Evidence for a gradient within the medial temporal lobes for flexible retrieval under hierarchical task rules.

A fundamental question in memory research is how the hippocampus processes contextual cues to retrieve distinct mnemonic associations. Prior research has emphasized the importance of hippocampal-prefrontal interactions for context-dependent memory. Our fMRI study examined the human medial temporal lobes (MTL) and their prefrontal interactions when retrieving memories associated with hierarchically organized task contexts. Participants learned virtual object-location associations governed by subordinate and superordinate task rules, which could be independently cued to change. On each fMRI trial, participants retrieved the correct object for convergent rule and location contextual information. Results demonstrated that hippocampal activity and hippocampal-prefrontal functional interconnectivity distinguished retrieval under different levels of hierarchically organized task rules. In explicit contrast to the hippocampal tail, anterior (body and head) regions were recruited specifically for superordinate changes in the contextual hierarchy. The hippocampal body also differed in its functional connectivity with the prefrontal cortex for superordinate versus subordinate changes. Our findings demonstrate a gradient in MTL for associative retrieval under changing task rules, and advance understanding of hippocampal-prefrontal interactions that support flexible contextual memory.

Structural brain measures linked to clinical phenotypes in major depression replicate across clinical centres.

Abnormalities in brain structural measures, such as cortical thickness and subcortical volumes, are observed in patients with major depressive disorder (MDD) who also often show heterogeneous clinical features. This study seeks to identify the multivariate associations between structural phenotypes and specific clinical symptoms, a novel area of investigation. T1-weighted magnetic resonance imaging measures were obtained using 3 T scanners for 178 unmedicated depressed patients at four academic medical centres. Cortical thickness and subcortical volumes were determined for the depressed patients and patients' clinical presentation was characterized by 213 item-level clinical measures, which were grouped into several large, homogeneous categories by K-means clustering. The multivariate correlations between structural and cluster-level clinical-feature measures were examined using canonical correlation analysis (CCA) and confirmed with both 5-fold and leave-one-site-out cross-validation. Four broad types of clinical measures were detected based on clustering: an anxious misery composite (composed of item-level depression, anxiety, anhedonia, neuroticism and suicidality scores); positive personality traits (extraversion, openness, agreeableness and conscientiousness); reported history of physical/emotional trauma; and a reported history of sexual abuse. Responses on the item-level anxious misery measures were negatively associated with cortical thickness/subcortical volumes in the limbic system and frontal lobe; reported childhood history of physical/emotional trauma and sexual abuse measures were negatively correlated with entorhinal thickness and left hippocampal volume, respectively. In contrast, the positive traits measures were positively associated with hippocampal and amygdala volumes and cortical thickness of the highly-connected precuneus and cingulate cortex. Our findings suggest that structural brain measures may reflect neurobiological mechanisms underlying MDD features.

Effect of escitalopram dose and treatment duration on CSF Aß levels in healthy older adults: A controlled clinical trial.

OBJECTIVE: To determine whether treatment with escitalopram compared with placebo would lower CSF ß-amyloid 42 (Aß42) levels. RATIONALE: Serotonin signaling suppresses Aß42 in animal models of Alzheimer disease (AD) and young healthy humans. In a prospective study in older adults, we examined dose and treatment duration effects of escitalopram. METHODS: Using lumbar punctures to sample CSF levels before and after a course of escitalopram treatment, cognitively normal older adults (n = 114) were assigned to placebo, 20 mg escitalopram × 2 weeks, 20 mg escitalopram × 8 weeks, or 30 mg escitalopram × 8 weeks; CSF sampled pretreatment and posttreatment and within-subject percent change in Aß42 was used as the primary outcome in subsequent analyses. RESULTS: An overall 9.4% greater reduction in CSF Aß42 was found in escitalopram-treated compared with placebo-treated groups (p < 0.001, 95% confidence interval [CI] 4.9%-14.2%, d = 0.81). Positive baseline Aß status (CSF Aß42 levels <250 pg/mL) was associated with smaller Aß42 reduction (p = 0.006, 95% CI -16.7% to 0.5%, d = -0.52) compared with negative baseline amyloid status (CSF Aß42 levels >250 pg/mL). CONCLUSIONS: Short-term longitudinal doses of escitalopram decreased CSF Aß42 in cognitively normal older adults, the target group for AD prevention. CLINICALTRIALSGOV IDENTIFIER: NCT02161458. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that for cognitively normal older adults, escitalopram decreases CSF Aß42.

Network changes associated with transdiagnostic depressive symptom improvement following cognitive behavioral therapy in MDD and PTSD.

Despite widespread use of cognitive behavioral therapy (CBT) in clinical practice, its mechanisms with respect to brain networks remain sparsely described. In this study, we applied tools from graph theory and network science to better understand the transdiagnostic neural mechanisms of this treatment for depression. A sample of 64 subjects was included in a study of network dynamics: 33 patients (15 MDD, 18 PTSD) received longitudinal fMRI resting state scans before and after 12 weeks of CBT. Depression severity was rated on the Montgomery-Asberg Depression Rating Scale (MADRS). Thirty-one healthy controls were included to determine baseline network roles. Univariate and multivariate regression analyses were conducted on the normalized change scores of within- and between-system connectivity and normalized change score of the MADRS. Penalized regression was used to select a sparse set of predictors in a data-driven manner. Univariate analyses showed greater symptom reduction was associated with an increased functional role of the Ventral Attention (VA) system as an incohesive provincial system (decreased between- and decreased within-system connectivity). Multivariate analyses selected between-system connectivity of the VA system as the most prominent feature associated with depression improvement. Observed VA system changes are interesting in light of brain controllability descriptions: attentional control systems, including the VA system, fall on the boundary between-network communities, and facilitate integration or segregation of diverse cognitive systems. Thus, increasing segregation of the VA system following CBT (decreased between-network connectivity) may result in less contribution of emotional attention to cognitive processes, thereby potentially improving cognitive control.

Structural Differences in Hippocampal and Entorhinal Gray Matter Volume Support Individual Differences in First Person Navigational Ability.

The ability to update position and orientation to reach a goal is crucial to spatial navigation and individuals vary considerably in this ability. The current structural MRI study used voxel-based morphometry (VBM) analysis to relate individual differences in human brain morphology to performance in an active navigation task that relied on updating position and orientation in a landmark-free environment. Goal-directed navigation took place from either a first person perspective, similar to a person walking through the landmark-free environment, or Survey perspective, a bird's eye view. Critically, the first person perspective required a transformation of spatial information from an allocentric into an egocentric reference frame for goal-directed navigation. Significant structural volume correlations in the hippocampus, entorhinal cortex, and thalamus were related to first person navigational accuracy. Our results support the theory that hippocampus, entorhinal cortex, and thalamus are key structures for updating position and orientation during ground-level navigation. Furthermore, the results suggest that morphological differences in these regions underlie individual navigational abilities, providing an important link between animal models of navigation and the variability in human navigation.

Harmonization of cortical thickness measurements across scanners and sites.

With the proliferation of multi-site neuroimaging studies, there is a greater need for handling non-biological variance introduced by differences in MRI scanners and acquisition protocols. Such unwanted sources of variation, which we refer to as "scanner effects", can hinder the detection of imaging features associated with clinical covariates of interest and cause spurious findings. In this paper, we investigate scanner effects in two large multi-site studies on cortical thickness measurements across a total of 11 scanners. We propose a set of tools for visualizing and identifying scanner effects that are generalizable to other modalities. We then propose to use ComBat, a technique adopted from the genomics literature and recently applied to diffusion tensor imaging data, to combine and harmonize cortical thickness values across scanners. We show that ComBat removes unwanted sources of scan variability while simultaneously increasing the power and reproducibility of subsequent statistical analyses. We also show that ComBat is useful for combining imaging data with the goal of studying life-span trajectories in the brain.

Individual Differences in Human Path Integration Abilities Correlate with Gray Matter Volume in Retrosplenial Cortex, Hippocampus, and Medial Prefrontal Cortex.

Humans differ in their individual navigational abilities. These individual differences may exist in part because successful navigation relies on several disparate abilities, which rely on different brain structures. One such navigational capability is path integration, the updating of position and orientation, in which navigators track distances, directions, and locations in space during movement. Although structural differences related to landmark-based navigation have been examined, gray matter volume related to path integration ability has not yet been tested. Here, we examined individual differences in two path integration paradigms: (1) a location tracking task and (2) a task tracking translational and rotational self-motion. Using voxel-based morphometry, we related differences in performance in these path integration tasks to variation in brain morphology in 26 healthy young adults. Performance in the location tracking task positively correlated with individual differences in gray matter volume in three areas critical for path integration: the hippocampus, the retrosplenial cortex, and the medial prefrontal cortex. These regions are consistent with the path integration system known from computational and animal models and provide novel evidence that morphological variability in retrosplenial and medial prefrontal cortices underlies individual differences in human path integration ability. The results for tracking rotational self-motion-but not translation or location-demonstrated that cerebellum gray matter volume correlated with individual performance. Our findings also suggest that these three aspects of path integration are largely independent. Together, the results of this study provide a link between individual abilities and the functional correlates, computational models, and animal models of path integration.

Structural differences in hippocampal and prefrontal gray matter volume support flexible context-dependent navigation ability.

Spatial navigation is a fundamental part of daily life. Humans differ in their individual abilities to flexibly navigate their world, and a critical question is how this variability relates to differences in underlying brain structure. Our experiment examined individual differences in the ability to flexibly navigate routes that overlap with, and must be distinguished from, previously learned trajectories. We related differences in flexible navigation performance to differences in brain morphology in healthy young adults using voxel-based morphometry. Our findings provide novel evidence that individual differences in gray matter volume in the hippocampus and dorsolateral prefrontal cortex correlate with our ability rapidly to learn and flexibly navigate routes through our world.