Dynamic State Transitions of Individuals Enhance Macroscopic Behavioral Diversity of Morphogenetic Collective Systems

Purpose: electroencephalographic (EEG) information is used to monitor the level of cortical depression of a patient undergoing surgical intervention under general anesthesia. The dynamic state transitions into and out of anesthetic-induced loss and return of responsiveness (LOR, ROR) present a possibility to evaluate the dynamics of the EEG induced by different substances. We evaluated changes in the EEG power spectrum during anesthesia emergence for three different anesthetic regimens. We also assessed the possible impact of these changes on processed EEG parameters such as the permutation entropy (PeEn) and the cerebral state index (CSI). Methods: we analyzed the EEG from 45 patients, equally assigned to three groups. All patients were induced with propofol and the groups differed by the maintenance anesthetic regimen, i.e., sevoflurane, isoflurane, or propofol. We evaluated the EEG and parameter dynamics during LOR and ROR. For the emergence period, we focused on possible differences in the EEG dynamics in the different groups. Results: depending on the substance, the EEG emergence patterns showed significant differences that led to a substance-specific early activation of higher frequencies as indicated by the “wake” CSI values that occurred minutes before ROR in the inhalational anesthetic groups. Conclusion: our results highlight substance-specific differences in the emergence from anesthesia that can influence the EEG-based monitoring that probably have to be considered in order to improve neuromonitoring during general anesthesia.

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Time-varying Dynamic Network Model For Dynamic Resting State Functional Connectivity in fMRI and MEG imaging

10.1101/2021.04.01.438060 ◽

2021 ◽

Author(s):

Fei Jiang ◽

Huaqing Jin ◽

Yijing Bao ◽

Xihe Xie ◽

Jennifer Cummings ◽

...

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Dynamic Network ◽

Dynamic State ◽

State Transitions ◽

Dimensional Manifold ◽

Time Varying ◽

Resting State Functional Connectivity ◽

Brain Signals ◽

Low Dimensional

Dynamic resting state functional connectivity (RSFC) characterizes fluctuations that occurs over time in functional brain networks. Existing methods to extract dynamic RSFCs, such as sliding-window and clustering methods, have various limitations due to their inherent non-adaptive nature and high-dimensionality including an inability to reconstruct brain signals, insufficiency of data for reliable estimation, insensitivity to rapid changes in dynamics, and a lack of generalizability across multi- modal functional imaging datasets. To overcome these deficiencies, we develop a novel and unifying time-varying dynamic network (TVDN) framework for examining dynamic resting state functional connectivity. TVDN includes a generative model that describes the relation between low-dimensional dynamic RSFC and the brain signals, and an inference algorithm that automatically and adaptively learns to detect dynamic state transitions in data and a low-dimensional manifold of dynamic RSFC. TVDN is generalizable to handle multimodal functional neuroimaging data (fMRI and MEG/EEG). The resulting estimated low-dimensional dynamic RSFCs manifold directly links to the frequency content of brain signals. Hence we can evaluate TVDN performance by examining whether learnt features can reconstruct observed brain signals. We conduct comprehensive simulations to evaluate TVDN under hypothetical settings. We then demonstrate the application of TVDN with real fMRI and MEG data, and compare the results with existing benchmarks. Results demonstrate that TVDN is able to correctly capture the dynamics of brain activity and more robustly detect brain state switching both in resting state fMRI and MEG data.

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STMC-14. GLIOBLASTOMA CANCER STEM CELLS UNDERGO DYNAMIC STATE TRANSITIONS

Neuro-Oncology ◽

10.1093/neuonc/now212.778 ◽

2016 ◽

Vol 18 (suppl_6) ◽

pp. vi185-vi185

Author(s):

Anne Dirkse ◽

Nicolaas H. C. Brons ◽

Thomas Buder ◽

Andreas Deutsch ◽

Sonia Leite ◽

...

Keyword(s):

Stem Cells ◽

Cancer Stem Cells ◽

Dynamic State ◽

State Transitions

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A Strategy to Formalize Specification and Its Application to an Advanced Railway System

International Journal of Software Engineering and Knowledge Engineering ◽

10.1142/s0218194014500181 ◽

2014 ◽

Vol 24 (03) ◽

pp. 465-492 ◽

Cited By ~ 1

Author(s):

Guo Xie ◽

Xinhong Hei ◽

Sei Takahashi ◽

Hideo Nakamura

Keyword(s):

Natural Language ◽

Unified Modeling Language ◽

System Structure ◽

Dynamic State ◽

State Transitions ◽

Functional Requirements ◽

Unified Modeling ◽

Railway System ◽

Novel Strategy ◽

Conventional Rail

This paper proposes a novel strategy for formally analyzing functional requirements specification (FRS) and applies it to the Automatic Train Protection and Block (ATPB) system, which is proposed to reconstruct conventional rail lines in Japan. Based on the FRS in natural language, firstly, dynamic state transitions are extracted to express the operational mechanisms and determine the system parameters. A complete model of the ATPB system is then established using Unified Modeling Language (UML) to express the system structure graphically and explicitly. After achieving a common understanding, a VDM++ model is established formally to redescribe the original FRS of the ATPB system which is written in natural language (i.e. Japanese). Following that, in order to ensure internal consistency of the specification, proof obligations of the VDM++ model are discharged. Furthermore, a comprehensive testing is implemented to ensure that the FRS meets actual requirements. Finally, the system is simulated strictly in accordance with the formal specification. Without any runtime errors, collisions or derailments, the results of the simulation demonstrate the high quality and safety of the specification.

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Inferring cell state by quantitative motility analysis reveals a dynamic state system and broken detailed balance

10.1101/168534 ◽

2017 ◽

Author(s):

Jacob C. Kimmel ◽

Amy Y. Chang ◽

Andrew S. Brack ◽

Wallace F. Marshall

Keyword(s):

Signaling Pathways ◽

Detailed Balance ◽

State System ◽

Dynamic State ◽

State Transitions ◽

Cell Behavior ◽

Flux Analysis ◽

Cell Heterogeneity ◽

Cell State ◽

Molecular Features

AbstractCell populations display heterogeneous phenotypic states at multiple scales. Similar to molecular features commonly used to explore cell heterogeneity, cell behavior is a rich phenotypic space that may allow for identification of relevant cell states. Inference of cell state from cell behavior across a time course may enable the investigation of dynamics of transitions between heterogeneous cell states, a task difficult to perform with destructive molecular observations. Cell motility is one such easily observed cell behavior with known biomedical relevance. To investigate cell heterogeneity through the lens of cell behavior, we developed Heteromotility, a software tool to extract quantitative motility features from timelapse cell images. In mouse embryonic fibroblasts (MEFs), myoblasts, and muscle stem cells (MuSCs), Heteromotility analysis identifies multiple motility phenotypes within the population. In all three systems, the motility state identity of individual cells is dynamic. Quantification of state transitions reveals that MuSCs undergoing activation transition through progressive motility states toward the myoblast phenotype. By probability flux analysis, we find that this MuSC motility state system breaks detailed balance, while the MEF and myoblast systems do not. Our data indicate that the system regulating cell behavior can be decomposed into a set of attractor states which depend on the identity of the cell, together with a set of transitions between states governed by inputs from signaling pathways such as oncogenes and growth factors. Within one state, equilibrium formalisms can capture variation in behavior, while switching between states violates equilibrium conditions and would require an external driving force. These results support a conceptual view of the cell as a non-deterministic state automaton, responding to inputs from signaling pathways and generating outputs in the form of observable motile behaviors.

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Dynamic State Transitions in the Nervous System: From Ion Channels to Neurons to Networks

Micro Meso Macro ◽

10.1142/9789812701404_0004 ◽

2005 ◽

pp. 37-72 ◽

Cited By ~ 4

Author(s):

Peter Århem ◽

Hans A. Braun ◽

Martin T. Huber ◽

Hans Liljenström

Keyword(s):

Nervous System ◽

Ion Channels ◽

Dynamic State ◽

State Transitions

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Pinocytotic-Like Forms of Mitochondria From Rat Anterior Pituitary

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100100470 ◽

1968 ◽

Vol 26 ◽

pp. 146-147

Author(s):

Burton B. Silver

Keyword(s):

Electron Micrographs ◽

Conformational Changes ◽

Anterior Pituitary ◽

Dynamic State ◽

Surrounding Cell ◽

The Matrix ◽

The Moment ◽

Cell Medium ◽

Sectioned Tissue ◽

State Of Activity

Sectioned tissue rarely indicates evidence of what is probably a highly dynamic state of activity in mitochondria which have been reported to undergo a variety of movements such as streaming, divisions and coalescence. Recently, mitochondria from the rat anterior pituitary have been fixed in a variety of configurations which suggest that conformational changes were occurring at the moment of fixation. Pinocytotic-like vacuoles which may be taking in or expelling materials from the surrounding cell medium, appear to be forming in some of the mitochondria. In some cases, pores extend into the matrix of the mitochondria. In other forms, the remains of what seems to be pinched off vacuoles are evident in the mitochondrial interior. Dense materials, resembling secretory droplets, appear at the junction of the pores and the cytoplasm. The droplets are similar to the secretory materials commonly identified in electron micrographs of the anterior pituitary.

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Macroorganisation and flexibility of thylakoid membranes

Biochemical Journal ◽

10.1042/bcj20190080 ◽

2019 ◽

Vol 476 (20) ◽

pp. 2981-3018 ◽

Cited By ~ 8

Author(s):

Petar H. Lambrev ◽

Parveen Akhtar

Keyword(s):

Light Harvesting ◽

Current Knowledge ◽

Three Dimensional ◽

Photosynthetic Apparatus ◽

Dynamic Responses ◽

State Transitions ◽

Photochemical Quenching ◽

Light Harvesting Complex ◽

Complex Ii ◽

Light Harvesting Complex Ii

Abstract The light reactions of photosynthesis are hosted and regulated by the chloroplast thylakoid membrane (TM) — the central structural component of the photosynthetic apparatus of plants and algae. The two-dimensional and three-dimensional arrangement of the lipid–protein assemblies, aka macroorganisation, and its dynamic responses to the fluctuating physiological environment, aka flexibility, are the subject of this review. An emphasis is given on the information obtainable by spectroscopic approaches, especially circular dichroism (CD). We briefly summarise the current knowledge of the composition and three-dimensional architecture of the granal TMs in plants and the supramolecular organisation of Photosystem II and light-harvesting complex II therein. We next acquaint the non-specialist reader with the fundamentals of CD spectroscopy, recent advances such as anisotropic CD, and applications for studying the structure and macroorganisation of photosynthetic complexes and membranes. Special attention is given to the structural and functional flexibility of light-harvesting complex II in vitro as revealed by CD and fluorescence spectroscopy. We give an account of the dynamic changes in membrane macroorganisation associated with the light-adaptation of the photosynthetic apparatus and the regulation of the excitation energy flow by state transitions and non-photochemical quenching.

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