Local Heterogeneity and Directed Connection Shape Spatio-temporal Correlation across Cortex
Poster No:
1209
Submission Type:
Abstract Submission
Authors:
Jiawen Chang1, Songjun Peng1, Changsong Zhou1
Institutions:
1Department of Physics, Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR, China
First Author:
Co-Author(s):
Changsong Zhou
Department of Physics, Hong Kong Baptist University
Kowloon Tong, Hong Kong SAR, China
Department of Physics, Hong Kong Baptist University
Kowloon Tong, Hong Kong SAR, China
Introduction:
The brain's neural dynamics arise from a complex interaction between asymmetric structural connectivity and region-specific intrinsic properties. Recent studies have shown that incorporating regional heterogeneity into large-scale models improves the ability to capture key dynamical properties and better explains the relationship between structural and functional connectivity (Demirtaş, 2019; Kong, 2021; Chaudhuri, 2015). Despite these advances, the combined impact of local heterogeneity and directional connectivity on large-scale brain dynamics remains insufficiently understood.
Methods:
To address this gap, we extended the exisiting dynamical differential covariance (DDC) method and developed a reconstruction framework to simultaneously estimate local circuit heterogeneity and asymmetric connections (Chen, 2022). The framework comprises two key components: (1) Temporal reconstruction, which decodes the directionality of neural activity into directed interactions using DDC, and (2) Spatial reconstruction, which disentangles effective heterogeneity and asymmetric connections from these directed interactions, constrained by empirical symmetric structural connectivity. This method was applied to human Magnetoencephalography (MEG) data, combined with MRI-derived structural connectivity.
Results:
This reconstruction method effectively reveals and separates the contributions of effective heterogeneity and asymmetric structural connectivity.
Forward simulations confirm that these factors not only reproduce resting-state functional connectivity but also account for regional variations in temporal autocorrelation timescales. Moreover, we demonstrate their distinct functional roles: while both factors similarly shape resting-state functional connectivity, they differ in their influence on autocorrelation timescales. Effective heterogeneity plays a crucial role in establishing the hierarchical organization of regional timescales, whereas asymmetric connections enhance the variability of timescales across the cortex.
Forward simulations confirm that these factors not only reproduce resting-state functional connectivity but also account for regional variations in temporal autocorrelation timescales. Moreover, we demonstrate their distinct functional roles: while both factors similarly shape resting-state functional connectivity, they differ in their influence on autocorrelation timescales. Effective heterogeneity plays a crucial role in establishing the hierarchical organization of regional timescales, whereas asymmetric connections enhance the variability of timescales across the cortex.
·Examples for asymmetric connections induce response timescale variability while maintaing resting state functional connectivity
Conclusions:
Together, our results present a unified framework for assessing the relative functional contributions of local heterogeneity and asymmetry to overall system dynamics. They underscore the importance of distinguishing between regional heterogeneity and directed inter-regional connections, highlighting their distinct roles in shaping large-scale dynamical patterns of the human cortex.
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 1
Diffusion MRI Modeling and Analysis 2
EEG/MEG Modeling and Analysis
Keywords:
Computational Neuroscience
MEG
Structures
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.
Chen, Y., (2022). Dynamical differential covariance recovers directional network structure in multiscale neural systems. Proceedings of the National Academy of Sciences, 119(24), e2117234119.
Demirtaş, M., (2019). Hierarchical heterogeneity across human cortex shapes large-scale neural dynamics. Neuron, 101(6), 1181-1194.
Kong, X., 2021). Sensory-motor cortices shape functional connectivity dynamics in the human brain. Nature communications, 12(1), 6373.