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matlab vr2018a  (MathWorks Inc)


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    MathWorks Inc matlab vr2018a
    Matlab Vr2018a, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/vr2018a/us12214189-240-6-8
    Average 90 stars, based on 1 article reviews
    matlab vr2018a - by Bioz Stars, 2026-10
    90/100 stars

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    Related Articles

    other:

    Article Title: The Effects of Interphase and Interpulse Delays and Pulse Widths on Induced Muscle Contractions, Pain and Therapeutic Efficacy in Electroporation-Based Therapies
    Article Snippet: Muscle responses: The responses (obtained with the goniometer as .matlab files) were filtered and analyzed in MATLAB vR2018a (MathWorks Inc., Natick, MA, USA) to determine the angle of ankle dorsiflexion for each protocol and amplitude delivered (for each individual separately).

    Article Title: Revealing the Metabolic Flexibility of “ Candidatus Accumulibacter phosphatis” through Redox Cofactor Analysis and Metabolic Network Modeling
    Article Snippet: All simulations were performed using MATLAB vR2018a (9.4.0.813654).

    Article Title: Muscle contractions and pain sensation accompanying high-frequency electroporation pulses
    Article Snippet: The statistical analysis was performed in MATLAB vR2018a (MathWorks Inc., Natick, MA, USA).

    Imaging:

    Article Title: Reduced Hippocampal-Cortical Connectivity During Memory Suppression Predicts the Ability to Forget Unwanted Memories
    Article Snippet: .. The brain imaging data were preprocessed using the CONN toolbox (version 19.c; ) in MATLAB vR2018a (The MathWorks, MA, USA). ..

    Article Title: Reduced hippocampal-cortical connectivity during memory suppression predicts the ability to forget unwanted memories.
    Article Snippet: .. The brain imaging data were preprocessed using the CONN toolbox (Whitfield-Gabrieli and Nieto-Castanon 2012) in MATLAB vR2018a (The MathWorks, MA, United States). ..

    Software:

    Article Title: Single cell analysis reveals multiple requirements for zinc in the mammalian cell cycle
    Article Snippet: Software , BD FACSDiva , BD Biosciences , , Version 8. .. Software , MATLAB , Mathworks , , V R2017b VR2018a. .. Software , KaleidaGraph , Synergy , , Version 4.02.



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    Methods for automatizing the detection and quantification of extracochlear electrodes. EL1 (electrode 1) refers to the most apical electrode, while EL16 (electrode 16) refers to the most basal electrode. A, Example of the calculation of the SCINSEV sum. A SCINSEV for a full insertion in a fresh-frozen cadaveric head is shown. The red markers show the datapoints as collected from recording electrode 3, while stimulating all the other electrodes, that is, 1–2 and 4–16 in this example. In the calculation of the SCINSEV sum, the value of all these datapoints (voltages induced at electrode 3 by stimulation of all other electrodes) are summed to form the SCINSEV sum for that electrode. This is repeated for each recording electrode. B, Example of the calculation of the SCINSEV sum 3 extracochlear electrodes in 1.0% saline in a fresh-frozen human cadaveric head. The blue markers show the datapoints as collected from recording electrode 3 and 15. In the calculation of the SCINSEV sum, the value of all these datapoints (voltages induced at electrode 3 and 15 by stimulation of all other electrodes) are summed to form the SCINSEV sum for that electrode. This is repeated for each recording electrode. C, Example of polynomial fit of the SCINSEV sum for 3 extracochlear electrodes. The sum of a SCINSEV (equal to Figure B) is flipped, shown here as a red dashed line. The changepoints are calculated using the <t>findchangepts</t> function <t>(MATLAB</t> <t>(vR2018A,</t> MathWorks Inc., Massachusetts, USA). The four segments are fitted to a polynomial, displayed with the corresponding polynomial function.
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    Methods for automatizing the detection and quantification of extracochlear electrodes. EL1 (electrode 1) refers to the most apical electrode, while EL16 (electrode 16) refers to the most basal electrode. A, Example of the calculation of the SCINSEV sum. A SCINSEV for a full insertion in a fresh-frozen cadaveric head is shown. The red markers show the datapoints as collected from recording electrode 3, while stimulating all the other electrodes, that is, 1–2 and 4–16 in this example. In the calculation of the SCINSEV sum, the value of all these datapoints (voltages induced at electrode 3 by stimulation of all other electrodes) are summed to form the SCINSEV sum for that electrode. This is repeated for each recording electrode. B, Example of the calculation of the SCINSEV sum 3 extracochlear electrodes in 1.0% saline in a fresh-frozen human cadaveric head. The blue markers show the datapoints as collected from recording electrode 3 and 15. In the calculation of the SCINSEV sum, the value of all these datapoints (voltages induced at electrode 3 and 15 by stimulation of all other electrodes) are summed to form the SCINSEV sum for that electrode. This is repeated for each recording electrode. C, Example of polynomial fit of the SCINSEV sum for 3 extracochlear electrodes. The sum of a SCINSEV (equal to Figure B) is flipped, shown here as a red dashed line. The changepoints are calculated using the findchangepts function (MATLAB (vR2018A, MathWorks Inc., Massachusetts, USA). The four segments are fitted to a polynomial, displayed with the corresponding polynomial function.

    Journal: Ear and Hearing

    Article Title: Detection of Extracochlear Electrodes in Cochlear Implants with Electric Field Imaging/Transimpedance Measurements:

    doi: 10.1097/AUD.0000000000000837

    Figure Lengend Snippet: Methods for automatizing the detection and quantification of extracochlear electrodes. EL1 (electrode 1) refers to the most apical electrode, while EL16 (electrode 16) refers to the most basal electrode. A, Example of the calculation of the SCINSEV sum. A SCINSEV for a full insertion in a fresh-frozen cadaveric head is shown. The red markers show the datapoints as collected from recording electrode 3, while stimulating all the other electrodes, that is, 1–2 and 4–16 in this example. In the calculation of the SCINSEV sum, the value of all these datapoints (voltages induced at electrode 3 by stimulation of all other electrodes) are summed to form the SCINSEV sum for that electrode. This is repeated for each recording electrode. B, Example of the calculation of the SCINSEV sum 3 extracochlear electrodes in 1.0% saline in a fresh-frozen human cadaveric head. The blue markers show the datapoints as collected from recording electrode 3 and 15. In the calculation of the SCINSEV sum, the value of all these datapoints (voltages induced at electrode 3 and 15 by stimulation of all other electrodes) are summed to form the SCINSEV sum for that electrode. This is repeated for each recording electrode. C, Example of polynomial fit of the SCINSEV sum for 3 extracochlear electrodes. The sum of a SCINSEV (equal to Figure B) is flipped, shown here as a red dashed line. The changepoints are calculated using the findchangepts function (MATLAB (vR2018A, MathWorks Inc., Massachusetts, USA). The four segments are fitted to a polynomial, displayed with the corresponding polynomial function.

    Article Snippet: In all cases, this was due to the findchangepts MATLAB (vR2018A, MathWorks Inc., MA) function not correctly identifying the most basal changepoint and therefore this basal segment with one extracochlear electrode had less influence on the mean and slope of the polynomial fit of the SCINSEV sum than with two or more extracochlear electrodes.

    Techniques: