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Attractor network

Luis Fernando Méndez-López, Jose Davila-Velderrain, Elisa Domínguez-Hüttinger, Christian Enríquez-Olguín, Juan Carlos Martínez-García, Elena R Alvarez-Buylla
BACKGROUND: Tumorigenic transformation of human epithelial cells in vitro has been described experimentally as the potential result of spontaneous immortalization. This process is characterized by a series of cell-state transitions, in which normal epithelial cells acquire first a senescent state which is later surpassed to attain a mesenchymal stem-like phenotype with a potentially tumorigenic behavior. In this paper we aim to provide a system-level mechanistic explanation to the emergence of these cell types, and to the time-ordered transition patterns that are common to neoplasias of epithelial origin...
February 16, 2017: BMC Systems Biology
Eugenio Azpeitia, Stalin Muñoz, Daniel González-Tokman, Mariana Esther Martínez-Sánchez, Nathan Weinstein, Aurélien Naldi, Elena R Álvarez-Buylla, David A Rosenblueth, Luis Mendoza
Molecular regulation was initially assumed to follow both a unidirectional and a hierarchical organization forming pathways. Regulatory processes, however, form highly interlinked networks with non-hierarchical and non-unidirectional structures that contain statistically overrepresented circuits or motifs. Here, we analyze the behavior of pathways containing non-unidirectional (i.e. bidirectional) and non-hierarchical interactions that create motifs. In comparison with unidirectional and hierarchical pathways, our pathways have a high diversity of behaviors, characterized by the size and number of attractors...
February 10, 2017: Scientific Reports
Edmund T Rolls
The art of memory (ars memoriae) used since classical times includes using a well-known scene to associate each view or part of the scene with a different item in a speech. This memory technique is also known as the 'method of loci'. The new theory is proposed that this type of memory is implemented in the CA3 region of the hippocampus where there are spatial view cells in primates that allow a particular view to be associated with a particular object in an event or episodic memory. Given that the CA3 cells with their extensive recurrent collateral system connecting different CA3 cells, and associative synaptic modifiability, form an autoassociation or attractor network, the spatial view cells with their approximately Gaussian view fields become linked in a continuous attractor network...
February 8, 2017: Hippocampus
Jiyoung Kang, Chongwon Pae, Hae-Jeong Park
The configuration of the human brain system at rest, which is in a transitory phase among multistable states, remains unknown. To investigate the dynamic systems properties of the human brain at rest, we constructed an energy landscape for the state dynamics of the subcortical brain network, a critical center that modulates whole brain states, using resting state fMRI. We evaluated alterations in energy landscapes following perturbation in network parameters, which revealed characteristics of the state dynamics in the subcortical brain system, such as maximal number of attractors, unequal temporal occupations, and readiness for reconfiguration of the system...
February 1, 2017: NeuroImage
Ian H Dinwoodie
For a Boolean network we consider asynchronous updates and define the exclusive asynchronous basin of attraction for any steady state or cyclic attractor. An algorithm based on commutative algebra is presented to compute the exclusive basin. Finally its use for targeting desirable attractors by selective intervention on network nodes is illustrated with two examples, one cell signalling network and one sensor network measuring human mobility.
December 2016: Discrete and Continuous Dynamical Systems. Series B
Ming-Jun Feng, Hui-Min Chu, Cai-Jie Shen, Bin He, Xian-Feng Du, Yi-Bo Yu, Jing Liu, Xiao-Min Chen
BACKGROUND: Our study was designed to identify the differential attractor modules related with hypertrophic cardiomyopathy (HCM) by integrating clustering-based on maximal cliques algorithm and Attract method. METHODS: We firstly recruited the HCM-related microarray data from ArrayExpress database. Next, protein-protein interaction (PPI) networks of normal and HCM were constructed and re-weighted using spearman correlation coefficient (SCC). Then, maximal cliques were found from the PPI networks through the clustering-based on maximal cliques approach...
January 19, 2017: Computational Biology and Chemistry
Andrea Insabato, Mario Pannunzi, Gustavo Deco
The uncertain option task has been recently adopted to investigate the neural systems underlying the decision confidence. Latterly single neurons activity has been recorded in lateral intraparietal cortex of monkeys performing an uncertain option task, where the subject is allowed to opt for a small but sure reward instead of making a risky perceptual decision. We propose a multiple choice model implemented in a discrete attractors network. This model is able to reproduce both behavioral and neurophysiological experimental data and therefore provides support to the numerous perspectives that interpret the uncertain option task as a sensory-motor association...
January 2017: PLoS Computational Biology
James J Bonaiuto, Archy de Berker, Sven Bestmann
Animals and humans have a tendency to repeat recent choices, a phenomenon known as choice hysteresis. The mechanism for this choice bias remains unclear. Using an established, biophysically informed model of a competitive attractor network for decision making, we found that decaying tail activity from the previous trial caused choice hysteresis, especially during difficult trials, and accurately predicted human perceptual choices. In the model, choice variability could be directionally altered through amplification or dampening of post-trial activity decay through simulated depolarizing or hyperpolarizing network stimulation...
December 22, 2016: ELife
András Szilágyi, István Zachar, Anna Fedor, Harold P de Vladar, Eörs Szathmáry
Background: The fact that surplus connections and neurons are pruned during development is well established. We complement this selectionist picture by a proof-of-principle model of evolutionary search in the brain, that accounts for new variations in theory space. We present a model for Darwinian evolutionary search for candidate solutions in the brain. Methods: We combine known components of the brain - recurrent neural networks (acting as attractors), the action selection loop and implicit working memory - to provide the appropriate Darwinian architecture...
2016: F1000Research
Akshata R Udyavar, David J Wooten, Megan D Hoeksema, Mukesh Bansal, Andrea Califano, Lourdes Estrada, Santiago Schnell, Jonathan M Irish, Pierre P Massion, Vito Quaranta
Small cell lung cancer (SCLC) is a devastating disease due to its propensity for early invasion and refractory relapse after initial treatment response. Although these aggressive traits have been associated with phenotypic heterogeneity, our understanding of this association remains incomplete. To fill this knowledge gap, we inferred a set of 33 transcription factors (TF) associated with gene signatures of the known neuroendocrine/epithelial (NE) and non-neuroendocrine/mesenchymal-like (ML) SCLC phenotypes...
December 8, 2016: Cancer Research
Dawid Dudkowski, Yuri Maistrenko, Tomasz Kapitaniak
We studied the phenomenon of chimera states in networks of non-locally coupled externally excited oscillators. Units of the considered networks are bi-stable, having two co-existing attractors of different types (chaotic and periodic). The occurrence of chimeras is discussed, and the influence of coupling radius and coupling strength on their co-existence is analyzed (including typical bifurcation scenarios). We present a statistical analysis and investigate sensitivity of the probability of observing chimeras to the initial conditions and parameter values...
November 2016: Chaos
Lei Zhao, Jin Wang
Recent studies on Caenorhabditis elegans reveal that gene manipulations can extend its lifespan several fold. However, how the genes work together to determine longevity is still an open question. Here we construct a gene regulatory network for worm ageing and quantify its underlying potential and flux landscape. We found ageing and rejuvenation states can emerge as basins of attraction at certain gene expression levels. The system state can switch from one attractor to another driven by the intrinsic or external perturbations through genetics or the environment...
November 2016: Journal of the Royal Society, Interface
Oliver Shipston-Sharman, Lukas Solanka, Matthew F Nolan
Neurons in the medial entorhinal cortex encode location through spatial firing fields that have a grid-like organisation. The challenge of identifying mechanisms for grid firing has been addressed through experimental and theoretical investigations of medial entorhinal circuits. Here, we discuss evidence for continuous attractor network models that account for grid firing by synaptic interactions between excitatory and inhibitory cells. These models assume that grid-like firing patterns are the result of computation of location from velocity inputs, with additional spatial input required to oppose drift in the attractor state...
November 15, 2016: Journal of Physiology
Jonathan Warrell, Musa Mhlanga
Coregulation of the expression of groups of genes has been extensively demonstrated empirically in bacterial and eukaryotic systems. Such coregulation can arise through the use of shared regulatory motifs, which allow the coordinated expression of modules (and module groups) of functionally related genes across the genome. Coregulation can also arise through the physical association of multi-gene complexes through chromosomal looping, which are then transcribed together. We present a general formalism for modeling coregulation rules in the framework of Random Boolean Networks (RBN), and develop specific models for transcription factor networks with modular structure (including module groups, and multi-input modules (MIM) with autoregulation) and multi-gene complexes (including hierarchical differentiation between multi-gene complex members)...
November 17, 2016: Journal of Theoretical Biology
Zhiwei He, Meng Zhan, Shuai Liu, Zebo Fang, Chenggui Yao
The detection of the singleton attractors is of great significance for the systematic study of genetic regulatory network. In this paper, we design an algorithm to compute the singleton attractors and pre-images of the strong-inhibition Boolean networks which is a biophysically plausible gene model. Our algorithm can not only identify accurately the singleton attractors, but also find easily the pre-images of the network. Based on extensive computational experiments, we show that the computational time of the algorithm is proportional to the number of the singleton attractors, which indicates the algorithm has much advantage in finding the singleton attractors for the networks with high average degree and less inhibitory interactions...
2016: PloS One
Oliver Lomp, Mathis Richter, Stephan K U Zibner, Gregor Schöner
Embodied artificial cognitive systems, such as autonomous robots or intelligent observers, connect cognitive processes to sensory and effector systems in real time. Prime candidates for such embodied intelligence are neurally inspired architectures. While components such as forward neural networks are well established, designing pervasively autonomous neural architectures remains a challenge. This includes the problem of tuning the parameters of such architectures so that they deliver specified functionality under variable environmental conditions and retain these functions as the architectures are expanded...
2016: Frontiers in Neurorobotics
Hannes Klarner, Adam Streck, Heike Siebert
MOTIVATION: The goal of this project is to provide a simple interface to working with Boolean networks. Emphasis is put on easy access to a large number of common tasks including the generation and manipulation of networks, attractor and basin computation, model checking and trap space computation, execution of established graph algorithms as well as graph drawing and layouts. RESULTS: PyBoolNet is a Python package for working with Boolean networks that supports simple access to model checking via NuSMV, standard graph algorithms via NetworkX and visualization via dot In addition, state of the art attractor computation exploiting Potassco ASP is implemented...
October 26, 2016: Bioinformatics
Julian Schwab, Andre Burkovski, Lea Siegle, Christoph Müssel, Hans A Kestler
: : Mathematical models and their simulation are increasingly used to gain insights into cellular pathways and regulatory networks. Dynamics of regulatory factors can be modeled using Boolean networks (BNs), among others. Text-based representations of models are precise descriptions, but hard to understand and interpret. ViSiBooL aims at providing a graphical way of modeling and simulating networks. By providing visualizations of static and dynamic network properties simultaneously, it is possible to directly observe the effects of changes in the network structure on the behavior...
October 22, 2016: Bioinformatics
Thomas Miconi, Jeffrey L McKinstry, Gerald M Edelman
Recent evidence suggests that neurons in primary sensory cortex arrange into competitive groups, representing stimuli by their joint activity rather than as independent feature analysers. A possible explanation for these results is that sensory cortex implements attractor dynamics, although this proposal remains controversial. Here we report that fast attractor dynamics emerge naturally in a computational model of a patch of primary visual cortex endowed with realistic plasticity (at both feedforward and lateral synapses) and mutual inhibition...
October 31, 2016: Nature Communications
Jeffrey Emenheiser, Airlie Chapman, Márton Pósfai, James P Crutchfield, Mehran Mesbahi, Raissa M D'Souza
Following the long-lived qualitative-dynamics tradition of explaining behavior in complex systems via the architecture of their attractors and basins, we investigate the patterns of switching between distinct trajectories in a network of synchronized oscillators. Our system, consisting of nonlinear amplitude-phase oscillators arranged in a ring topology with reactive nearest-neighbor coupling, is simple and connects directly to experimental realizations. We seek to understand how the multiple stable synchronized states connect to each other in state space by applying Gaussian white noise to each of the oscillators' phases...
September 2016: Chaos
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