All movements are generated by the activation of motoneurons, and hence their input-output properties define the final step in processing of all motor commands. A major challenge to understanding this transformation has been the striking nonlinear behavior of motoneurons conferred by the activation of persistent inward currents (PICs) mediated by their voltage-gated Na and Ca channels. In this review, we focus on the contribution that these PICs make to motoneuronal discharge and how the nonlinearities they engender impede the construction of a comprehensive model of motor control.
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http://dx.doi.org/10.1152/physiol.00026.2019 | DOI Listing |
Sci Rep
January 2025
Department of Mathematics, King's College London, Strand, London, WC2R 2LS, UK.
Ranking sectors and countries within global value chains is of paramount importance to estimate risks and forecast growth in large economies. However, this task is often non-trivial due to the lack of complete and accurate information on the flows of money and goods between sectors and countries, which are encoded in input-output (I-O) tables. In this work, we show that an accurate estimation of the role played by sectors and countries in supply chain networks can be achieved without full knowledge of the I-O tables, but only relying on local and aggregate information, e.
View Article and Find Full Text PDFNonlinear activation functions (NAFs) are essential in artificial neural networks, enhancing learning capabilities by capturing complex input-output relationships. However, most NAF implementations rely on additional optoelectronic devices or digital computers, reducing the benefits of optical computing. To address this, we propose what we believe to be the first implementation of a nonlinear modulation process using an electro-optic IQ modulator on a silicon photonic convolution operator chip as a novel NAF.
View Article and Find Full Text PDFPolymers (Basel)
December 2024
Faculty of Printing, Packaging Engineering and Digital Media Technology, Xi'an University of Technology, Xi'an 710048, China.
This paper addresses the issue of the high-precision control of substrate tension in an accumulator during the roll-to-roll coating process. First, a coupling model for tension errors in the substrate within the accumulator is established, along with dynamic models for the input-output rollers, carriage, and the thrust model of the ball screw. Based on these models, a simulation model is built in MATLAB/Simulink to analyze the main causes of substrate tension errors in the accumulator under uncontrolled conditions.
View Article and Find Full Text PDFbioRxiv
December 2024
The Edmond and Lily Safra center for Brain Sciences (ELSC), The Hebrew University of Jerusalem, Jerusalem, Israel.
Humans exhibit unique cognitive abilities within the animal kingdom, but the neural mechanisms driving these advanced capabilities remain poorly understood. Human cortical neurons differ from those of other species, such as rodents, in both their morphological and physiological characteristics. Could the distinct properties of human cortical neurons help explain the superior cognitive capabilities of humans? Understanding this relationship requires a metric to quantify how neuronal properties contribute to the functional complexity of single neurons, yet no such standardized measure currently exists.
View Article and Find Full Text PDFISA Trans
December 2024
College of Information Science and Engineering, Huaqiao University, Xiamen, 361002, China. Electronic address:
Iterative learning control (ILC) is a well-established method for achieving precise tracking in repetitive tasks. However, most ILC algorithms rely on a nominal plant model, making them susceptible to model mismatches. This paper introduces a novel normalization concept, developed from a frequency-domain perspective using a data-driven approach, thus eliminating the need for system model information.
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