Task Descriptions

The following tasks are available in the MultiTaskBattery. Each task entry shows its description, recorded behavioral metrics, available conditions, and reference where applicable.

Rest

Summary:: Participants are instructed to fixate on a central crosshair.
Details:: Participants lie still and fixate on a central crosshair. No stimuli are presented and no response is required. For most fMRI experiments, rest is used as the baseline condition, and it is therefore recommended to include it into every task battery to allow for alignment with other datasets. However, rest does not minimize brain activity. Some region (the default mode network) are quite activated during rest.
Recorded metrics:: None
Reference:: Gusnard, D.A., Raichle, M.E., and Raichle, M.E. (2001). Searching for a baseline: functional imaging and the resting human brain. Nat. Rev. Neurosci. 2, 685-694.

Task file columns

Column	Type	Description
`trial_num`	int	Trial number (0-indexed).
`trial_dur`	float	Duration of the trial (in seconds).
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).

Toe movement

Summary:: Toe movements. Alternating periods of flexing/extending toes.
Details:: Participants alternate between flexing and extending their toes, paced by visual cues.
Recorded metrics:: None

Task file columns

Column	Type	Description
`trial_num`	int	Cue index within the block (0-indexed); one row per cue.
`stim`	str	The cue shown this row: ‘flexion’ or ‘extension’. Rows alternate between the two across the block.
`trial_dur`	float	How long this cue is shown, in seconds (e.g. 2).
`start_time`	float	Cue onset, relative to the block start (in seconds).
`end_time`	float	Cue offset, relative to the block start (in seconds).

Finger sequence

Summary:: Discrete sequence production task.
Details:: In each trial, a sequence of 6 digits (1-4) is displayed. Participants are instructed to press the corresponding buttons in order as quickly and accurately as possible, starting immediately after presentation. For each correct press, the corresponding digit turns green, for each incorrect press, red. In the standard version, each trial has a length of 3.25s with an ITI of 0.5s. Recorded accuracy is the average press accuracy, and reaction time is the average inter-press-interval. No consecutive repeats appear in the sequence.
Recorded metrics:: Accuracy + RT
Reference:: Wiestler, T., & Diedrichsen, J. (2013). Skill learning strengthens cortical representations of motor sequences. eLife.

Task file columns

Column	Type	Description
`trial_num`	int	Trial number (0-indexed).
`hand`	str	Which hand responds (‘left’, ‘right’, or ‘bimanual’).
`trial_dur`	float	Duration of the trial (in seconds).
`iti_dur`	float	Inter-trial interval after the trial (in seconds).
`display_trial_feedback`	bool	Whether to show green/red feedback after the trial.
`stim`	str	The 6-digit sequence to tap, space-separated (e.g. ‘1 3 2 4 1 3’).
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).

Serial reaction time

Summary:: Participants need to make one of 4 button presses at time, cued by a spatial location of a box
Details:: Four boxes are displayed in a row. On each trial one box lights up green (for 0.5s every 1,5s) and the participant presses the corresponding button as fast as possible. Stimuli are randomized, such that there is no implicit sequence learning. The only constraint is that the same box never lights up on consecutive trials. The task measures basic visuomotor response speed. By default, the 4 buttons are pressed with index and middle finger of the left and right hand.
Recorded metrics:: RT
Reference:: Nissen, M. J., & Bullemer, P. (1987). Attentional requirements of learning: Evidence from performance measures. Cognitive psychology, 19(1), 1-32.

Task file columns

Column	Type	Description
`trial_num`	int	Trial number (0-indexed).
`hand`	str	Which hand responds (‘left’, ‘right’, or ‘bimanual’).
`trial_dur`	float	Duration of the trial (in seconds).
`iti_dur`	float	Inter-trial interval after the trial (in seconds).
`stim`	int	Which box lights up this trial (1-4).
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).

Tongue movement

Summary:: Participants move their tongue right to left against the upper premolar teeth, paced by a flashing circle around a fixation cross.
Details:: Participants move their tongue from right to left, touching their upper premolar teeth on each side. A flashing black circle around a fixation crosshair guides the rhythm at 1-second periods: a black circle cues a movement to the right, no circle cues a movement to the left. The task targets tongue-related somatomotor activation.
Recorded metrics:: None
Reference:: A Third Somatomotor Representation in the Human Cerebellum (Bucknet et al., 2022)

Task file columns

Column	Type	Description
`trial_num`	int	Trial number (0-indexed).
`trial_dur`	float	Duration of the trial (in seconds).
`iti_dur`	float	Inter-trial interval after the trial (in seconds).
`trial_type`	str	Cued movement direction: ‘right’ or ‘left’.
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).

Finger rhythmic

Summary:: Rhythmic tapping production task. Participants are instructed to produce a regular series of taps at a prescribed target interval.
Details:: A timing production task in which participants listen to a train of auditory tones and tap along at the same pace. The task engages motor timing.
Reference:: Ivry, R. B., & Keele, S. W. (1989). Timing Functions of the Cerebellum. Journal of Cognitive Neuroscience, 1(2), 136-152.

Task file columns

Column	Type	Description
`key_one`	int	Response key used to tap.
`trial_num`	int	Trial number (0-indexed).
`hand`	str	Which hand responds (‘left’, ‘right’, or ‘bimanual’).
`trial_dur`	float	Duration of the trial (in seconds).
`iti_dur`	float	Inter-trial interval after the trial (in seconds).
`ioi`	float	Inter-onset interval (pace) for this trial, in seconds.
`stim`	str	Always ‘generated’ — the tone train is synthesized at runtime.
`display_trial_feedback`	bool	Whether to show green/red feedback after the trial.
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).

Time perception

Summary:: Assess the precision of internal timing mechanisms by measuring participants’ perceptual acuity in discriminating short auditory intervals. Participants are presented with sequences of tones and must decide whether a comparison interval is longer or shorter than a standard reference interval.
Recorded metrics:: Accuracy + RT
Reference:: Ivry, R. B., & Keele, S. W. (1989). Timing Functions of the Cerebellum. Journal of Cognitive Neuroscience, 1(2), 136-152.

Task file columns

Column	Type	Description
`trial_num`	int	Trial number (0-indexed).
`modality`	str	Which dimension is judged (‘time’ or ‘volume’).
`side`	str	Correct answer (‘shorter’/’longer’ for time, ‘quieter’/’louder’ for volume).
`key_one`	int	Response key for the left option.
`key_two`	int	Response key for the right option.
`trial_type`	int	Correct-response code: 1 = left option (shorter/quieter), 2 = right option (longer/louder).
`question_dur`	float	Response window after the tones (in seconds).
`trial_dur`	float	Duration of the trial (in seconds).
`iti_dur`	float	Inter-trial interval after the trial (in seconds).
`display_trial_feedback`	bool	Whether to show green/red feedback after the trial.
`comparison_ms`	float	Comparison interval used (filled at runtime; NaN in the generated file).
`comparison_dba`	float	Comparison volume used (filled at runtime; NaN in the generated file).
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).

Visual search

Summary:: A set of letter Ls with different orientations are presented each trial, participants must identify if ‘L’ is present or not.
Details:: Participants view a display of geometric shapes at different rotations (90, 180, 270, 360 degrees) and must determine whether a L is present in the canonical orientation. The number of shapes is flexible, on easy trials 4 shapes are shown, on hard trials 8 shapes are shown. Participants press one button if the target is present and another if it is absent. The task requires a serial search of the display as indicated by RTs increasing linearly in the array size. The task requires shifts of visual attention and elicits eye-movement related activity.
Recorded metrics:: Accuracy + RT
Conditions:: Configurable difficulty via set size (e.g. 4-items / 8-items).
Reference:: Duncan, J., & Humphreys, G. W. (1989). Visual search and stimulus similarity. Psychological review, 96(3), 433.

Task file columns

Column	Type	Description
`key_true`	int	Response key for ‘target present’.
`key_false`	int	Response key for ‘target absent’.
`trial_num`	int	Trial number (0-indexed).
`hand`	str	Which hand responds (‘left’, ‘right’, or ‘bimanual’).
`trial_dur`	float	Duration of the trial (in seconds).
`iti_dur`	float	Inter-trial interval after the trial (in seconds).
`display_trial_feedback`	bool	Whether to show green/red feedback after the trial.
`trial_type`	int	Whether the target ‘L’ is present (1) or absent (0).
`condition`	str	Difficulty as the number of search items / set size, e.g. ‘4-items’ (easy) or ‘8-items’ (hard).
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).

Action observation

Summary:: Participants watch a video of a knot being tied, followed by a rotating 360 view of the knot. A made-up name of the knot is displayed.
Details:: Participants watch videos of a knot being tied then immediately a 360-degree view of the completed knot. Each video/trial is 14s long. The first trial in a block shows the knot-tying action, and subsequent trial shows the static knot view. No motor response during scanning is required, but participants are instructed to learn the knot so they could reproduce it after the scan. The task is designed to engage action observation.
Recorded metrics:: None
Conditions:: action, control
Reference:: Cross, E. S., Cohen, N. R., Hamilton, A. F. de C., Ramsey, R., Wolford, G., & Grafton, S. T. (2012). Physical experience leads to enhanced object perception in parietal cortex: Insights from knot tying. Neuropsychologia, 50(14), 3207-3217.

Task file columns

Column	Type	Description
`trial_num`	int	Trial number (0-indexed).
`trial_dur`	float	Duration of the trial (in seconds).
`iti_dur`	float	Inter-trial interval after the trial (in seconds).
`condition`	str	‘action’ (watching the knot being tied) or ‘control’ (a rotating 360-degree view of the completed knot).
`stim`	str	Knot video filename — ‘knotAction<Name>.mov’ on the first trial (tying), ‘knotControl<Name>.mov’ afterwards (360 deg view).
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).

N back

Summary:

Participants see a stream of images one at a time and press a button on each to indicate whether it matches the image shown n items earlier.

Details:

Participants see a continuous stream of images presented one at a time, drawn from a small set of pictures. On every image they make a two-alternative button press indicating whether the current image is the same as the one shown n items earlier or not. The sequence is generated so that about half of the trials are n-back matches. Non-match trials never repeat any of the just presented images, so a match always requires holding the n-back item in mind rather than just detecting a repeat. The memory load is configurable, so the same task can run as a 1-back, 2-back, 3-back, and so on. This continuous n-back paradigm engages working memory and the domain-general multiple-demand / frontoparietal control network. After each response, the participant receives trial-specific feedback: a green check mark for a correct answer and a red cross for an incorrect one.

Recorded metrics:

Accuracy + RT

Conditions:

Configurable (not predefined): set the memory load via the n-back level (e.g. 1-back / 2-back / 3-back).

References:

Ragland, J. D., Turetsky, B. I., Gur, R. C., Gunning-Dixon, F., Turner, T., Schroeder, L., … & Gur, R. E. (2002). Working memory for complex figures: an fMRI comparison of letter and fractal n-back tasks. Neuropsychology, 16(3), 370.

King, M., Hernandez-Castillo, C. R., Poldrack, R. A., Ivry, R. B., & Diedrichsen, J. (2019). Functional boundaries in the human cerebellum revealed by a multi-domain task battery. Nature neuroscience, 22(8), 1371-1378.

Task file columns

Column	Type	Description
`trial_num`	int	Trial number (0-indexed).
`hand`	str	Which hand responds (‘left’, ‘right’, or ‘bimanual’).
`trial_dur`	float	Duration of the trial (in seconds).
`iti_dur`	float	Inter-trial interval after the trial (in seconds).
`picture_scale`	float	Scaling factor applied to the stimulus image (>1 enlarges).
`condition`	str	The n-back level as an ‘N-back’ label (e.g. ‘2-back’ = a match refers to the item 2 back). This is the modeling-level condition and the only place the n-back level is stored.
`display_trial_feedback`	bool	Whether to show green/red feedback after the trial.
`key_match`	int	Response key for a ‘match’ judgment.
`key_nomatch`	int	Response key for a ‘no-match’ judgment.
`trial_type`	int	Whether the current image matches the one n items back: 1 = match, 0 = no-match.
`stim`	str	Image filename shown this trial.
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).

Demand grid

Summary:: Participants see a sequence of steps that each light up boxes in a grid, mentally combine them into a single pattern, then choose which of two grids matches the full sequence.
Details:: A spatial working memory task. A grid is presented (typically 3x4) and at each step (typically 3) a number of boxes (typically 2) light up for 1.3 s. Participants need to mentally integrate the steps to build the overall pattern. After the sequence, two grids appear side by side, one showing the correct pattern and the other with one of the steps modified. Participants need to make a button press (within 3s) to choose the correct options. Grid size, number of steps, and boxes lit per step are adjustable to vary working memory load. Contrasting harder against easier trials localizes the domain-general Multiple Demand (MD) network in frontal and parietal cortex. The easier>harder or easier>fixation contrasts can be used to localize the Default Mode Network (DMN). After each response, the participant receives trial-specific feedback: a green check mark for a correct answer and a red cross for an incorrect one.
Recorded metrics:: Accuracy + RT
Conditions:: Configurable (not predefined): vary the working-memory load through several parameters — grid size (grid_size) / number of steps (num_steps) / boxes lit per step (num_boxes_lit).
Reference:: Fedorenko, E., Duncan, J., & Kanwisher, N. (2013). Broad domain generality in focal regions of frontal and parietal cortex. Proceedings of the National Academy of Sciences of the United States of America, 110(41), 16616-16621.

Task file columns

Column	Type	Description
`key_left`	int	Response key for choosing the left grid.
`key_right`	int	Response key for choosing the right grid.
`correct_side`	str	Which side shows the correct grid (‘left’ or ‘right’).
`trial_type`	int	Numeric code for the correct side (0 = left, 1 = right).
`trial_num`	int	Trial number (0-indexed).
`hand`	str	Which hand responds (‘left’, ‘right’, or ‘bimanual’).
`grid_size`	tuple	Grid dimensions as (rows, cols).
`num_steps`	int	Number of steps in the sequence.
`original_sequence`	list	Flattened list of all lit cells across the sequence (the correct pattern).
`modified_sequence`	list	Flattened list of lit cells for the incorrect (modified) grid.
`original_step_1`	list	Cells lit during step 1.
`original_step_2`	list	Cells lit during step 2.
`original_step_3`	list	Cells lit during step 3.
`display_trial_feedback`	bool	Whether to show green/red feedback after the trial.
`trial_dur`	float	Duration of the trial (in seconds).
`sequence_dur`	float	Duration of the sequence-presentation phase (in seconds).
`question_dur`	float	Duration of the two-grid choice phase (in seconds).
`iti_dur`	float	Inter-trial interval after the trial (in seconds).
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).

Oddball

Summary:: Participants see a black or red ‘K’ or ‘O’ on screen and press a button only when a red ‘K’ appears.
Details:: Participants see a single letter (‘K’ or ‘O’) briefly shown in either black or red on each trial. They press a button when they see a red ‘K’ (the infrequent target) and withhold responses to all other stimuli. The red ‘K’ appears on 10% of the trials, with the remaining trials split between black ‘K’ (40%), black ‘O’ (40%), and red ‘O’ (10%) non-targets. This task explores detection of transient responses to salient, visual oddball targets that are uncommon relative to irrelevant nontargets and distracting nontargets. The goal of the task is to activate the SAL/PMN and CG-OP networks.
Recorded metrics:: Accuracy + RT
Reference:: Du, J., DiNicola, L. M., Angeli, P. A., Saadon-Grosman, N., Sun, W., Kaiser, S., … & Buckner, R. L. (2024). Organization of the human cerebral cortex estimated within individuals: networks, global topography, and function. Journal of neurophysiology, 131(6), 1014-1082.

Task file columns

Column	Type	Description
`key_one`	int	Response key to press when a red ‘K’ target appears.
`trial_num`	int	Trial number (0-indexed).
`hand`	str	Which hand responds (‘left’, ‘right’, or ‘bimanual’).
`trial_dur`	float	Duration of the trial (in seconds).
`iti_dur`	float	Inter-trial interval after the trial (in seconds).
`trial_type`	int	Whether this is the target: 1 = red ‘K’ (target), 0 = non-target.
`stim`	str	Stimulus shown: ‘black_K’, ‘black_O’, ‘red_O’, or ‘red_K’.
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).

Passage listening

Summary:: Participants listen to intact or acoustically degraded (muffled) speech passages
Details:: Participants listen to excerpts from speeches and talks from several sources (e.g., The moth podcast, Ted talks, celebrity interviews). In the intact condition the audio is intelligible. In the degraded condition the same type of audio is acoustically degraded so it is matched in lower level acoustic properties but the content can no longer be understood. Participants are instructed to only listen attentively; no response is required. The intact>degraded contrast localizes high-level language processing brain regions.
Recorded metrics:: None
Conditions:: intact, degraded
Reference:: Scott, T. L., Gallee, J., & Fedorenko, E. (2017). A new fun and robust version of an fMRI localizer for the frontotemporal language system. Cognitive Neuroscience, 8(3), 167-176.

Task file columns

Column	Type	Description
`trial_num`	int	Trial number (0-indexed).
`trial_dur`	float	Duration of the trial (in seconds).
`iti_dur`	float	Inter-trial interval after the trial (in seconds).
`condition`	str	Speech condition: ‘intact’ (intelligible) or ‘degraded’ (acoustically degraded).
`stim`	str	Audio filename played this trial.
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).

Reading

Summary:: Participants read sentences or nonword sequences.
Details:: One word or non-word is shown at a time. Participants are instructed to read silently as they would when reading a book. In the standard version of the task, each sentence has 12 words / nonwords, and each word is presented for 450ms. At the end of each sentence/nonword sequence, participants see a picture of a finger pressing a button; whenever they see that picture they need to make a button press within 400ms (to help them stay alert during throughout the task. The sentences>nonwords contrast can be used to localize high-level language processing brain regions, i.e., regions that support lexico-semantic and combinatorial (syntactic and semantic) processes.
Recorded metrics:: RT
Conditions:: sentences, nonwords
Reference:: Fedorenko, E., Hsieh, P.-J., Nieto-Castanon, A., Whitfield-Gabrieli, S., & Kanwisher, N. (2010). New method for fMRI investigations of language: defining ROIs functionally in individual subjects. Journal of Neurophysiology, 104(2), 1177-1194.

Task file columns

Column	Type	Description
`trial_num`	int	Trial number (0-indexed).
`trial_dur`	float	Duration of the trial (in seconds).
`iti_dur`	float	Inter-trial interval after the trial (in seconds).
`condition`	str	‘sentences’ or ‘nonwords’.
`stim`	str	The sentence or nonword string shown (presented one word at a time).
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).

Semantic prediction

Summary:: Participants read a sentence presented one word at a time, then decide whether the final word makes the sentence meaningful or meaningless.
Details:: Participants read a sentence presented one word at a time. Each word is presented for 0.8 seconds. After the sentence, a brief fixation cross is shown and then the final, critical word appears; participants make a two-alternative button press to indicate whether that word makes the sentence meaningful (a sensible completion) or meaningless. About half of the trials end with the sentence’s plausible word and half with an implausible word, so participants must use the accumulating sentence context to predict and evaluate the ending. The task engages language comprehension and semantic processing. After each response, the participant receives trial-specific feedback: a green check mark for a correct answer and a red cross for an incorrect one.
Recorded metrics:: Accuracy + RT
Reference:: Moberget, T., Gullesen, E. H., Andersson, S., Ivry, R. B., & Endestad, T. (2014). Generalized role for the cerebellum in encoding internal models: Evidence from semantic processing. The Journal of Neuroscience, 34(8), 2871-2878.

Task file columns

Column	Type	Description
`key_true`	int	Response key for ‘meaningful’.
`key_false`	int	Response key for ‘meaningless’.
`trial_num`	int	Trial number (0-indexed).
`hand`	str	Which hand responds (‘left’, ‘right’, or ‘bimanual’).
`trial_dur`	float	Duration of the trial (in seconds).
`sentence_dur`	float	Response window for the final word (in seconds).
`sentence`	str	The lead-in sentence (without the final word), with words separated by ‘\|’; the runtime splits on ‘\|’ and shows one word at a time (e.g. ‘A\|Dalmatian\|dog\|is\|recognized\|by\|its\|black\|and\|white’).
`trial_type`	int	Whether the final word makes the sentence meaningful (1) or meaningless (0).
`last_word`	str	The final (critical) word shown after the sentence.
`display_trial_feedback`	bool	Whether to show green/red feedback after the trial.
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).

Verb generation

Summary:: Participants see words one at a time and, either silently read each word (read condition) or covertly generate a verb associated with it (generate condition).
Details:: Participants see words presented one at a time. In the ‘read’ condition they silently read each word as it appears. In the ‘generate’ condition they covertly think of a verb associated with each word. A persistent colour-coded label at the top of the screen indicates the current condition (‘READ’ in red or ‘GENERATE’ in green) and stays on throughout. No button response is required. The generate>read contrast is designed to engage language and semantic-retrieval processing.
Recorded metrics:: None
Conditions:: read, generate
Reference:: Adapted by changing into covert rather than overt reading/generation from Raichle, M. E., Fiez, J. A., Videen, T. O., MacLeod, A. M. K., Pardo, J. V., Fox, P. T., & Petersen, S. E. (1994). Practice-related changes in human brain functional anatomy during nonmotor learning. Cerebral cortex, 4(1), 8-26.

Task file columns

Column	Type	Description
`trial_num`	int	Trial number (0-indexed).
`condition`	str	‘read’ (silently read each word) or ‘generate’ (covertly generate a verb).
`trial_dur`	float	Duration of the trial (in seconds).
`iti_dur`	float	Inter-trial interval after the trial (in seconds).
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).
`stim`	str	The word shown this trial.

Movie

Summary:

Participants passively watch a 30-second movie clip (nature, animated romance, or landscape scenery) without audio or subtitles.

Details:

Participants passively watch a single 30-second video clip per block, presented without audio or subtitles, and are instructed to keep their head still and attend to the screen; no response is required. Three clip conditions are available: ‘nature’ — a nature documentary clip (kickboxing kangaroos, from ‘Planet Earth II: Islands’); ‘romance’ — an emotional love story between two characters from the Pixar movie ‘Up’; and ‘landscape’ — an aesthetically-pleasing clip depicting diverse scenery (sourced from Vimeo). The clips of a given condition are presented in order across runs so they unfold as a continuous sequence over the session. Movie watching is a naturalistic-viewing task that engages visual and dynamic-scene processing, with the romance condition additionally recruiting social and emotional processing.

Recorded metrics:

None

Conditions:

romance, nature, landscape

References:

Nguyen, V. T., Sonkusare, S., Stadler, J., Hu, X., Breakspear, M., & Guo, C. C. (2017). Distinct cerebellar contributions to cognitive-perceptual dynamics during natural viewing. Cerebral Cortex, 27(12), 5652-5662.

King, M., Hernandez-Castillo, C. R., Poldrack, R. A., Ivry, R. B., & Diedrichsen, J. (2019). Functional boundaries in the human cerebellum revealed by a multi-domain task battery. Nature neuroscience, 22(8), 1371-1378.

Task file columns

Column	Type	Description
`trial_num`	int	Trial number (0-indexed).
`trial_dur`	float	Duration of the trial (in seconds).
`iti_dur`	float	Inter-trial interval after the trial (in seconds).
`stim`	str	Movie clip filename played this trial.
`condition`	str	Clip category: ‘romance’, ‘nature’, or ‘landscape’.
`media_scale`	float	Clip width as a fraction of the window width (controls on-screen video size).
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).

Auditory narrative

Summary:: Participants listen to 30-second audio snippets from The Moth Radio Hour story ‘Where There’s Smoke’.
Details:: The audio clips are presented sequentially across runs so the participant follows the narrative. The task is designed to engage auditory cortex, the language network and higher-level narrative comprehension.
Recorded metrics:: None
Reference:: Tang, J., LeBel, A., Jain, S., & Huth, A. G. (2023). Semantic reconstruction of continuous language from non-invasive brain recordings. Nature Neuroscience, 26(5), 858-866.

Task file columns

Column	Type	Description
`trial_num`	int	Trial number (0-indexed).
`trial_dur`	float	Duration of the trial (in seconds).
`iti_dur`	float	Inter-trial interval after the trial (in seconds).
`stim`	str	Audio filename (‘narrative_NN.wav’) played this trial.
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).

Spatial navigation

Summary:: Imagined navigation through a remembered environment.
Details:: Participants are instructed to imagine walking from one room to another room in their childhood home. No visual stimuli are presented beyond the instruction. The task is designed to engage spatial memory and mental navigation.
Recorded metrics:: None
Reference:: Boly, M., Coleman, M. R., Davis, M. H., Hampshire, A., Bor, D., Moonen, G., … & Owen, A. M. (2007). When thoughts become action: an fMRI paradigm to study volitional brain activity in non-communicative brain injured patients. Neuroimage, 36(3), 979-992.

Task file columns

Column	Type	Description
`trial_num`	int	Trial number (0-indexed).
`trial_dur`	float	Duration of the trial (in seconds).
`iti_dur`	float	Inter-trial interval after the trial (in seconds).
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).
`location_1`	str	Start location of the imagined route.
`location_2`	str	Destination location of the imagined route.

Affective

Summary:

Participants view a picture (scenes, animals, or foods) and choose whether it is pleasant or unpleasant.

Details:

Participants view pictures drawn from the International Affective Picture System (IAPS) — depicting scenes, animals, and foods — and indicate via a button press whether each image is pleasant or unpleasant. The task is designed to engage affective/emotional valence processing. After each response, the participant receives trial-specific feedback: a green check mark for a correct answer and a red cross for an incorrect one.

Recorded metrics:

Accuracy + RT

References:

Lang, P. J., Bradley, M. M., & Cuthbert, B. N. (1997). International affective picture system (IAPS): Technical manual and affective ratings. NIMH Center for the Study of Emotion and Attention, 1(39-58), 3.

Moulton, E. A., Elman, I., Pendse, G., Schmahmann, J., Becerra, L., & Borsook, D. (2011). Aversion-related circuitry in the cerebellum: responses to noxious heat and unpleasant images. Journal of neuroscience, 31(10), 3795-3804.

Task file columns

Column	Type	Description
`trial_num`	int	Trial number (0-indexed).
`stim`	str	IAPS image filename; valence is encoded in the prefix (‘pleasant…’ / ‘unpleasant…’).
`trial_type`	int	Image valence: 1 = unpleasant, 2 = pleasant.
`hand`	str	Which hand responds (‘left’, ‘right’, or ‘bimanual’).
`trial_dur`	float	Duration of the trial (in seconds).
`iti_dur`	float	Inter-trial interval after the trial (in seconds).
`key_unpleasant`	int	Response key for an ‘unpleasant’ judgment.
`key_pleasant`	int	Response key for a ‘pleasant’ judgment.
`display_trial_feedback`	bool	Whether to show green/red feedback after the trial.
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).

Theory of mind

Summary:: Participants read a short story, followed by a statement they must judge as true or false.
Details:: Participants read short stories. Each story is followed by a statement and a true/false judgment. In the belief condition, stories require inferring what another person believes, even if this belief does not match the state of the world (false belief); in the photo condition, stories require reasoning about outdated content of a physical or external representation such as a photograph, a map or a book, whose information no longer accurate. Both conditions are matched in structure (each involves holding a mental representation that conflicts with the current reality). Only the belief condition involves another person’s mind. Participants press a button to indicate whether the statement about the story is true or false. Task is designed to engage mentalizing (theory of mind): reasoning about other people’s mental states. After each response, the participant receives trial-specific feedback: a green check mark for a correct answer and a red cross for an incorrect one.
Recorded metrics:: Accuracy + RT
Conditions:: belief, photo
Reference:: Saxe, R. and Kanwisher, N. (2003) People thinking about thinking people: The role of the temporo-parietal junction in “theory of mind”, NeuroImage, 19(4), pp. 1835-1842.

Task file columns

Column	Type	Description
`key_true`	int	Response key for a ‘True’ judgment.
`key_false`	int	Response key for a ‘False’ judgment.
`trial_type`	int	Numeric code for the correct answer: 1 = True, 0 = False.
`trial_num`	int	Trial number (0-indexed).
`hand`	str	Which hand responds (‘left’, ‘right’, or ‘bimanual’).
`trial_dur`	float	Duration of the trial (in seconds).
`iti_dur`	float	Inter-trial interval after the trial (in seconds).
`story`	str	The short story text shown in the first phase.
`question`	str	The true/false statement shown after the story.
`condition`	str	‘belief’ (infer a false belief) or ‘photo’ (reason about an outdated representation).
`story_dur`	float	How long the story is displayed (in seconds).
`question_dur`	float	How long the question is displayed (in seconds).
`text_height`	float	Height of the story/question text (degrees of visual angle).
`display_trial_feedback`	bool	Whether to show green/red feedback after the trial.
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).

Reading the mind in the eyes

Summary:: Participants see pictures of faces with different emotions presented (eyes only) along with four options (for either emotion or age), participants must identify which option describes person best.
Details:: Participants see a photograph of a person’s eye region (just the eyes) together with four descriptive words, and press a button to choose the option that best fits the person. In the emotion condition the options are mental-state words and participants infer what the person is thinking or feeling, which engages mentalizing (theory of mind) and social cognition. In the age condition the same eye images are shown but the options are age ranges and participants judge the person’s age instead; this is matched in low-level visual demands and face processing but does not require inferring a mental state, so it serves as a control. The emotion>age contrast isolates mental-state inference from basic face perception. After each response, the participant receives trial-specific feedback: a green check mark for a correct answer and a red cross for an incorrect one.
Recorded metrics:: Accuracy + RT
Conditions:: age, emotion
Reference:: Kim, H.A. et al. (2024) ‘Multiracial Reading the Mind in the Eyes Test (MRMET): An inclusive version of an influential measure’, Behavior Research Methods. Revised from Baron-Cohen, Wheelwright, Hill, Raste, & Plumb, 2001

Task file columns

Column	Type	Description
`key_one`	int	Response key for option 1 (button 1).
`key_two`	int	Response key for option 2 (button 2).
`key_three`	int	Response key for option 3 (button 3).
`key_four`	int	Response key for option 4 (button 4).
`trial_num`	int	Trial number (0-indexed).
`hand`	str	Which hand responds (‘left’, ‘right’, or ‘bimanual’).
`trial_dur`	float	Duration of the trial (in seconds).
`iti_dur`	float	Inter-trial interval after the trial (in seconds).
`option_text_height`	float	Height of the answer-option text (degrees of visual angle).
`option_position_scale`	float	Scaling of option positions (<1 brings options closer together).
`picture_scale`	float	Scaling of the eye-region image (>1 enlarges).
`stim`	str	Eye-region image filename shown this trial.
`options`	str	The four answer options.
`condition`	str	‘emotion’ (infer the mental state) or ‘age’ (judge the person’s age — control).
`answer`	str	The correct option.
`display_trial_feedback`	bool	Whether to show green/red feedback after the trial.
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).

Faux pas

Summary:: Stories of (potential) faux pas situations, participants must answer questions about the interaction.
Details:: On each trial a short social scenario is presented followed by a yes/no question about whether anyone said something they should not have said. The task is designed to engage social cognition and mentalizing regions.
Recorded metrics:: Accuracy + RT
Conditions:: social, control
Reference:: Stone, V.E., Baron-Cohen, S. & Knight, R.T. (1998). Frontal lobe contributions to theory of mind. Journal of Cognitive Neuroscience, 10, 640-656. Gregory, C. , Lough, S., Stone, V.E., Erzinclioglu, S., Martin, L., Baron-Cohen, S. & Hodges, J. (2002). Theory of mind in frontotemporal dementia and Alzheimer’s disease: Theoretical and practical implications. Brain, 125, 752-64.

Task file columns

Column	Type	Description
`key_yes`	int	Response key for ‘Yes’ (a faux pas occurred).
`key_no`	int	Response key for ‘No’.
`trial_num`	int	Trial number (0-indexed).
`hand`	str	Which hand responds (‘left’, ‘right’, or ‘bimanual’).
`trial_dur`	float	Duration of the trial (in seconds).
`iti_dur`	float	Inter-trial interval after the trial (in seconds).
`story`	str	The short social scenario text.
`question`	str	The yes/no question about the scenario.
`options`	str	The answer options.
`trial_type`	int	Numeric code for the correct answer: 1 = Yes, 2 = No.
`condition`	str	‘social’ (a faux-pas story) or ‘control’.
`story_dur`	float	How long the story is displayed (in seconds).
`question_dur`	float	How long the question is displayed (in seconds).
`text_height`	float	Height of the story/question text (degrees of visual angle).
`display_trial_feedback`	bool	Whether to show green/red feedback after the trial.
`start_time`	float	Trial start, relative to the block start (in seconds).
`end_time`	float	Trial end, relative to the block start (in seconds).