RESUMEN
Background: Depression and suicide are leading global causes of disability and death and are highly familial. Family and individual history of depression are associated with neurobiological differences including decreased white matter connectivity; however, this has only been shown for individual regions. We use graph theory models to account for the network structure of the brain with high levels of specialization and integration and examine whether they differ by family history of depression or of suicidality within a three-generation longitudinal family study with well-characterized clinical histories. Methods: Clinician interviews across three generations were used to classify family risk of depression and suicidality. Then, we created weighted network models using 108 cortical and subcortical regions of interest for 96 individuals using diffusion tensor imaging derived fiber tracts. Global and local summary measures (clustering coefficient, characteristic path length, and global and local efficiencies) and network-based statistics were utilized for group comparison of family history of depression and, separately, of suicidality, adjusted for personal psychopathology. Results: Clustering coefficient (connectivity between neighboring regions) was lower in individuals at high family risk of depression and was associated with concurrent clinical symptoms. Network-based statistics showed hypoconnected subnetworks in individuals with high family risk of depression and of suicidality, after controlling for personal psychopathology. These subnetworks highlighted cortical-subcortical connections including between the superior frontal cortex, thalamus, precuneus, and putamen. Conclusions: Family history of depression and of suicidality are associated with hypoconnectivity between subcortical and cortical regions, suggesting brain-wide impaired information processing, even in those personally unaffected.
RESUMEN
The dentate gyrus (DG) is crucial for behaviorally discriminating similar spatial memories, predicting that DG place cells change ("remap") their relative spatial tuning ("place fields") for memory discrimination. This prediction was never tested, although DG place cells remap across similar environments without memory tasks. We confirm this prior finding but find that DG place fields do not remap across spatial tasks that require DG-dependent memory discrimination. Instead of remapping, place-discriminating discharge is observed transiently among DG place cells, particularly when memory discrimination is most necessary. The DG network may signal memory discrimination by expressing distinctive sub-second network patterns of co-firing at memory discrimination sites. This involves increased coupling of discharge from place cells and interneurons, as was observed during successful, but not failed, behavioral expression of memory discrimination. Instead of remapping, these findings indicate that memory discrimination is signaled by sub-second patterns of correlated discharge within the dentate network.