Mapping White Matter Tracts to NeuroSynth Cognitive Functions
Poster No:
2181
Submission Type:
Abstract Submission
Authors:
Joelle Bagautdinova1, Audrey Luo1, Golia Shafiei1, Aaron Alexander-Bloch1, Margaret Gardner1, Arielle Keller1, Margaret Pecsok1, Taylor Salo1, Russell Shinohara1, Valerie Sydnor2, Fang-Cheng Yeh3, Bratislav Misic4, Matthew Cieslak5, Theodore Satterthwaite5
Institutions:
1University of Pennsylvania, Philadelphia, PA, 2Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, 3Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, 4McGill University, Montreal, Quebec, 5UPenn, Philadelphia, PA
First Author:
Co-Author(s):
Introduction:
White matter tracts efficiently support the relay of information between distant brain regions and thus facilitate integrative cognition (Fields, 2008; Goddings et al., 2021). However, no systematic mapping exists that links tracts to specific cognitive functions in humans. Here, we capitalize on NeuroSynth (Yarkoni et al., 2011) and a recently developed white matter atlas of probabilistic tract-to-region mappings (Yeh, 2022) to systematically delineate the core cognitive functions of canonical white matter tracts. We hypothesized that white matter tract architecture is linked to the spatial organization of cognitive functions.
Methods:
Probabilistic estimates of white matter tract-to-surface connections derived from 1,065 young adults in the Human Connectome Project were used to link cognitive function maps and canonical white matter tracts. Specifically, the probability that each of 50 tracts (Yeh et al., 2018) reconstructed with DSI Studio (http://dsi-studio.labsolver.org) connected to each of 360 cortical regions (Glasser atlas) was determined at the population-level (Yeh, 2022). Next, we leveraged coordinate-based cognitive maps from NeuroSynth (Yarkoni et al., 2011) to annotate white matter tracts using a subset of 12 core cognitive functions from the Cognitive Atlas (Poldrack et al., 2011), including attention, cognitive control, inhibition, decision making, planning, imagery, language, memory, working memory movement, emotion, and social cognition. We used two different approaches to determine whether the spatial organization of core functional activation maps reflect the architecture of underlying structural connections. First, for each cognitive activation map, we used mass-univariate t-tests in each cognitive map and tract to assess whether the distribution of cognitive activations differed between regions that are connected to the tract vs. other unconnected regions within the same hemisphere. Second, we fit multiple linear regression models to evaluate if tract-to-region probability maps (i.e., independent variables) were associated with each cognitive map (i.e., dependent variable). To account for the inherent spatial autocorrelation in the covariance structure of the cortical surface, 10,000 spin-based spatial permutations were used for significance testing in both independent t-tests and regressions (Alexander-Bloch et al., 2018).
Results:
Half (25 out of 50) of the white matter tracts were enriched for specific cognitive functions (Figure 1A; pspin<0.05). We found some expected tract-to-function relationships, such as a specialization for language in the arcuate fasciculus, for memory in cingulum tracts, and for emotion in uncinate tracts (Figure 1B; pspin<0.05). Results also uncovered lesser-known tract functions, including an enrichment for imagery in the middle longitudinal fasciculus, and a specific involvement of attention in the posterior thalamic radiation (pspin<0.05). White matter tracts explained the spatial organization of attention, cognitive control, and working memory maps (Figure 2; pspin<0.05; R2:0.5 to 0.8). The frontal aslant, superior longitudinal and corticostriatal tracts were particularly strongly associated with working memory.
Conclusions:
We introduced a novel framework for ascribing cognitive functions to white matter tracts. This allowed us to both validate expected tract-to-function relationships and suggest new links. Moreover, structural connectivity patterns of white matter tracts explained the topographical organization of several cognitive functions. Taken together, this work bridges the gap between the functional neuroimaging-based literature of cognitive functions and white matter architecture, providing a systematic mapping of tract-to-function relationships. This framework may be used in future studies to help annotate tracts using contemporary representations of cognitive functions.
Higher Cognitive Functions:
Higher Cognitive Functions Other 2
Modeling and Analysis Methods:
Multivariate Approaches
Univariate Modeling
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
White Matter Anatomy, Fiber Pathways and Connectivity 1
Keywords:
Cognition
FUNCTIONAL MRI
Open Data
White Matter
1|2Indicates the priority used for review
Provide references using author date format
Fields, R. D. (2008). White matter in learning, cognition and psychiatric disorders. Trends in Neurosciences, 31(7), 361–370.
Goddings, A. L., et al. (2021). Development of white matter microstructure and executive functions during childhood and adolescence: A review of diffusion MRI studies. In Developmental Cognitive Neuroscience (Vol. 51).
Poldrack, R., et al. (2011). The Cognitive Atlas: Toward a Knowledge Foundation for Cognitive Neuroscience. Frontiers in Neuroinformatics, 5.
Yarkoni, T., et al. (2011). Large-scale automated synthesis of human functional neuroimaging data. Nature Methods, 8(8), Article 8.
Yeh, F.-C. (2022). Population-based tract-to-region connectome of the human brain and its hierarchical topology. Nature Communications, 13(1), Article 1.
Yeh, F.-C., et al. (2018). Population-averaged atlas of the macroscale human structural connectome and its network topology. NeuroImage, 178, 57–68.