High-frequency BOLD signal enhances structural-functional couplings in transmodal cortex
Poster No:
1710
Submission Type:
Abstract Submission
Authors:
Robin Pedersen1, Anna Rieckmann2, Alireza Salami1
Institutions:
1Umeå University, Umeå, Sweden, 2University of the Bundeswehr Munich, Munich, Bavaria
First Author:
Co-Author(s):
Introduction:
Understanding how functional brain dynamics and interregional interactions are shaped by the underlying anatomical structure remain an ongoing challenge. The prevailing hypothesis posits an imperfect and spatially varying correspondence between brain structure and function that are tightly coupled in primary sensorimotor areas, but diverge in polysensory association areas, gradually decoupling along a macroscale functional gradient from unimodal to transmodal cortex (Suarez et al., 2020). However, this hypothesis is constrained by assumptions about the underlying model of structural-functional interactions. While recent studies have considered higher-order structural models, highlighting that brain function is supported by increasingly complex structural constraints along the unimodal–transmodal hierarchy (e.g., Zamani Esfahlani et al., 2022; Yang et al., 2023), they have generally overlooked the temporal features of brain function. Here, we leverage the full frequency range of fMRI BOLD dynamics to examine how frequency-specific fluctuations modulate the relationship between structural and functional connectivity (SC; FC) across the cortex.
Methods:
We analyzed a multimodal MRI dataset of 175 healthy adults (20–79 years) from the DyNAMiC study (Nordin et al., 2022). Whole-brain SC were dervied from preprocessed diffusion-weighted MRI data using anatomically constrained probabilistic tractography (Tournier et al., 2007; Smith et al., 2012). FC were estimated from fMRI (TR = 2 s); acquired during resting-state, movie-watching, and a (n-back) working-memory task; using continuous wavelet transforms to decompose BOLD signals into 16 frequency bins per octave spanning 0.01–0.25 Hz. We generated frequency-specific FC matrices by computing the degree of phase coherence between pairwise brain regions. Associations between SC and FC were evaluated using linear regression models on whole-brain and regional levels. All reported results represent group-average effects.
Results:
We found a spatial distribution of structural-functional couplings to follow the established pattern of unimodal-to-transmodal decoupling across all fMRI conditions. However, the degree of coupling expressed robust frequency-dependent variations across all fMRI conditions. Specifically, context-specific cortical areas exhibited enhanced structural-functional coupling at higher frequencies (up to 0.25 Hz), while context-unspecific areas showed stronger structure–function relationships at lower frequencies (Fig. 1a). Whole-brain coupling peaked around 0.05 Hz (R = ~0.35; Fig. 1b) while regional couplings expressed a wide distribution across the frequency range, ranging from R2 = 0.07 to R2 = 0.58 across the cortex (Fig. 1c). These findings indicate that functional frequency content may shape the degree to which anatomical architecture guides functional interactions.
Conclusions:
Our results demonstrate that the imperfect correspondence between structure and function can be partially understood through frequency-dependent functional dynamics. Specifically, we observed that high-frequency BOLD co-fluctuations selectively strengthen structural–functional couplings in context-specific cortical areas during resting and task, potentially reflecting greater structural constraints for local high-frequency fluctuations. This perspective extends current models, which have primarily focused on higher-order structural motifs (Avena-Koenigsberger et al., 2018; Seguin et al., 2018; Zamani Esfahlani et al., 2022; Yang et al., 2023), by highlighting the critical role of temporal variability in functional brain signals. Moreover, our work underlines the value of considering high-frequency BOLD signal – which is often dismissed as being noisy or prone to physiological artifacts – carrying meaningful information about the interplay between structural wiring and dynamic functional integration.
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural)
Diffusion MRI Modeling and Analysis
fMRI Connectivity and Network Modeling
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Anatomy and Functional Systems 1
White Matter Anatomy, Fiber Pathways and Connectivity 2
Keywords:
Cortex
FUNCTIONAL MRI
MRI
STRUCTURAL MRI
Systems
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
Other - Connectivity
1|2Indicates the priority used for review
Abstract Information
By submitting your proposal, you grant permission for the Organization for Human Brain Mapping (OHBM) to distribute your work in any format, including video, audio print and electronic text through OHBM OnDemand, social media channels, the OHBM website, or other electronic publications and media.
The Open Science Special Interest Group (OSSIG) is introducing a reproducibility challenge for OHBM 2025. This new initiative aims to enhance the reproducibility of scientific results and foster collaborations between labs. Teams will consist of a “source” party and a “reproducing” party, and will be evaluated on the success of their replication, the openness of the source work, and additional deliverables. Click here for more information. Propose your OHBM abstract(s) as source work for future OHBM meetings by selecting one of the following options:
Please indicate below if your study was a "resting state" or "task-activation” study.
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Was this research conducted in the United States?
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Were any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.
Please indicate which methods were used in your research:
For human MRI, what field strength scanner do you use?
Which processing packages did you use for your study?
Provide references using APA citation style.
2. Nordin, K. (2022). DyNAMiC: A prospective longitudinal study of dopamine and brain connectomes: A new window into cognitive aging. Journal of Neuroscience Research, 100(6), 1296-1320.
3. Seguin, C. (2018). Navigation of brain networks. Proceedings of the National Academy of Sciences, 115(24), 6297-6302.
4. Smith, R. E. (2012). Anatomically-constrained tractography: Improved diffusion MRI streamlines tractography through effective use of anatomical information. NeuroImage, 62(3), 1924-1938.
5. Suárez, L. E. (2020). Linking structure and function in macroscale brain networks. Trends in Cognitive Sciences, 24(4), 302-315.
6. Tournier, J. D. (2007). Robust determination of the fibre orientation distribution in diffusion MRI: Non-negativity constrained super-resolved spherical deconvolution. NeuroImage, 35(4), 1459-1472.
7. Yang, Y. (2023). Enhanced brain structure-function tethering in transmodal cortex revealed by high-frequency eigenmodes. Nature Communications, 14(1), 6744.
8. Zamani Esfahlani, F. (2022). Local structure-function relationships in human brain networks across the lifespan. Nature Communications, 13(1), 2053.