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- 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.
- 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.
- 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.
- ItemModification of brain oscillations via rhythmic light stimulation provides evidence for entrainment but not for superposition of event-related responses(Lausanne : Frontiers Media, 2016) Notbohm, Annika; Kurths, Jürgen; Herrmann, Christoph S.The functional relevance of brain oscillations in the alpha frequency range (8–13 Hz) has been repeatedly investigated through the use of rhythmic visual stimulation. The underlying mechanism of the steady-state visual evoked potential (SSVEP) measured in EEG during rhythmic stimulation, however, is not known. There are two hypotheses on the origin of SSVEPs: entrainment of brain oscillations and superposition of event-related responses (ERPs). The entrainment but not the superposition hypothesis justifies rhythmic visual stimulation as a means to manipulate brain oscillations, because superposition assumes a linear summation of single responses, independent from ongoing brain oscillations. Here, we stimulated participants with a rhythmic flickering light of different frequencies and intensities. We measured entrainment by comparing the phase coupling of brain oscillations stimulated by rhythmic visual flicker with the oscillations induced by arrhythmic jittered stimulation, varying the time, stimulation frequency, and intensity conditions. In line with a theoretical concept of entrainment (the so called Arnold tongue), we found the phase coupling to be more pronounced with increasing stimulation intensity as well as at stimulation frequencies closer to each participant's intrinsic frequency. Only inside the Arnold tongue did the conditions significantly differ from the jittered stimulation. Furthermore, even in a single sequence of an SSVEP, we found non-linear features (intermittency of phase locking) that contradict the linear summation of single responses, as assumed by the superposition hypothesis. Our findings provide unequivocal evidence that visual rhythmic stimulation entrains brain oscillations, thus validating the approach of rhythmic stimulation as a manipulation of brain oscillations.
- 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.
- 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.
- 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.
- ItemThe stress and vascular catastrophes in newborn rats: Mechanisms preceding and accompanying the brain hemorrhages(Lausanne : Frontiers Media, 2016) Semyachkina-Glushkovskaya, Oxana; Borisova, Ekaterina; Abakumov, Maxim; Gorin, Dmitry; Avramov, Latchezar; Fedosov, Ivan; Namykin, Anton; Abdurashitov, Arkady; Serov, Alexander; Pavlov, Alexey; Zinchenko, Ekaterina; Lychagov, Vlad; Navolokin, Nikita; Shirokov, Alexander; Maslyakova, Galina; Zhu, Dan; Luo, Qingming; Chekhonin, Vladimir; Tuchin, Valery; Kurths, JürgenIn this study, we analyzed the time-depended scenario of stress response cascade preceding and accompanying brain hemorrhages in newborn rats using an interdisciplinary approach based on: a morphological analysis of brain tissues, coherent-domain optical technologies for visualization of the cerebral blood flow, monitoring of the cerebral oxygenation and the deformability of red blood cells (RBCs). Using a model of stress-induced brain hemorrhages (sound stress, 120 dB, 370 Hz), we studied changes in neonatal brain 2, 4, 6, 8 h after stress (the pre-hemorrhage, latent period) and 24 h after stress (the post-hemorrhage period). We found that latent period of brain hemorrhages is accompanied by gradual pathological changes in systemic, metabolic, and cellular levels of stress. The incidence of brain hemorrhages is characterized by a progression of these changes and the irreversible cell death in the brain areas involved in higher mental functions. These processes are realized via a time-depended reduction of cerebral venous blood flow and oxygenation that was accompanied by an increase in RBCs deformability. The significant depletion of the molecular layer of the prefrontal cortex and the pyramidal neurons, which are crucial for associative learning and attention, is developed as a consequence of homeostasis imbalance. Thus, stress-induced processes preceding and accompanying brain hemorrhages in neonatal period contribute to serious injuries of the brain blood circulation, cerebral metabolic activity and structural elements of cognitive function. These results are an informative platform for further studies of mechanisms underlying stress-induced brain hemorrhages during the first days of life that will improve the future generation's health.
- 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.