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Journal articles on the topic 'Microstate analysis'

Author: Grafiati

Published: 28 June 2021

Last updated: 11 February 2022

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1

Fu, Yunfa, Jian Chen, and Xin Xiong. "Calculation and Analysis of Microstate Related to Variation in Executed and Imagined Movement of Force of Hand Clenching." Computational Intelligence and Neuroscience 2018 (August 27, 2018): 1–15. http://dx.doi.org/10.1155/2018/9270685.

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Objective. In order to investigate electroencephalogram (EEG) instantaneous activity states related to executed and imagined movement of force of hand clenching (grip force: 4 kg, 10 kg, and 16 kg), we utilized a microstate analysis in which the spatial topographic map of EEG behaves in a certain number of discrete and stable global brain states. Approach. Twenty subjects participated in EEG collection; the global field power of EEG and its local maximum were calculated and then clustered using cross validation and statistics; the 4 parameters of each microstate (duration, occurrence, time coverage, and amplitude) were calculated from the clustering results and statistically analyzed by analysis of variance (ANOVA); finally, the relationship between the microstate and frequency band was analyzed. Main Results. The experimental results showed that all microstates related to executed and imagined grip force tasks were clustered into 3 microstate classes (A, B, and C); these microstates generally transitioned from A to B and then from B to C. With the increase of the target value of executed and imagined grip force, the duration and time coverage of microstate B gradually decreased, while these parameters of microstate C gradually increased. The occurrence times of microstate B and C related to executed grip force were significantly more than those related to imagined grip force; furthermore, the amplitudes of these 3 microstates related to executed grip force were significantly greater than those related to imagined grip force. The correlation coefficients between the microstates and the frequency bands indicated that the microstates were correlated to mu rhythm and beta frequency bands, which are consistent with event-related desynchronization/synchronization (ERD/ERS) phenomena of sensorimotor rhythm. Significance. It is expected that this microstate analysis may be used as a new method for observing EEG instantaneous activity patterns related to variation in executed and imagined grip force and also for extracting EEG features related to these tasks. This study may lay a foundation for the application of executed and imagined grip force training for rehabilitation of hand movement disorders in patients with stroke in the future.

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Khazaei, Mohammad, Khadijeh Raeisi, Pierpaolo Croce, Gabriella Tamburro, Anton Tokariev, Sampsa Vanhatalo, Filippo Zappasodi, and Silvia Comani. "Characterization of the Functional Dynamics in the Neonatal Brain during REM and NREM Sleep States by means of Microstate Analysis." Brain Topography 34, no. 5 (July 13, 2021): 555–67. http://dx.doi.org/10.1007/s10548-021-00861-1.

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AbstractNeonates spend most of their life sleeping. During sleep, their brain experiences fast changes in its functional organization. Microstate analysis permits to capture the rapid dynamical changes occurring in the functional organization of the brain by representing the changing spatio-temporal features of the electroencephalogram (EEG) as a sequence of short-lasting scalp topographies—the microstates. In this study, we modeled the ongoing neonatal EEG into sequences of a limited number of microstates and investigated whether the extracted microstate features are altered in REM and NREM sleep (usually known as active and quiet sleep states—AS and QS—in the newborn) and depend on the EEG frequency band. 19-channel EEG recordings from 60 full-term healthy infants were analyzed using a modified version of the k-means clustering algorithm. The results show that ~ 70% of the variance in the datasets can be described using 7 dominant microstate templates. The mean duration and mean occurrence of the dominant microstates were significantly different in the two sleep states. Microstate syntax analysis demonstrated that the microstate sequences characterizing AS and QS had specific non-casual structures that differed in the two sleep states. Microstate analysis of the neonatal EEG in specific frequency bands showed a clear dependence of the explained variance on frequency. Overall, our findings demonstrate that (1) the spatio-temporal dynamics of the neonatal EEG can be described by non-casual sequences of a limited number of microstate templates; (2) the brain dynamics described by these microstate templates depends on frequency; (3) the features of the microstate sequences can well differentiate the physiological conditions characterizing AS and QS.

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Shaw, Saurabh Bhaskar, Kiret Dhindsa, James P. Reilly, and Suzanna Becker. "Capturing the Forest but Missing the Trees: Microstates Inadequate for Characterizing Shorter-Scale EEG Dynamics." Neural Computation 31, no. 11 (November 2019): 2177–211. http://dx.doi.org/10.1162/neco_a_01229.

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The brain is known to be active even when not performing any overt cognitive tasks, and often it engages in involuntary mind wandering. This resting state has been extensively characterized in terms of fMRI-derived brain networks. However, an alternate method has recently gained popularity: EEG microstate analysis. Proponents of microstates postulate that the brain discontinuously switches between four quasi-stable states defined by specific EEG scalp topologies at peaks in the global field potential (GFP). These microstates are thought to be “atoms of thought,” involved with visual, auditory, salience, and attention processing. However, this method makes some major assumptions by excluding EEG data outside the GFP peaks and then clustering the EEG scalp topologies at the GFP peaks, assuming that only one microstate is active at any given time. This study explores the evidence surrounding these assumptions by studying the temporal dynamics of microstates and its clustering space using tools from dynamical systems analysis, fractal, and chaos theory to highlight the shortcomings in microstate analysis. The results show evidence of complex and chaotic EEG dynamics outside the GFP peaks, which is being missed by microstate analysis. Furthermore, the winner-takes-all approach of only one microstate being active at a time is found to be inadequate since the dynamic EEG scalp topology does not always resemble that of the assigned microstate, and there is competition among the different microstate classes. Finally, clustering space analysis shows that the four microstates do not cluster into four distinct and separable clusters. Taken collectively, these results show that the discontinuous description of EEG microstates is inadequate when looking at nonstationary short-scale EEG dynamics.

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4

Shi, Wen, Yamin Li, Zhian Liu, Jing Li, Qiang Wang, Xiangguo Yan, and Gang Wang. "Non-Canonical Microstate Becomes Salient in High Density EEG During Propofol-Induced Altered States of Consciousness." International Journal of Neural Systems 30, no. 02 (January 23, 2020): 2050005. http://dx.doi.org/10.1142/s0129065720500057.

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Dynamically assessing the level of consciousness is still challenging during anesthesia. With the help of Electroencephalography (EEG), the human brain electric activity can be noninvasively measured at high temporal resolution. Several typical quasi-stable states are introduced to represent the oscillation of the global scalp electric field. These so-called microstates reflect spatiotemporal dynamics of coherent neural activities and capture the switch of brain states within the millisecond range. In this study, the microstates of high-density EEG were extracted and investigated during propofol-induced transition of consciousness. To analyze microstates on the frequency domain, a novel microstate-wise spectral analysis was proposed by the means of multivariate empirical mode decomposition and Hilbert–Huang transform. During the transition of consciousness, a map with a posterior central maximum denoted as microstate F appeared and became salient. The current results indicated that the coverage, occurrence, and power of microstate F significantly increased in moderate sedation. The results also demonstrated that the transition of brain state from rest to sedation was accompanied by significant increase in mean energy of all frequency bands in microstate F. Combined with studies on the possible cortical sources of microstates, the findings reveal that non-canonical microstate F is highly associated with propofol-induced altered states of consciousness. The results may also support the inference that this distinct topography can be derived from canonical microstate C (anterior-posterior orientation). Finally, this study further develops pertinent methodology and extends possible applications of the EEG microstate during propofol-induced anesthesia.

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5

Kim, Kyungwon, Nguyen Thanh Duc, Min Choi, and Boreom Lee. "EEG microstate features for schizophrenia classification." PLOS ONE 16, no. 5 (May 14, 2021): e0251842. http://dx.doi.org/10.1371/journal.pone.0251842.

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Electroencephalography (EEG) microstate analysis is a method wherein spontaneous EEG activity is segmented at sub-second levels to analyze quasi-stable states. In particular, four archetype microstates and their features are known to reflect changes in brain state in neuropsychiatric diseases. However, previous studies have only reported differences in each microstate feature and have not determined whether microstate features are suitable for schizophrenia classification. Therefore, it is necessary to validate microstate features for schizophrenia classification. Nineteen microstate features, including duration, occurrence, and coverage as well as thirty-one conventional EEG features, including statistical, frequency, and temporal characteristics were obtained from resting-state EEG recordings of 14 patients diagnosed with schizophrenia and from 14 healthy (control) subjects. Machine-learning based multivariate analysis was used to evaluate classification performance. EEG recordings of patients and controls showed different microstate features. More importantly, when differentiating among patients and controls, EEG microstate features outperformed conventional EEG ones. The performance of the microstate features exceeded that of conventional EEG, even after optimization using recursive feature elimination. EEG microstate features applied with conventional EEG features also showed better classification performance than conventional EEG features alone. The current study is the first to validate the use of microstate features to discriminate schizophrenia, suggesting that EEG microstate features are useful for schizophrenia classification.

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6

Jabès, Adeline, Giuliana Klencklen, Paolo Ruggeri, Christoph M. Michel, Pamela Banta Lavenex, and Pierre Lavenex. "Resting‐State EEG Microstates Parallel Age‐Related Differences in Allocentric Spatial Working Memory Performance." Brain Topography 34, no. 4 (April 19, 2021): 442–60. http://dx.doi.org/10.1007/s10548-021-00835-3.

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AbstractAlterations of resting-state EEG microstates have been associated with various neurological disorders and behavioral states. Interestingly, age-related differences in EEG microstate organization have also been reported, and it has been suggested that resting-state EEG activity may predict cognitive capacities in healthy individuals across the lifespan. In this exploratory study, we performed a microstate analysis of resting-state brain activity and tested allocentric spatial working memory performance in healthy adult individuals: twenty 25–30-year-olds and twenty-five 64–75-year-olds. We found a lower spatial working memory performance in older adults, as well as age-related differences in the five EEG microstate maps A, B, C, C′ and D, but especially in microstate maps C and C′. These two maps have been linked to neuronal activity in the frontal and parietal brain regions which are associated with working memory and attention, cognitive functions that have been shown to be sensitive to aging. Older adults exhibited lower global explained variance and occurrence of maps C and C′. Moreover, although there was a higher probability to transition from any map towards maps C, C′ and D in young and older adults, this probability was lower in older adults. Finally, although age-related differences in resting-state EEG microstates paralleled differences in allocentric spatial working memory performance, we found no evidence that any individual or combination of resting-state EEG microstate parameter(s) could reliably predict individual spatial working memory performance. Whether the temporal dynamics of EEG microstates may be used to assess healthy cognitive aging from resting-state brain activity requires further investigation.

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7

Ruiz, Pablo, Raquel Tinoco-Egas, and Carlos Cevallos. "Neural States in Tourism Travel Videos." Proceedings 71, no. 1 (November 18, 2020): 6. http://dx.doi.org/10.3390/iecbs-08465.

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In marketing, there are many methods to relate reactions to products to customer preference. Current electroencephalography (EEG) signal analysis in the neuromarketing field focuses mainly on correlations between selected electrodes and hemisphere-based analysis on single scalp measures. The present study shows microstate analysis of brain EEG signals in goal-oriented videos. We measured a 16 channel EEG with an Emotiv EPOC+ device. We used two oriented videos from the Ecuadorian Government to publicize Ecuador as a tourist destination. We used a Topographic Atomize and Agglomerate Hierarchical Clustering (TAAHC) microstate analysis for the duration of the EEG as the participants watched each video. We picked the four predominant, in total time and repeatability, microstate maps that represent more than 50% of the entire recording time. We also show, in time, how topographies are represented along the video, which in a later step could be correlated with the images observed in the videos. We show the existing relations between the existing microstates. A microstate analysis of brain signal behavior across time might be a valid methodology and useful tool to analyze videos with marketing purposes.

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8

Liang, Andi, Shanguang Zhao, Jing Song, Yan Zhang, Yue Zhang, Xiaodan Niu, Tao Xiao, and Aiping Chi. "Treatment Effect of Exercise Intervention for Female College Students with Depression: Analysis of Electroencephalogram Microstates and Power Spectrum." Sustainability 13, no. 12 (June 16, 2021): 6822. http://dx.doi.org/10.3390/su13126822.

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This paper aims to assess the effect of exercise intervention on the improvement of college students with depression and to explore the change characteristics of microstates and the power spectrum in their resting-state electroencephalogram (EEG). Forty female college students with moderate depression were screened according to the Beck Depression Inventory-II (BDI-II) and Depression Self-Rating Scale (SDS) scores, and half of them received an exercise intervention for 18 weeks. The study utilized an EEG to define the resting-state networks, and the scores of all the participants were tracked during the intervention. Compared with those in the depression group, the power spectrum values in the θ and α bands were significantly decreased (p < 0.05), and the duration of microstate C increased significantly (p < 0.05), while the frequency of microstate B decreased significantly (p < 0.05) in the exercise intervention group. The transition probabilities showed that the exercise intervention group had a higher probability from B to D than those in the depression group (p < 0.01). In addition, the power of the δ and α bands were negatively correlated with the occurrence of microstate C (r = −0.842, p < 0.05 and r = −0.885, p < 0.01, respectively), and the power of the β band was positively correlated with the duration of microstate C (r = 0.900, p < 0.01) after exercise intervention. Our results suggest that the decreased duration of microstate C and the increased α power in depressed students are associated with reduced cognitive ability, emotional stability, and brain activity. Depression symptoms were notably improved after exercise intervention, thus providing a more scientific index for the research, rehabilitation mechanisms, and treatment of depression.

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9

Milz, P. "Keypy – An Open Source Library For EEG Microstate Analysis." European Psychiatry 33, S1 (March 2016): S493. http://dx.doi.org/10.1016/j.eurpsy.2016.01.1812.

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The brain's electric field configuration reflects its momentary, global functional state. The fluctuations of these states can be analyzed at millisecond resolution by the EEG microstate analysis. This analysis reportedly allowed the detection of brain state duration, occurrence, and sequence aberrations in psychiatric disorders such as schizophrenia, dementia, and depression. Several existing software solutions implement the microstate analysis, but they all require extensive user-interaction. This represents a major obstacle to time-efficient automated analyses and parameter exploration of large EEG datasets. Scriptable programming languages such as Python provide a means to efficiently automate such analysis workflows.For this reason, I developed the KEY EEG Python Library keypy. This library implements all steps necessary to compute the microstate analysis based on artefact free segments of EEG. It includes functions to carry out the necessary preprocessing (data loading, filtering, average referencing), modified k-means clustering based microstate identification, principal component based mean computation (across recording runs, conditions, participants, and or participant groups), and to retrieve the microstate class based statistics necessary to compare microstate parameters between groups and/or conditions. Keypy is an open source library and freely available from https://www.github.com/keyinst/keypy.Keypy provides a platform for automated microstate analysis of large-scale EEG datasets from psychiatric patient populations and their comparison to healthy controls. It is easily applicable and allows efficient identification of deviant brain states in clinical conditions.Disclosure of interestThe authors have not supplied their declaration of competing interest.

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10

Hu, Yanzhu, Zhen Meng, Xinbo Ai, Han Li, Yu Hu, and Huiyang Zhao. "Hybrid Feature Extraction of Pipeline Microstates Based on Φ-OTDR Sensing System." Journal of Control Science and Engineering 2019 (September 22, 2019): 1–10. http://dx.doi.org/10.1155/2019/6087582.

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This paper proposes a general integration method which can effectively describe the characteristics of pipeline leakage and help distinguish multiple pipeline microstates. Since the rapid development of Φ-OTDR in recent years, this technology has been applied to more and more fields, such as fiber optic safety monitoring, seismic monitoring, and structural health monitoring. Among them, Φ-OTDR has the characteristic of continuous full-scale monitoring in pipeline monitoring, but there are few researches on pipeline state characteristics at present. In this paper, based on the analysis of the pipeline state with Φ-OTDR technology, a method of extracting multiple microstates of pipelines is proposed. This method combined with the peak-to-average power ratio, short-term interval zero crossing, and fractal characteristics in the frequency domain can effectively characterize the microstate of pipes and provide support for identification of more microstates of pipelines. These features reflect the common characteristics of leaks in gas pipelines and liquid pipelines. Meanwhile, their combination features can represent the small differences in pipeline states. The experimental results show that the method can effectively characterize the microstate information of the pipeline, and the recognition rate of the hybrid feature under two kinds of pipeline leakage and multipressure conditions reaches 91% and 83%.

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11

Wardani, Indra K., Phakkharawat Sittiprapaporn, Djohan Djohan, Fortunata Tyasrinestu, and Prayoon Suyajai. "Keyseg: adaptive segmentation for spontaneous electroencephalography map series into spatially defined microstates of musicians’ brain." Bulletin of Electrical Engineering and Informatics 10, no. 4 (August 1, 2021): 2006–15. http://dx.doi.org/10.11591/eei.v10i4.3063.

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Music is being studied related to either its impact on the psychological interaction or cognitive process behind it. These examinations bring out music's coordination to numerous disciplines including neuroscience. A few past examinations exhibited the contrast among musicians and non-musicians regarding brain structure and brain activity. The current investigation exhibited the diverse brain activation while musicians tuned in to music with regards to their musical experiences utilizing microstate classes method analysis. The investigation intended to determine electroencephalography microstate changes in Karawitan musicians' brain while tuning in to Gendhing Lancaran. Applying the electroencephalography microstate investigation of Karawitan musicians, the occurrence parameters was computed for four microstate classes (A, B, C, and D). Microstate properties were compared among subjects and correlated to Gendhing Lancaran perception. The present results revealed that Karawitan musicians' brain were characterized by microstate classes with the increased prominence of classes A, B, and D, but decreased prominence of classes C while tuning in to Gendhing Lancaran. Our finding is the first study to identify the typical microstate characteristics of the Karawitan musician’s brains while tuning in to Gendhing Lancaran by using the microstate segmentaion method.

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Gärtner, Matthias, Verena Brodbeck, Helmut Laufs, and Gaby Schneider. "A stochastic model for EEG microstate sequence analysis." NeuroImage 104 (January 2015): 199–208. http://dx.doi.org/10.1016/j.neuroimage.2014.10.014.

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13

Gold, Michael C., Shiwen Yuan, Eric Tirrell, Eugenia F. Kronenberg, JeeWon Kang, Lauren Hindley, Joshua Brown, and Linda L. Carpenter. "EEG Microstate Analysis of Response to TMS Therapy." Brain Stimulation 14, no. 5 (September 2021): 1412. http://dx.doi.org/10.1016/j.brs.2021.07.047.

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14

Ikeda, Shunichiro, Masafumi Yoshimura, Keiichiro Nishida, Yuichi Kitaura, Koji Katsura, Shota Minami, Ryouhei Ishii, et al. "S2-3. Utility of microstate analysis in psychiatric disorders." Clinical Neurophysiology 130, no. 10 (October 2019): e189. http://dx.doi.org/10.1016/j.clinph.2019.06.080.

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15

Norindr, Ainhoa, Andrew Valadez, and Rustin Berlow. "Microstate Analysis Before and After Transcranial Magnetic Stimulation (TMS)." Brain Stimulation 12, no. 4 (July 2019): e138. http://dx.doi.org/10.1016/j.brs.2019.03.051.

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16

Li, Shuaiyang, Yuxia Hu, Hongcan Zhu, Rui Zhang, Mingming Chen, Li Shi, Dezhong Yao, Xinjun Wang, Qingyong Zhu, and Lipeng Zhang. "EEG Microstate Analysis in Patients With Increased Intracranial Pressure." International Journal of Psychophysiology 168 (October 2021): S108. http://dx.doi.org/10.1016/j.ijpsycho.2021.07.322.

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17

Kikuchi, Mitsuru, Thomas Koenig, Toshio Munesue, Akira Hanaoka, Werner Strik, Thomas Dierks, Yoshifumi Koshino, and Yoshio Minabe. "EEG Microstate Analysis in Drug-Naive Patients with Panic Disorder." PLoS ONE 6, no. 7 (July 29, 2011): e22912. http://dx.doi.org/10.1371/journal.pone.0022912.

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18

Chu, Chunguang, Xing Wang, Lihui Cai, Lei Zhang, Jiang Wang, Chen Liu, and Xiaodong Zhu. "Spatiotemporal EEG microstate analysis in drug-free patients with Parkinson's disease." NeuroImage: Clinical 25 (2020): 102132. http://dx.doi.org/10.1016/j.nicl.2019.102132.

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19

Giroud, Nathalie, Ulrike Lemke, Philip Reich, Katarina L. Matthes, and Martin Meyer. "Longitudinal auditory learning facilitates auditory cognition as revealed by microstate analysis." Biological Psychology 123 (February 2017): 25–36. http://dx.doi.org/10.1016/j.biopsycho.2016.11.007.

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20

Damborska, A., M. Tomescu, R. Bartecek, E. Honzirkova, D. Drobisz, and C. Michel. "Electrophysiological brain abnormalities in depression: microstate analysis on resting high-density EEG." Brain Stimulation 12, no. 2 (March 2019): 503. http://dx.doi.org/10.1016/j.brs.2018.12.647.

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21

Deng, Ming, Ming Ming Chen, and Guo Song Ning. "Wear Resistance Experimental Analysis of Closed Extruding Fine Blanking Parts Surface." Advanced Materials Research 499 (April 2012): 384–87. http://dx.doi.org/10.4028/www.scientific.net/amr.499.384.

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Closed extruding fine blanking parts is processed under strong hydrostatic pressure, material microstate and mechanical properties near the surface change greatly. In order to research the closed extruding fine blanking parts surface wear resistance, make a reciprocating friction test, and make wear resistance comparative analysis between closed extruding fine blanking parts and turning parts which has the same surface roughness. The results show that in the running wear stage and stable wear stage the wear resistance of closed extruding fine blanking parts is better than turning parts, closed extruding fine blanking process has greatly improved the surface wear resistance.

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Xi, Lei, Qiang Wang, Hui Zhang, Yan Na Ren, Lon Gong Zhang, Zhi Yuan Hou, and Xin Ming Ma. "Wheat Three-Dimensional Reconstruction and Visualization System." Applied Mechanics and Materials 195-196 (August 2012): 1300–1307. http://dx.doi.org/10.4028/www.scientific.net/amm.195-196.1300.

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The study object is wheat. Through the observation and analysis on the morphological structure of wheat plant, the concepts of microstate, substrate and microstate are put forward, the wheat growth mechanism model is established, and thus the description and control of wheat morphogenesis process could be realized. Based on the branch structure characteristics of plant, the wheat morphological data model based on axis structure is proposed to realize the structural storage of plant topological structure and organ morphological feature data. On this basis, based on the thought of "growth model - morphological feature model - geometric modeling - display model", the technical framework of wheat form visualization is established and on the VC++ platform, the virtual wheat growth system is built with OpenGL. The running result of the system shows that wheat morphological feature can be well simulated with the system to realize the virtual display of the growth process in the individual growth period of wheat.

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23

Mingo, Erick Hinds, and David Jennings. "Decomposable coherence and quantum fluctuation relations." Quantum 3 (November 11, 2019): 202. http://dx.doi.org/10.22331/q-2019-11-11-202.

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In Newtonian mechanics, any closed-system dynamics of a composite system in a microstate will leave all its individual subsystems in distinct microstates, however this fails dramatically in quantum mechanics due to the existence of quantum entanglement. Here we introduce the notion of a `coherent work process', and show that it is the direct extension of a work process in classical mechanics into quantum theory. This leads to the notion of `decomposable' and `non-decomposable' quantum coherence and gives a new perspective on recent results in the theory of asymmetry as well as early analysis in the theory of classical random variables. Within the context of recent fluctuation relations, originally framed in terms of quantum channels, we show that coherent work processes play the same role as their classical counterparts, and so provide a simple physical primitive for quantum coherence in such systems. We also introduce a pure state effective potential as a tool with which to analyze the coherent component of these fluctuation relations, and which leads to a notion of temperature-dependent mean coherence, provides connections with multi-partite entanglement, and gives a hierarchy of quantum corrections to the classical Crooks relation in powers of inverse temperature.

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Tanaka, Hideaki, Dietrich Lehmann, and Koichi Hirata. "Microstate analysis of information processing in a reading task with Kanji and Katakana." International Congress Series 1232 (April 2002): 397–401. http://dx.doi.org/10.1016/s0531-5131(02)00144-9.

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Ricci, Lorenzo, Pierpaolo Croce, Jacopo Lanzone, Marilisa Boscarino, Filippo Zappasodi, Mario Tombini, Vincenzo Di Lazzaro, and Giovanni Assenza. "Transcutaneous Vagus Nerve Stimulation Modulates EEG Microstates and Delta Activity in Healthy Subjects." Brain Sciences 10, no. 10 (September 25, 2020): 668. http://dx.doi.org/10.3390/brainsci10100668.

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Transcutaneous vagus nerve stimulation (tVNS) is an alternative non-invasive method for the electrical stimulation of the vagus nerve with the goal of treating several neuropsychiatric disorders. The objective of this study is to assess the effects of tVNS on cerebral cortex activity in healthy volunteers using resting-state microstates and power spectrum electroencephalography (EEG) analysis. Eight male subjects aged 25–45 years were recruited in this randomized sham-controlled double-blind study with cross-over design. Real tVNS was administered at the left external acoustic meatus, while sham stimulation was performed at the left ear lobe, both of them for 60 min. The EEG recording lasted 5 min and was performed before and 60 min following the tVNS experimental session. We observed that real tVNS induced an increase in the metrics of microstate A mean duration (p = 0.039) and an increase in EEG power spectrum activity in the delta frequency band (p < 0.01). This study confirms that tVNS is an effective way to stimulate the vagus nerve, and the mechanisms of action of this activation can be successfully studied using scalp EEG quantitative metrics. Future studies are warranted to explore the clinical implications of these findings and to focus the research of the prognostic biomarkers of tVNS therapy for neuropsychiatric diseases.

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Morgado, Leonor, Ana P. Fernandes, Joana M. Dantas, Marta A. Silva, and Carlos A. Salgueiro. "On the road to improve the bioremediation and electricity-harvesting skills of Geobacter sulfurreducens: functional and structural characterization of multihaem cytochromes." Biochemical Society Transactions 40, no. 6 (November 21, 2012): 1295–301. http://dx.doi.org/10.1042/bst20120099.

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Extracellular electron transfer is one of the physiological hallmarks of Geobacter sulfurreducens, allowing these bacteria to reduce toxic and/or radioactive metals and grow on electrode surfaces. Aiming to functionally optimize the respiratory electron-transfer chains, such properties can be explored through genetically engineered strains. Geobacter species comprise a large number of different multihaem c-type cytochromes involved in the extracellular electron-transfer pathways. The functional characterization of multihaem proteins is particularly complex because of the coexistence of several microstates in solution, connecting the fully reduced and oxidized states. NMR spectroscopy has been used to monitor the stepwise oxidation of each individual haem and thus to obtain information on each microstate. For the structural study of these proteins, a cost-effective isotopic labelling of the protein polypeptide chains was combined with the comparative analysis of 1H-13C HSQC (heteronuclear single-quantum correlation) NMR spectra obtained for labelled and unlabelled samples. These new methodological approaches allowed us to study G. sulfurreducens haem proteins functionally and structurally, revealing functional mechanisms and key residues involved in their electron-transfer capabilities. Such advances can now be applied to the design of engineered haem proteins to improve the bioremediation and electricity-harvesting skills of G. sulfurreducens.

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Lehmann, Dietrich, Roberto D. Pascual-Marqui, Werner K. Strik, and Thomas Koenig. "Core networks for visual-concrete and abstract thought content: A brain electric microstate analysis." NeuroImage 49, no. 1 (January 2010): 1073–79. http://dx.doi.org/10.1016/j.neuroimage.2009.07.054.

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Hart, Brian, Stephen Malone, and Mark Fiecas. "A grouped beta process model for multivariate resting‐state EEG microstate analysis on twins." Canadian Journal of Statistics 49, no. 1 (February 18, 2021): 89–106. http://dx.doi.org/10.1002/cjs.11589.

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von Wegner, F., E. Tagliazucchi, and H. Laufs. "Information-theoretical analysis of resting state EEG microstate sequences - non-Markovianity, non-stationarity and periodicities." NeuroImage 158 (September 2017): 99–111. http://dx.doi.org/10.1016/j.neuroimage.2017.06.062.

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Cheng, D., K. Fjeld, and G. Binsted. "The event related potential technique and microstate analysis of memory guided and visually guided movements." Journal of Vision 14, no. 10 (August 22, 2014): 303. http://dx.doi.org/10.1167/14.10.303.

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Case, Michelle, Clara Zhang, John Mundahl, Yvonne Datta, Stephen C. Nelson, Kalpna Gupta, and Bin He. "Recognition of Biomarkers of Brain Connectivity and Pain Using Multi-Modal Imaging in Patients with Sickle Cell Disease." Blood 126, no. 23 (December 3, 2015): 971. http://dx.doi.org/10.1182/blood.v126.23.971.971.

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Abstract Sickle cell disease (SCD) is associated with impaired cognitive function, pain, cerebral stroke and other neural dysfunctions suggestive of altered brain function. The most common reason for hospitalization of SCD patients is pain. Sickle pain is unique compared to other clinical pain conditions because it includes chronic pain as well as acute pain due to vasoocclusive crisis. The neuropathic and nociceptive aspects of pain in SCD make pain treatment challenging. Opioids, the most common analgesics, are associated with liabilities, such as addiction and tolerance. As a result, patients are often under-treated because of a lack of an objective pain measurement system. We therefore sought to develop an unbiased pain quantification method using non-invasive imaging techniques to recognize the biomarkers of pain and altered brain function. We examined the brain network connectivity in SCD patients (N=14) and healthy controls (N=13) to identify altered activity between the two groups that can be used as biomarkers for chronic pain. All experimental procedures were approved by the IRB of the University of Minnesota, and all subjects gave written informed consent before participating in the study. Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) were simultaneously recorded while the subjects were in a wakeful resting state. A 3T Siemens Trio whole-body scanner and a 16 channel head coil with an echo-planar imaging (EPI) sequence were used to acquire fMRI data. EEG data was recorded using a 64-channel EEG cap and MR-compatible amplifiers. Seed-based region of interest (ROI) analysis was performed on the fMRI data using Brain Voyager QX software. EEG informed fMRI (EEG-fMRI) was performed for power and microstate analysis using Matlab and SPM8 software. Statistical activation maps (p<0.001, uncorrected) were generated from general linear models (GLM) based on the time courses found from power and microstate analysis. Seeds were placed in the insula regions, and the functional connectivity between the left and right insula appeared to be stronger in SCD patients than in healthy controls. This result was verified in EEG-fMRI analysis. Activation of the insula and striatum regions positively correlated with the beta band in SCD patients, where healthy controls showed less activation in the insula in the same frequency band. Microstates corresponding to insula activation were observed in both healthy controls and SCD patients; however, activation seems stronger in SCD patients. Activation in the striatum regions was also observed in microstates for SCD patients, but not for healthy controls. These results show that the insula and striatum regions have greater activation in SCD patients compared to controls, and that patients have altered brain connectivity during resting state. Insula activation could be related to the salience network, a resting state network that is responsible for processing external input, or to pain processing. The insula and striatum are some of the common brain regions that have been shown to be active during painful stimuli. This altered activation could be caused by sickle pain and could be a potential biomarker of pain intensity. Due to the non-invasive nature of these quantitative data, this method can have applications in the unbiased objective quantification of pain and treatment outcomes. Altered connectivity observed in SCD patients can also be used to help better understand the neural pathophysiology of sickle pain and can lead to better management strategies for these patients. This work was supported in part by NIH grant U01-HL117664 and NSF IGERT grant DGE-1069104. Disclosures No relevant conflicts of interest to declare.

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Gschwind, Markus, Christoph M. Michel, and Dimitri Van De Ville. "Long-range dependencies make the difference—Comment on “A stochastic model for EEG microstate sequence analysis”." NeuroImage 117 (August 2015): 449–55. http://dx.doi.org/10.1016/j.neuroimage.2015.05.062.

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Atluri, Sravya, Willy Wong, Daniel M. Blumberger, Zafiris J. Daskalakis, and Faranak Farzan. "533. Insights from EEG Microstate Analysis on the Pathophysiology of Depression and Mechanisms of Seizure Therapy." Biological Psychiatry 81, no. 10 (May 2017): S216. http://dx.doi.org/10.1016/j.biopsych.2017.02.1141.

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Zhang, Kexu, Wen Shi, Chang Wang, Yamin Li, Zhian Liu, Tun Liu, Jing Li, et al. "Reliability of EEG microstate analysis at different electrode densities during propofol-induced transitions of brain states." NeuroImage 231 (May 2021): 117861. http://dx.doi.org/10.1016/j.neuroimage.2021.117861.

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SCHACK, BÄRBEL. "HOW TO CONSTRUCT A MICROSTATE-BASED ALPHABET FOR EVALUATING INFORMATION PROCESSING IN TIME." International Journal of Bifurcation and Chaos 14, no. 02 (February 2004): 793–814. http://dx.doi.org/10.1142/s0218127404009478.

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Cognitive processes are highly dynamic processes concatenating different components of human thinking successively or parallel in time. Thereby, different cortical networks are generated, transient or stable in time. One important integration mechanism between different cortical sites is the synchronization of electrical oscillations of neural ensembles. Prior studies have shown that instantaneous EEG coherence analysis is a useful tool to unhide transient synchronization phenomena (see e.g. [Krause et al., 1998; Miltner et al., 1999; Schack et al., 1999a, 1999b]). In those studies instantaneous coherence was investigated for selected short time intervals, respectively, specific time parameters of instantaneous coherence were examined.The present study proposes a method for the evaluation of the whole cognitive process on the basis of instantaneous coherence without loss of time and process information. To this purpose prototypical microstates of synchronous oscillations are constructed. Their temporal, sequential and topographical properties reflect the underlying process of the dynamic activation and deactivation of neuronal networks during information processing. The sequence of microstates may be understood as the orderly arrangement of words of an alphabet in the correspondent thinking process.The presented method is applied to an event-related cognitive task of comparing categorization processes, pattern comparison, and to an irreproducible long task when solving mathematical problems. In both cases we obtain detailed information about temporal structures and strategies of human thinking.

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Li, Zhenjiang, Libo Zhang, Fengrui Zhang, Ruolei Gu, Weiwei Peng, and Li Hu. "Demystifying signal processing techniques to extract resting-state EEG features for psychologists." Brain Science Advances 6, no. 3 (September 2020): 189–209. http://dx.doi.org/10.26599/bsa.2020.9050019.

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Electroencephalography (EEG) is a powerful tool for investigating the brain bases of human psychological processes non‐invasively. Some important mental functions could be encoded by resting‐state EEG activity; that is, the intrinsic neural activity not elicited by a specific task or stimulus. The extraction of informative features from resting‐state EEG requires complex signal processing techniques. This review aims to demystify the widely used resting‐state EEG signal processing techniques. To this end, we first offer a preprocessing pipeline and discuss how to apply it to resting‐state EEG preprocessing. We then examine in detail spectral, connectivity, and microstate analysis, covering the oft‐used EEG measures, practical issues involved, and data visualization. Finally, we briefly touch upon advanced techniques like nonlinear neural dynamics, complex networks, and machine learning.

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Fu, Yi, Xin Hua Ji, and Yu Wen Qin. "Experimental Study of Micro Displacement Field of Microstate of Crack Tips of Ceramics Plasticized with Zirconia and Stabilized by Yttrium Oxide – Application of Digital Image Correlation Method Based on Analysis by Scanning Electron Microscope." Key Engineering Materials 336-338 (April 2007): 2436–39. http://dx.doi.org/10.4028/www.scientific.net/kem.336-338.2436.

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To study the deformation reaction of different metallurgical phases of the micron structure of crack tips of zirconia ceramics in the loading state, the paper presents the micro experimental study based on the digital correlated method of analysis by scanning electron microscope on the displacement field in the micro areas of crack tip of the specimen of the Y2O3-ZrO2 toughened ceramic with the simple edge notch beam method and under the action of three-point bending loads. First, SEM analyses was made on the local area of the crack tip of a specimen’s polished surface before and after loads are applied to the specimen, thus obtaining two SEM images, one before the application of the loads and another after the load application, which contained their displacement information. Then, digital correlation calculations were made between the gray scales of the pixels of the two images in order to obtain the microscopic displacement fields of the crack tips in the microstate, thus unveiling the deformation modality and displacement response of different metallurgical phases of the crack tips of zirconia ceramics when subject to loads. The results of the studies will provide foundations and basis for further research in the mechanical properties of the ceramics with Y2O3-ZrO2 and their relationship with the microstructures.

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Arruda Baltazar, Carlos Arruda, Maria Isabel Barros Guinle, Cora Jirschik Caron, Edson Amaro, and Birajara Soares Machado. "Connective Core Structures in Cognitive Networks: the Role of Hubs." Entropy 21, no. 10 (September 30, 2019): 961. http://dx.doi.org/10.3390/e21100961.

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Complex network analysis applied to the resting brain has shown that sets of highly interconnected networks with coherent activity may support a default mode of brain function within a global workspace. Perceptual processing of environmental stimuli induces architectural changes in network topology with higher specialized modules. Evidence shows that during cognitive tasks, network topology is reconfigured and information is broadcast from modular processors to a connective core, promoting efficient information integration. In this paper, we explored how the brain adapts its effective connectivity within the connective core and across behavioral states. We used complex network metrics to identify hubs and proposed a method of classification based on the effective connectivity patterns of information flow. Finally, we interpreted the role of the connective core and each type of hub on the network effectiveness. We also calculated the complexity of electroencephalography microstate sequences across different tasks. We observed that divergent hubs contribute significantly to the network effectiveness and that part of this contribution persists across behavioral states, forming an invariant structure. Moreover, we found that a large quantity of multiple types of hubs may be associated with transitions of functional networks.

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Law, Zhe Kang, Carein Todd, Ramtin Mehraram, Julia Schumacher, Mark R. Baker, Fiona E. N. LeBeau, Alison Yarnall, et al. "The Role of EEG in the Diagnosis, Prognosis and Clinical Correlations of Dementia with Lewy Bodies—A Systematic Review." Diagnostics 10, no. 9 (August 20, 2020): 616. http://dx.doi.org/10.3390/diagnostics10090616.

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Despite improvements in diagnostic criteria for dementia with Lewy bodies (DLB), the ability to discriminate DLB from Alzheimer’s disease (AD) and other dementias remains suboptimal. Electroencephalography (EEG) is currently a supportive biomarker in the diagnosis of DLB. We performed a systematic review to better clarify the diagnostic and prognostic role of EEG in DLB and define the clinical correlates of various EEG features described in DLB. MEDLINE, EMBASE, and PsycINFO were searched using search strategies for relevant articles up to 6 August 2020. We included 43 studies comparing EEG in DLB with other diagnoses, 42 of them included a comparison of DLB with AD, 10 studies compared DLB with Parkinson’s disease dementia, and 6 studies compared DLB with other dementias. The studies were visual EEG assessment (6), quantitative EEG (35) and event-related potential studies (2). The most consistent observation was the slowing of the dominant EEG rhythm (<8 Hz) assessed visually or through quantitative EEG, which was observed in ~90% of patients with DLB and only ~10% of patients with AD. Other findings based on qualitative rating, spectral power analyses, connectivity, microstate and machine learning algorithms were largely heterogenous due to differences in study design, EEG acquisition, preprocessing and analysis. EEG protocols should be standardized to allow replication and validation of promising EEG features as potential biomarkers in DLB.

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Armengol, Ramon, Marta Bassols, and Lorenzo Fraile. "A Cow–Calf Farming System Fully Adapted to Elevation and Harsh Conditions in Andorra (Europe)." Animals 11, no. 3 (February 26, 2021): 611. http://dx.doi.org/10.3390/ani11030611.

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The use of natural resources is an important topic to optimize the efficiency of cattle production. The purpose of this work is to describe the project of the Bruna d’Andorra; a local cow breed under an extensive cow–calf system in Andorra (Europe), as an example of local farming and marketing of its meat products in an area with adverse environmental conditions. This breed is located in Andorra, a microstate that consists predominantly of rugged mountains and harsh weather conditions. The cow–calf Bruna d’Andorra extensive system is thoroughly described and productive and reproductive performance, compiled over 21 years (2000–2020), has been analyzed by years with the Chi-square test or ANOVA to compare proportions or means, respectively, and regression analysis was used to decipher evolution across years. The results show a population with a census large and stable enough to avoid inbreeding. Moreover, a sustained improvement of the productive performance and maternal fitness has been observed along the studied period for Bruna d’Andorra. The work concludes that local breeds can achieve sustainable animal production, especially when farmers, public administration and commercial circuits in the area agree to cooperate on such projects. The study also concludes that the Bruna d’Andorra cow breed can still improve in meat and reproductive performance.

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Jung, Kenley. "Fractal entropies and dimensions for microstates spaces." Journal of Functional Analysis 222, no. 1 (May 2005): 217–51. http://dx.doi.org/10.1016/j.jfa.2004.08.002.

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Shlyakhtenko, Dimitri. "Lower estimates on microstates free entropy dimension." Analysis & PDE 2, no. 2 (May 1, 2009): 119–46. http://dx.doi.org/10.2140/apde.2009.2.119.

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43

Aagaard, Lars. "The non-microstates free entropy dimension of DT-operators." Journal of Functional Analysis 213, no. 1 (August 2004): 176–205. http://dx.doi.org/10.1016/j.jfa.2004.04.012.

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Mineyev, I., and D. Shlyakhtenko. "Non-microstates free entropy dimension for groups." GAFA Geometric And Functional Analysis 15, no. 2 (April 2005): 476–90. http://dx.doi.org/10.1007/s00039-005-0513-z.

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GÖKOĞLU, GÖKHAN, HANDAN ARKIN, and TARIK ÇELIK. "CONFORMATIONAL ANALYSIS OF POLYALANYL CHAINS." International Journal of Modern Physics C 16, no. 03 (March 2005): 455–63. http://dx.doi.org/10.1142/s0129183105007236.

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Including all-atom interactions and solution effects, we have simulated the monoalanine dipeptide and short polyalanyl chains by multicanonical algorithm, in order to determine and compare their low-lying microstates and thermodynamically stable conformations.

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ZINCHENKO, O. V. "Forms Of Government In European Microstates (Comparative Analysis)." JOURNAL OF THE NATIONAL ACADEMY OF LEGAL SCIENCES OF UKRAINE 25, no. 2 (2018): 99–113. http://dx.doi.org/10.31359/1993-0909-2018-25-2-99.

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SEN, ASHOKE. "QUANTUM ENTROPY FUNCTION FROM AdS2/CFT1 CORRESPONDENCE." International Journal of Modern Physics A 24, no. 23 (September 20, 2009): 4225–44. http://dx.doi.org/10.1142/s0217751x09045893.

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We review and extend recent attempts to find a precise relation between extremal black hole entropy and degeneracy of microstates using AdS 2/ CFT 1 correspondence. Our analysis leads to a specific relation between degeneracy of black hole microstates and an appropriately defined partition function of string theory on the near horizon geometry — named the quantum entropy function. In the classical limit this reduces to the usual relation between statistical entropy and Wald entropy.

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Dabrowski, Yoann. "A note about proving non-Γ under a finite non-microstates free Fisher information assumption." Journal of Functional Analysis 258, no. 11 (June 2010): 3662–74. http://dx.doi.org/10.1016/j.jfa.2010.02.010.

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Michalopoulos, Kostas, Michalis Zervakis, Marie-Pierre Deiber, and Nikolaos Bourbakis. "Classification of EEG Single Trial Microstates Using Local Global Graphs and Discrete Hidden Markov Models." International Journal of Neural Systems 26, no. 06 (July 19, 2016): 1650036. http://dx.doi.org/10.1142/s0129065716500362.

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We present a novel synergistic methodology for the spatio-temporal analysis of single Electroencephalogram (EEG) trials. This new methodology is based on the novel synergy of Local Global Graph (LG graph) to characterize define the structural features of the EEG topography as a global descriptor for robust comparison of dominant topographies (microstates) and Hidden Markov Models (HMM) to model the topographic sequence in a unique way. In particular, the LG graph descriptor defines similarity and distance measures that can be successfully used for the difficult comparison of the extracted LG graphs in the presence of noise. In addition, hidden states represent periods of stationary distribution of topographies that constitute the equivalent of the microstates in the model. The transitions between the different microstates and the formed syntactic patterns can reveal differences in the processing of the input stimulus between different pathologies. We train the HMM model to learn the transitions between the different microstates and express the syntactic patterns that appear in the single trials in a compact and efficient way. We applied this methodology in single trials consisting of normal subjects and patients with Progressive Mild Cognitive Impairment (PMCI) to discriminate these two groups. The classification results show that this approach is capable to efficiently discriminate between control and Progressive MCI single trials. Results indicate that HMMs provide physiologically meaningful results that can be used in the syntactic analysis of Event Related Potentials.

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Meng, Yilin, Diwakar Shukla, Vijay S. Pande, and Benoît Roux. "Transition path theory analysis of c-Src kinase activation." Proceedings of the National Academy of Sciences 113, no. 33 (August 1, 2016): 9193–98. http://dx.doi.org/10.1073/pnas.1602790113.

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Nonreceptor tyrosine kinases of the Src family are large multidomain allosteric proteins that are crucial to cellular signaling pathways. In a previous study, we generated a Markov state model (MSM) to simulate the activation of c-Src catalytic domain, used as a prototypical tyrosine kinase. The long-time kinetics of transition predicted by the MSM was in agreement with experimental observations. In the present study, we apply the framework of transition path theory (TPT) to the previously constructed MSM to characterize the main features of the activation pathway. The analysis indicates that the activating transition, in which the activation loop first opens up followed by an inward rotation of the αC-helix, takes place via a dense set of intermediate microstates distributed within a fairly broad “transition tube” in a multidimensional conformational subspace connecting the two end-point conformations. Multiple microstates with negligible equilibrium probabilities carry a large transition flux associated with the activating transition, which explains why extensive conformational sampling is necessary to accurately determine the kinetics of activation. Our results suggest that the combination of MSM with TPT provides an effective framework to represent conformational transitions in complex biomolecular systems.

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