@article{1104,
abstract = {In the early visual system, cells of the same type perform the same computation in different places of the visual field. How these cells code together a complex visual scene is unclear. A common assumption is that cells of a single-type extract a single-stimulus feature to form a feature map, but this has rarely been observed directly. Using large-scale recordings in the rat retina, we show that a homogeneous population of fast OFF ganglion cells simultaneously encodes two radically different features of a visual scene. Cells close to a moving object code quasilinearly for its position, while distant cells remain largely invariant to the object's position and, instead, respond nonlinearly to changes in the object's speed. We develop a quantitative model that accounts for this effect and identify a disinhibitory circuit that mediates it. Ganglion cells of a single type thus do not code for one, but two features simultaneously. This richer, flexible neural map might also be present in other sensory systems.},
author = {Deny, Stephane and Ferrari, Ulisse and Mace, Emilie and Yger, Pierre and Caplette, Romain and Picaud, Serge and Tkacik, Gasper and Marre, Olivier},
issn = {20411723},
journal = {Nature Communications},
number = {1},
publisher = {Nature Publishing Group},
title = {{Multiplexed computations in retinal ganglion cells of a single type}},
doi = {10.1038/s41467-017-02159-y},
volume = {8},
year = {2017},
}
@article{720,
abstract = {Advances in multi-unit recordings pave the way for statistical modeling of activity patterns in large neural populations. Recent studies have shown that the summed activity of all neurons strongly shapes the population response. A separate recent finding has been that neural populations also exhibit criticality, an anomalously large dynamic range for the probabilities of different population activity patterns. Motivated by these two observations, we introduce a class of probabilistic models which takes into account the prior knowledge that the neural population could be globally coupled and close to critical. These models consist of an energy function which parametrizes interactions between small groups of neurons, and an arbitrary positive, strictly increasing, and twice differentiable function which maps the energy of a population pattern to its probability. We show that: 1) augmenting a pairwise Ising model with a nonlinearity yields an accurate description of the activity of retinal ganglion cells which outperforms previous models based on the summed activity of neurons; 2) prior knowledge that the population is critical translates to prior expectations about the shape of the nonlinearity; 3) the nonlinearity admits an interpretation in terms of a continuous latent variable globally coupling the system whose distribution we can infer from data. Our method is independent of the underlying system’s state space; hence, it can be applied to other systems such as natural scenes or amino acid sequences of proteins which are also known to exhibit criticality.},
author = {Humplik, Jan and Tkacik, Gasper},
issn = {1553734X},
journal = {PLoS Computational Biology},
number = {9},
publisher = {Public Library of Science},
title = {{Probabilistic models for neural populations that naturally capture global coupling and criticality}},
doi = {10.1371/journal.pcbi.1005763},
volume = {13},
year = {2017},
}
@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{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},
}
@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{613,
abstract = {Bacteria in groups vary individually, and interact with other bacteria and the environment to produce population-level patterns of gene expression. Investigating such behavior in detail requires measuring and controlling populations at the single-cell level alongside precisely specified interactions and environmental characteristics. Here we present an automated, programmable platform that combines image-based gene expression and growth measurements with on-line optogenetic expression control for hundreds of individual Escherichia coli cells over days, in a dynamically adjustable environment. This integrated platform broadly enables experiments that bridge individual and population behaviors. We demonstrate: (i) population structuring by independent closed-loop control of gene expression in many individual cells, (ii) cell-cell variation control during antibiotic perturbation, (iii) hybrid bio-digital circuits in single cells, and freely specifiable digital communication between individual bacteria. These examples showcase the potential for real-time integration of theoretical models with measurement and control of many individual cells to investigate and engineer microbial population behavior.},
author = {Chait, Remy P and Ruess, Jakob and Bergmiller, Tobias and Tkacik, Gasper and Guet, Calin C},
issn = {20411723},
journal = {Nature Communications},
number = {1},
publisher = {Nature Publishing Group},
title = {{Shaping bacterial population behavior through computer interfaced control of individual cells}},
doi = {10.1038/s41467-017-01683-1},
volume = {8},
year = {2017},
}
@inproceedings{652,
abstract = {We present an approach that enables robots to self-organize their sensorimotor behavior from scratch without providing specific information about neither the robot nor its environment. This is achieved by a simple neural control law that increases the consistency between external sensor dynamics and internal neural dynamics of the utterly simple controller. In this way, the embodiment and the agent-environment coupling are the only source of individual development. We show how an anthropomorphic tendon driven arm-shoulder system develops different behaviors depending on that coupling. For instance: Given a bottle half-filled with water, the arm starts to shake it, driven by the physical response of the water. When attaching a brush, the arm can be manipulated into wiping a table, and when connected to a revolvable wheel it finds out how to rotate it. Thus, the robot may be said to discover the affordances of the world. When allowing two (simulated) humanoid robots to interact physically, they engage into a joint behavior development leading to, for instance, spontaneous cooperation. More social effects are observed if the robots can visually perceive each other. Although, as an observer, it is tempting to attribute an apparent intentionality, there is nothing of the kind put in. As a conclusion, we argue that emergent behavior may be much less rooted in explicit intentions, internal motivations, or specific reward systems than is commonly believed.},
author = {Der, Ralf and Martius, Georg S},
isbn = {978-150905069-7},
location = {Cergy-Pontoise, France},
publisher = {IEEE},
title = {{Dynamical self consistency leads to behavioral development and emergent social interactions in robots}},
doi = {10.1109/DEVLRN.2016.7846789},
year = {2017},
}
@article{823,
abstract = {The resolution of a linear system with positive integer variables is a basic yet difficult computational problem with many applications. We consider sparse uncorrelated random systems parametrised by the density c and the ratio α=N/M between number of variables N and number of constraints M. By means of ensemble calculations we show that the space of feasible solutions endows a Van-Der-Waals phase diagram in the plane (c, α). We give numerical evidence that the associated computational problems become more difficult across the critical point and in particular in the coexistence region.},
author = {Colabrese, Simona and De Martino, Daniele and Leuzzi, Luca and Marinari, Enzo},
issn = {17425468},
journal = { Journal of Statistical Mechanics: Theory and Experiment},
number = {9},
publisher = {IOPscience},
title = {{Phase transitions in integer linear problems}},
doi = {10.1088/1742-5468/aa85c3},
volume = {2017},
year = {2017},
}
@article{993,
abstract = {In real-world applications, observations are often constrained to a small fraction of a system. Such spatial subsampling can be caused by the inaccessibility or the sheer size of the system, and cannot be overcome by longer sampling. Spatial subsampling can strongly bias inferences about a system’s aggregated properties. To overcome the bias, we derive analytically a subsampling scaling framework that is applicable to different observables, including distributions of neuronal avalanches, of number of people infected during an epidemic outbreak, and of node degrees. We demonstrate how to infer the correct distributions of the underlying full system, how to apply it to distinguish critical from subcritical systems, and how to disentangle subsampling and finite size effects. Lastly, we apply subsampling scaling to neuronal avalanche models and to recordings from developing neural networks. We show that only mature, but not young networks follow power-law scaling, indicating self-organization to criticality during development.},
author = {Levina (Martius), Anna and Priesemann, Viola},
issn = {20411723},
journal = {Nature Communications},
publisher = {Nature Publishing Group},
title = {{Subsampling scaling}},
doi = {10.1038/ncomms15140},
volume = {8},
year = {2017},
}
@article{943,
abstract = {Like many developing tissues, the vertebrate neural tube is patterned by antiparallel morphogen gradients. To understand how these inputs are interpreted, we measured morphogen signaling and target gene expression in mouse embryos and chick ex vivo assays. From these data, we derived and validated a characteristic decoding map that relates morphogen input to the positional identity of neural progenitors. Analysis of the observed responses indicates that the underlying interpretation strategy minimizes patterning errors in response to the joint input of noisy opposing gradients. We reverse-engineered a transcriptional network that provides a mechanistic basis for the observed cell fate decisions and accounts for the precision and dynamics of pattern formation. Together, our data link opposing gradient dynamics in a growing tissue to precise pattern formation.},
author = {Zagórski, Marcin P and Tabata, Yoji and Brandenberg, Nathalie and Lutolf, Matthias and Tkacik, Gasper and Bollenbach, Tobias and Briscoe, James and Kicheva, Anna},
issn = {00368075},
journal = {Science},
number = {6345},
pages = {1379 -- 1383},
publisher = {American Association for the Advancement of Science},
title = {{Decoding of position in the developing neural tube from antiparallel morphogen gradients}},
doi = {10.1126/science.aam5887},
volume = {356},
year = {2017},
}