Preprocessing was conducted with EEGLAB (Delorme & Makeig, 2004 (link)) and ERPLAB (Lopez-Calderon & Luck, 2014) (link) in MATLAB (Mathworks, Natick, MA). Data were re-referenced off-line to the average reference. Band-pass filtering (0.01-30Hz) was applied to the continuous EEG data, which were then divided into 1000-ms epochs starting at 200ms before and ending at 800ms after the presentation of the object. Since the signals near the end of the stimulus presentation was not of interest, the last 200ms of stimuli presentation (i.e., 800-1000ms) was not used for artifact rejection to avoid rejecting epochs due to artifacts during this time window. Incorrect trials were also excluded from further analyses. Epochs with ocular artifacts were removed by visual inspection and by the moving-window peak-to-peak function in ERPLAB on VEOG, HEOG and the channels selected in the decoding analysis with a threshold of 100 μV, a window size of 200ms and a step size of 50ms. On average, 4.57% and 6.24% of the trials were rejected due to incorrect responses and artifacts respectively.
128 channel eego system
The 128-channel eego system is a high-density EEG (Electroencephalography) recording system designed for advanced neuroscience research applications. It features 128 channels for simultaneous data acquisition, enabling comprehensive brain activity monitoring and analysis.
Lab products found in correlation
2 protocols using 128 channel eego system
EEG Processing and Analysis Protocol
Preprocessing was conducted with EEGLAB (Delorme & Makeig, 2004 (link)) and ERPLAB (Lopez-Calderon & Luck, 2014) (link) in MATLAB (Mathworks, Natick, MA). Data were re-referenced off-line to the average reference. Band-pass filtering (0.01-30Hz) was applied to the continuous EEG data, which were then divided into 1000-ms epochs starting at 200ms before and ending at 800ms after the presentation of the object. Since the signals near the end of the stimulus presentation was not of interest, the last 200ms of stimuli presentation (i.e., 800-1000ms) was not used for artifact rejection to avoid rejecting epochs due to artifacts during this time window. Incorrect trials were also excluded from further analyses. Epochs with ocular artifacts were removed by visual inspection and by the moving-window peak-to-peak function in ERPLAB on VEOG, HEOG and the channels selected in the decoding analysis with a threshold of 100 μV, a window size of 200ms and a step size of 50ms. On average, 4.57% and 6.24% of the trials were rejected due to incorrect responses and artifacts respectively.
EEG Processing and Analysis Protocol
Preprocessing was conducted with EEGLAB (Delorme & Makeig, 2004 (link)) and ERPLAB (Lopez-Calderon & Luck, 2014) (link) in MATLAB (Mathworks, Natick, MA). Data were re-referenced off-line to the average reference. Band-pass filtering (0.01-30Hz) was applied to the continuous EEG data, which were then divided into 1000-ms epochs starting at 200ms before and ending at 800ms after the presentation of the object. Since the signals near the end of the stimulus presentation was not of interest, the last 200ms of stimuli presentation (i.e., 800-1000ms) was not used for artifact rejection to avoid rejecting epochs due to artifacts during this time window. Incorrect trials were also excluded from further analyses. Epochs with ocular artifacts were removed by visual inspection and by the moving-window peak-to-peak function in ERPLAB on VEOG, HEOG and the channels selected in the decoding analysis with a threshold of 100 μV, a window size of 200ms and a step size of 50ms. On average, 4.57% and 6.24% of the trials were rejected due to incorrect responses and artifacts respectively.
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