Presented During:
Thursday, June 27, 2024: 11:30 AM - 12:45 PM
COEX
Room:
Grand Ballroom 103
Poster No:
2231
Submission Type:
Abstract Submission
Authors:
Ana Fernanda Ponce Martinez1, Himanshu Aggarwal2, Alexis Thual3, Swetha Shankar1, Ana Luisa Pinho4, Bertrand Thirion5
Institutions:
1Inria Saclay, Palaiseau, Ile de France, 2INRIA Saclay, France, Paris, Ile-de-France, 3Inria, Palaiseau, Other, 4Western University, London, Ontario, 5inria, Palaiseau, NA
First Author:
Co-Author(s):
Introduction:
The Individual Brain Charting (IBC) [8] project was initiated in 2015, with the aim of constructing an extensive neuroimaging dataset, primarily focused on functional Magnetic Resonance Imaging (fMRI) data, that would capture core functional organization across individual brains by spanning a wide array of cognitive domains. This would enable detailed characterization of individual topographies and a more comprehensive understanding of factors influencing cognitive processes.
Methods:
Here we present the final release of the IBC dataset, which comprises 1.5mm-resolution fMRI data from 8 to 12 participants, each undergoing 50 hours of fMRI data collection (with 12 participants completing 40 hours, and subsequently, some dropouts). Throughout these hours, participants engaged in over 80 different cognitive tasks. Additionally, we provide a glance of the broad spectrum of stimuli and tasks featured throughout all the IBC data collection years, aiming to offer a comprehensive view of the intensive and cumulative coverage of various cognitive domains.
Prior releases have laid the groundwork for a very wide range of tasks and explored several domains: mathematical calculations, language, social reasoning, gambling, mental time traveling, spatial navigation, emotional memory, risk evaluation, motor planning, response inhibition, to mention some.
This ultimate release builds upon these domains and introduces new exciting paradigms:
- Color effects in motion perception and working memory [7]
- Motion detection and visual awareness [5]
- Optimism bias for future projection and past recall [9]
- Gender and emotion interaction [10]
- Effect of face perception on gender and emotion perception [10]
- Working memory related to orientation [10]
- Outline and form recognition [6]
- Movie watching and resting state [6]
- Semantics processing and prediction [6]
- Action observation and retrieval [6]
- Motor execution [6]
- Negative scenarios impact on emotional state [3]
- Tactile stimulation and tactile working memory [2]
- Video-game playing [1,4]
Results:
The collected data underwent preprocessing and statistical analysis, resulting in over 700 contrasts, described based on more than 200 cognitive atoms sourced from the Cognitive Atlas. Additionally, the IBC dataset includes resting-state fMRI and diffusion-weighted imaging data, a series of anatomical images acquired repeatedly over the years and the subjects' behavioral performance results on each task.
With this, and thanks to the consistent environment throughout all acquisitions, we have completed a years-long effort to acquire a high resolution dataset, free from inter-subject and inter-site variability, to characterize individual responses to a broad range of stimuli and assignments.
![Supporting Image: tags_through_releases.jpg](https://files.aievolution.com/prd/hbm2401/abstracts/abs_3588/tags_through_releases.jpg)
·Evolution of the study of various cognitive atoms over different years and IBC releases
Conclusions:
All data, at every processing stage (raw data and derivatives), are accessible through open-data platforms, with EBRAINS serving as the primary repository. The IBC project is committed to reproducibility and open science, openly sharing all routines and scripts used for protocol implementation and data analysis. This makes IBC a vast resource of ready-to-run tasks. Additionally, we develop and maintain tools to facilitate easy data or task fetching with just a few lines of code, with the aim of enabling convenient reuse by the community.
![Supporting Image: IBC_nutshell.jpg](https://files.aievolution.com/prd/hbm2401/abstracts/abs_3588/IBC_nutshell.jpg)
·Overview of the IBC project.
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI)
Neuroinformatics and Data Sharing:
Databasing and Data Sharing 1
Novel Imaging Acquisition Methods:
BOLD fMRI 2
Keywords:
Atlasing
Cognition
Data analysis
Data Organization
Design and Analysis
FUNCTIONAL MRI
Open Data
Open-Source Code
1|2Indicates the priority used for review
Provide references using author date format
1. Bellec, P. (2019), 'Bridging the gap between perception and action: the case for neuroimaging, AI and video games', PsyArXiv
2. Erb, J. (2019), 'Homology and Specificity of Natural Sound-Encoding in Human and Monkey Auditory Cortex', Cerebral Cortex, vol. 29, no. 9, pp. 3636–3650
3. Favre, P. (2021), 'Decreased emotional reactivity after 3-month socio-affective but not attention- or meta-cognitive-based mental training: A randomized, controlled, longitudinal fMRI study', NeuroImage, vol. 237
4. Harel, Y. (2023), 'Open design of a reproducible videogame controller for MRI and MEG', PLoS ONE, vol. 18, no. 11
5. Helfrich, R.F. (2013), 'Processing of Coherent Visual Motion in Topographically Organized Visual Areas in Human Cerebral Cortex', Brain Topography, vol. 26, pp. 247–263
6. King, M. (2019), 'Functional boundaries in the human cerebellum revealed by a multi-domain task battery', Nature Neuroscience, vol. 22, pp. 1371–1378
7. McKeefry, D. J. (1997), 'The position and topography of the human colour centre as revealed by functional magnetic resonance imaging', Brain, vol 120, issue 12, pp. 2229–2242
8. Pinho, A.L. (2020), 'Individual Brain Charting dataset extension, second release of high-resolution fMRI data for cognitive mapping', Scientific Data, vol. 7, no. 353
9. Sharot, T. (2007), 'Neural mechanisms mediating optimism bias', Nature, vol. 450, pp. 102–105
10. Snoek, L. (2021), 'The Amsterdam Open MRI Collection, a set of multimodal MRI datasets for individual difference analyses', Scientific Data, vol. 8, no. 85