Task events

The purpose of this file is to describe timing and other properties of events recorded during a run. Events are, for example, stimuli presented to the participant or participant responses (see Definitions). A single event file MAY include any combination of stimulus, response, and other events. Events MAY overlap in time. Please mind that this does not imply that only so called "event related" study designs are supported (in contrast to "block" designs) - each "block of events" can be represented by an individual row in the events.tsv file (with a long duration).

Template:

sub-<label>/[ses-<label>]
    <data_type>/
        <matches>_events.tsv
        <matches>_events.json

Where <matches> corresponds to task filename. For example: sub-control01_task-nback.

Each task events file REQUIRES a corresponding task data file. It is also possible to have a single events.tsv file describing events for all participants and runs (see Inheritance Principle). As with all other tabular data, events.tsv files MAY be accompanied by a JSON file describing the columns in detail (see Tabular Files).

The tabular files consists of one row per event and a set of REQUIRED and OPTIONAL columns:

Column name	Requirement Level	Data type	Description
onset	REQUIRED	number	Onset (in seconds) of the event, measured from the beginning of the acquisition of the first data point stored in the corresponding task data file. Negative onsets are allowed, to account for events that occur prior to the first stored data point. For example, in case there is an in-scanner training phase that begins before the scanning sequence has started events from this sequence should have negative onset time counting down to the beginning of the acquisition of the first volume. If any data points have been discarded before forming the data file (for example, "dummy volumes" in BOLD fMRI), a time of 0 corresponds to the first stored data point and not the first acquired data point. This column must appear first in the file.
duration	REQUIRED	number or `"n/a"`	Duration of the event (measured from onset) in seconds. Must always be either zero or positive (or `n/a` if unavailable). A "duration" value of zero implies that the delta function or event is so short as to be effectively modeled as an impulse. This column must appear second in the file.
trial_type	OPTIONAL	string	Primary categorisation of each trial to identify them as instances of the experimental conditions. For example: for a response inhibition task, it could take on values `go` and `no-go` to refer to response initiation and response inhibition experimental conditions. This column may appear anywhere in the file.
response_time	OPTIONAL	number or `"n/a"`	Response time measured in seconds. A negative response time can be used to represent preemptive responses and `n/a` denotes a missed response. This column may appear anywhere in the file.
HED	OPTIONAL	string	Hierarchical Event Descriptor (HED) Tag. See the HED Appendix for details. This column may appear anywhere in the file.
stim_file	OPTIONAL	string	Represents the location of the stimulus file (such as an image, video, or audio file) presented at the given onset time. There are no restrictions on the file formats of the stimuli files, but they should be stored in the `/stimuli` directory (under the root directory of the dataset; with OPTIONAL subdirectories). The values under the `stim_file` column correspond to a path relative to `/stimuli`. For example `images/cat03.jpg` will be translated to `/stimuli/images/cat03.jpg`. This column may appear anywhere in the file.
channel	OPTIONAL	string	Channel(s) associated with an event. If multiple channels are specified, they MUST be separated by a delimiter specified in the `"Delimiter"` field describing the `channel` column. For example, channels separated with a comma (`,`) require the `events.json` file to contain `"channel": {"Delimiter": ","}`. In the absence of a delimiter, tools MUST interpret any character as being part of a channel name. Note that this column only applies to data types where channels are specified, such as EEG, iEEG, MEG or NIRS. This column may appear anywhere in the file.
Additional Columns	OPTIONAL	`n/a`	Additional columns are allowed.

The content of events.tsv files SHOULD be sorted by values in the onset column.

An arbitrary number of additional columns can be added. Those allow describing other properties of events that could be later referenced in modeling and hypothesis extensions of BIDS. Note that the trial_type and any additional columns in a TSV file SHOULD be documented in an accompanying JSON sidecar file.

Regarding the precision of numeric metadata

For the precision of numeric metadata, it is RECOMMENDENDED that dataset curators specify numeric metadata like onset and duration with as much decimal precision as is reasonable in the context of the experiment. For example in an EEG experiment with devices operating at 1000 Hz sampling frequency, dataset curators SHOULD specify at least 3 figures after the decimal point.

For fMRI data

For fMRI data if any acquired scans have been discarded before forming the imaging data file, ensure that an onset of 0 corresponds to the time the first image was stored. For example in case there is an in scanner training phase that begins before the scanning sequence has started events from this sequence should have negative onset time counting down to the beginning of the acquisition of the first volume.

Example:

└─ sub-control01/
   └─ func/
      ├─ sub-control01_task-stopsignal_events.tsv 
      └─ sub-control01_task-stopsignal_events.json

Example of the content of the TSV file:

onset   duration    trial_type  response_time   stim_file   channel annots
1.23    0.65    start   1.435   images/red_square.jpg   n/a n/a
5.65    0.65    stop    1.739   images/blue_square.jpg  n/a n/a
12.1    2.35    n/a n/a n/a F,1|F,2|Cz  musc

In the accompanying JSON sidecar, the trial_type column might look as follows:

{
    "trial_type": {
        "LongName": "Event category",
        "Description": "Indicator of type of action that is expected",
        "Levels": {
            "start": "A red square is displayed to indicate starting",
            "stop": "A blue square is displayed to indicate stopping"
        }
    },
    "channel": {
        "Description": "Channel(s) associated with the event",
        "Delimiter": "|"
    },
    "annots": {
        "LongName": "Annotations",
        "Description": "Annotations associated with channels indicated in the channel column.",
        "Levels": {
            "musc": "Muscle artifact. A very common, high frequency, sharp artifact that corresponds with agitation/nervousness in a patient."
        },
        "HED": {
            "musc": "EMG-artifact"
        }
    }
}

Note

In the example above:

Only a subset of columns are described for the sake of brevity. In a real dataset, all other columns SHOULD also be described.
The channel column contains a list of values that are separated by a delimiter (|), as is declared in the Delimiter metadata field of the events.json file. Thus, the channels related to the event in the third row of the example are called F,1, F,2, and Cz.
The example contains a column called annots. This column is not defined in BIDS, and constitutes additional, arbitrary (that is, unofficial) metadata. In the present case, it is used to describe artifacts in the data, in reference to the channel column. The annots column is making use of the powerful HED system for documenting events, see below.

Events MAY also be documented in machine-actionable form using HED (Hierarchical Event Descriptor) tags. This type of documentation is particularly useful for datasets likely to be used in event-related analyses. See Hierarchical Event Descriptors for additional information and examples.

For multi-echo files, the events.tsv file is applicable to all echos of a particular run:

└─ sub-01/
   └─ func/
      ├─ sub-01_task-cuedSGT_run-1_events.tsv 
      ├─ sub-01_task-cuedSGT_run-1_echo-1_bold.nii.gz 
      ├─ sub-01_task-cuedSGT_run-1_echo-2_bold.nii.gz 
      └─ sub-01_task-cuedSGT_run-1_echo-3_bold.nii.gz

Stimuli

Additional information about the stimuli can be added in the events.tsv and events.json files.

This can be done by using a /stimuli directory or by reference to a stimuli database.

Stimuli directory

The stimulus files can be added in a /stimuli directory (under the root directory of the dataset; with optional subdirectories) AND using a stim_file column in events.tsv mentioning which stimulus file was used for a given event,

There are no restrictions on the file formats of the stimuli files, but they should be stored in the /stimuli directory.

Stimuli databases

References to existing databases can also be encoded using additional columns. The following example includes references to the Karolinska Directed Emotional Faces (KDEF) database.

└─ sub-control01/
   └─ func/
      ├─ sub-control01_task-emoface_events.tsv 
      └─ sub-control01_task-emoface_events.json

Example of the content of the TSV file:

onset duration  trial_type  identifier  database  response_time
1.2 0.6 afraid  AF01AFAF  kdef  1.435
5.6 0.6 angry AM01AFAN  kdef  1.739
5.6 0.6 sad AF01ANSA  kdef  1.739

The trial_type and identifier columns from the events.tsv files might be described in the accompanying JSON sidecar as follows:

{
    "trial_type": {
        "LongName": "Emotion image type",
        "Description": "Type of emotional face from Karolinska database that is displayed",
        "Levels": {
            "afraid": "A face showing fear is displayed",
            "angry": "A face showing anger is displayed",
            "sad": "A face showing sadness is displayed"
        }
    },
    "identifier": {
        "LongName": "Karolinska (KDEF) database identifier",
        "Description": "ID from KDEF database used to identify the displayed image"
    }
}

Note that all other columns SHOULD also be described but are omitted for the sake of brevity.

Stimulus presentation details

It is RECOMMENDED to include details of the stimulus presentation software, when applicable:

Key name	Requirement Level	Data type	Description
StimulusPresentation	RECOMMENDED	object	Object containing key-value pairs related to the software used to present the stimuli during the experiment.
VisionCorrection	OPTIONAL	string	Equipment used to correct participant vision during an experiment. Example: "spectacles", "lenses", "none".

The object supplied for StimulusPresentation SHOULD include the following key-value pairs:

Key name	Requirement Level	Data type	Description
OperatingSystem	RECOMMENDED	string	Operating system used to run the stimuli presentation software (for formatting recommendations, see examples below this table).
ScreenDistance	RECOMMENDED	number or `"n/a"`	Distance between the participant's eye and the screen. If no screen was used, use `n/a`.
ScreenRefreshRate	RECOMMENDED	number	Refresh rate of the screen (when used), in Hertz (equivalent to frames per second, "FPS").
ScreenResolution	RECOMMENDED	array of integers or `"n/a"`	Screen resolution in pixel (for example `[1920, 1200]` for a screen of 1920-width by 1080-height pixels), if no screen use `n/a`.
ScreenSize	RECOMMENDED	array of numbers or `"n/a"`	Screen size in m, excluding potential screen borders (for example `[0.472, 0.295]` for a screen of 47.2-width by 29.5-height cm), if no screen use `n/a`.
SoftwareName	RECOMMENDED	string	Name of the software that was used to present the stimuli.
SoftwareRRID	RECOMMENDED	string	Research Resource Identifier of the software that was used to present the stimuli. Examples: The RRID for Psychtoolbox is 'SCR_002881', and that of PsychoPy is 'SCR_006571'.
SoftwareVersion	RECOMMENDED	string	Version of the software that was used to present the stimuli.
Code	RECOMMENDED	string	URI of the code used to present the stimuli. Persistent identifiers such as DOIs are preferred. If multiple versions of code may be hosted at the same location, revision-specific URIs are RECOMMENDED.

The operating system description SHOULD include the following attributes:

type (for example, Windows, macOS, Linux)
distribution (if applicable, for example, Ubuntu, Debian, CentOS)
the version number (for example, 18.04.5)

Examples:

Windows 10, Version 2004
macOS 10.15.6
Linux Ubuntu 18.04.5

The amount of information supplied for the OperatingSystem SHOULD be sufficient to re-run the code under maximally similar conditions.

The information related to stimulus presentation might be described in the accompanying JSON sidecar as follows (based on the example of the previous section):

{
    "trial_type": {
        "LongName":   "Emotion image type",
        "Description": "Type of emotional face from Karolinska database that is displayed",
        "Levels": {
            "afraid": "A face showing fear is displayed",
            "angry":  "A face showing anger is displayed",
            "sad":    "A face showing sadness is displayed"
        }
    },
    "identifier": {
        "LongName": "Unique identifier from Karolinska (KDEF) database",
        "Description": "ID from KDEF database used to identify the displayed image"
    },
    "StimulusPresentation": {
        "OperatingSystem": "Linux Ubuntu 18.04.5",
        "SoftwareName": "Psychtoolbox",
        "SoftwareRRID": "SCR_002881",
        "SoftwareVersion": "3.0.14",
        "Code": "doi:10.5281/zenodo.3361717",
        "ScreenDistance": 1.8,
        "ScreenRefreshRate": 60,
        "ScreenResolution": [1920, 1200],
        "ScreenSize": [0.472, 0.295],
        "HeadStabilization": "none"
    },
    "VisionCorrection": "lenses"
}

Example datasets

The following BIDS-Examples showcase stimulus-related signals and may be used as a reference when curating a new dataset:

"synthetic" example dataset.

Signals related to stimuli (such as parameters of a film or audio stimuli) that are evenly recorded at a constant sampling frequency MUST be specified using a compressed tabular file (TSV.GZ file) and a corresponding JSON file for storing metadata fields (see below).

Template:

sub-<label>/[ses-<label>/]
    <datatype>/
        <matches>_stim.tsv.gz
        <matches>_stim.json

For the template directory name, <datatype> can correspond to any data recording modality.

In the template filenames, the <matches> part corresponds to task filename before the suffix. For example for the file sub-control01_task-nback_run-1_bold.nii.gz, <matches> would correspond to sub-control01_task-nback_run-1.

Caution

<matches>_stim.tsv.gz files MUST NOT include a header line, as established by the common-principles. As a result, when supplying a <matches>_stim.tsv.gz file, an accompanying <matches>_stim.json MUST be present to indicate the column names.

If the same continuous recording has been used for all subjects (for example in the case where they all watched the same movie), one file placed in the root directory (for example, <root>/task-movie_stim.<tsv.gz|json>) MAY be used and will apply to all <matches>_task-movie_<matches>_<suffix>.<ext> files. In the following example, the two task-nback_stim.<json|tsv.gz> apply to all the task-nback runs across the two available subjects:

├─ sub-01/
│  └─ func/
│     ├─ sub-01_task-nback_run-1_bold.nii.gz 
│     └─ sub-01_task-nback_run-2_bold.nii.gz 
├─ sub-02/
│  └─ func/
│     ├─ sub-02_task-nback_run-1_bold.nii.gz 
│     └─ sub-02_task-nback_run-2_bold.nii.gz 
├─ task-nback_stim.json 
└─ task-nback_stim.tsv.gz

The following table specifies metadata fields for the <matches>_stim.json file.

Key name	Requirement Level	Data type	Description
SamplingFrequency	REQUIRED	number	Sampling frequency (in Hz) of all the data in the recording, regardless of their type (for example, `2400`).
StartTime	REQUIRED	number	Start time in seconds in relation to the start of acquisition of the first data sample in the corresponding (neural) dataset (negative values are allowed). This data MAY be specified with sub-second precision using the syntax `s[.000000]`, where `s` reflects whole seconds, and `.000000` reflects OPTIONAL fractional seconds.
Columns	REQUIRED	array of strings	Names of columns in file.

Additional metadata may be included as in any TSV file to specify, for example, the units of the recorded time series for each column.

Task events

Stimuli

Stimuli directory

Stimuli databases

Stimulus presentation details

Continuously-sampled, stimulus-related signals