@article{2845,
abstract = {At synapses formed between dissociated neurons, about half of all synaptic vesicles are refractory to evoked release, forming the so-called "resting pool." Here, we use optical measurements of vesicular pH to study developmental changes in pool partitioning and vesicle cycling in cultured hippocampal slices. Two-photon imaging of a genetically encoded two-color release sensor (ratio-sypHy) allowed us to perform calibrated measurements at individual Schaffer collateral boutons. Mature boutons released a large fraction of their vesicles during simulated place field activity, and vesicle retrieval rates were 7-fold higher compared to immature boutons. Saturating stimulation mobilized essentially all vesicles at mature synapses. Resting pool formation and a concomitant reduction in evoked release was induced by chronic depolarization but not by acute inhibition of the protein phosphatase calcineurin. We conclude that synapses in CA1 undergo a prominent refinement of vesicle use during early postnatal development that is not recapitulated in dissociated neuronal culture.},
author = {Rose, Tobias and Schönenberger, Philipp and Jezek, Karel and Oertner, Thomas},
journal = {Neuron},
number = {6},
pages = {1109 -- 1121},
publisher = {Elsevier},
title = {{Developmental refinement of vesicle cycling at Schaffer collateral synapses}},
doi = {10.1016/j.neuron.2013.01.021},
volume = {77},
year = {2013},
}
@article{2846,
abstract = {The Red Queen hypothesis proposes that coevolving parasites select for outcrossing in the host. Outcrossing relies on males, which often show lower immune investment due to, for example, sexual selection. Here, we demonstrate that such sex differences in immunity interfere with parasite-mediated selection for outcrossing. Two independent coevolution experiments with Caenorhabditis elegans and its microparasite Bacillus thuringiensis produced decreased yet stable frequencies of outcrossing male hosts. A subsequent systematic analysis verified that male C. elegans suffered from a direct selective disadvantage under parasite pressure (i.e. lower resistance, decreased sexual activity, increased escape behaviour), which can reduce outcrossing and thus male frequencies. At the same time, males offered an indirect selective benefit, because male-mediated outcrossing increased offspring resistance, thus favouring male persistence in the evolving populations. As sex differences in immunity are widespread, such interference of opposing selective constraints is likely of central importance during host adaptation to a coevolving parasite.},
author = {El Masri, Leila and Schulte, Rebecca and Timmermeyer, Nadine and Thanisch, Stefanie and Crummenerl, Lena and Jansen, Gunther and Michiels, Nico and Schulenburg, Hinrich},
journal = {Ecology Letters},
number = {4},
pages = {461 -- 468},
publisher = {Wiley-Blackwell},
title = {{Sex differences in host defence interfere with parasite-mediated selection for outcrossing during host-parasite coevolution}},
doi = {10.1111/ele.12068},
volume = {16},
year = {2013},
}
@inproceedings{2847,
abstract = {Depth-Bounded Systems form an expressive class of well-structured transition systems. They can model a wide range of concurrent infinite-state systems including those with dynamic thread creation, dynamically changing communication topology, and complex shared heap structures. We present the first method to automatically prove fair termination of depth-bounded systems. Our method uses a numerical abstraction of the system, which we obtain by systematically augmenting an over-approximation of the system’s reachable states with a finite set of counters. This numerical abstraction can be analyzed with existing termination provers. What makes our approach unique is the way in which it exploits the well-structuredness of the analyzed system. We have implemented our work in a prototype tool and used it to automatically prove liveness properties of complex concurrent systems, including nonblocking algorithms such as Treiber’s stack and several distributed processes. Many of these examples are beyond the scope of termination analyses that are based on traditional counter abstractions.},
author = {Bansal, Kshitij and Koskinen, Eric and Wies, Thomas and Zufferey, Damien},
editor = {Piterman, Nir and Smolka, Scott},
location = {Rome, Italy},
pages = {62 -- 77},
publisher = {Springer},
title = {{Structural Counter Abstraction}},
doi = {10.1007/978-3-642-36742-7_5},
volume = {7795},
year = {2013},
}
@article{2850,
abstract = {Recent work emphasizes that the maximum entropy principle provides a bridge between statistical mechanics models for collective behavior in neural networks and experiments on networks of real neurons. Most of this work has focused on capturing the measured correlations among pairs of neurons. Here we suggest an alternative, constructing models that are consistent with the distribution of global network activity, i.e. the probability that K out of N cells in the network generate action potentials in the same small time bin. The inverse problem that we need to solve in constructing the model is analytically tractable, and provides a natural 'thermodynamics' for the network in the limit of large N. We analyze the responses of neurons in a small patch of the retina to naturalistic stimuli, and find that the implied thermodynamics is very close to an unusual critical point, in which the entropy (in proper units) is exactly equal to the energy. © 2013 IOP Publishing Ltd and SISSA Medialab srl.
},
author = {Tkacik, Gasper and Marre, Olivier and Mora, Thierry and Amodei, Dario and Berry, Michael and Bialek, William},
journal = {Journal of Statistical Mechanics Theory and Experiment},
number = {3},
publisher = {IOP Publishing Ltd.},
title = {{The simplest maximum entropy model for collective behavior in a neural network}},
doi = {10.1088/1742-5468/2013/03/P03011},
volume = {2013},
year = {2013},
}
@article{2851,
abstract = {The number of possible activity patterns in a population of neurons grows exponentially with the size of the population. Typical experiments explore only a tiny fraction of the large space of possible activity patterns in the case of populations with more than 10 or 20 neurons. It is thus impossible, in this undersampled regime, to estimate the probabilities with which most of the activity patterns occur. As a result, the corresponding entropy - which is a measure of the computational power of the neural population - cannot be estimated directly. We propose a simple scheme for estimating the entropy in the undersampled regime, which bounds its value from both below and above. The lower bound is the usual 'naive' entropy of the experimental frequencies. The upper bound results from a hybrid approximation of the entropy which makes use of the naive estimate, a maximum entropy fit, and a coverage adjustment. We apply our simple scheme to artificial data, in order to check their accuracy; we also compare its performance to those of several previously defined entropy estimators. We then apply it to actual measurements of neural activity in populations with up to 100 cells. Finally, we discuss the similarities and differences between the proposed simple estimation scheme and various earlier methods. © 2013 IOP Publishing Ltd and SISSA Medialab srl.},
author = {Berry, Michael and Tkacik, Gasper and Dubuis, Julien and Marre, Olivier and Da Silveira, Ravá},
journal = {Journal of Statistical Mechanics Theory and Experiment},
number = {3},
publisher = {IOP Publishing Ltd.},
title = {{A simple method for estimating the entropy of neural activity}},
doi = {10.1088/1742-5468/2013/03/P03015},
volume = {2013},
year = {2013},
}