NMR spectra of milk samples were aligned using Icoshift by co-shifting of the whole spectra according to the anomeric lactose proton at 5.23 ppm [31 (link)]. The proton NMR spectra were subdivided into 0.01 ppm bins, reducing each spectrum into 957 separate variables in the regions 10.00–5.00 and 4.72–0.5 ppm. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed in order to identify differences in the metabolite profiles. The data was mean-centred and Pareto-scaled prior to analysis. The OPLS-DA model was cross-validated using segmentation with seven splits. Covariance was investigated by analysis of OPLS-DA regression coefficients back-transformed to original data and colour coded by the loading weights [32 (link)]. The multivariate data analysis was performed using SIMCA-P + 13 (Umetrics AB, Umeå, Sweden). Alignment by Icoshift, binning, and analysis of OPLS-DA plots were performed in MATLAB 7.13 using in-house developed scripts (MathWorks Inc., Natick, MA, USA). Univariate statistical significance was evaluated by Student’s t-test using the Statistics Toolbox in MATLAB 7.13 (MathWorks Inc., Natick, MA, USA).
Matlab 7
Manufactured by MathWorks
Sourced in United States, United Kingdom, Germany
MATLAB 7.0 is a high-level programming language and numerical computing environment designed for technical computing. It provides a wide range of tools for data analysis, algorithm development, and visualization. MATLAB 7.0 is widely used in various scientific and engineering fields for tasks such as signal processing, image analysis, control system design, and computational biology.
Automatically generated - may contain errors
Lab products found in correlation
Fluo 4 am, by Thermo Fisher Scientific (6 mentions)
858 minibiox 2, by MTS Systems (6 mentions)
Orca er digital camera, by Hamamatsu Photonics (4 mentions)
Statistics toolbox, by MathWorks (4 mentions)
Labview, by National Instruments (4 mentions)
Ix81 inverted fluorescence confocal microscope, by Olympus (3 mentions)
Eyelink 1000, by SR Research (3 mentions)
Spike2, by Cambridge Electronic Design (3 mentions)
Statistica 5, by StatSoft (3 mentions)
Teststar iis system version 2, by MTS Systems (3 mentions)
Jem 1230 electron microscope, by JEOL (3 mentions)
Imagej, by MathWorks (2 mentions)
Pentium 4, by MathWorks (2 mentions)
Somatom sensation 128, by Siemens (2 mentions)
Signa twin speed excite 3t system, by GE Healthcare (2 mentions)
Signa echospeed, by GE Healthcare (2 mentions)
Simca p 11, by Sartorius (2 mentions)
Spss v21, by IBM (2 mentions)
Prism 5, by GraphPad (2 mentions)
Neural network toolbox, by MathWorks (2 mentions)
562 protocols using matlab 7
1
Metabolic Profiling of Milk Samples
2
Bipolar Disorder Treatment Evaluation
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Descriptive statistical methods were used to characterize the sample. The association between treatment and the primary outcome YMRS total score as well as secondary actigraph outcomes was assessed in a linear model with repeated measures, with time, treatment and their interaction as predictors using simple contrasts (all time‐points compared with the baseline value). The single items were assessed by graphical methods and means with 95% confidence intervals (CIs) at each time‐point. Average activity (counts/min) was calculated for all subjects by use of the Actiware Statistics program. Computation was otherwise performed using SPSS 22 (IBM Corp., Armonk, NY, USA) and Matlab 7.1 (Mathworks, Inc., Natick, MA, USA) and all graphics were produced in Matlab 7.1.
3
Neuronal and EMG Signal Analysis
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Neuronal and EMG signals were converted into Spike2 format (Cambridge Electronic Design, Cambridge, UK) for discrimination [23 (link), 27 (link)]. Only stable, well-isolated single neurons seen in recordings longer than 15 s without voluntary movements and artifact were processed. Spikes with a signal-to-noise ratio greater than 2:1 were used. The interspike interval (ISI), the ISI histogram, and the coefficient of variation (CV) of ISI were performed to explore the mean spontaneous firing rate (MSFR) and patterns.
All neuronal and EMG signals were then full wave rectified and imported into MATLAB 7 (The MathWorks, Natick, MA, USA). Power spectrum density (PSD) analysis evaluated neuronal oscillation. A Hanning window at a 50% overlap between windows was used. The significant oscillatory frequencies were determined when exceeding a threshold of 5 SD above the mean power in the 30–100 Hz band [23 (link)].
The relationship between neuronal oscillation and EMG was determined using coherence analysis. A coherence of > 0.42 at a given frequency indicated that the two signals were likely to be related linearly at that frequency (p < 0.05) [22 (link)]. All data analysis was carried out using Spike II 7.02 (Cambridge Electronic Design, Cambridge, UK), MATLAB 7.0 (The MathWorks, Natick, MA, USA) and Origin 7.5 (OriginLab Corporation, Northampton, MA, USA).
All neuronal and EMG signals were then full wave rectified and imported into MATLAB 7 (The MathWorks, Natick, MA, USA). Power spectrum density (PSD) analysis evaluated neuronal oscillation. A Hanning window at a 50% overlap between windows was used. The significant oscillatory frequencies were determined when exceeding a threshold of 5 SD above the mean power in the 30–100 Hz band [23 (link)].
The relationship between neuronal oscillation and EMG was determined using coherence analysis. A coherence of > 0.42 at a given frequency indicated that the two signals were likely to be related linearly at that frequency (p < 0.05) [22 (link)]. All data analysis was carried out using Spike II 7.02 (Cambridge Electronic Design, Cambridge, UK), MATLAB 7.0 (The MathWorks, Natick, MA, USA) and Origin 7.5 (OriginLab Corporation, Northampton, MA, USA).
4
Calcium Signaling in iPSC-derived Neurons
5
Comparative Analysis of Responders and Nonresponders
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Data analysis was performed using MATLAB 7.2 (The MathWorks Inc., Natick, MA). Normal distribution of the data was confirmed with the Lilliefors test. Results were expressed as mean values ± SD. A 2-sample t test was applied to assess the differences in various parameters measured in responders and nonresponders. A P value <0.05 was considered statistically significant.
6
Calcium Imaging of PSC-derived Neurons
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Calcium imaging was performed as described (Chailangkarn et al, 2016 ). Briefly, PSC‐derived neuronal networks were transduced a lentivirus Syn::RFP reporter construct. Cultures were washed with Krebs HEPES buffer and incubated with Fluo‐4AM (Molecular Probes/Invitrogen, Carlsbad, CA, USA). A Hamamatsu ORCA‐ER digital camera (Hamamatsu Photonics, Japan) with 488 nm filter on an Olympus IX81 inverted fluorescence confocal microscope (Olympus Optical, Tokyo, Japan) acquired 5000 frames at 28 Hz in a 256 × 256‐pixel region (100× magnification). Images were acquired with MetaMorph7.7 (MDS Analytical Technologies, Sunnyvale, CA, USA) and analyzed using ImageJ and Matlab7.2 (Mathworks, Natick, MA, USA) using PeakCaller script. A 95th percentile threshold of amplitude for calcium spikes was set for event detection; signal amplitude is presented as fluorescence change (ΔF/F) following background subtraction.
7
Spatio-Temporal Analysis of Dendritic Spine Dynamics
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A short burst of presynaptic uncaging events equally spaced in time with inter stimulus interval (ISI) between 1 and 20 ms was applied on 1–7 visually identified dendritic spines. For each dendritic branch either the number of stimuli or the ISI was varied. Uncaging exposure time was 100–500 μs and the inter-trial interval was 10 s. All data was acquired using custom written software in Matlab 7.2 (Mathworks). The original data recorded at 50 kHz were averaged across identical trials, filtered with a Gaussian kernel with ms and subsampled at 2 kHz for analyses. All spines were responsive in the neocortical experiments.
8
Calcium Imaging of iPSC-Derived Neurons
9
Monitoring Neuronal Network Calcium Dynamics
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Neuronal networks derived from hESCs and hiPSCs were infected with the Synapsin-DsRed lentiviral vector. Cell cultures were incubated with 2–5 μM Fluo-4AM (Molecular Probes/Invitrogen) for 40 min at room temperature. The threshold for activity was set at the 95th percentile of the amplitude for all detected events. Images were acquired with MetaMorph 7.7 (MDS Analytical Technologies) and processed using ImageJ (http://rsbweb.nih.gov/ij/ ) and custom-written routines in Matlab 7.2 (Mathworks).
10
Functional MRI Data Preprocessing
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Imaging data were preprocessed using Statistical Parametric Mapping 2 (Wellcome Trust Centre for Neuroimaging, London, UK) implemented in MATLAB 7.2 (Mathworks Inc., Sherbon, MA).
To reduce the effects of head motion, each subject’s images were realigned to the first volume of each series. The realigned functional images were then spatially normalized to a standard echo-planar imaging template supplied by SPM2. All images were then spatially smoothed with an 8 mm FWHM Gaussian smoothing kernel.
To reduce the effects of head motion, each subject’s images were realigned to the first volume of each series. The realigned functional images were then spatially normalized to a standard echo-planar imaging template supplied by SPM2. All images were then spatially smoothed with an 8 mm FWHM Gaussian smoothing kernel.
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