Structural covariance network of the hippocampus–amygdala complex in medication-nale patients with first-episode major depressive disorder

Background The hippocampus and amygdala are densely interconnected structures that work together in multiple affective and cognitive processes that are important to the etiology of major depressive disorder(MDD).Each of these structures consists of several heterogeneous subfields.We aim to explore the topologic properties of the volume-based intrinsic network within the hippocampus–amygdala complex in medication-nale patients with first-episode MDD.Methods High-resolution T1-weighted magnetic resonance imaging scans were acquired from 123 first-episode,medication-nale,and noncomorbid MDD patients and 81 age-,sex-,and education level-matched healthy control participants(HCs).The structural covariance network(SCN)was constructed for each group using the volumes of the hippocampal subfields and amygdala subregions;the weights of the edges were defined by the partial correlation coefficients between each pair of subfields/subregions,controlled for age,sex,education level,and intracranial volume.The global and nodal graphmetrics were calculated and compared between groups.Results Compared with HCs,the SCN within the hippocampus–amygdala complex in patients with MDD showed a shortened mean characteristic path length,reduced modularity,and reduced small-worldness index.At the nodal level,the left hippocampal tail showed increased measures of centrality,segregation,and integration,while nodes in the left amygdala showed decreased measures of centrality,segregation,and integration in patients with MDD compared with HCs.Conclusion Our results provide the first evidence of atypical topologic characteristics within the hippocampus–amygdala complex in patients with MDD using structure network analysis.It provides more delineate mechanism of those two structures that underlying neuropathologic process in MDD.

Investigation of white matter functional networks underlying different behavioral profiles in attention-deficit/hyperactivity disorder

Background Cortical functional network alterations have been widely accepted as the neural basis of attention-deficit/hyperactivity disorder(ADHD).Recently,white matter has also been recognized as a novel neuroimaging marker of psychopathology and has been used as a complement to cortical functional networks to investigate brain–behavior relationships.However,disorder-specific features of white matter functional networks(WMFNs)are less well understood than those of gray matter functional networks.In the current study,we constructed WMFNs using a new strategy to characterize behavior-related network features in ADHD.Methods We recruited 46 drug-nale boys with ADHD and 46 typically developing(TD)boys,and used clustering analysis on restingstate functional magnetic resonance imaging data to generate WMFNs in each group.Intrinsic activity within each network was extracted,and the associations between network activity and behavior measures were assessed using correlation analysis.Results Nine WMFNs were identified for both ADHD and TD participants.However,boys with ADHD showed a splitting of the inferior corticospinal–cerebellar network and lacked a cognitive control network.In addition,boys with ADHD showed increased activity in the dorsal attention network and somatomotor network,which correlated positively with attention problems and hyperactivity symptom scores,respectively,while they presented decreased activity in the frontoparietal network and frontostriatal network in association with poorer performance in response inhibition,working memory,and verbal fluency.Conclusions We discovered a dual pattern of white matter network activity in drug-nale ADHD boys,with hyperactive symptom-related networks and hypoactive cognitive networks.These findings characterize two distinct types of WMFN in ADHD psychopathology.