19 research outputs found
epiasini/SubPID: Version bump
No full textNumerical implementation of the subatomic partial information decomposition proposed in Pica, G., Piasini, E., Chicharro, D., and Panzeri, S., Invariant Components of Synergy, Redundancy, and Unique Information Among Three Variables. Entropy 2017, 19, 451, doi:10.3390/e19090451
SubPID: Subatomic Partial Information Decomposition
No full text<p>Numerical implementation of the subatomic partial information decomposition proposed in Pica, G., Piasini, E., Chicharro, D., and Panzeri, S., Invariant Components of Synergy, Redundancy, and Unique Information Among Three Variables. Entropy 2017, 19, 451, doi:10.3390/e19090451.</p>
Invariant Components of Synergy, Redundancy, and Unique Information among Three Variables
No full textIn a system of three stochastic variables, the Partial Information Decomposition (PID) of Williams and Beer dissects the information that two variables (sources) carry about a third variable (target) into nonnegative information atoms that describe redundant, unique, and synergistic modes of dependencies among the variables. However, the classification of the three variables into two sources and one target limits the dependency modes that can be quantitatively resolved, and does not naturally suit all systems. Here, we extend the PID to describe trivariate modes of dependencies in full generality, without introducing additional decomposition axioms or making assumptions about the target/source nature of the variables. By comparing different PID lattices of the same system, we unveil a finer PID structure made of seven nonnegative information subatoms that are invariant to different target/source classifications and that are sufficient to describe the relationships among all PID lattices. This finer structure naturally splits redundant information into two nonnegative components: the source redundancy, which arises from the pairwise correlations between the source variables, and the non-source redundancy, which does not, and relates to the synergistic information the sources carry about the target. The invariant structure is also sufficient to construct the system’s entropy, hence it characterizes completely all the interdependencies in the system
Intersection information and SubPID (Subatomic Partial Information Decomposition)
No full text<p>This package is composed by four parts:</p>
<ul>
<li>A MATLAB implementation of the partial information decomposition (PID) for distributions over three random variables using the definitions from Bertschinger, N., Rauh, J., Olbrich, E., Jost, J., and Ay, N. <em>Quantifying unique information.</em>. Entropy 2014, 16(4):2161–2183.</li>
<li>Two MATLAB implementations of the intersection information I_{II}(S;R;C) that, in perceptual discrimination experiments, quantifies the sensory information in the recorded neural response R that is relevant to behavior. This measure is defined and described in Pica, G., Piasini, E., Safaai, H., Runyan, C.A., Diamond, M.E., Fellin, T., Kayser, C., Harvey, C.D., Panzeri, S., <em>Quantifying how much sensory information in a neural code is relevant for behavior</em>, Advances in neural information processing 2017, 3687-3697. The first implementation, "src/matlab/intersection information.m", evaluates I_{II}(S;R;C) starting from the empirical joint probability distribution p(s,r,c). The second implementation, "src/matlab/intersection information_from_binned_response.m", evaluates I_{II}(S;R;C) starting from vectors containing the stimulus s, the response r, and the choice c, corresponding to each trial. Here, the response is discretized into equipopulated bins for a conservative estimate of I_{II}(S;R;C).</li>
<li>A MATLAB numerical implementation of the subatomic partial information decomposition proposed in Pica, G., Piasini, E., Chicharro, D., and Panzeri, S. <em>Invariant Components of Synergy, Redundancy, and Unique Information Among Three Variables.</em>. Entropy 2017, 19, 451, doi:10.3390/e19090451.</li>
</ul>
Effect of Geometric Complexity on Intuitive Model Selection
No full textOccam’s razor is the principle stating that, all else being equal, simpler explanations for a set of observations are to be preferred to more complex ones. This idea can be made precise in the context of statistical inference, where the same quantitative notion of complexity of a statistical model emerges naturally from different approaches based on Bayesian model selection and information theory. The broad applicability of this mathematical formulation suggests a normative model of decision-making under uncertainty: complex explanations should be penalized according to this common measure of complexity. However, little is known about if and how humans intuitively quantify the relative complexity of competing interpretations of noisy data. Here we measure the sensitivity of naive human subjects to statistical model complexity. Our data show that human subjects bias their decisions in favor of simple explanations based not only on the dimensionality of the alternatives (number of model parameters), but also on finer-grained aspects of their geometry. In particular, as predicted by the theory, models intuitively judged as more complex are not only those with more parameters, but also those with larger volume and prominent curvature or boundaries. Our results imply that principled notions of statistical model complexity have direct quantitative relevance to human decision-making
A one-year prospective costing study of botulinum toxin type A treatment of chronic tension headache
No full textThe objective was to measure the cost of botulinum toxin type A (BTX-A) treatment of chronic tension-type headache. A prospective pharmaceutical costing analysis was completed in the Day Hospital of the Regional Referral Headache Centre at Sant'Andrea Hospital in Rome, chronic tension-type headache patients were treated from February 2003 to January 2004. Patients were treated with 100 U of BTX-A every three months for one year by using the Fixed Doses Fixed Sites procedure. The cost of treatment was based on drug acquisition costs, supplies and professional time needed to administer treatment. The average cost of conventional headache medications was € 853.43 before BTX-A treatment, and € 450.47 after. The cost of BTX-A treatment was € 642.00. Adding the cost of adjunctive conventional medications brought the total cost of BTX-A treatment to € 1092.47. BTX-A treatment reduced use of conventional headache medications and expenditures although the net cost of treatment increased with BTX-A use. © Springer-Verlag Italia 2004
Network structure within the cerebellar input layer enables lossless sparse encoding.
No full textThe synaptic connectivity within neuronal networks is thought to determine the information processing they perform, yet network structure-function relationships remain poorly understood. By combining quantitative anatomy of the cerebellar input layer and information theoretic analysis of network models, we investigated how synaptic connectivity affects information transmission and processing. Simplified binary models revealed that the synaptic connectivity within feedforward networks determines the trade-off between information transmission and sparse encoding. Networks with few synaptic connections per neuron and network-activity-dependent threshold were optimal for lossless sparse encoding over the widest range of input activities. Biologically detailed spiking network models with experimentally constrained synaptic conductances and inhibition confirmed our analytical predictions. Our results establish that the synaptic connectivity within the cerebellar input layer enables efficient lossless sparse encoding. Moreover, they provide a functional explanation for why granule cells have approximately four dendrites, a feature that has been evolutionarily conserved since the appearance of fish
LEMS: a language for expressing complex biological models in concise and hierarchical form and its use in underpinning NeuroML 2.
No full textComputational models are increasingly important for studying complex neurophysiological systems. As scientific tools, it is essential that such models can be reproduced and critically evaluated by a range of scientists. However, published models are currently implemented using a diverse set of modeling approaches, simulation tools, and computer languages making them inaccessible and difficult to reproduce. Models also typically contain concepts that are tightly linked to domain-specific simulators, or depend on knowledge that is described exclusively in text-based documentation. To address these issues we have developed a compact, hierarchical, XML-based language called LEMS (Low Entropy Model Specification), that can define the structure and dynamics of a wide range of biological models in a fully machine readable format. We describe how LEMS underpins the latest version of NeuroML and show that this framework can define models of ion channels, synapses, neurons and networks. Unit handling, often a source of error when reusing models, is built into the core of the language by specifying physical quantities in models in terms of the base dimensions. We show how LEMS, together with the open source Java and Python based libraries we have developed, facilitates the generation of scripts for multiple neuronal simulators and provides a route for simulator free code generation. We establish that LEMS can be used to define models from systems biology and map them to neuroscience-domain specific simulators, enabling models to be shared between these traditionally separate disciplines. LEMS and NeuroML 2 provide a new, comprehensive framework for defining computational models of neuronal and other biological systems in a machine readable format, making them more reproducible and increasing the transparency and accessibility of their underlying structure and properties
A one-year retrospective economic evaluation of botulinum toxin type A treatment of chronic tension headache
No full textThe objective was to measure the impact of botulinum toxin type A (BTX-A) treatment on symptoms and medication utilisation patterns in patients with chronic tension-type headache. A retrospective chart analysis was completed in the Day Hospital of the Regional Referral Headache Centre at Sant' Andrea Hospital in Rome. Clinical charts were randomly selected for 100 patients treated from February 2002 to January 2003. Patients were treated with 100 U of BTX-A every three months for one year by using the Fixed Doses Fixed Sites procedure. Treatment outcome ranged from complete resolution of headache symptoms to a worsening of symptoms resulting in discontinuation. Headache medication use before and after treatment was analysed. After BTX-A treatment, 85% of patients experienced at least some degree of pain relief and reduced their use of analgesics. The reduced percentages of patients using a variety of headache medications after BTX-A treatment results from a reduction in their headache symptoms. © Springer-Verlag Italia 2004
