narratives 🟠 Alpha

Subjects

5 — sub-01 ✅ · sub-02 ✅ · sub-03 ✅ · sub-04 ❌ · sub-05 ✅ · sub-06 ✅

Maturity

🟠 Alpha — Not fully acquired or released, or missing a README.

Data

🧠 fMRI — 9.7 h/subject

🔊 Audio — 3.2 h/subject

🗣️ Speech listening — 3.2 h/subject

Assets

📁 BIDS · 🧠 fMRIPrep · timeseries

How to cite

Toneva, M., Borghesani, V., St-Laurent, M., Pinsard, B., Boyle, J., et al. (2027). CNeuroMod-Narratives: naturalistic spoken narrative comprehension, recall, and recency judgments in deeply sampled individuals.

Contributors

Conceptualization: Mariya Toneva · Valentina Borghesani · Lune Bellec

Data curation: Marie St-Laurent · Basile Pinsard

Funding acquisition: Lune Bellec

Methodology: Mariya Toneva · Valentina Borghesani

Project administration: Marie St-Laurent · Basile Pinsard · Julie A. Boyle · Lune Bellec

Resources: Julie A. Boyle · Lune Bellec

Software: Marie St-Laurent · Basile Pinsard

Supervision: Lune Bellec

Funding: Courtois Foundation · Institut de valorisation des données (IVADO)

Overview

Five participants (sub-01, sub-02, sub-03, sub-05, sub-06) completed 12 fMRI sessions in which they listened to spoken stories and performed two behavioural tasks (free recall and recency judgment) immediately after each story. Each session included two stories, and the full set of eight stories was repeated three times across sessions (4 pairs of stories × 3 repetitions = 12 sessions). The stimuli are a sub-selection of eight stories (~102 min of unique audio in total) drawn from the Narratives collection (Nastase et al., 2021):

  • “Lucy” (Lucy) — 9 min

  • “The Man Who Forgot Ray Bradbury” (Forgot) — 14 min

  • “I Knew You Were Black” (Black) — 13 min

  • “It’s Not the Fall That Gets You” (Notthefallintact) — 9 min

  • “Slumlord” (Slumlord) — 15 min

  • “Pie Man” (Pieman) — 7 min

  • “Pretty Mouth and Green My Eyes” (Prettymouth) — 11 min

  • “Tunnel Under the World” (Tunnelpart1, Tunnelpart2) — split in two blocks of 12 min each

What makes this dataset distinctive is that it pairs naturalistic spoken-narrative comprehension with in-scanner spoken free recall and episodic recency judgments across three repetitions within the same deeply sampled CNeuroMod participants, enabling comparisons with the larger cross-sectional Narratives benchmark as well as other CNeuroMod language and movie-watching datasets (langlocalizer, harrypotter, friends, movie10).

Tasks

For each story <Story>, three functional runs were acquired in sequence. Tunnel Under the World is the exception: each of its two parts has its own listening and recall runs, followed by a single recency run (task-TunnelRecency).

  • listening (task-<Story>Story): Participants were asked to listen to the story very carefully.

  • recall (task-<Story>Recall): Participants were asked to provide a spoken account of what they heard. They were told they had as much time as needed and were asked to provide as many details as they could.

  • recency (task-<Story>Recency): Presented with two fragments from the story, participants had to choose which of the two fragments came first.

Tasks were presented with custom PsychoPy scripts synchronized to the scanner trigger. Sounds were delivered through Sensimetrics S15 insert headphones.