11759806
Structural and biophysical mechanisms underlying dynamic sensitivity of primary sensory interneurons in the cricket cercal sensory system
Abstract We constructed probabilistic models of afferent inputs and compartmental models of interneurons in the cricket cercal system to examine the effects of dendritic morphology, distribution of synaptic inputs, and membrane properties on interneuron directional tuning properties. The mean directional tuning of afferent inputs to an interneuron was an excellent predictor of its directional tuning. Location of the synapses on the interneurons’ dendrites was not essential to determining tuning characteristics, but had a substantial effect on sensitivity. Thus, we conclude that both sampling of the afferent population, and anatomical distribution of synaptic inputs are important determinants of an interneuron's directional response.
35037776
Assessing the Performance of Neural Encoding Models in the Presence of Noise
An analytical method is introduced for evaluating the performance of neural encoding models. The method addresses a critical question that arises during the course of the development and validation of encoding models: is a given model near optimal in terms of its accuracy in predicting the stimulus-elicited responses of a neural system, or can the predictive accuracy be improved significantly by further model development? The evaluation method is based on a derivation of the minimum mean-square error between actual responses and modeled responses. It is formulated as a comparison between the mean-square error of the candidate model and the theoretical minimum mean-square error attainable through an optimal model for the system. However, no a priori information about the nature of the optimal model is required. The theoretically minimum error is determined solely from the coherence function between pairs of system responses to repeated presentations of the same dynamic stimulus. Thus, the performance of the candidate model is judged against the performance of an optimal model rather than against that of an arbitrarily assumed model.Using this method, we evaluated a linear model for neural encoding by mechanosensory cells in the cricket cercal system. At low stimulus intensities, the best-fit linear model of encoding by single cells was found to be nearly optimal, even though the coherence between stimulus-response pairs (a commonly used measure of system linearity) was low. In this low-stimulus-intensity regime, the mean square error of the linear model was on the order of the power of the cell responses. In contrast, at higher stimulus intensities the linear model was not an accurate representation of neural encoding, even though the stimulus-response coherence was substantially higher than in the low-intensity regime.
410715
Phased array processing for spike discrimination
We present a novel approach for the detection, discrimination, and identification of superimposed neuronal action potentials from multineuronal, multichannel extracellular nerve recordings with low signal-to-noise ratios. The approach uses phased-array processing techniques to identify the spikes from different neurons on the basis of their unique propagation velocities. We evaluated this new approach using simulated electrophysiological data, under conditions that are known to limit the effectiveness of existing spike discrimination techniques. This approach enabled discrimination of simulated spikes from multiple simultaneously active neurons with a high degree of reliability and robustness within the expected range of experimental recording conditions, even in situations where there was a high degree of spike waveform superposition on the recording channels. Moreover, the technique enables the reliable detection and discrimination of spikes recorded with signal-to-noise ratios less than 1.
8691336
Effectiveness for Embedded Spheres and Balls
Abstract We consider arbitrary dimensional spheres and closed balls embedded in Rn as ⫫01 classes. Such a strong restriction on the topology of a ⫫01 class has computability theoretic repercussions. Algebraic topology plays a crucial role in our exploration of these consequences; the use of homology chains as computational objects allows us to take algorithmic advantage of the topological structure of our ⫫01 classes. We show that a sphere embedded as a ⫫01 class is necessarily located, i.e., the distance to the class is a computable function, or equivalently, the class contains a computably enumerable dense set of computable points. Similarly, a ball embedded as a ⫫01 class has a dense set of computable points, though not necessarily c.e. To prove location for balls, it is sufficient to assume that both it and its boundary sphere are ⫫01. However, the converse fails, even for arcs; using a priority argument, we prove that there is a located arc in R2 without computable endpoints. Finally, the requirement that the embedding map itself be computable is shown to be stronger than the other effectiveness criteria considered. A characterization in terms of computable local contractibility is stated the proof will be the subject of a sequel.
1173889
Effectiveness for infinite variable words and the Dual Ramsey Theorem
Abstract.We examine the Dual Ramsey Theorem and two related combinatorial principles VW(k,l) and OVW(k,l) from the perspectives of reverse mathematics and effective mathematics. We give a statement of the Dual Ramsey Theorem for open colorings in second order arithmetic and formalize work of Carlson and Simpson [1] to show that this statement implies ACA0 over RCA0. We show that neither VW(2,2) nor OVW(2,2) is provable in WKL0. These results give partial answers to questions posed by Friedman and Simpson [3].
8365397
Input modeling when simple models fail
A simulation model is composed of inputs and logic; the inputs represent the uncertainty or randomness in the system, while the logic determines how the system reacts to the uncertain elements. Simple input models, consisting of independent and identically distributed sequences of random variates from standard probability distributions, are included in every commercial simulation language. Software to fit these distributions to data is also available. In this tutorial we describe input models that are useful when simple models are not.
25032718
Using simulation to facilitate effective workflow adaptation
In order to support realistic real-world processes, workflow systems need to be able to adapt to changes. Detecting the need to change and deciding what changes to carry out are very difficult. Simulation analysis can play an important role in this. It can be used in tuning quality of service metrics and exploring "what-if" questions. Before a change is actually made, its possible effects can be explored with simulation. To facilitate rapid feedback, the workflow system (METEOR) and simulation system (JSIM) need to interoperate. In particular, workflow specification documents need to be translated into simulation model specification documents so that the new model can be executed/animated on-the-fly. Fortunately, modern Web technology (e.g., XML, DTD, XSLT) make this relatively straightforward. The utility of using simulation in adapting a workflow is illustrated with an example from a genome workflow.
7800547
Design of an Object-Oriented Database for Reverse Genetics
We present the design of an object-oriented database system for reverse genetics applications. Such a database will encapsulate not only the data in the genetic and physical maps, but also the methods used to create the maps as well as methods to link them to other databases, such as GenBank, PIR, and MedLine. The purpose of this database is to provide the fungal genetics community with an electronic tool for identifying the biochemical function of any DNA fragment in the database--electronic reverse genetics. Such a tool for reverse genetics will enable researchers to identify the biochemical functions associated with genes encoding proteins in fungal development pathways, purine metabolism, the heat shock response, and molecular chromosome mechanics and evolution. Our initial goal is to apply the database for the genome mapping of the filamentous fungi, Aspergillus nidulans and Neurospora crassa, at the University of Georgia and the University of Leeds in England.