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Minimal frustration underlies the usefulness of incomplete regulatory network models in biology

Proceedings of the National Academy of Sciences of the United States of America 2023年第1期120卷 e2216109120-e2216109120页

作者： Tripathi, Shubham Kessler, David A. Levine, Herbert PhD Program in Systems Synthetic and Physical Biology Rice University Houston 77005 TX United States Center for Theoretical Biological Physics Northeastern University Boston 02115 MA United States Department of Physics Northeastern University Boston 02115 MA United States Department of Physics Bar-Ilan University Ramat-Gan 52900 Israel

Regulatory networks as large and complex as those implicated in cell-fate choice are expected to exhibit intricate, very high-dimensional dynamics. Cell-fate choice, however, is a macroscopically simple process. Additionally, regulatory network models are almost always incomplete and/or inexact, and do not incorporate all the regulators and interactions that may be involved in cell-fate regulation. In spite of these issues, regulatory network models have proven to be incredibly effective tools for understanding cell-fate choice across contexts and for making useful predictions. Here, we show that minimal frustration-a feature of biological networks across contexts but not of random networks-can compel simple, low-dimensional steady-state behavior even in large and complex networks. Moreover, the steady-state behavior of minimally frustrated networks can be recapitulated by simpler networks such as those lacking many of the nodes and edges and those that treat multiple regulators as one. The present study provides a theoretical explanation for the success of network models in biology and for the challenges in network inference. © 2022 the Author(s).

关键词： cell-fate choice frustration gene regulatory networks network inference sloppiness

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Eclipse timing variations in the WD + dM eclipsing binary RR Cae

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Monthly Notices of the Royal Astronomical Society 2023年第4期523卷 5086-5108页

作者： Rattanamala, R. Awiphan, S. Komonjinda, S. Phriksee, A. Sappankum, P. A-Thano, N. Chitchak, S. Rittipruk, P. Sawangwit, U. Poshyachinda, S. Reichart, D.E. Haislip, J.B. PhD Program in Astronomy Department of Physics and Materials Science Faculty of Science Chiang Mai University Chiang Mai50200 Thailand Physics and General Science Program Faculty of Science and Technology Nakhon Ratchasima Rajabhat University Nakhon Ratchasima30000 Thailand 260 Moo 4 Donkaew Mae Rim Chiang Mai50180 Thailand Department of Physics and Materials Science Faculty of Science Chiang Mai University Chiang Mai50200 Thailand Institute of Astronomy National Tsing Hua University Hsinchu30013 Taiwan Department of Physics Faculty of Science Udon Thani Rajabhat University Udon Thani41000 Thailand Department of Physics and Astronomy University of North Carolina at Chapel Hill Chapel HillNC27599 United States

We present the binary model and the eclipse timing variations of the eclipsing binary RR Cae, which consists of a white dwarf eclipsed by an M-type dwarf companion. The multiwavelength optical photometry from the Transiting Exoplanet Survey Satellite (TESS), the 0.6-m PROMPT-8 telescope, and the 0.7-m Thai Robotic Telescope at Spring Brook Observatory, combined with archive H α radial velocities from the Very Large Telescope (VLT) are analysed. From the data, the physical parameters of the system are obtained along with 430 new times of minima. The TESS light curves in 2018 and 2020 show out-of-eclipse variations, which might be caused by a large spot on the secondary component. The light travel time effect models due to the gravitational interaction of one or two circumbinary objects are adopted to fit the cyclic variations in the RR Cae’s O-C curve. The fitting solution of the O-C curve with one circumbinary object model shows a periodic variation with a period of 16.6 ± 0.2 yr and an amplitude of 14 ± 1 s, which can be caused by a planet with a minimum mass of 3.4 ± 0.2 MJup. When we consider the model with two circumbinary objects, the O-C curve shows cyclic variations with periods of 15.0 ± 0.5 yr and 39 ± 5 yr and amplitudes of 12 ± 1 s and 20 ± 5 s, respectively, corresponding to minimum masses of 3.0 ± 0.3 MJup and 2.7 ± 0.7 MJup © 2023 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society.

关键词： Travel time

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Chaos physics in High School - Challenges in Multimedia Application

Chaos Physics in High School - Challenges in Multimedia Appl...

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GIREP Malta Webinar 2020

作者： Bajkó, Ildikó Szent István High School Budapest Ajtósi Dürer sor 15 Budapest1146 Hungary Physics Education PhD Program Eötvös Loránd University Budapest Hungary

Besides being an active field of research, chaotic phenomena are also encountered in our everyday life, thus it's worth discussing them also in formal education in public schools. This paper presents the authors' experiences in teaching chaos on secondary level. A teaching module that encompasses mechanics lab experiments and numerical simulations of typical chaotic systems have been implemented and evaluated. The module offers a number of multimedia applications whose availability in teacher education is also discussed. © Published under licence by IOP Publishing Ltd.

关键词： Chaotic systems

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Period variation of an eclipsing binary system BQ Ari 17

Period variation of an eclipsing binary system BQ Ari

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17th Siam physics Congress: Carbon Neutrality, SPC 2022

作者： Rattanamala, R. Komonjinda, S. Awiphan, S. Wutsang, S. Sappankum, P. Deesuan, L. Department of Physics and General Science Faculty of Science and Technology Nakhon Ratchasima Rajabhat University Nakhon Ratchasima30000 Thailand PhD Program in Astronomy Department of Physics and Materials Science Faculty of Science Chiang Mai University Chiang Mai50200 Thailand Department of Physics and Materials Science Faculty of Science Chiang Mai University Chiang Mai50200 Thailand 260 Moo 4 Donkaew Mae Rim Chiang Mai50180 Thailand

This study was aimed to study the period variation of the eclipsing binary BQ Ari. The system was observed from Thai Robotic Telescope at Spring Brook Observatory (TRT-SBO) between 2019 and 2020, Regional Observatory for Public, Chachoengsao (ROP-CCO) in 2021, and Transiting Exoplanet Survey Satellite (TESS) in Sector 42 and 43. The data obtained were used to create the light curves in each wavelength and compute the times of minima. As the result, we receive 311 time of minima. We combined the time of minima from the previously published with our values to calculate the O - C diagram. The O - C diagram shown the period variation with a period about 6-8 years and amplitude about 0.0020 days. The possibility of the period variation of BQ Ari may be due to the third body component with the mass of 0.0948 M o (M dwarf) and the orbital separation (a 3sini) around 3.96 AU. © Published under licence by IOP Publishing Ltd.

关键词： Observatories

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Information geometry of the retinal representation manifold 23

Information geometry of the retinal representation manifold

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Proceedings of the 37th International Conference on Neural Information Processing Systems

作者： Xuehao Ding Dongsoo Lee Joshua B. Melander George Sivulka Surya Ganguli Stephen A. Baccus Department of Applied Physics Stanford University Neurosciences Phd Program Stanford University Department of Electrical Engineering Stanford University Department of Neurobiology Stanford University

The ability for the brain to discriminate among visual stimuli is constrained by their retinal representations. Previous studies of visual discriminability have been limited to either low-dimensional artificial stimuli or pure theoretical considerations without a realistic encoding model. Here we propose a novel framework for understanding stimulus discriminability achieved by retinal representations of naturalistic stimuli with the method of information geometry. To model the joint probability distribution of neural responses conditioned on the stimulus, we created a stochastic encoding model of a population of salamander retinal ganglion cells based on a three-layer convolutional neural network model. This model not only accurately captured the mean response to natural scenes but also a variety of second-order statistics. With the model and the proposed theory, we computed the Fisher information metric over stimuli to study the most discriminable stimulus directions. We found that the most discriminable stimulus varied substantially across stimuli, allowing an examination of the relationship between the most discriminable stimulus and the current stimulus. By examining responses generated by the most discriminable stimuli we further found that the most discriminative response mode is often aligned with the most stochastic mode. This finding carries the important implication that under natural scenes, retinal noise correlations are information-limiting rather than increasing information transmission as has been previously speculated. We additionally observed that sensitivity saturates less in the population than for single cells and that as a function of firing rate, Fisher information varies less than sensitivity. We conclude that under natural scenes, population coding benefits from complementary coding and helps to equalize the information carried by different firing rates, which may facilitate decoding of the stimulus under principles of information maximizatio

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Self-Consistent Stochastic Dynamics for Finite-Size Networks of Spiking Neurons

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Physical Review Letters 2023年第9期130卷 097402-097402页

作者： Gianni V. Vinci Roberto Benzi Maurizio Mattia Natl. Center for Radiation Protection and Computational Physics Istituto Superiore di Sanità 00161 Roma Italy PhD Program in Physics Dept. of Physics “Tor Vergata” University of Rome 00133 Roma Italy Dept. of Physics and INFN “Tor Vergata” University of Rome 00133 Roma Italy Centro Ricerche “E. Fermi ” 00184 Roma Italy

Despite the huge number of neurons composing a brain network, ongoing activity of local cell assemblies is intrinsically stochastic. Fluctuations in their instantaneous rate of spike firing ν(t) scale with the size of the assembly and persist in isolated networks, i.e., in the absence of external sources of noise. Although deterministic chaos due to the quenched disorder of the synaptic couplings underlies this seemingly stochastic dynamics, an effective theory for the network dynamics of a finite assembly of spiking neurons is lacking. Here, we fill this gap by extending the so-called population density approach including an activity- and size-dependent stochastic source in the Fokker-Planck equation for the membrane potential density. The finite-size noise embedded in this stochastic partial derivative equation is analytically characterized leading to a self-consistent and nonperturbative description of ν(t) valid for a wide class of spiking neuron networks. Power spectra of ν(t) are found in excellent agreement with those from detailed simulations both in the linear regime and across a synchronization phase transition, when a size-dependent smearing of the critical dynamics emerges.

关键词： Neuronal dynamics Neuronal network activity Population dynamics Spiking neurons Synchronization transition Nerve cells Neuronal networks Stochastic dynamical systems Bifurcation analysis Dynamical mean field theory Finite-size scaling First passage problems Fokker–Planck equation Langevin equation Spiking neuron models Stochastic differential equations

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Robustness and stability of spin-glass ground states to perturbed interactions

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Physical Review E 2023年第1期107卷 014126-014126页

作者： Vaibhav Mohanty Ard A. Louis Rudolf Peierls Centre for Theoretical Physics University of Oxford Oxford OX1 3NP United Kingdom MD-PhD Program and Program in Health Sciences and Technology Harvard Medical School Boston Massachusetts 02125 USA and Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA

Across many problems in science and engineering, it is important to consider how much the output of a given system changes due to perturbations of the input. Here, we investigate the glassy phase of ±J spin glasses at zero temperature by calculating the robustness of the ground states to flips in the sign of single interactions. For random graphs and the Sherrington-Kirkpatrick model, we find relatively large sets of bond configurations that generate the same ground state. These sets can themselves be analyzed as subgraphs of the interaction domain, and we compute many of their topological properties. In particular, we find that the robustness, equivalent to the average degree, of these subgraphs is much higher than one would expect from a random model. Most notably, it scales in the same logarithmic way with the size of the subgraph as has been found in genotype-phenotype maps for RNA secondary structure folding, protein quaternary structure, gene regulatory networks, as well as for models for genetic programming. The similarity between these disparate systems suggests that this scaling may have a more universal origin.

关键词： Degree correlations Mutation Network structure Scaling laws of complex systems Real world networks Spin glasses

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Adaptive Behavior with Stable Synapses

arXiv

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arXiv 2024年

作者： Capone, Cristiano Falorsi, Luca Natl. Center for Radiation Protection and Computational Physics Istituto Superiore di Sanità Rome00161 Italy PhD Program in Mathematics Dept. of Mathematics "Sapienza" University of Rome Rome00185 Italy

Behavioral changes in animals and humans, as a consequence of an error or a verbal instruction, can be extremely rapid. Improvement in behavioral performances are usually associated learning theories to synaptic plasticity. However, such rapid changes are not coherent with the timescales of biological synaptic plasticity, suggesting that the mechanism responsible for that could be a dynamical reconfiguration of the network involved, without changing its weights. In the last few years, similar capabilities have been observed in transformers, foundational architecture in the field of machine learning that are widely used in applications such as natural language and image processing. Transformers are capable of in-context learning, the ability to adapt and acquire new information dynamically within the context of the task or environment they are currently engaged in, without the need for significant changes to their underlying parameters. Building upon the notion of something unique within transformers enabling the emergence of this property, we claim that it could be supported by gain-modulation, feature extensively observed in biological networks, such as in pyramidal neurons thanks to input segregation and dendritic amplification. We propose a constructive approach to induce in-context learning in an architecture composed of recurrent networks with gain modulation, demonstrating abilities inaccessible to standard networks. In particular, we show that, such architecture can dynamically implement standard gradient-based by encoding weight changes in the activity of another network. We argue that, while these algorithms are traditionally associated with synaptic plasticity, their reliance on non-local terms suggests that, in the brain, they can be more naturally realized at the level of neural circuits. We demonstrate that we can extend our approach to non-linear and temporal tasks and to reinforcement learning. Our framework contributes to understanding the principles

关键词： Reinforcement learning

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To Sharpen or not to Sharpen? On the Effect of Sharpening Filters Applied to Magnified Images 14

To Sharpen or not to Sharpen? On the Effect of Sharpening Fi...

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14th International Conference on Digital Image Processing, ICDIP 2022

作者： Emmendorfer, Leonardo R. de Olviveira, Vinicius Menezes Schein, Tatiana T. de Jesus, Junior C. Rodriguez, Bárbara D.A. Electrical Energy Processing Department Federal University of Santa Maria 97105-340 Brazil Center for Computational Science Federal University of Rio Grande 96201-900 Brazil Computational Modeling PhD Program Federal University of Rio Grande 96201-900 Brazil Computer Engineering Graduate Program Federal University of Rio Grande 96201-900 Brazil Institute of Mathematics Statistics and Physics Federal University of Rio Grande 96201-900 Brazil

ISBN: (纸本)9781510657564

Super-resolution algorithms aim to produce magnified high-resolution versions from low-resolution images. Some methods, however, are prone to generate blur during the process. Simple sharpening filters are adopted to alleviate this type of artifact. However, the actual effectiveness of this approach is not clear-cut in the literature. This work evaluates the effect of three simple sharpening filters on the quality of images obtained from super-resolution methods. Two metrics were considered in the evaluation: the Peak signal-to-noise ratio (PSNR) metric, and the Learned Perceptual Image Patch Similarity (LPIPS). One of the filters could consistently improve the LPIPS metric of magnified images from diverse benchmark sets on top of seven super-resolution methods. The increments obtained for the perceptual metric seem to occur due to the sharpening effect. Improvements on PSNR values were not as consistent. © 2022 SPIE.

关键词： Quality control

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Fibration symmetries and cluster synchronization in the Caenorhabditis elegans connectome

arXiv

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arXiv 2023年

作者： Avila, Bryant Augusto, Pedro Zimmer, Manuel Serafino, Matteo Makse, Hernán A. Levich Institute Physics Department City College of New York New YorkNY United States Vienna Biocenter PhD Program Doctoral School the University of Vienna Medical University of Vienna Vienna Austria University of Vienna Vienna Austria University of Vienna Vienna Austria

Capturing how the Caenorhabditis elegans connectome structure gives rise to its neuron functionality remains unclear. It is through fiber symmetries found in its neuronal connectivity that synchronization of a group of neurons can be determined. To understand these we investigate graph symmetries and search for such in the symmetrized versions of the forward and backward locomotive sub-networks of the Caenorhabditi elegans worm neuron network. The use of ordinarily differential equations simulations admissible to these graphs are used to validate the predictions of these fiber symmetries and are compared to the more restrictive orbit symmetries. Additionally fibration symmetries are used to decompose these graphs into their fundamental building blocks which reveal units formed by nested loops or multilayered fibers. It is found that fiber symmetries of the connectome can accurately predict neuronal synchronization even under not idealized connectivity as long as the dynamics are within stable regimes of simulations. © 2023, CC BY.

关键词： Fibers

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