Pregnancy results in obvious physiological changes to the female body, but data as to what happens to the maternal brain after giving birth are sparse as well as inconsistent. The overall goal of ...this study is to determine the nature of cerebral change in the postpartum period. For this purpose, we analyzed T1-weighted brain images of 14 healthy women (age range: 25–38 years) at two time points, specifically within 1–2 days of childbirth (immediate postpartum) and at 4–6 weeks after childbirth (late postpartum). When comparing voxel-wise gray matter between these two time points, there was no evidence of any significant decrease. Instead, we detected a pronounced gray matter increase involving both cortical and subcortical regions, such as the pre- and postcentral gyrus, the frontal and central operculum, the inferior frontal gyrus, the precuneus, and the middle occipital gyrus, as well as the thalamus and caudate. These structural changes occurring within only 4–6 weeks after delivery are reflective of a high degree of neuroplasticity and massive adaptations in the maternal brain. They may suggest a restoration of brain tissue following pregnancy and/or a substantial brain reorganization, possibly to accommodate a multi-faceted repertoire of complex behaviors associated with being a mother.
•Brains at late postpartum were estimated to be younger than at early postpartum.•On average, that difference was about five years.•These findings suggest a substantial restoration/rejuvenation ...effect after giving birth.•The effect seems to be already evident within 4–6 weeks postpartum.
Pregnancy is accompanied by complex biological adaptations, including extreme hormonal fluctuations. Moreover, changes on the endocrine level are accompanied by changes in cerebral anatomy, such as reductions in brain or gray matter volume. Since declining brain and tissue volumes are characteristic for normal aging, the question arises of whether such pregnancy-induced anatomical effects are permanent or transient. To answer this question, we acquired high-resolution brain image data of 14 healthy women in their mid-twenties to late thirties at two time points: within 1–2 days of childbirth (early postpartum) and at 4–6 weeks after childbirth (late postpartum). At both time points, we estimated the brain ages for each woman using a well-validated machine learning approach based on pattern recognition. Ultimately, this algorithm – designed to identify anatomical correlates of age across the entire brain – reveals a single score for each individual: the BrainAGE index. Comparing the BrainAGE indices between both time points, female brains at late postpartum were estimated to be considerably younger than at early postpartum. On average, that difference was about five years (mean ± SD: 5.4 ± 2.4 years). These findings suggest a substantial restoration/rejuvenation effect after giving birth, which is evident already within the first couple of months.
Abstract
In recent years, replicability of neuroscientific findings, specifically those concerning correlates of morphological properties of gray matter (GM), have been subject of major scrutiny. Use ...of different processing pipelines and differences in their estimates of the macroscale GM may play an important role in this context. To address this issue, here, we investigated the cortical thickness estimates of three widely used pipelines. Based on analyses in two independent large-scale cohorts, we report high levels of within-pipeline reliability of the absolute cortical thickness-estimates and comparable spatial patterns of cortical thickness-estimates across all pipelines. Within each individual, absolute regional thickness differed between pipelines, indicating that in-vivo thickness measurements are only a proxy of actual thickness of the cortex, which shall only be compared within the same software package and thickness estimation technique. However, at group level, cortical thickness-estimates correlated strongly between pipelines, in most brain regions. The smallest between-pipeline correlations were observed in para-limbic areas and insula. These regions also demonstrated the highest interindividual variability and the lowest reliability of cortical thickness-estimates within each pipeline, suggesting that structural variations within these regions should be interpreted with caution.
Lifestyle may be one source of unexplained variance in the great interindividual variability of the brain in age-related structural differences. While physical and social activity may protect against ...structural decline, other lifestyle behaviors may be accelerating factors. We examined whether riskier lifestyle correlates with accelerated brain aging using the BrainAGE score in 622 older adults from the 1000BRAINS cohort. Lifestyle was measured using a combined lifestyle risk score, composed of risk (smoking, alcohol intake) and protective variables (social integration and physical activity). We estimated individual BrainAGE from T1-weighted MRI data indicating accelerated brain atrophy by higher values. Then, the effect of combined lifestyle risk and individual lifestyle variables was regressed against BrainAGE. One unit increase in combined lifestyle risk predicted 5.04 months of additional BrainAGE. This prediction was driven by smoking (0.6 additional months of BrainAGE per pack-year) and physical activity (0.55 less months in BrainAGE per metabolic equivalent). Stratification by sex revealed a stronger association between physical activity and BrainAGE in males than females. Overall, our observations may be helpful with regard to lifestyle-related tailored prevention measures that slow changes in brain structure in older adults.
Abstract Bipolar disorder and schizophrenia share phenotypic and genotypic features, but might differ in aspects of abnormal neurodevelopmental trajectories. We studied gyrification, a marker of ...early developmental pathology, in high-resolution MRI scans of 34 patients with schizophrenia, 17 euthymic bipolar I disorder patients with previous psychotic symptoms, and 34 matched healthy controls in order to test the hypothesis of overlapping and diverging prefrontal gyrification abnormalities. We applied a novel, validated method for measuring local gyrification in each vertex point of the reconstructed cortical surface. Psychotic bipolar I patients had higher gyrification in dorsal anterior and infragenual cingulate cortex compared to either schizophrenia or healthy controls, while schizophrenia patients had higher gyrification than controls in anterior medial (BA 10) and orbitofrontal areas, altogether indicating disease-specific alterations in the prefrontal cortex. Our findings indicate gyrification changes in a specific subgroup of bipolar I disorder to affect an area relevant to emotion regulation, and distinct from changes seen in schizophrenia.
•Perception learning causes a transient increase in brain grey matter volume detectable by MRI.•This learning results in pronounced changes of neuronal dendrites and an increase in the number of ...dendritic spines.•Structural neuronal plasticity is associated with a reorganization and transient swelling of astrocytes.•Brain volume and astrocyte volume return to baseline post-learning, with a persistent increase in the number of mature spines.
Volumetric magnetic resonance imaging studies have shown that intense learning can be associated with grey matter volume increases in the adult brain. The underlying mechanisms are poorly understood. Here we used monocular deprivation in rats to analyze the mechanisms underlying use-dependent grey matter increases. Optometry for quantification of visual acuity was combined with volumetric magnetic resonance imaging and microscopic techniques in longitudinal and cross-sectional studies. We found an increased spatial vision of the open eye which was associated with a transient increase in the volumes of the contralateral visual and lateral entorhinal cortex. In these brain areas dendrites of neurons elongated, and there was a strong increase in the number of spines, the targets of synapses, which was followed by spine maturation and partial pruning. Astrocytes displayed a transient pronounced swelling and underwent a reorganization of their processes. The use-dependent increase in grey matter corresponded predominantly to the swelling of the astrocytes. Experience-dependent increase in brain grey matter volume indicates a gain of structure plasticity with both synaptic and astrocyte remodeling.
Brain morphological changes are among the best-studied potential endophenotypes in schizophrenia and linked to genetic liability and expression of disease phenotype. Yet, there is considerable ...heterogeneity across individual subjects making its use as a disease-specific marker difficult. In this study we consider psychopathological variability of disease phenotype to delineate subsyndromes of schizophrenia, link them to distinct brain morphological patterns, and use a classification approach to test specificity of achieved discrimination. We first applied voxel-based morphometry (VBM) to compare 99 patients with DSM-IV schizophrenia (stable psychopathology and antipsychotic medication) with 113 matched healthy controls, then delineated three subgroups within the patient cohort based on psychopathology pattern and compared differential patterns of grey matter abnormalities. Finally, we tested accuracy of assigning any individual MRI scan to either the control group or any of the three patient subgroups. While VBM analysis showed overlap of brain structural deficits mostly in prefrontal areas, the disorganised subsyndrome showed stronger deficits in medial temporal and cerebellar regions, the paranoid/hallucinatory subsyndrome showed additional effects in the superior temporal cortex, and the negative subsyndrome showed stronger deficits in the thalamus. Using an automated algorithm, we achieved 95.8% accuracy classifying any given scan to one of the subgroups. Patterns of psychopathology are meaningful parameters in reducing heterogeneity of brain morphological endophenotypes in schizophrenia.
Case-control studies in major depression have established patterns of regional gray matter loss, including the hippocampus, which might show state-related effects dependent on disease stage. However, ...there is still limited knowledge on compensation effects that might occur in people resilient to depression showing only subclinical symptoms. We used voxel-based morphometry on a multicenter data set of 409 healthy nonclinical subjects to test the hypothesis that local hippocampal volume would be inversely correlated with subclinical depressive symptoms Symptom Checklist 90-Revised (SCL-90-R) depression scores. Our region-of-interest results show a significant (
= 0.042, FWE cluster-level corrected) positive correlation of SCL-90-R scores for depression and a left hippocampus cluster. Additionally, we provide an exploratory finding of gyrification, a surface-based morphometric marker, correlating with a right postcentral gyrus cluster
= 0.031, family-wise error (FWE) cluster-level corrected. Our findings provide first preliminary evidence of an inverse relationship for subjects in the absence of clinical depression and might thus point to processes related to compensation. Similar effects have been observed in remission from major depression and thus deserve further study to evaluate hippocampal volume not only as a state-dependent marker of disease but also of resilience.
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