Atypical Connectome Topography and Signal Flow in Temporal Lobe Epilepsy

Neurology Basic Medical Sciences Medical Imaging Medicine
temporal lobe epilepsy multi-site multimodal gradient effective connectivity memory

Epilepsy is one of the most common neurological disorders, with temporal lobe epilepsy (TLE) being the most prevalent form of drug-resistant epilepsy in adults. Numerous studies have indicated that TLE involves not only pathological changes in the medial temporal lobe but also affects widespread brain structures and functions. In this scientific report on TLE, we will detail a research paper written by Kexie et al., published in the journal “Progress in Neurobiology”. This paper explores the abnormalities in brain functional topological structures and signal flow patterns in TLE patients, providing new insights that help us better understand the temporal lobe pathology and cognitive dysfunctions associated with TLE.

Research Background

Temporal lobe epilepsy is the most common form of drug-resistant epilepsy, primarily associated with medial temporal lobe pathology. However, recent research indicates that the impact of TLE on brain structures and functions extends beyond the temporal lobe, particularly affecting memory capability in cognitive functions. Existing studies have found that TLE patients exhibit abnormal functional connectivity across the brain, but large-scale functional reorganization has not been fully understood. Brain connectivity is highly complex, and understanding its manifestation in broader network structures is crucial for capturing pathophysiological changes related to TLE.

Research Source

Group Differences in Connectomics Topological Features This paper was co-authored by the team of Boris C. Bernhardt from McGill University and several collaborators from other institutions. The research team members include Ke Xie, Jessica Royer, Sara Larivière, Raul Rodriguez-Cruces, and Stefan Frässle, among others. It was published in April 2024 in the journal “Progress in Neurobiology.”

Research Objectives

Previous studies on TLE have primarily focused on functional connectivity abnormalities in local brain regions, while understanding of whole-brain functional network reorganization remains insufficient. This paper aims to comprehensively evaluate the functional topological structure and signal flow patterns among large-scale neural circuits in TLE patients at rest through multimodal imaging and connectomics analysis.

Research Process and Methods

1. Participants and Data Collection

Researchers recruited 95 TLE patients and 95 healthy controls from three independent institutions. To obtain consistent cross-regional results, the research data included T1-weighted magnetic resonance imaging (MRI), resting-state functional MRI (rs-fMRI), and diffusion-weighted imaging (DWI) data. Participants were sourced from the Montreal Neurological Institute and Hospital, Universidad Nacional Autónoma de México, and Nanjing University School of Medicine.

2. Data Processing and Analysis

Imaging data were standardized using the Micapipe toolbox, including steps such as denoising, image reorientation, and registration. Subsequently, the Brainspace toolbox was utilized to reduce the dimensionality of the functional connectivity matrix, capturing topological gradient features of brain connectivity overall. The specific gradient mapping method employed nonlinear manifold learning techniques, primarily using the diffusion map embedding method.

For the analysis of directional signal flow patterns, Regression Dynamic Causal Modeling (RDCM) was used. This model efficiently handles effective connectivity of large-scale networks, revealing the direction and intensity of functional signals between nodes.

3. Main Experimental Steps

  • Functional Topology Gradient Analysis: By reducing the dimensionality of high-dimensional functional connectivity matrices, a series of low-dimensional features were obtained, particularly the first gradient, representing the hierarchical transition from sensory/motor systems to transmodal association systems.
  • Effective Connectivity Analysis: The RDCM method was employed to estimate whole-brain effective connectivity matrices, quantitatively analyzing the differences in signal flow across the whole brain between TLE patients and healthy controls.
  • Structure-Function Relationship Analysis: The relationship between structural MRI and DWI data was studied to explore whether changes in white matter microstructure mediate changes in functional connectivity.

Research Results

1. Functional Topology Gradient Changes

The study found significant contraction in the primary functional gradient across the entire cerebral cortex in TLE patients, particularly notable in bilateral temporal lobes and ventromedial prefrontal cortex. The reduction in segregation of these regions suggests that TLE may impair the differentiation functions between different brain systems.

2. Effective Connectivity Changes

Using the RDCM method, the study revealed significant abnormalities in signal flow within multiple brain functional systems in TLE patients, primarily involving bilateral temporal and frontoparietal cortices. Compared to healthy controls, both directions of signal flow were significantly reduced in TLE patients, indicating significant changes in the hierarchical organization of brain networks.

3. Structure-Function Correlation

Further analysis showed that changes in the superficial white matter (SWM) microstructure partly mediated changes in the functional topology gradient in TLE patients, consistent with previous studies on widespread white matter alterations caused by TLE. However, changes in the functional topology gradient were not significantly correlated with cortical atrophy.

4. Cognitive Function Correlation

Behavioral analysis indicated that functional indicators were significantly correlated with individual overall memory capability, suggesting a close relationship between abnormalities in functional gradients and signal flow and memory dysfunction. These results highlight the contribution of large-scale functional reorganization to common memory impairments in TLE patients.

Conclusions and Significance

This study utilized topological gradient mapping techniques and effective connectivity analysis with generative models to reveal large-scale brain functional network reorganization in TLE patients at rest. The study shows that TLE affects not only the medial temporal lobe but also triggers chain reactions in the functional networks of widespread cortical areas. These findings provide new perspectives for understanding cognitive dysfunctions associated with TLE, bearing significant scientific and potential clinical value.

Main Highlights

  • Discovery of Significant Contraction in Whole-Brain Functional Topology Gradients: Especially in bilateral temporal lobes and ventromedial prefrontal cortex, revealing disruptions in large-scale neural network functional differentiation due to TLE.
  • Effective Connectivity Analysis Revealed Signal Flow Abnormalities: Reduced signal flow in multiple brain functional systems in TLE patients indicates significant changes in the hierarchical organization of brain networks.
  • Tight Structure-Function Correlation: Changes in superficial white matter microstructure partly mediate the changes in functional topology gradients.
  • Cognitive Function Correlation Analysis: Emphasizes the impact of large-scale functional network reorganization on memory impairment in TLE patients.

These research findings enrich our understanding of TLE pathophysiological mechanisms and provide new directions for developing more effective diagnostic and therapeutic methods in the future.