agricultural approaches to reducing malnutrition (FAARM): Protocol for a cluster-randomised controlled trial to evaluate the impact of a Homestead Food Production programme on undernutrition in rural Bangladesh(London : BMJ Publishing Group, 2019) Wendt, Amanda S.; Sparling, Thalia M.; Waid, Jillian L.; Mueller, Anna A.; Gabrysch, SabineIntroduction Chronic undernutrition affects over 150 million children worldwide and has serious consequences. The causes are complex and include insufficient dietary diversity and poor hygiene practices. Systematic reviews of nutrition-sensitive agricultural interventions concluded that while these hold promise, there is insufficient evidence for their impact on child growth. The Food and Agricultural Approaches to Reducing Malnutrition (FAARM) project is a 1:1 cluster-randomised trial aiming to evaluate the impact of a Homestead Food Production (HFP) programme implemented by Helen Keller International on women's and children's undernutrition. Methods and analysis The HFP intervention comprises training of women's groups and asset distribution to support year-round home gardening, poultry rearing and improved nutrition and hygiene practices. Formal trainings are supplemented by behaviour change communication during household visits, and facilitated links between producer groups and market actors. The FAARM trial will examine if and how this complex intervention reduces undernutrition. In 2015, FAARM enrolled married women and their children (0-3 years) in 96 rural settlements of Habiganj district in Sylhet division, Bangladesh. Covariate-constrained randomisation was used to assign 48 settlements to receive a 3-year HFP intervention, with the other 48 acting as controls, targeting over 2700 women. To study impact pathways, a surveillance system collects data on all participants every 2 months. In late 2019, children 0-3 years of age (born during the intervention period) will be surveyed, thus capturing impact during the critical first 1000 days of life. Children's length/height-for-age z-scores will be compared between intervention and control arms using mixed-effects linear regression. Secondary outcomes include women's and children's micronutrient status, dietary intake, dietary diversity and other indicators of child growth, development and morbidity. Ethics and dissemination Ethical approval was received in Bangladesh and Germany. Results will be disseminated through peer-reviewed publications and presentations in Bangladesh and internationally. Trial registration number NCT02505711; Pre-results. © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. Published by BMJ.
- ItemThe stability of memristive multidirectional associative memory neural networks with time-varying delays in the leakage terms via sampled-data control(San Francisco, California, US : PLOS, 2018) Wang, Weiping; Yu, Xin; Luo, Xiong; Wang, Long; Li, Lixiang; Kurths, Jürgen; Zhao, Wenbing; Xiao, JiuhongIn this paper, we propose a new model of memristive multidirectional associative memory neural networks, which concludes the time-varying delays in leakage terms via sampled-data control. We use the input delay method to turn the sampling system into a continuous time-delaying system. Then we analyze the exponential stability and asymptotic stability of the equilibrium points for this model. By constructing a suitable Lyapunov function, using the Lyapunov stability theorem and some inequality techniques, some sufficient criteria for ensuring the stability of equilibrium points are obtained. Finally, numerical examples are given to demonstrate the effectiveness of our results.
- ItemParameterization-induced uncertainties and impacts of crop management harmonization in a global gridded crop model ensemble(San Francisco, California, US : PLOS, 2019) Folberth, Christian; Elliott, Joshua; Müller, Christoph; Balkovič, Juraj; Chryssanthacopoulos, James; Izaurralde, Roberto C.; Jones, Curtis D.; Khabarov, Nikolay; Liu, Wenfeng; Reddy, Ashwan; Schmid, Erwin; Skalský, Rastislav; Yang, Hong; Arneth, Almut; Ciais, Philippe; Deryng, Delphine; Lawrence, Peter J.; Olin, Stefan; Pugh, Thomas A.M.; Ruane, Alex C.; Wang, XuhuiGlobal gridded crop models (GGCMs) combine agronomic or plant growth models with gridded spatial input data to estimate spatially explicit crop yields and agricultural externalities at the global scale. Differences in GGCM outputs arise from the use of different biophysical models, setups, and input data. GGCM ensembles are frequently employed to bracket uncertainties in impact studies without investigating the causes of divergence in outputs. This study explores differences in maize yield estimates from five GGCMs based on the public domain field-scale model Environmental Policy Integrated Climate (EPIC) that participate in the AgMIP Global Gridded Crop Model Intercomparison initiative. Albeit using the same crop model, the GGCMs differ in model version, input data, management assumptions, parameterization, and selection of subroutines affecting crop yield estimates via cultivar distributions, soil attributes, and hydrology among others. The analyses reveal inter-annual yield variability and absolute yield levels in the EPIC-based GGCMs to be highly sensitive to soil parameterization and crop management. All GGCMs show an intermediate performance in reproducing reported yields with a higher skill if a static soil profile is assumed or sufficient plant nutrients are supplied. An in-depth comparison of setup domains for two EPIC-based GGCMs shows that GGCM performance and plant stress responses depend substantially on soil parameters and soil process parameterization, i.e. hydrology and nutrient turnover, indicating that these often neglected domains deserve more scrutiny. For agricultural impact assessments, employing a GGCM ensemble with its widely varying assumptions in setups appears the best solution for coping with uncertainties from lack of comprehensive global data on crop management, cultivar distributions and coefficients for agro-environmental processes. However, the underlying assumptions require systematic specifications to cover representative agricultural systems and environmental conditions. Furthermore, the interlinkage of parameter sensitivity from various domains such as soil parameters, nutrient turnover coefficients, and cultivar specifications highlights that global sensitivity analyses and calibration need to be performed in an integrated manner to avoid bias resulting from disregarded core model domains. Finally, relating evaluations of the EPIC-based GGCMs to a wider ensemble based on individual core models shows that structural differences outweigh in general differences in configurations of GGCMs based on the same model, and that the ensemble mean gains higher skill from the inclusion of structurally different GGCMs. Although the members of the wider ensemble herein do not consider crop-soil-management interactions, their sensitivity to nutrient supply indicates that findings for the EPIC-based sub-ensemble will likely become relevant for other GGCMs with the progressing inclusion of such processes.
- ItemA meta-analysis of crop response patterns to nitrogen limitation for improved model representation(San Francisco, California, US : PLOS, 2019) Seufert, Verena; Granath, Gustaf; Müller, ChristophThe representation of carbon-nitrogen (N) interactions in global models of the natural or managed land surface remains an important knowledge gap. To improve global process-based models we require a better understanding of how N limitation affects photosynthesis and plant growth. Here we present the findings of a meta-analysis to quantitatively assess the impact of N limitation on source (photosynthate production) versus sink (photosynthate use) activity, based on 77 highly controlled experimental N availability studies on 11 crop species. Using meta-regressions, we find that it can be insufficient to represent N limitation in models merely as inhibiting carbon assimilation, because in crops complete N limitation more strongly influences leaf area expansion (-50%) than photosynthesis (-34%), while leaf starch is accumulating (+83%). Our analysis thus offers support for the hypothesis of sink limitation of photosynthesis and encourages the exploration of more sink-driven crop modelling approaches. We also show that leaf N concentration changes with N availability and that the allocation of N to Rubisco is reduced more strongly compared to other photosynthetic proteins at low N availability. Furthermore, our results suggest that different crop species show generally similar response patterns to N limitation, with the exception of leguminous crops, which respond differently. Our meta-analysis offers lessons for the improved depiction of N limitation in global terrestrial ecosystem models, as well as highlights knowledge gaps that need to be filled by future experimental studies on crop N limitation response.