Mapping Small-World Properties through Development in the Human Brain: Disruption in Schizophrenia

Dardo Tomasi,Nora D Volkow,Gaolang Gong

doi:10.1371/journal.pone.0096176

Abstract

Evidence from imaging studies suggests that the human brain has a small-world network topology that might be disrupted in certain brain disorders. However, current methodology is based on global graph theory measures, such as clustering, C, characteristic path length, L, and small-worldness, S, that lack spatial specificity and are insufficient to identify regional brain abnormalities. Here we propose novel ultra-fast methodology for mapping local properties of brain network topology such as local C, L and S (lC, lL and lS) in the human brain at 3-mm isotropic resolution from ‘resting-state’ magnetic resonance imaging data. Test-retest datasets from 40 healthy children/adolescents were used to demonstrate the overall good reliability of the measures across sessions and computational parameters (intraclass correlation > 0.5 for lC and lL) and their low variability across subjects (< 29%). Whereas regions with high local functional connectivity density (lFCD; local degree) in posterior parietal and occipital cortices demonstrated high lC and short lL, subcortical regions (globus pallidus, thalamus, hippocampus and amygdala), cerebellum (lobes and vermis), cingulum and temporal cortex also had high, lS, demonstrating stronger small-world topology than other hubs. Children/adolescents had stronger lFCD, higher lC and longer lL in most cortical regions and thalamus than 74 healthy adults, consistent with pruning of functional connectivity during maturation. In contrast, lFCD, lC and lL were weaker in thalamus and midbrain, and lL was shorter in frontal cortical regions and cerebellum for 69 schizophrenia patients than for 74 healthy controls, suggesting exaggerated pruning of connectivity in schizophrenia. Follow up correlation analyses for seeds in thalamus and midbrain uncovered lower positive connectivity of these regions in thalamus, putamen, cerebellum and frontal cortex (cingulum, orbitofrontal, inferior frontal) and lower negative connectivity in auditory, visual, motor, premotor and somatosensory cortices for schizophrenia patients than for controls, consistent with prior findings of thalamic disconnection in schizophrenia.

Highlights

Graph theory postulates that real networks have a ‘small-world’ topology with high clustering and short path length that ensures within-network maximal communication rate with minimal wiring cost [1]
Brain functional connectivity computed from magnetic resonance imaging (MRI) data collected in resting conditions demonstrated the distribution of functional connectivity hubs in the human brain [8,9,10,11], and is a powerful method for studying the topology of the brain in health and disease conditions [10,12,13] with high spatial resolution (3mm isotropic)
Ethics Statement This study is based on existing datasets that were distributed with the approval of the corresponding Institutional Review Boards (IRB) and in compliance with the Health Insurance Portability and Accountability (HIPAA) privacy rules via the International Neuroimaging Data-sharing Initiative

Summary

Introduction

Graph theory postulates that real networks have a ‘small-world’ topology with high clustering and short path length that ensures within-network maximal communication rate with minimal wiring cost [1]. The human brain is a complex network of highly interconnected regions and an example of a real network with small-world topology [2]. Consistent with the small-world network topology [1], the architecture of the brain include few ‘‘hubs’’ (nodes with high connectivity degree) interconnecting distributed local networks, and abundant weakly connected nodes [7]. The lack of additional voxelwise graph theory measures (clustering and path length) limits our interpretation of abnormalities in the strength of the connectivity hubs in psychiatric populations

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Discussion

Conclusion