A radial histogenetic model of the mouse pallial amygdala

Conventional anatomic models of the rodent (mammalian) amygdala are based on section planes oblique to its intrinsic radial glial organization. As a result, we still lack a model of amygdalar histogenesis in terms of radial units (progenitor domains and related radial migration and layering patterns). A radial model of the mouse pallial amygdala is first offered here, based on three logical steps: (1) analysis of amygdalar radial structure in variously discriminative genoarchitectonic material, using an optimal ad hoc section plane; (2) testing preliminary models with experiments labelling at the brain surface single packets of radial glia processes, to be followed into the ventricular surface across intervening predicted elements; (3) selection of 81 differential amygdalar gene markers and checking planar and radial aspects of their distribution across the model elements. This approach shows that subtle changes to the conventional schema of the amygdala allow a radial histogenetic model to be recognized, which is consistent with molecularly coded differential identities of its units and strata. It is expected that this model will help both causal studies of amygdalar developmental patterning and comparative evolutionary studies. It also may have potential impact on hodological and functional studies.

Amygdalar nuclei and hippocampal subfields on MRI: Test-retest reliability of automated volumetry across different MRI sites and vendors

BACKGROUND

The amygdala and the hippocampus are two limbic structures that play a critical role in cognition and behavior, however their manual segmentation and that of their smaller nuclei/subfields in multicenter datasets is time consuming and difficult due to the low contrast of standard MRI. Here, we assessed the reliability of the automated segmentation of amygdalar nuclei and hippocampal subfields across sites and vendors using FreeSurfer in two independent cohorts of older and younger healthy adults.

METHODS

Sixty-five healthy older (cohort 1) and 68 younger subjects (cohort 2), from the PharmaCog and CoRR consortia, underwent repeated 3D-T1 MRI (interval 1-90 days). Segmentation was performed using FreeSurfer v6.0. Reliability was assessed using volume reproducibility error (ε) and spatial overlapping coefficient (DICE) between test and retest session.

RESULTS

Significant MRI site and vendor effects (p ​< ​.05) were found in a few subfields/nuclei for the ε, while extensive effects were found for the DICE score of most subfields/nuclei. Reliability was strongly influenced by volume, as ε correlated negatively and DICE correlated positively with volume size of structures (absolute value of Spearman's r correlations >0.43, p ​< ​1.39E-36). In particular, volumes larger than 200 ​mm³ (for amygdalar nuclei) and 300 ​mm³ (for hippocampal subfields, except for molecular layer) had the best test-retest reproducibility (ε ​< ​5% and DICE ​> ​0.80).

CONCLUSION

Our results support the use of volumetric measures of larger amygdalar nuclei and hippocampal subfields in multisite MRI studies. These measures could be useful for disease tracking and assessment of efficacy in drug trials.