Structural connectivity analysis reveals topological aberrations in patients with schizophrenia

Area of Science:

• Neuroscience
• Network Science
• Psychiatry

Background:

• Topological analysis aids in understanding brain networks in health and disease.
• Small-worldness is a key measure for network competency and brain connectivity.
• Disruptions in brain connectivity are implicated in neuropsychiatric conditions like schizophrenia.

Purpose of the Study:

• To assess structural differences in brain networks between schizophrenia patients and healthy controls.
• To investigate the utility of graph network distance metrics in identifying brain alterations in schizophrenia.
• To elucidate the topological architecture of structural brain networks in schizophrenia.

Main Methods:

• Diffusion tensor imaging (DTI) data from schizophrenia patients and matched healthy controls.
• Application of graph network distance metrics, including shortest path length and clustering coefficient.
• Comparative analysis of network topological properties between groups.

Main Results:

• Schizophrenia patients exhibited a lower clustering coefficient compared to controls.
• Schizophrenia patients demonstrated longer path lengths.
• Reduced small-worldness was observed in schizophrenia patients, indicating aberrant network topology.

Conclusions:

• Schizophrenia is associated with aberrant topological architecture in structural brain networks.
• The findings suggest potential impacts on psychopathological and cognitive manifestations of schizophrenia.
• Shortest path length and clustering coefficient are sensitive metrics for detecting anatomical changes in neuron deficiency.