Decoupling of brain function from structure reveals regional behavioral specialization in humans (1905.07813v2)

Abstract: The brain is an assembly of neuronal populations interconnected by structural pathways. Brain activity is expressed on and constrained by this substrate. Therefore, statistical dependencies between functional signals in directly connected areas can be expected higher. However, the degree to which brain function is bound by the underlying wiring diagram remains a complex question that has been only partially answered. Here, we introduce the structural-decoupling index to quantify the coupling strength between structure and function, and we reveal a macroscale gradient from brain regions more strongly coupled, to regions more strongly decoupled, than expected by realistic surrogate data. This gradient spans behavioral domains from lower-level sensory function to high-level cognitive ones and shows for the first time that the strength of structure-function coupling is spatially varying in line with evidence derived from other modalities, such as functional connectivity, gene expression, microstructural properties and temporal hierarchy.

• The paper introduces the structural-decoupling index to quantify the coupling strength between brain structure and function using energy ratios of filtered brain signals.
• It applies graph signal processing and Human Connectome Project data to map a gradient from high sensory coupling to low cognitive coupling.
• The findings suggest that flexible cognitive functions are enabled by decoupling from anatomical constraints, with implications for clinical neuroscience.

Decoupling of Brain Function from Structure Reveals Regional Behavioral Specialization in Humans

This paper examines the intricate relationship between brain structural connectivity (SC) and functional connectivity (FC) and introduces a novel metric—the structural-decoupling index—to quantify how strongly functional signals are coupled with the underlying anatomical structure across different regions of the brain.

Introduction to Structure-Function Coupling

The paper begins by recognizing that brain activity is constrained by the structural pathways formed by neuronal connections. Functional activity, measured via FC, reflects statistical dependencies between activation timecourses, while SC reveals these white-matter pathways. Previous research primarily explored SC-FC relationships through correlation, dynamic causal modeling, and graph modeling. However, the complexity of brain function’s dependence on structuring frameworks remains insufficiently understood.

Methodology and Structural-Decoupling Index

The authors introduce the structural-decoupling index to measure the strength of coupling between SC and functional brain signals. This index evaluates function-structure coupling by filtering brain activity into two energy-equivalent parts: a low-frequency component (strongly coupled) and a high-frequency component (weakly coupled). The energy ratio of these components informs the structural-decoupling index. The research employs the Human Connectome Project’s data, constructing both SC-ignorant and SC-informed null models to benchmark empirical results.

Results: Functional-Structural Coupling Gradient

Analyzing data from the Human Connectome Project, the paper maps a spatial gradient of function-structure coupling across the brain. Sensory regions such as visual, auditory, and somatomotor areas show higher coupling with SC, whereas higher-level cognitive regions like executive control networks, language centers, and emotion-related areas exhibit greater decoupling. This gradient aligns with prior findings from modalities such as gene expression and microstructural analysis.

Harmonics and Graph Signal Processing

The authors leverage graph signal processing (GSP) techniques, specifically using structural connectome harmonics derived from the Laplacian eigendecomposition. This spectral approach allows decomposition and characterization of functional signals relative to the structural graph, facilitating a nuanced understanding of brain activity and its SC coupling.

Implications and Future Directions

The paper's results imply that lower-level sensory functions are more constrained by anatomical pathways, while higher cognitive functions exhibit a more flexible architecture. This decoupling might explain the need for adaptability in complex cognitive tasks, where deterministic pathways are insufficient. The structural-decoupling index could provide insights into variations due to neurological conditions, opening pathways for research into brain function plasticity and adaptability.

Conclusion

This research provides a sophisticated framework for quantifying the relationship between brain structure and function, emphasizing regional differences in behavioral specialization. The proposed structural-decoupling index embodies a significant advancement in modeling and understanding the anatomical-functional interface, suggesting potential applications in clinical neuroscience and cognitive science research.