Topological regularization of networks in temporal lobe epilepsy: a structural MRI study

Area of Science:

• Neuroimaging
• Network Neuroscience
• Epilepsy Research

Background:

• Temporal Lobe Epilepsy (TLE) is frequently associated with neurocognitive deficits.
• The underlying pathogenesis of cognitive impairment in TLE remains poorly understood.
• Investigating structural connectivity networks (SCN) may elucidate these mechanisms.

Purpose of the Study:

• To detect alterations in SCN of TLE patients.
• To analyze topological characteristics and robustness of gray matter structural networks in TLE.
• To explore potential neurobiological mechanisms of TLE using graph theoretical analysis.

Main Methods:

• 35 TLE patients and 47 normal controls (NC) underwent 3.0T MRI brain scans.
• Structural covariance networks were constructed based on gray matter volume.
• Graph theory analyzed topological changes in the SCN.

Main Results:

• TLE patients' SCN exhibited topological irregularities, including increased small-world properties and normalized clustering coefficient, with decreased transfer coefficient compared to NC.
• Local network analysis revealed decreased nodal betweenness and degree in specific brain regions (left lingual gyrus, right middle occipital gyrus, right thalamus) in TLE patients.
• TLE SCN showed increased stability against random faults but reduced fault tolerance.

Conclusions:

• Graph theoretical analysis reveals significant topological alterations in the structural brain networks of TLE patients.
• These network changes may contribute to the neurocognitive deficits observed in TLE.
• The findings highlight the utility of network-level analysis in understanding TLE pathophysiology.