571 research outputs found
Integrated information increases with fitness in the evolution of animats
One of the hallmarks of biological organisms is their ability to integrate
disparate information sources to optimize their behavior in complex
environments. How this capability can be quantified and related to the
functional complexity of an organism remains a challenging problem, in
particular since organismal functional complexity is not well-defined. We
present here several candidate measures that quantify information and
integration, and study their dependence on fitness as an artificial agent
("animat") evolves over thousands of generations to solve a navigation task in
a simple, simulated environment. We compare the ability of these measures to
predict high fitness with more conventional information-theoretic processing
measures. As the animat adapts by increasing its "fit" to the world,
information integration and processing increase commensurately along the
evolutionary line of descent. We suggest that the correlation of fitness with
information integration and with processing measures implies that high fitness
requires both information processing as well as integration, but that
information integration may be a better measure when the task requires memory.
A correlation of measures of information integration (but also information
processing) and fitness strongly suggests that these measures reflect the
functional complexity of the animat, and that such measures can be used to
quantify functional complexity even in the absence of fitness data.Comment: 27 pages, 8 figures, one supplementary figure. Three supplementary
video files available on request. Version commensurate with published text in
PLoS Comput. Bio
Optimal learning rules for familiarity detection
It has been suggested that the mammalian memory system has both familiarity and recollection components. Recently, a high-capacity network to store familiarity has been proposed. Here we derive analytically the optimal learning rule for such a familiarity memory using a signalto- noise ratio analysis. We find that in the limit of large networks the covariance rule, known to be the optimal local, linear learning rule for pattern association, is also the optimal learning rule for familiarity discrimination. The capacity is independent of the sparseness of the patterns, as long as the patterns have a fixed number of bits set. The corresponding information capacity is 0.057 bits per synapse, less than typically found for associative networks
Design, Synthesis and Characterization of a Highly Effective Inhibitor for Analog-Sensitive (as) Kinases
Highly selective, cell-permeable and fast-acting inhibitors of individual kinases are sought-after as tools for studying the cellular function of kinases in real time. A combination of small molecule synthesis and protein mutagenesis, identified a highly potent inhibitor (1-Isopropyl-3-(phenylethynyl)-1H-pyrazolo[3,4-d]pyrimidin-4-amine) of a rationally engineered Hog1 serine/threonine kinase (Hog1T100G). This inhibitor has been successfully used to study various aspects of Hog1 signaling, including a transient cell cycle arrest and gene expression changes mediated by Hog1 in response to stress. This study also underscores that the general applicability of this approach depends, in part, on the selectivity of the designed the inhibitor with respect to activity versus the engineered and wild type kinases. To explore this specificity in detail, we used a validated chemogenetic assay to assess the effect of this inhibitor on all gene products in yeast in parallel. The results from this screen emphasize the need for caution and for case-by-case assessment when using the Analog-Sensitive Kinase Allele technology to assess the physiological roles of kinases
Isolation and characterization of resident endogenous c-Kitâș cardiac stem cells from the adult mouse and rat heart
This protocol describes the isolation of endogenous c-Kit (also known as CD117)-positive (c-Kitâș), CD45-negative (CD45â») cardiac stem cells (eCSCs) from whole adult mouse and rat hearts. The heart is enzymatically digested via retrograde perfusion of the coronary circulation, resulting in rapid and extensive breakdown of the whole heart. Next, the tissue is mechanically dissociated further and cell fractions are separated by centrifugation. The c-Kitâș CD45â» eCSC population is isolated by magnetic-activated cell sorting technology and purity and cell numbers are assessed by flow cytometry. This process takes âŒ4 h for mouse eCSCs or 4.5 h for rat eCSCs. We also describe how to characterize c-Kitâș CD45â» eCSCs. The c-Kitâș CD45â»eCSCs exhibit the defining characteristics of stem cells: they are self-renewing, clonogenic and multipotent. This protocol also describes how to differentiate eCSCs into three main cardiac lineages: functional, beating cardiomyocytes, smooth muscle, and endothelial cells. These processes take 17-20 d
Cross-Talk between Signaling Pathways Can Generate Robust Oscillations in Calcium and cAMP
BACKGROUND:To control and manipulate cellular signaling, we need to understand cellular strategies for information transfer, integration, and decision-making. A key feature of signal transduction is the generation of only a few intracellular messengers by many extracellular stimuli. METHODOLOGY/PRINCIPAL FINDINGS:Here we model molecular cross-talk between two classic second messengers, cyclic AMP (cAMP) and calcium, and show that the dynamical complexity of the response of both messengers increases substantially through their interaction. In our model of a non-excitable cell, both cAMP and calcium concentrations can oscillate. If mutually inhibitory, cross-talk between the two second messengers can increase the range of agonist concentrations for which oscillations occur. If mutually activating, cross-talk decreases the oscillation range, but can generate 'bursting' oscillations of calcium and may enable better filtering of noise. CONCLUSION:We postulate that this increased dynamical complexity allows the cell to encode more information, particularly if both second messengers encode signals. In their native environments, it is unlikely that cells are exposed to one stimulus at a time, and cross-talk may help generate sufficiently complex responses to allow the cell to discriminate between different combinations and concentrations of extracellular agonists
Phenotypic and genotypic diversity of wine yeasts used for acidic musts
The aim of this study was to examine the physiological and genetic stability of the industrial wine yeasts Saccharomyces cerevisiae and Saccharomyces bayanus var. uvarum under acidic stress during fermentation. The yeasts were sub-cultured in aerobic or fermentative conditions in media with or without l-malic acid. Changes in the biochemical profiles, karyotypes, and mitochondrial DNA profiles were assessed after minimum 50 generations. All yeast segregates showed a tendency to increase the range of compounds used as sole carbon sources. The wild strains and their segregates were aneuploidal or diploidal. One of the four strains of S. cerevisiae did not reveal any changes in the electrophoretic profiles of chromosomal and mitochondrial DNA, irrespective of culture conditions. The extent of genomic changes in the other yeasts was strain-dependent. In the karyotypes of the segregates, the loss of up to 2 and the appearance up to 3 bands was noted. The changes in their mtDNA patterns were much broader, reaching 5 missing and 10 additional bands. The only exception was S. bayanus var. uvarum Y.00779, characterized by significantly greater genome plasticity only under fermentative stress. Changes in karyotypes and mtDNA profiles prove that fermentative stress is the main driving force of the adaptive evolution of the yeasts. l-malic acid does not influence the extent of genomic changes and the resistance of wine yeasts exhibiting increased demalication activity to acidic stress is rather related to their ability to decompose this acid. The phenotypic changes in segregates, which were found even in yeasts that did not reveal deviations in their DNA profiles, show that phenotypic characterization may be misleading in wine yeast identification. Because of yeast gross genomic diversity, karyotyping even though it does not seem to be a good discriminative tool, can be useful in determining the stability of wine yeasts. Restriction analysis of mitochondrial DNA appears to be a more sensitive method allowing for an early detection of genotypic changes in yeasts. Thus, if both of these methods are applied, it is possible to conduct the quick routine assessment of wine yeast stability in pure culture collections depositing industrial strains
Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV
The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of âs = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pTâ„20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60â€pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2â€{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration
Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector
The inclusive and dijet production cross-sections have been measured for jets
containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass
energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The
measurements use data corresponding to an integrated luminosity of 34 pb^-1.
The b-jets are identified using either a lifetime-based method, where secondary
decay vertices of b-hadrons in jets are reconstructed using information from
the tracking detectors, or a muon-based method where the presence of a muon is
used to identify semileptonic decays of b-hadrons inside jets. The inclusive
b-jet cross-section is measured as a function of transverse momentum in the
range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet
cross-section is measured as a function of the dijet invariant mass in the
range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets
and the angular variable chi in two dijet mass regions. The results are
compared with next-to-leading-order QCD predictions. Good agreement is observed
between the measured cross-sections and the predictions obtained using POWHEG +
Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet
cross-section. However, it does not reproduce the measured inclusive
cross-section well, particularly for central b-jets with large transverse
momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final
version published in European Physical Journal
Binary Willshaw learning yields high synaptic capacity for long-term familiarity memory
We investigate from a computational perspective the efficiency of the
Willshaw synaptic update rule in the context of familiarity discrimination, a
binary-answer, memory-related task that has been linked through psychophysical
experiments with modified neural activity patterns in the prefrontal and
perirhinal cortex regions. Our motivation for recovering this well-known
learning prescription is two-fold: first, the switch-like nature of the induced
synaptic bonds, as there is evidence that biological synaptic transitions might
occur in a discrete stepwise fashion. Second, the possibility that in the
mammalian brain, unused, silent synapses might be pruned in the long-term.
Besides the usual pattern and network capacities, we calculate the synaptic
capacity of the model, a recently proposed measure where only the functional
subset of synapses is taken into account. We find that in terms of network
capacity, Willshaw learning is strongly affected by the pattern coding rates,
which have to be kept fixed and very low at any time to achieve a non-zero
capacity in the large network limit. The information carried per functional
synapse, however, diverges and is comparable to that of the pattern association
case, even for more realistic moderately low activity levels that are a
function of network size.Comment: 20 pages, 4 figure
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