@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},
}
@article{2818,
abstract = {Models of neural responses to stimuli with complex spatiotemporal correlation structure often assume that neurons are selective for only a small number of linear projections of a potentially high-dimensional input. In this review, we explore recent modeling approaches where the neural response depends on the quadratic form of the input rather than on its linear projection, that is, the neuron is sensitive to the local covariance structure of the signal preceding the spike. To infer this quadratic dependence in the presence of arbitrary (e.g., naturalistic) stimulus distribution, we review several inference methods, focusing in particular on two information theory–based approaches (maximization of stimulus energy and of noise entropy) and two likelihood-based approaches (Bayesian spike-triggered covariance and extensions of generalized linear models). We analyze the formal relationship between the likelihood-based and information-based approaches to demonstrate how they lead to consistent inference. We demonstrate the practical feasibility of these procedures by using model neurons responding to a flickering variance stimulus.},
author = {Rajan, Kanaka and Marre, Olivier and Tkacik, Gasper},
journal = {Neural Computation},
number = {7},
pages = {1661 -- 1692},
publisher = {MIT Press },
title = {{Learning quadratic receptive fields from neural responses to natural stimuli}},
doi = {10.1162/NECO_a_00463},
volume = {25},
year = {2013},
}
@article{3261,
abstract = {Cells in a developing embryo have no direct way of "measuring" their physical position. Through a variety of processes, however, the expression levels of multiple genes come to be correlated with position, and these expression levels thus form a code for "positional information." We show how to measure this information, in bits, using the gap genes in the Drosophila embryo as an example. Individual genes carry nearly two bits of information, twice as much as expected if the expression patterns consisted only of on/off domains separated by sharp boundaries. Taken together, four gap genes carry enough information to define a cell's location with an error bar of ~1% along the anterior-posterior axis of the embryo. This precision is nearly enough for each cell to have a unique identity, which is the maximum information the system can use, and is nearly constant along the length of the embryo. We argue that this constancy is a signature of optimality in the transmission of information from primary morphogen inputs to the output of the gap gene network.},
author = {Dubuis, Julien and Tkacik, Gasper and Wieschaus, Eric and Gregor, Thomas and Bialek, William},
journal = {PNAS},
number = {41},
pages = {16301 -- 16308},
publisher = {National Academy of Sciences},
title = {{Positional information, in bits}},
doi = {10.1073/pnas.1315642110},
volume = {110},
year = {2013},
}
@article{499,
abstract = {Exposure of an isogenic bacterial population to a cidal antibiotic typically fails to eliminate a small fraction of refractory cells. Historically, fractional killing has been attributed to infrequently dividing or nondividing "persisters." Using microfluidic cultures and time-lapse microscopy, we found that Mycobacterium smegmatis persists by dividing in the presence of the drug isoniazid (INH). Although persistence in these studies was characterized by stable numbers of cells, this apparent stability was actually a dynamic state of balanced division and death. Single cells expressed catalase-peroxidase (KatG), which activates INH, in stochastic pulses that were negatively correlated with cell survival. These behaviors may reflect epigenetic effects, because KatG pulsing and death were correlated between sibling cells. Selection of lineages characterized by infrequent KatG pulsing could allow nonresponsive adaptation during prolonged drug exposure.},
author = {Wakamoto, Yurichi and Dhar, Neraaj and Chait, Remy P and Schneider, Katrin and Signorino Gelo, François and Leibler, Stanislas and Mckinney, John},
journal = {Science},
number = {6115},
pages = {91 -- 95},
publisher = {American Association for the Advancement of Science},
title = {{Dynamic persistence of antibiotic-stressed mycobacteria}},
doi = {10.1126/science.1229858},
volume = {339},
year = {2013},
}
@article{3262,
abstract = {Living cells must control the reading out or "expression" of information encoded in their genomes, and this regulation often is mediated by transcription factors--proteins that bind to DNA and either enhance or repress the expression of nearby genes. But the expression of transcription factor proteins is itself regulated, and many transcription factors regulate their own expression in addition to responding to other input signals. Here we analyze the simplest of such self-regulatory circuits, asking how parameters can be chosen to optimize information transmission from inputs to outputs in the steady state. Some nonzero level of self-regulation is almost always optimal, with self-activation dominant when transcription factor concentrations are low and self-repression dominant when concentrations are high. In steady state the optimal self-activation is never strong enough to induce bistability, although there is a limit in which the optimal parameters are very close to the critical point.},
author = {Tkacik, Gasper and Walczak, Aleksandra and Bialek, William},
journal = { Physical Review E statistical nonlinear and soft matter physics },
number = {4},
publisher = {American Institute of Physics},
title = {{Optimizing information flow in small genetic networks. III. A self-interacting gene}},
doi = {10.1103/PhysRevE.85.041903},
volume = {85},
year = {2012},
}
@article{3274,
abstract = {A boundary element model of a tunnel running through horizontally layered soil with anisotropic material properties is presented. Since there is no analytical fundamental solution for wave propagation inside a layered orthotropic medium in 3D, the fundamental displacements and stresses have to be calculated numerically. In our model this is done in the Fourier domain with respect to space and time. The assumption of a straight tunnel with infinite extension in the x direction makes it possible to decouple the system for every wave number kx, leading to a 2.5D-problem, which is suited for parallel computation. The special form of the fundamental solution, resulting from our Fourier ansatz, and the fact, that the calculation of the boundary integral equation is performed in the Fourier domain, enhances the stability and efficiency of the numerical calculations.},
author = {Rieckh, Georg and Kreuzer, Wolfgang and Waubke, Holger and Balazs, Peter},
journal = { Engineering Analysis with Boundary Elements},
number = {6},
pages = {960 -- 967},
publisher = {Elsevier},
title = {{A 2.5D-Fourier-BEM model for vibrations in a tunnel running through layered anisotropic soil}},
doi = {10.1016/j.enganabound.2011.12.014},
volume = {36},
year = {2012},
}
@article{3384,
abstract = {Here we introduce a database of calibrated natural images publicly available through an easy-to-use web interface. Using a Nikon D70 digital SLR camera, we acquired about six-megapixel images of Okavango Delta of Botswana, a tropical savanna habitat similar to where the human eye is thought to have evolved. Some sequences of images were captured unsystematically while following a baboon troop, while others were designed to vary a single parameter such as aperture, object distance, time of day or position on the horizon. Images are available in the raw RGB format and in grayscale. Images are also available in units relevant to the physiology of human cone photoreceptors, where pixel values represent the expected number of photoisomerizations per second for cones sensitive to long (L), medium (M) and short (S) wavelengths. This database is distributed under a Creative Commons Attribution-Noncommercial Unported license to facilitate research in computer vision, psychophysics of perception, and visual neuroscience.},
author = {Tkacik, Gasper and Garrigan, Patrick and Ratliff, Charles and Milcinski, Grega and Klein, Jennifer and Seyfarth, Lucia and Sterling, Peter and Brainard, David and Balasubramanian, Vijay},
journal = {PLoS One},
number = {6},
publisher = {Public Library of Science},
title = {{Natural images from the birthplace of the human eye}},
doi = {10.1371/journal.pone.0020409},
volume = {6},
year = {2011},
}
@article{3374,
abstract = {Genetic regulatory networks enable cells to respond to changes in internal and external conditions by dynamically coordinating their gene expression profiles. Our ability to make quantitative measurements in these biochemical circuits has deepened our understanding of what kinds of computations genetic regulatory networks can perform, and with what reliability. These advances have motivated researchers to look for connections between the architecture and function of genetic regulatory networks. Transmitting information between a network's inputs and outputs has been proposed as one such possible measure of function, relevant in certain biological contexts. Here we summarize recent developments in the application of information theory to gene regulatory networks. We first review basic concepts in information theory necessary for understanding recent work. We then discuss the functional complexity of gene regulation, which arises from the molecular nature of the regulatory interactions. We end by reviewing some experiments that support the view that genetic networks responsible for early development of multicellular organisms might be maximizing transmitted 'positional information'.},
author = {Tkacik, Gasper and Walczak, Aleksandra},
journal = {Journal of Physics: Condensed Matter},
number = {15},
publisher = {IOP Publishing Ltd.},
title = {{Information transmission in genetic regulatory networks a review}},
doi = {10.1088/0953-8984/23/15/153102},
volume = {23},
year = {2011},
}