@article{31,
abstract = {Correlations in sensory neural networks have both extrinsic and intrinsic origins. Extrinsic or stimulus correlations arise from shared inputs to the network and, thus, depend strongly on the stimulus ensemble. Intrinsic or noise correlations reflect biophysical mechanisms of interactions between neurons, which are expected to be robust to changes in the stimulus ensemble. Despite the importance of this distinction for understanding how sensory networks encode information collectively, no method exists to reliably separate intrinsic interactions from extrinsic correlations in neural activity data, limiting our ability to build predictive models of the network response. In this paper we introduce a general strategy to infer population models of interacting neurons that collectively encode stimulus information. The key to disentangling intrinsic from extrinsic correlations is to infer the couplings between neurons separately from the encoding model and to combine the two using corrections calculated in a mean-field approximation. We demonstrate the effectiveness of this approach in retinal recordings. The same coupling network is inferred from responses to radically different stimulus ensembles, showing that these couplings indeed reflect stimulus-independent interactions between neurons. The inferred model predicts accurately the collective response of retinal ganglion cell populations as a function of the stimulus.},
author = {Ferrari, Ulisse and Deny, Stephane and Chalk, Matthew J and Tkacik, Gasper and Marre, Olivier and Mora, Thierry},
issn = {24700045},
journal = {Physical Review E},
number = {4},
publisher = {American Physical Society},
title = {{Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons}},
doi = {10.1103/PhysRevE.98.042410},
volume = {98},
year = {2018},
}
@article{548,
abstract = {In this work maximum entropy distributions in the space of steady states of metabolic networks are considered upon constraining the first and second moments of the growth rate. Coexistence of fast and slow phenotypes, with bimodal flux distributions, emerges upon considering control on the average growth (optimization) and its fluctuations (heterogeneity). This is applied to the carbon catabolic core of Escherichia coli where it quantifies the metabolic activity of slow growing phenotypes and it provides a quantitative map with metabolic fluxes, opening the possibility to detect coexistence from flux data. A preliminary analysis on data for E. coli cultures in standard conditions shows degeneracy for the inferred parameters that extend in the coexistence region.},
author = {De Martino, Daniele},
issn = {24700045},
journal = {Physical Review E},
number = {6},
publisher = {American Physiological Society},
title = {{Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes}},
doi = {10.1103/PhysRevE.96.060401},
volume = {96},
year = {2017},
}
@article{673,
abstract = {We present a numerical study of wavy supercritical cylindrical Couette flow between counter-rotating cylinders in which the wavy pattern propagates either prograde with the inner cylinder or retrograde opposite the rotation of the inner cylinder. The wave propagation reversals from prograde to retrograde and vice versa occur at distinct values of the inner cylinder Reynolds number when the associated frequency of the wavy instability vanishes. The reversal occurs for both twofold and threefold symmetric wavy vortices. Moreover, the wave propagation reversal only occurs for sufficiently strong counter-rotation. The flow pattern reversal appears to be intrinsic in the system as either periodic boundary conditions or fixed end wall boundary conditions for different system sizes always result in the wave propagation reversal. We present a detailed bifurcation sequence and parameter space diagram with respect to retrograde behavior of wavy flows. The retrograde propagation of the instability occurs when the inner Reynolds number is about two times the outer Reynolds number. The mechanism for the retrograde propagation is associated with the inviscidly unstable region near the inner cylinder and the direction of the global average azimuthal velocity. Flow dynamics, spatio-temporal behavior, global mean angular velocity, and torque of the flow with the wavy pattern are explored.},
author = {Altmeyer, Sebastian and Lueptow, Richard},
issn = {24700045},
journal = {Physical Review E - Statistical, Nonlinear, and Soft Matter Physics},
number = {5},
publisher = {American Physiological Society},
title = {{Wave propagation reversal for wavy vortices in wide gap counter rotating cylindrical Couette flow}},
doi = {10.1103/PhysRevE.95.053103},
volume = {95},
year = {2017},
}
@article{700,
abstract = {Microtubules provide the mechanical force required for chromosome separation during mitosis. However, little is known about the dynamic (high-frequency) mechanical properties of microtubules. Here, we theoretically propose to control the vibrations of a doubly clamped microtubule by tip electrodes and to detect its motion via the optomechanical coupling between the vibrational modes of the microtubule and an optical cavity. In the presence of a red-detuned strong pump laser, this coupling leads to optomechanical-induced transparency of an optical probe field, which can be detected with state-of-the art technology. The center frequency and line width of the transparency peak give the resonance frequency and damping rate of the microtubule, respectively, while the height of the peak reveals information about the microtubule-cavity field coupling. Our method opens the new possibilities to gain information about the physical properties of microtubules, which will enhance our capability to design physical cancer treatment protocols as alternatives to chemotherapeutic drugs.},
author = {Barzanjeh, Shabir and Salari, Vahid and Tuszynski, Jack and Cifra, Michal and Simon, Christoph},
issn = {24700045},
journal = { Physical Review E Statistical Nonlinear and Soft Matter Physics },
number = {1},
publisher = {American Institute of Physics},
title = {{Optomechanical proposal for monitoring microtubule mechanical vibrations}},
doi = {10.1103/PhysRevE.96.012404},
volume = {96},
year = {2017},
}
@article{959,
abstract = {In this work it is shown that scale-free tails in metabolic flux distributions inferred in stationary models are an artifact due to reactions involved in thermodynamically unfeasible cycles, unbounded by physical constraints and in principle able to perform work without expenditure of free energy. After implementing thermodynamic constraints by removing such loops, metabolic flux distributions scale meaningfully with the physical limiting factors, acquiring in turn a richer multimodal structure potentially leading to symmetry breaking while optimizing for objective functions.},
author = {De Martino, Daniele},
issn = {24700045},
journal = { Physical Review E Statistical Nonlinear and Soft Matter Physics },
number = {6},
pages = {062419},
publisher = {American Institute of Physics},
title = {{Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics}},
doi = {10.1103/PhysRevE.95.062419},
volume = {95},
year = {2017},
}
@article{947,
abstract = {Viewing the ways a living cell can organize its metabolism as the phase space of a physical system, regulation can be seen as the ability to reduce the entropy of that space by selecting specific cellular configurations that are, in some sense, optimal. Here we quantify the amount of regulation required to control a cell's growth rate by a maximum-entropy approach to the space of underlying metabolic phenotypes, where a configuration corresponds to a metabolic flux pattern as described by genome-scale models. We link the mean growth rate achieved by a population of cells to the minimal amount of metabolic regulation needed to achieve it through a phase diagram that highlights how growth suppression can be as costly (in regulatory terms) as growth enhancement. Moreover, we provide an interpretation of the inverse temperature β controlling maximum-entropy distributions based on the underlying growth dynamics. Specifically, we show that the asymptotic value of β for a cell population can be expected to depend on (i) the carrying capacity of the environment, (ii) the initial size of the colony, and (iii) the probability distribution from which the inoculum was sampled. Results obtained for E. coli and human cells are found to be remarkably consistent with empirical evidence.},
author = {De Martino, Daniele and Capuani, Fabrizio and De Martino, Andrea},
issn = {24700045},
journal = { Physical Review E Statistical Nonlinear and Soft Matter Physics },
number = {1},
publisher = {American Institute of Physics},
title = {{Quantifying the entropic cost of cellular growth control}},
doi = {10.1103/PhysRevE.96.010401},
volume = {96},
year = {2017},
}