Description¶
Performs pre-processing and block average analysis of an individual session of an event-related task with multiple trials of event types. Includes block average waveforms.
Report sections¶
This pipeline generates a report in HTML format that contains the following:
- Analysis by Channels
- Block Average Analysis (line plots)
References¶
PARAMETERS¶
Category: Input¶
This pipeline expects one file (or a Path Iterator formatted path name) and its path is relative to your Neuroscale account storage bucket. (The easiest way to run it is to go to your Storage page, select the file, click the Task button which will take you to the Create Task page, and then select this pipeline. The filename will be filed in automatically.)
input path¶
The path to the file to be processed (see above).
device¶
Devices for which custom preset settings will apply. Select 'Default' if the device from which the data was recorded is not listed here.
device info¶
A dictionary of metadata specific to a particular device and cap. At present this is required for LUMO devices in the following format: {'cap_id': string, 'group_id': string, 'montage': json or path to .json file}. If the cap_id is registered with Neuropype, the group_id and montage can be skipped.
nirs stream¶
The name of the NIRS stream if not the default ('nirs').
Category: Events¶
assign targets¶
Mapping of matching criteria (e.g., marker strings) to target values. Any instances that match a given criterion will be assigned the associated target value. The mapping should be a dictionary of {crit1: target-value1, crit2: target-value2, ...}. These target events will be the trial onset anchors for segmenting ERPs/epochs.
time bounds¶
Time range in seconds relative to the target event (typically stimulus or response onset), within which data will be selected to represent the individual trials. Express in this format: [-1.5, 2] (will select from 1.5 seconds before the event to 2 seconds after).
baseline range¶
Time range (in seconds) representing the baseline to be removed from the data relative to target event. Note these values need to be within the bounds of the specified 'time bounds' window.
Category: Preprocessing¶
artifact regression¶
If True and a treshold value for short cannels is specified, regress short channels that are shorter than the given value, in millimeters, as part of the preprocessing process (on optical density signal data only).
rename channels¶
Rename channels using a regex pattern. This is a list with two strings, one containing the search pattern and the other containing the replace pattern. In the replace pattern using a double backslash \ to indicate the group number, i.e., \1.
resample¶
Resample signal to a given sampling rate. This uses a polyphase implementation. This node currently only supports resampling during offline processing, and uses a zero-phase FIR filter (that is, it is not strictly causal, but the filter is usually quite short).
group by cluster¶
Group channels by cluster of source/detectors to reduce the channel count. (Currently only applicable if 'lumo' device is selected.
segments to drop¶
A list of pairs of markers between which data will be dropped before computing quality metrics, such as breaks or baseline data. Use the following format: [('baseline-begin', 'baseline-end'), ('break-begin', 'break-end')].
baseline pca¶
Do baseline PCA on the optical density data as part of the preprocessing. If enabled the baseline start and end markers must be specified in 'baseline_markers'.
baseline markers¶
A pair of markers used to indicate baseline data. This is used to remove the baseline from the data using PCA if Baseline_PCA is selected as part of the preprocessing. Example: ['baseline-begin', 'baseline-end'].
trim ends¶
Trim data at both ends before processing. Use this to drop a certain number of seconds of data from the beginning or the end (i.e., when adjusting or taking off device) that should not be taken into account when computing data quality. This should be a list of two numbers, the first represents the start trim position from the beginning, in seconds, while the second should be a negative number indicating the end trim position from the end of the data, also in seconds. Example: [30, -30] will trim the first and last 30 seconds of data, whereas [30, 0] will trim only the first 30 seconds of data.
short channel threshold¶
Drop channels with a source-detector distance below than this value (in mm). Set to 0 to allow all short channels.
long channel threshold¶
Drop channels with a source-detector distance greater than this value (in mm). Set to 0 to allow all long channels.
highpass cutoff¶
Frequency cutoff (lower bound) for highpass filter. Leave empty to skip highpass filter. Use a two value list to specify the rolloff.
lowpass cutoff¶
Frequency cutoff (upper bound) for lowpass filter. Leave empty to skip lowpass filter. Use a two value list to specify the rolloff.
detrend¶
Detrend the data as a preprocessing step.
tddr¶
Apply TDDR as a preprocessing step.
Category: Style¶
style figure font¶
Font to be used throughout the report
Category: Output¶
The pipeline will automatically generate a .html report into the same path as the input file using an appropriate tag to indicate the type of report that was run. There are additional optional outputs one can choose to save out.
export pkl¶
Whether or not to export a .pkl format structure file of session means. These files are needed from individual session analyses if the dataset will be used in a group analysis pipeline.