1,756 research outputs found
Global Analysis of Dynamical Decision-Making Models through Local Computation around the Hidden Saddle
Bistable dynamical switches are frequently encountered in mathematical modeling of biological systems because binary decisions are at the core of many cellular processes. Bistable switches present two stable steady-states, each of them corresponding to a distinct decision. In response to a transient signal, the system can flip back and forth between these two stable steady-states, switching between both decisions. Understanding which parameters and states affect this switch between stable states may shed light on the mechanisms underlying the decision-making process. Yet, answering such a question involves analyzing the global dynamical (i.e., transient) behavior of a nonlinear, possibly high dimensional model. In this paper, we show how a local analysis at a particular equilibrium point of bistable systems is highly relevant to understand the global properties of the switching system. The local analysis is performed at the saddle point, an often disregarded equilibrium point of bistable models but which is shown to be a key ruler of the decision-making process. Results are illustrated on three previously published models of biological switches: two models of apoptosis, the programmed cell death and one model of long-term potentiation, a phenomenon underlying synaptic plasticity
Coupled Reversible and Irreversible Bistable Switches Underlying TGF-\beta-induced Epithelial to Mesenchymal Transition
Epithelial to mesenchymal transition (EMT) plays important roles in embryonic
development, tissue regeneration and cancer metastasis. While several feedback
loops have been shown to regulate EMT, it remains elusive how they coordinately
modulate EMT response to TGF-\beta treatment. We construct a mathematical model
for the core regulatory network controlling TGF-\beta-induced EMT. Through
deterministic analyses and stochastic simulations, we show that EMT is a
sequential two-step program that an epithelial cell first transits to partial
EMT then to the mesenchymal state, depending on the strength and duration of
TGF-\beta stimulation. Mechanistically the system is governed by coupled
reversible and irreversible bistable switches. The SNAIL1/miR-34 double
negative feedback loop is responsible for the reversible switch and regulates
the initiation of EMT, while the ZEB/miR-200 feedback loop is accountable for
the irreversible switch and controls the establishment of the mesenchymal
state. Furthermore, an autocrine TGF-\beta/miR-200 feedback loop makes the
second switch irreversible, modulating the maintenance of EMT. Such coupled
bistable switches are robust to parameter variation and molecular noise. We
provide a mechanistic explanation on multiple experimental observations. The
model makes several explicit predictions on hysteretic dynamic behaviors,
system response to pulsed stimulation and various perturbations, which can be
straightforwardly tested.Comment: 32 pages, 8 figures, accepted by Biophysical Journa
Requirements for efficient cell-type proportioning: regulatory timescales, stochasticity and lateral inhibition
The proper functioning of multicellular organisms requires the robust
establishment of precise proportions between distinct cell-types. This
developmental differentiation process typically involves intracellular
regulatory and stochastic mechanisms to generate cell-fate diversity as well as
intercellular mechanisms to coordinate cell-fate decisions at tissue level. We
thus surmise that key insights about the developmental regulation of cell-type
proportion can be captured by the modeling study of clustering dynamics in
population of inhibitory-coupled noisy bistable systems. This general class of
dynamical system is shown to exhibit a very stable two-cluster state, but also
frustrated relaxation, collective oscillations or steady-state hopping which
prevents from timely and reliably reaching a robust and well-proportioned
clustered state. To circumvent these obstacles or to avoid fine-tuning, we
highlight a general strategy based on dual-time positive feedback loops, such
as mediated through transcriptional versus epigenetic mechanisms, which
improves proportion regulation by coordinating early and flexible lineage
priming with late and firm commitment. This result sheds new light on the
respective and cooperative roles of multiple regulatory feedback, stochasticity
and lateral inhibition in developmental dynamics
Introduction to Focus Issue : Dynamics in Systems Biology
Peer reviewedPublisher PD
Quantum effects in linguistic endeavors
Classifying the information content of neural spike trains in a linguistic
endeavor, an uncertainty relation emerges between the bit size of a word and
its duration. This uncertainty is associated with the task of synchronizing the
spike trains of different duration representing different words. The
uncertainty involves peculiar quantum features, so that word comparison amounts
to measurement-based-quantum computation. Such a quantum behavior explains the
onset and decay of the memory window connecting successive pieces of a
linguistic text. The behavior here discussed is applicable to other reported
evidences of quantum effects in human linguistic processes, so far lacking a
plausible framework, since either no efforts to assign an appropriate quantum
constant had been associated or speculating on microscopic processes dependent
on Planck's constant resulted in unrealistic decoherence times
Nonlinear Dynamics in Distributed Systems
We build on a previous statistical model for distributed systems and
formulate it in a way that the deterministic and stochastic processes within
the system are clearly separable. We show how internal fluctuations can be
analysed in a systematic way using Van Kanpen's expansion method for Markov
processes. We present some results for both stationary and time-dependent
states. Our approach allows the effect of fluctuations to be explored,
particularly in finite systems where such processes assume increasing
importance.Comment: Two parts: 8 pages LaTeX file and 5 (uuencoded) figures in Postscript
forma
SIMPEL: Circuit model for photonic spike processing laser neurons
We propose an equivalent circuit model for photonic spike processing laser
neurons with an embedded saturable absorber---a simulation model for photonic
excitable lasers (SIMPEL). We show that by mapping the laser neuron rate
equations into a circuit model, SPICE analysis can be used as an efficient and
accurate engine for numerical calculations, capable of generalization to a
variety of different laser neuron types found in literature. The development of
this model parallels the Hodgkin--Huxley model of neuron biophysics, a circuit
framework which brought efficiency, modularity, and generalizability to the
study of neural dynamics. We employ the model to study various
signal-processing effects such as excitability with excitatory and inhibitory
pulses, binary all-or-nothing response, and bistable dynamics.Comment: 16 pages, 7 figure
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