No evidence for association between late pregnancy maternal cortisol and gray matter volume in a healthy community sample of young adolescents

A compelling amount of animal and human research has shown that perceived maternal stress during pregnancy can affect the neurodevelopment of the offspring. Prenatal maternal cortisol is frequently proposed as the biological key mechanism underlying this link; however, literature that investigates the effects of prenatal cortisol on subsequent neurodevelopment in humans is scarce. By using longitudinal data from a relatively large community sample of mother-child dyads (N = 73), this pre-registered study prospectively examined the role of maternal prenatal cortisol concentrations on subsequent individual differences in gray matter volume (GMV) and hippocampal subfield volumes at the onset of puberty of the offspring (12 years of age). Two markers of cortisol, that is, evening cortisol and circadian decline over the day, were used as indicators of maternal physiological stress during the last trimester of pregnancy. The results indicate that prenatal maternal cortisol levels were not associated with GMV or hippocampal subfield volumes of the children. These findings suggest that late pregnancy maternal cortisol may not be related to the structural development of the offspring’s brain, at least not in healthy community samples and at the onset of puberty. When examining the influence of prenatal stress on offspring neurodevelopment, future investigations should delineate gestational timing effects of the cortisol exposure, cortisol assessment method, and impact of additional biomarkers, as these were not investigated in this study

Depression recurrence is accompanied by longer periods in default mode and more frequent attentional and reward processing dynamic brain-states during resting-state activity

Recurrence in major depressive disorder (MDD) is common, but neurobiological models capturing vulnerability for recurrences are scarce. Disturbances in multiple resting-state networks have been linked to MDD, but most approaches focus on stable (vs. dynamic) network characteristics. We investigated how the brain's dynamical repertoire changes after patients transition from remission to recurrence of a new depressive episode. Sixty two drug-free, MDD-patients with ≥2 episodes underwent a baseline resting-state fMRI scan when in remission. Over 30-months follow-up, 11 patients with a recurrence and 17 matched-remitted MDD-patients without a recurrence underwent a second fMRI scan. Recurrent patterns of functional connectivity were characterized by applying Leading Eigenvector Dynamics Analysis (LEiDA). Differences between baseline and follow-up were identified for the 11 non-remitted patients, while data from the 17 matched-remitted patients was used as a validation dataset. After the transition into a depressive state, basal ganglia-anterior cingulate cortex (ACC) and visuo-attentional networks were detected significantly more often, whereas default mode network activity was found to have a longer duration. Additionally, the fMRI signal in the basal ganglia-ACC areas underlying the reward network, were significantly less synchronized with the rest of the brain after recurrence (compared to a state of remission). No significant changes were observed in the matched-remitted patients who were scanned twice while in remission. These findings characterize changes that may be associated with the transition from remission to recurrence and provide initial evidence of altered dynamical exploration of the brain's repertoire of functional networks when a recurrent depressive episode occurs.</p

Depression recurrence is accompanied by longer periods in default mode and more frequent attentional and reward processing dynamic brain-states during resting-state activity

Recurrence in major depressive disorder (MDD) is common, but neurobiological models capturing vulnerability for recurrences are scarce. Disturbances in multiple resting-state networks have been linked to MDD, but most approaches focus on stable (vs. dynamic) network characteristics. We investigated how the brain's dynamical repertoire changes after patients transition from remission to recurrence of a new depressive episode. Sixty two drug-free, MDD-patients with ≥2 episodes underwent a baseline resting-state fMRI scan when in remission. Over 30-months follow-up, 11 patients with a recurrence and 17 matched-remitted MDD-patients without a recurrence underwent a second fMRI scan. Recurrent patterns of functional connectivity were characterized by applying Leading Eigenvector Dynamics Analysis (LEiDA). Differences between baseline and follow-up were identified for the 11 non-remitted patients, while data from the 17 matched-remitted patients was used as a validation dataset. After the transition into a depressive state, basal ganglia-anterior cingulate cortex (ACC) and visuo-attentional networks were detected significantly more often, whereas default mode network activity was found to have a longer duration. Additionally, the fMRI signal in the basal ganglia-ACC areas underlying the reward network, were significantly less synchronized with the rest of the brain after recurrence (compared to a state of remission). No significant changes were observed in the matched-remitted patients who were scanned twice while in remission. These findings characterize changes that may be associated with the transition from remission to recurrence and provide initial evidence of altered dynamical exploration of the brain's repertoire of functional networks when a recurrent depressive episode occurs.</p

Emotional Biases and Recurrence in Major Depressive Disorder. Results of 2.5 Years Follow-Up of Drug-Free Cohort Vulnerable for Recurrence

An interesting factor explaining recurrence risk in Major Depressive Disorder (MDD) may be neuropsychological functioning, i.e., processing of emotional stimuli/information. Negatively biased processing of emotional stimuli/information has been found in both acute and (inconclusively) remitted states of MDD, and may be causally related to recurrence of depression. We aimed to investigate self-referent, memory and interpretation biases in recurrently depressed patients in remission and relate these biases to recurrence. We included 69 remitted recurrent MDD-patients (rrMDD-patients), 35–65 years, with ≥2 episodes, voluntarily free of antidepressant maintenance therapy for at least 4 weeks. We tested self-referent biases with an emotional categorization task, bias in emotional memory by free recall of the emotion categorization task 15 min after completing it, and interpretation bias with a facial expression recognition task. We compared these participants with 43 never-depressed controls matched for age, sex and intelligence. We followed the rrMDD-patients for 2.5 years and assessed recurrent depressive episodes by structured interview. The rrMDD-patients showed biases toward emotionally negative stimuli, faster responses to negative self-relevant characteristics in the emotional categorization, better recognition of sad faces, worse recognition of neutral faces with more misclassifications as angry or disgusting faces and less misclassifications as neutral faces (0.001 &lt; p &lt; 0.05). Of these, the number of misclassifications as angry and the overall performance in the emotional memory task were significantly associated with the time to recurrence (p ≤ 0.04), independent of residual symptoms and number of previous episodes. In a support vector machine data-driven model, prediction of recurrence-status could best be achieved (relative to observed recurrence-rate) with demographic and childhood adversity parameters (accuracy 78.1%; 1-sided p = 0.002); neuropsychological tests could not improve this prediction. Our data suggests a persisting (mood-incongruent) emotional bias when patients with recurrent depression are in remission. Moreover, these persisting biases might be mechanistically important for recurrence and prevention thereof

Structural brain correlates of childhood inhibited temperament: an ENIGMA-Anxiety Mega-analysis

NWORubicon 019.201SG.022Pathways through Adolescenc

The brain-derived neurotrophic factor Val66Met polymorphism affects encoding of object locations during active navigation

Contains fulltext : 173908.pdf (publisher's version ) (Open Access)The brain-derived neurotrophic factor (BDNF) was shown to be involved in spatial memory and spatial strategy preference. A naturally occurring single nucleotide polymorphism of the BDNF gene (Val66Met) affects activity-dependent secretion of BDNF. The current event-related fMRI study on preselected groups of 'Met' carriers and homozygotes of the 'Val' allele investigated the role of this polymorphism on encoding and retrieval in a virtual navigation task in thirty-seven healthy volunteers. In each trial, participants navigated towards a target object. During encoding, three positional cues (columns) with directional cues (shadows) were available. During retrieval, the invisible target had to be replaced while either two objects without shadows (objects trial) or one object with a shadow (shadow trial) were available. The experiment consisted of blocks, informing participants of which trial type would be most likely to occur during retrieval. We observed no differences between genetic groups in task performance or time to complete the navigation tasks. The imaging results show that Met carriers compared to Val homozygotes activate the left hippocampus more during successful object location memory encoding. The observed effects were independent of non-significant performance differences or volumetric differences in the hippocampus. These results indicate that variations of the BDNF gene affect memory encoding during spatial navigation, suggesting that lower levels of BDNF in the hippocampus results in less efficient spatial memory processing.11 p

Dataset corresponding to "Investigation of the stability of human freezing-like responses to social threat from mid to late adolescence": Freezing and stability

The data set contains preprocessed body sway (in mm) and heart rate (in beats-per-minute) data at ages 14 and 17, as well as raw data of life events (assessed at ages 2.5, 5, and 17), state anxiety (assessed at ages 14 and 17), participants’ height (at age 17), and attachment (assessed at 15-months of age). This data was used for analyses in the research described in the Frontiers in Behavioral Neuroscience paper by Niermann et al. (2018). The current study tested the stability of freezing-like behavior in a prospective longitudinal study investigation, following 75 adolescents from mid to late adolescence. To assess adolescents’ freezing behavior, we used a well-established method combining electrocardiography (heart rate) and posturography (body sway) in response to emotional picture-viewing of angry, happy, and neutral faces. A full description of the procedure and the measures is given in the Methodology file. The R-syntax files contain a description of data as well as all steps of data analysis that were performed. The results of those analyses are described in the paper