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. Author manuscript; available in PMC: 2020 Jul 15.
Published in final edited form as: J Neurosci Methods. 2019 May 6;323:13–21. doi: 10.1016/j.jneumeth.2019.05.002

Figure 3.

Figure 3.

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.