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Analog input recordings <t>with</t> <t>MATLAB</t> <t>DAQ</t> Toolbox and NIMH DAQ Toolbox. The input signal was a 20-Hz sine wave and the sampling rate was 1 kHz. A. Due to the delay in sample transfers, MATLAB DAQ can check new samples only at a rate of ~67 Hz during the logging-mode recordings, which results in aliasing (see the main text). The buffer size was adjusted so that the sample transfers could occur as frequently as possible. B. NIMH DAQ Toolbox retrieves new samples at any time requested even in the logging mode and shows no aliasing. C. The number of available samples increases by 1 every millisecond in NIMH DAQ Toolbox, whereas it increases by 15 every 15 milliseconds in MATLAB DAQ Toolbox. D. The temporal cost of checking the current input state as a function of the number of channels.
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psychophysics toolbox  (MathWorks Inc)
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MathWorks Inc psychophysics toolbox
Analog input recordings <t>with</t> <t>MATLAB</t> <t>DAQ</t> Toolbox and NIMH DAQ Toolbox. The input signal was a 20-Hz sine wave and the sampling rate was 1 kHz. A. Due to the delay in sample transfers, MATLAB DAQ can check new samples only at a rate of ~67 Hz during the logging-mode recordings, which results in aliasing (see the main text). The buffer size was adjusted so that the sample transfers could occur as frequently as possible. B. NIMH DAQ Toolbox retrieves new samples at any time requested even in the logging mode and shows no aliasing. C. The number of available samples increases by 1 every millisecond in NIMH DAQ Toolbox, whereas it increases by 15 every 15 milliseconds in MATLAB DAQ Toolbox. D. The temporal cost of checking the current input state as a function of the number of channels.
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temporal response function toolbox in matlab  (MathWorks Inc)
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Analog input recordings <t>with</t> <t>MATLAB</t> <t>DAQ</t> Toolbox and NIMH DAQ Toolbox. The input signal was a 20-Hz sine wave and the sampling rate was 1 kHz. A. Due to the delay in sample transfers, MATLAB DAQ can check new samples only at a rate of ~67 Hz during the logging-mode recordings, which results in aliasing (see the main text). The buffer size was adjusted so that the sample transfers could occur as frequently as possible. B. NIMH DAQ Toolbox retrieves new samples at any time requested even in the logging mode and shows no aliasing. C. The number of available samples increases by 1 every millisecond in NIMH DAQ Toolbox, whereas it increases by 15 every 15 milliseconds in MATLAB DAQ Toolbox. D. The temporal cost of checking the current input state as a function of the number of channels.
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Image Search Results


Analog input recordings with MATLAB DAQ Toolbox and NIMH DAQ Toolbox. The input signal was a 20-Hz sine wave and the sampling rate was 1 kHz. A. Due to the delay in sample transfers, MATLAB DAQ can check new samples only at a rate of ~67 Hz during the logging-mode recordings, which results in aliasing (see the main text). The buffer size was adjusted so that the sample transfers could occur as frequently as possible. B. NIMH DAQ Toolbox retrieves new samples at any time requested even in the logging mode and shows no aliasing. C. The number of available samples increases by 1 every millisecond in NIMH DAQ Toolbox, whereas it increases by 15 every 15 milliseconds in MATLAB DAQ Toolbox. D. The temporal cost of checking the current input state as a function of the number of channels.

Journal: Journal of neuroscience methods

Article Title: NIMH MonkeyLogic: Behavioral control and data acquisition in MATLAB

doi: 10.1016/j.jneumeth.2019.05.002

Figure Lengend Snippet: Analog input recordings with MATLAB DAQ Toolbox and NIMH DAQ Toolbox. The input signal was a 20-Hz sine wave and the sampling rate was 1 kHz. A. Due to the delay in sample transfers, MATLAB DAQ can check new samples only at a rate of ~67 Hz during the logging-mode recordings, which results in aliasing (see the main text). The buffer size was adjusted so that the sample transfers could occur as frequently as possible. B. NIMH DAQ Toolbox retrieves new samples at any time requested even in the logging mode and shows no aliasing. C. The number of available samples increases by 1 every millisecond in NIMH DAQ Toolbox, whereas it increases by 15 every 15 milliseconds in MATLAB DAQ Toolbox. D. The temporal cost of checking the current input state as a function of the number of channels.

Article Snippet: It also depends on the legacy 32-bit interface of the MATLAB Data Acquisition (DAQ) Toolbox, which was discontinued from MATLAB R2016a.

Techniques: Sampling