Frontiers in Neuroinformatics

Publisher: Frontiers Research Foundation, Frontiers

Description

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  • 5-year impact
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  • ISSN
    1662-5196
  • OCLC
    250621701
  • Material type
    Document, Internet resource
  • Document type
    Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Frontiers

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    • Author can archive a pre-print version
  • Post-print
    • Author cannot archive a post-print version
  • Conditions
    • On open access repositories
    • Authors retain copyright
    • Creative Commons Attribution License
    • Published source must be acknowledged
    • Publisher's version/PDF must be used for post-print
    • Set statement to accompany [This Document is Protected by copyright and was first published by Frontiers. All rights reserved. it is reproduced with permission.]
    • Articles are placed in PubMed Central immediately on behalf of authors.
    • Publisher last contacted on 04/10/2013
    • All titles are open access journals
  • Classification
    ​ green

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: Two-photon calcium imaging of neuronal responses is an increasingly accessible technology for probing population responses in cortex at single cell resolution, and with reasonable and improving temporal resolution. However, analysis of two-photon data is usually performed using ad-hoc solutions. To date, no publicly available software exists for straightforward analysis of stimulus-triggered two-photon imaging experiments. In addition, the increasing data rates of two-photon acquisition systems imply increasing cost of computing hardware required for in-memory analysis. Here we present a Matlab toolbox, "FocusStack", for simple and efficient analysis of two-photon calcium imaging stacks on consumer-level hardware, with minimal memory footprint. We also present a Matlab toolbox, "StimServer", for generation and sequencing of visual stimuli, designed to be triggered over a network link from a two-photon acquisition system. "FocusStack" is compatible out of the box with several existing two-photon acquisition systems, and is simple to adapt to arbitrary binary file formats. Analysis tools such as stack alignment for movement correction, automated cell detection and peri-stimulus time histograms are already provided, and further tools can be easily incorporated. Both packages are available as publicly-accessible source-code repositories.
    Frontiers in Neuroinformatics 12/2014;
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    ABSTRACT: Background / Purpose: Benign childhood epilepsy with centrotemporal spikes (BCECTS) is the most common idiopathic epileptic syndrome with prevalence of approximately 15% in children with seizures. Cognitive impairments in memory and language are often associated with BCECTS. Functional connectivity analysis may provide key information to better understand the functional interactions of neural dynamics in patients with BCECTS. Main conclusion: BCECTS patients were characterized with altered resting state brain dynamics and impaired functional connectivity.
    Neuroinformatics 2014; 09/2014
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    ABSTRACT: We recently introduced an eScience infrastructure for the secure sharing of neuroimaging data and running validated analysis pipelines on a high performance cloud [1]. We have populated this infrastructure with two thousand structural MR images from four Dutch medical centers. As a pilot project, we are segmenting the hippocampus for each of these images, thereby running into a number of practical issues. The most prominent question is whether the pipeline that we use, which has been tuned to perform optimally on data from a single MR scanner, can be directly applied to the four datasets, which differ in resolution, scanner type, and acquisition protocol. The most prominent step of the pipeline [2] is the registration of a set of twenty reference segmentations to the target scan in order to create a probabilistic atlas in target space. This is then combined with an intensity model, and the energy function is minimized via graph cuts. Ideally the pipeline would be able to accept new scans of unknown source, and use a standard set of manual segmentations for registration. We have however observed that the (nonlinear) registration performs worse when the source and target scans have dissimilar tissue intensity scales, which leads to an increased bias and variance of derived results such as the hippocampal volume. An alternative approach is not to use a single set of manual segmentations for all data, but use separate segmentations for each cohort that is added to the platform. This introduces another type of bias when the manual segmentations have been carried out by different investigators using different criteria. We investigate whether the improved statistical power of combining cohorts outweighs the bias and variance introduced by the different scan parameters.
    ICNF2014; 08/2014
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    ABSTRACT: In this work we make a bifurcation analysis for a single compartment representation of Traub model, one of the most important conductance-based models. The analysis focuses in two principal parameters: current and leakage conductance. Study of stable and unstable solutions is explored; also Hopf-bifurcation and frequency interpretation when current varies are examined. This is the first analysis done that considers single-compartment version of a Traub model. This study allows having control of neuron dynamics and neuron response when these parameters change. Analyses like these are particularly important for several applications such as: tuning parameters in learning processes, neuron excitability tests, measure bursting properties of the neuron, among others. Finally a hardware implementation tests were developed to corroborate these results. The leakage conductance value was tuned in order the neuron remains at fixed value when it is at resting state. This parameter is the best option to change if does not want to compromise the dynamic of the original model. Through bifurcation analysis, it was detected one stable and one unstable solution (equilibrium points) for this model. A Hopf bifurcation was discovered at the point I = 90 mA, given to the current range [0 90]mA a set of stable periodic orbits with different action potentials amplitudes. The frequencies range for this periodic orbits are from 50 to 341 Hz.
    Neuroinformatics 2014; 08/2014