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Data acquisition toolbox

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The Data Acquisition Toolbox is a software tool provided by MathWorks. It enables the acquisition, processing, and analysis of data from various measurement devices and sensors.

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Lab products found in correlation

Usb 1208fs, by MathWorks (2 mentions) Matlab, by MathWorks (2 mentions) Ni 9215, by National Instruments (1 mentions) Hd 280, by Sennheiser (1 mentions)

4 protocols using data acquisition toolbox

1

Measuring Proboscis Extension Response in Flies

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Pulse width (ms) and LED light intensity (mW/mm2) were varied in PER experiments. The number of pulses (25) and the frequency (40 Hz) were fixed. For each fly, a total of 10 parameter sets (5 per parameter) were tested in each lighting condition with 5 repetitions. Inter-stimulus-interval (ISI) was 30 seconds. To minimize desensitization, trials were ordered from low to higher light intensity and low to higher pulse widths. The LED was controlled using a data acquisition device (Measurement Computing, USB-1208FS) and the Data Acquisition Toolbox (MathWorks). Fly behavior was recorded using a camera from 1 second before to 2 seconds after the initiation of each trial. The positions of the neck connectives and the root of the antennae were manually determined. The position of the tip of the proboscis was determined by finding the maximum horizontal coordinate of non-zero pixels after the image was thresholded. The PER score was scaled by the size of the head capsule (Supplementary Fig. 15a). All trials were manually proofread to correct image corruption by leg movement. Five flies were used for each combination of wavelength and fly group.
Klapoetke N.C., Murata Y., Kim S.S., Pulver S.R., Birdsey-Benson A., Cho Y.K., Morimoto T.K., Chuong A.S., Carpenter E.J., Tian Z., Wang J., Xie Y., Yan Z., Zhang Y., Chow B.Y., Surek B., Melkonian M., Jayaraman V., Constantine-Paton M., Wong G.K, & Boyden E.S. (2014). Independent Optical Excitation of Distinct Neural Populations. Nature methods, 11(3), 338-346.
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2

Measuring Proboscis Extension Response in Flies

Check if the same lab product or an alternative is used in the 5 most similar protocols
Pulse width (ms) and LED light intensity (mW/mm2) were varied in PER experiments. The number of pulses (25) and the frequency (40 Hz) were fixed. For each fly, a total of 10 parameter sets (5 per parameter) were tested in each lighting condition with 5 repetitions. Inter-stimulus-interval (ISI) was 30 seconds. To minimize desensitization, trials were ordered from low to higher light intensity and low to higher pulse widths. The LED was controlled using a data acquisition device (Measurement Computing, USB-1208FS) and the Data Acquisition Toolbox (MathWorks). Fly behavior was recorded using a camera from 1 second before to 2 seconds after the initiation of each trial. The positions of the neck connectives and the root of the antennae were manually determined. The position of the tip of the proboscis was determined by finding the maximum horizontal coordinate of non-zero pixels after the image was thresholded. The PER score was scaled by the size of the head capsule (Supplementary Fig. 15a). All trials were manually proofread to correct image corruption by leg movement. Five flies were used for each combination of wavelength and fly group.
Klapoetke N.C., Murata Y., Kim S.S., Pulver S.R., Birdsey-Benson A., Cho Y.K., Morimoto T.K., Chuong A.S., Carpenter E.J., Tian Z., Wang J., Xie Y., Yan Z., Zhang Y., Chow B.Y., Surek B., Melkonian M., Jayaraman V., Constantine-Paton M., Wong G.K, & Boyden E.S. (2014). Independent Optical Excitation of Distinct Neural Populations. Nature methods, 11(3), 338-346.
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3

Multi-electrode Electrical Stimulation Protocol

Cited 1 time
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The electrical stimulation hardware consisted of an MEA interfacing headstage, a digital to analog conversion board, a router circuitry, and a controlling PC (Lenovo). Plexon MHP64 headstage was used for interfacing MEAs which was designed for the 64 channel MEA layouts. A custom designed router circuitry was employed for directing analog stimulation signals to selected channel or channels from 64 alternatives. Digital stimulation signals were converted to analog voltages using National Instruments (NI) 6001 board, at a sampling rate of 5 kHz. Digital to analog conversion and router circuitry were controlled with a custom software written in MATLAB (Mathworks Inc.) incorporating Data Acquisition Toolbox (Mathworks Inc.) and utilizing the NI drivers and libraries. All stimulation signals were voltage controlled biphasic pulses and the stimulation parameters were adapted from previous studies [17 (link)–19 (link)]. The pulse durations and the amplitudes that elicit stable and reproducible responses were empirically adjusted in the ranges of 100–500 μs and 1–3 V, respectively.
Bayat F.K., Polat Budak B., Yiğit E.N., Öztürk G., Gülçür H.Ö, & Güveniş A. (2021). Adult mouse dorsal root ganglia neurons form aberrant glutamatergic connections in dissociated cultures. PLoS ONE, 16(3), e0246924.
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4

Force Generation and Auditory Task Protocol

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The main settings and procedures were the same as those in our previous study [9 (link)]. The participants were seated in front of a monitor (EV2450, EIZO) with headphones (HD280, Sennheiser). The right hand was used for the force generation task, and the left hand was used to respond to the auditory task by a keypress. In the force generation task, the force signals from the sensor (USL06-H5-50N-D-FZ, Tec Gihan) were transferred to a laptop computer at a sampling frequency of 200 Hz via an analog-to-digital converter (NI 9215, National Instruments). Data acquisition and stimulus presentation were carried out using MATLAB (MathWorks, Inc.) with the Data Acquisition Toolbox (MathWorks, Inc.) and Psychophysics Toolbox extensions [15 (link)–17 (link)].
Endo N., Ito T., Watanabe K, & Nakazawa K. (2021). Enhancement of loudness discrimination acuity for self-generated sound is independent of musical experience. PLoS ONE, 16(12), e0260859.
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