[{"intvolume":"        98","article_processing_charge":"No","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","department":[{"_id":"GaTk"}],"acknowledgement":"This work was supported by ANR Trajectory, the French State program Investissements d’Avenir managed by the Agence Nationale de la Recherche (LIFESENSES; ANR-10-LABX-65), EC Grant No. H2020-785907 from the Human Brain Project, NIH Grant No. U01NS090501, and an AVIESAN-UNADEV grant to O.M. M.C. was supported by the Agence Nationale de la Recherche Jeune Chercheur/Jeune Chercheuse grant (ANR-17-CE37-0013).","date_created":"2018-12-11T11:44:15Z","article_number":"042410","volume":98,"article_type":"original","isi":1,"publication_identifier":{"issn":["24700045"]},"publist_id":"8024","quality_controlled":"1","month":"10","type":"journal_article","year":"2018","publisher":"American Physical Society","doi":"10.1103/PhysRevE.98.042410","language":[{"iso":"eng"}],"date_published":"2018-10-17T00:00:00Z","_id":"31","oa":1,"author":[{"first_name":"Ulisse","full_name":"Ferrari, Ulisse","last_name":"Ferrari"},{"last_name":"Deny","full_name":"Deny, Stephane","first_name":"Stephane"},{"first_name":"Matthew J","full_name":"Chalk, Matthew J","last_name":"Chalk"},{"first_name":"Gasper","full_name":"Tkacik, Gasper","orcid":"0000-0002-6699-1455","last_name":"Tkacik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Olivier","full_name":"Marre, Olivier","last_name":"Marre"},{"last_name":"Mora","full_name":"Mora, Thierry","first_name":"Thierry"}],"scopus_import":"1","issue":"4","citation":{"short":"U. Ferrari, S. Deny, M.J. Chalk, G. Tkačik, O. Marre, T. Mora, Physical Review E 98 (2018).","mla":"Ferrari, Ulisse, et al. “Separating Intrinsic Interactions from Extrinsic Correlations in a Network of Sensory Neurons.” <i>Physical Review E</i>, vol. 98, no. 4, 042410, American Physical Society, 2018, doi:<a href=\"https://doi.org/10.1103/PhysRevE.98.042410\">10.1103/PhysRevE.98.042410</a>.","ista":"Ferrari U, Deny S, Chalk MJ, Tkačik G, Marre O, Mora T. 2018. Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons. Physical Review E. 98(4), 042410.","apa":"Ferrari, U., Deny, S., Chalk, M. J., Tkačik, G., Marre, O., &#38; Mora, T. (2018). Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons. <i>Physical Review E</i>. American Physical Society. <a href=\"https://doi.org/10.1103/PhysRevE.98.042410\">https://doi.org/10.1103/PhysRevE.98.042410</a>","ama":"Ferrari U, Deny S, Chalk MJ, Tkačik G, Marre O, Mora T. Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons. <i>Physical Review E</i>. 2018;98(4). doi:<a href=\"https://doi.org/10.1103/PhysRevE.98.042410\">10.1103/PhysRevE.98.042410</a>","chicago":"Ferrari, Ulisse, Stephane Deny, Matthew J Chalk, Gašper Tkačik, Olivier Marre, and Thierry Mora. “Separating Intrinsic Interactions from Extrinsic Correlations in a Network of Sensory Neurons.” <i>Physical Review E</i>. American Physical Society, 2018. <a href=\"https://doi.org/10.1103/PhysRevE.98.042410\">https://doi.org/10.1103/PhysRevE.98.042410</a>.","ieee":"U. Ferrari, S. Deny, M. J. Chalk, G. Tkačik, O. Marre, and T. Mora, “Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons,” <i>Physical Review E</i>, vol. 98, no. 4. American Physical Society, 2018."},"project":[{"name":"Human Brain Project Specific Grant Agreement 2 (HBP SGA 2)","_id":"26436750-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","grant_number":"785907"}],"title":"Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons","external_id":{"isi":["000447486100004"]},"publication":"Physical Review E","main_file_link":[{"open_access":"1","url":"https://www.biorxiv.org/content/10.1101/243816v2.full"}],"status":"public","date_updated":"2023-09-18T09:18:44Z","abstract":[{"text":"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.","lang":"eng"}],"ec_funded":1,"day":"17","oa_version":"Preprint","publication_status":"published"},{"date_updated":"2023-02-23T12:56:35Z","status":"public","abstract":[{"text":"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.","lang":"eng"}],"ec_funded":1,"day":"12","publication_status":"published","oa_version":"Submitted Version","citation":{"chicago":"Barzanjeh, Shabir, Vahid Salari, Jack Tuszynski, Michal Cifra, and Christoph Simon. “Optomechanical Proposal for Monitoring Microtubule Mechanical Vibrations.” <i> Physical Review E Statistical Nonlinear and Soft Matter Physics </i>. American Institute of Physics, 2017. <a href=\"https://doi.org/10.1103/PhysRevE.96.012404\">https://doi.org/10.1103/PhysRevE.96.012404</a>.","ieee":"S. Barzanjeh, V. Salari, J. Tuszynski, M. Cifra, and C. Simon, “Optomechanical proposal for monitoring microtubule mechanical vibrations,” <i> Physical Review E Statistical Nonlinear and Soft Matter Physics </i>, vol. 96, no. 1. American Institute of Physics, 2017.","short":"S. Barzanjeh, V. Salari, J. Tuszynski, M. Cifra, C. Simon,  Physical Review E Statistical Nonlinear and Soft Matter Physics  96 (2017).","mla":"Barzanjeh, Shabir, et al. “Optomechanical Proposal for Monitoring Microtubule Mechanical Vibrations.” <i> Physical Review E Statistical Nonlinear and Soft Matter Physics </i>, vol. 96, no. 1, 012404, American Institute of Physics, 2017, doi:<a href=\"https://doi.org/10.1103/PhysRevE.96.012404\">10.1103/PhysRevE.96.012404</a>.","apa":"Barzanjeh, S., Salari, V., Tuszynski, J., Cifra, M., &#38; Simon, C. (2017). Optomechanical proposal for monitoring microtubule mechanical vibrations. <i> Physical Review E Statistical Nonlinear and Soft Matter Physics </i>. American Institute of Physics. <a href=\"https://doi.org/10.1103/PhysRevE.96.012404\">https://doi.org/10.1103/PhysRevE.96.012404</a>","ista":"Barzanjeh S, Salari V, Tuszynski J, Cifra M, Simon C. 2017. Optomechanical proposal for monitoring microtubule mechanical vibrations.  Physical Review E Statistical Nonlinear and Soft Matter Physics . 96(1), 012404.","ama":"Barzanjeh S, Salari V, Tuszynski J, Cifra M, Simon C. Optomechanical proposal for monitoring microtubule mechanical vibrations. <i> Physical Review E Statistical Nonlinear and Soft Matter Physics </i>. 2017;96(1). doi:<a href=\"https://doi.org/10.1103/PhysRevE.96.012404\">10.1103/PhysRevE.96.012404</a>"},"project":[{"_id":"258047B6-B435-11E9-9278-68D0E5697425","name":"Microwave-to-Optical Quantum Link: Quantum Teleportation and Quantum Illumination with cavity Optomechanics","call_identifier":"H2020","grant_number":"707438"}],"scopus_import":1,"issue":"1","main_file_link":[{"open_access":"1","url":"https://arxiv.org/pdf/1612.07061.pdf"}],"title":"Optomechanical proposal for monitoring microtubule mechanical vibrations","publication":" Physical Review E Statistical Nonlinear and Soft Matter Physics ","year":"2017","publisher":"American Institute of Physics","doi":"10.1103/PhysRevE.96.012404","language":[{"iso":"eng"}],"type":"journal_article","_id":"700","oa":1,"author":[{"first_name":"Shabir","full_name":"Barzanjeh, Shabir","last_name":"Barzanjeh","id":"2D25E1F6-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-0415-1423"},{"last_name":"Salari","full_name":"Salari, Vahid","first_name":"Vahid"},{"first_name":"Jack","full_name":"Tuszynski, Jack","last_name":"Tuszynski"},{"first_name":"Michal","full_name":"Cifra, Michal","last_name":"Cifra"},{"first_name":"Christoph","full_name":"Simon, Christoph","last_name":"Simon"}],"date_published":"2017-07-12T00:00:00Z","department":[{"_id":"JoFi"}],"article_number":"012404","date_created":"2018-12-11T11:48:00Z","intvolume":"        96","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","publication_identifier":{"issn":["24700045"]},"publist_id":"6997","quality_controlled":"1","month":"07","volume":96},{"publication":" Physical Review E Statistical Nonlinear and Soft Matter Physics ","title":"Quantifying the entropic cost of cellular growth control","external_id":{"isi":["000405194200002"]},"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1703.00219"}],"scopus_import":"1","issue":"1","citation":{"ama":"De Martino D, Capuani F, De Martino A. Quantifying the entropic cost of cellular growth control. <i> Physical Review E Statistical Nonlinear and Soft Matter Physics </i>. 2017;96(1). doi:<a href=\"https://doi.org/10.1103/PhysRevE.96.010401\">10.1103/PhysRevE.96.010401</a>","short":"D. De Martino, F. Capuani, A. De Martino,  Physical Review E Statistical Nonlinear and Soft Matter Physics  96 (2017).","ista":"De Martino D, Capuani F, De Martino A. 2017. Quantifying the entropic cost of cellular growth control.  Physical Review E Statistical Nonlinear and Soft Matter Physics . 96(1), 010401.","mla":"De Martino, Daniele, et al. “Quantifying the Entropic Cost of Cellular Growth Control.” <i> Physical Review E Statistical Nonlinear and Soft Matter Physics </i>, vol. 96, no. 1, 010401, American Institute of Physics, 2017, doi:<a href=\"https://doi.org/10.1103/PhysRevE.96.010401\">10.1103/PhysRevE.96.010401</a>.","apa":"De Martino, D., Capuani, F., &#38; De Martino, A. (2017). Quantifying the entropic cost of cellular growth control. <i> Physical Review E Statistical Nonlinear and Soft Matter Physics </i>. American Institute of Physics. <a href=\"https://doi.org/10.1103/PhysRevE.96.010401\">https://doi.org/10.1103/PhysRevE.96.010401</a>","ieee":"D. De Martino, F. Capuani, and A. De Martino, “Quantifying the entropic cost of cellular growth control,” <i> Physical Review E Statistical Nonlinear and Soft Matter Physics </i>, vol. 96, no. 1. American Institute of Physics, 2017.","chicago":"De Martino, Daniele, Fabrizio Capuani, and Andrea De Martino. “Quantifying the Entropic Cost of Cellular Growth Control.” <i> Physical Review E Statistical Nonlinear and Soft Matter Physics </i>. American Institute of Physics, 2017. <a href=\"https://doi.org/10.1103/PhysRevE.96.010401\">https://doi.org/10.1103/PhysRevE.96.010401</a>."},"project":[{"name":"International IST Postdoc Fellowship Programme","_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734","call_identifier":"FP7"}],"day":"10","oa_version":"Submitted Version","publication_status":"published","abstract":[{"text":"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.","lang":"eng"}],"ec_funded":1,"status":"public","date_updated":"2023-09-22T10:03:50Z","isi":1,"volume":96,"month":"07","publication_identifier":{"issn":["24700045"]},"publist_id":"6470","quality_controlled":"1","article_processing_charge":"No","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","intvolume":"        96","article_number":"010401","date_created":"2018-12-11T11:49:21Z","department":[{"_id":"GaTk"}],"date_published":"2017-07-10T00:00:00Z","author":[{"last_name":"De Martino","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-5214-4706","first_name":"Daniele","full_name":"De Martino, Daniele"},{"full_name":"Capuani, Fabrizio","first_name":"Fabrizio","last_name":"Capuani"},{"first_name":"Andrea","full_name":"De Martino, Andrea","last_name":"De Martino"}],"_id":"947","oa":1,"type":"journal_article","doi":"10.1103/PhysRevE.96.010401","language":[{"iso":"eng"}],"year":"2017","publisher":"American Institute of Physics"},{"scopus_import":"1","issue":"6","citation":{"apa":"De Martino, D. (2017). Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics. <i> Physical Review E Statistical Nonlinear and Soft Matter Physics </i>. American Institute of Physics. <a href=\"https://doi.org/10.1103/PhysRevE.95.062419\">https://doi.org/10.1103/PhysRevE.95.062419</a>","short":"D. De Martino,  Physical Review E Statistical Nonlinear and Soft Matter Physics  95 (2017) 062419.","mla":"De Martino, Daniele. “Scales and Multimodal Flux Distributions in Stationary Metabolic Network Models via Thermodynamics.” <i> Physical Review E Statistical Nonlinear and Soft Matter Physics </i>, vol. 95, no. 6, American Institute of Physics, 2017, p. 062419, doi:<a href=\"https://doi.org/10.1103/PhysRevE.95.062419\">10.1103/PhysRevE.95.062419</a>.","ista":"De Martino D. 2017. Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics.  Physical Review E Statistical Nonlinear and Soft Matter Physics . 95(6), 062419.","ama":"De Martino D. Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics. <i> Physical Review E Statistical Nonlinear and Soft Matter Physics </i>. 2017;95(6):062419. doi:<a href=\"https://doi.org/10.1103/PhysRevE.95.062419\">10.1103/PhysRevE.95.062419</a>","chicago":"De Martino, Daniele. “Scales and Multimodal Flux Distributions in Stationary Metabolic Network Models via Thermodynamics.” <i> Physical Review E Statistical Nonlinear and Soft Matter Physics </i>. American Institute of Physics, 2017. <a href=\"https://doi.org/10.1103/PhysRevE.95.062419\">https://doi.org/10.1103/PhysRevE.95.062419</a>.","ieee":"D. De Martino, “Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics,” <i> Physical Review E Statistical Nonlinear and Soft Matter Physics </i>, vol. 95, no. 6. American Institute of Physics, p. 062419, 2017."},"project":[{"call_identifier":"FP7","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme"}],"publication":" Physical Review E Statistical Nonlinear and Soft Matter Physics ","title":"Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics","external_id":{"isi":["000404546400004"]},"main_file_link":[{"url":"https://arxiv.org/pdf/1703.00853.pdf","open_access":"1"}],"status":"public","date_updated":"2023-09-22T09:59:01Z","day":"28","oa_version":"Submitted Version","page":"062419","publication_status":"published","abstract":[{"lang":"eng","text":"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."}],"ec_funded":1,"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","article_processing_charge":"No","intvolume":"        95","date_created":"2018-12-11T11:49:25Z","department":[{"_id":"GaTk"}],"isi":1,"volume":95,"month":"06","publication_identifier":{"issn":["24700045"]},"publist_id":"6446","quality_controlled":"1","type":"journal_article","doi":"10.1103/PhysRevE.95.062419","language":[{"iso":"eng"}],"year":"2017","publisher":"American Institute of Physics","date_published":"2017-06-28T00:00:00Z","author":[{"full_name":"De Martino, Daniele","first_name":"Daniele","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","last_name":"De Martino","orcid":"0000-0002-5214-4706"}],"_id":"959","oa":1}]