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Background: In the last decade, many studies have reported abnormal connectivity within the default mode network (DMN) in patients with Alzheimer disease. Few studies, however, have investigated other networks and their association with pathophysiological proteins obtained from cerebrospinal fluid (CSF). Methods: We performed 3 T imaging in patients with mild Alzheimer disease, patients with amnestic mild cognitive impairment (aMCI) and healthy controls, and we collected CSF samples from the patients with aMCI and mild Alzheimer disease. We analyzed 57 regions from 8 networks. Additionally, we performed correlation tests to investigate possible associations between the networks’ functional connectivity and the protein levels obtained from the CSF of patients with aMCI and Alzheimer disease. Results: Our sample included 41 patients with Alzheimer disease, 35 with aMCI and 48 controls. We found that the main connectivity abnormalities in those with Alzheimer disease occurred between the DMN and task-positive networks: these patients presented not only a decreased anticorrelation between some regions, but also an inversion of the correlation signal (positive correlation instead of anti-correlation). Those with aMCI did not present statistically different connectivity from patients with Alzheimer disease or controls. Abnormal levels of CSF proteins were associated with functional disconnectivity between several regions in both the aMCI and mild Alzheimer disease groups, extending well beyond the DMN or temporal areas. Limitations: The presented data are cross-sectional in nature, and our findings are dependent on the choice of seed regions used. Conclusion: We found that the main functional connectivity abnormalities occur between the DMN and task-positive networks and that the pathological levels of CSF biomarkers correlate with functional connectivity disruption in patients with Alzheimer disease.

Advanced magnetic resonance imaging (MRI) techniques are improving our understanding of cerebrovascular diseases. Elucidation of the critical pathways in post-stroke recovery would not only provide important fundamental insight in brain function and plasticity but could also lead the way toward development of new rehabilitation strategies for recovering stroke patients. Improvements in hardware and pulse sequences that decrease scan time while maintaining resolution will continue to impact the field. Post-processing strategies must evolve to encompass these increasingly complicated data sets. It also seems clear that multimodal imaging strategies are necessary to develop more detailed patient profiles that can be used for precision medicine.

Depression and anxiety symptoms are common after stroke and associated to reduction in quality of life and poor physical and social outcomes. The Default Mode Network (DMN) plays an important role in the emotional processing. We investigated whether these symptoms are associated to a disruption of DMN functional connectivity in the first month after stroke. Thirty-four subacute ischemic stroke patients were submitted to: 1) behavioral assessment through Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI) and Structured Clinical Interview for DSM Disorders; 2) neuropsychological assessment using Mini Mental State Examination and Montreal Cognitive Assessment; 3) resting state functional magnetic resonance imaging acquisition using a 3 T scanner (Philips Achieva). Patients with depression and/or anxiety symptoms showed an increased DMN functional connectivity in left inferior parietal gyrus and left basal nuclei, when compared to stroke controls. Specific correlation between BDI/BAI scores and DMN functional connectivity indicated that depression symptoms are correlated with increased functional connectivity in left inferior parietal gyrus, while anxiety symptoms are correlated with increased functional connectivity in cerebellum, brainstem and right middle frontal gyrus. Our study provides new insights into the underlying mechanisms of post stroke depression and anxiety, suggesting an alternate explanation other than regional structural damage following ischemic event, that these psychiatric symptoms are related to brain network dysfunction.

Mild cognitive impairment (aMCI) is a clinical condition, with high risk to develop Alzheimer’s disease. Physical exercise may have positive effect on cognition and brain structure in older adults. However, it is still under research whether these influences are true on aMCI subjects with low Ab_42 and high total tau in cerebrospinal fluid (CSF), which is considered a biomarker for AD. Therefore, we aimed to investigate a possible relation between aerobic fitness (AF) and gray matter (GM) volume and AF and white matter (WM) integrity in aMCI with a CSF biomarker. Twenty-two participants with aMCI acquired the images on a 3.0-T MRI. AF was assessed by a graded exercise test on a treadmill. Voxel-based morphometry and tract-based spatial statistic methods were used to analyze the GM volume and WM microstructural integrity, respectively. We correlated AF and GM volume and WM integrity in aMCI (p < 0.05, FWE corrected, cluster with at least five voxels). There was a positive relation between AF and GM volume mostly in frontal superior cortex. In WM integrity, AF was positively correlated with fractional anisotropy and negatively correlated with mean diffusivity and radial diffusivity, all in the same tracts that interconnect frontal, temporal, parietal, and occipital areas (longitudinal fasciculus, fronto-occipital fasciculus, and corpus callosum). These results suggest that aerobic fitness may have a positive influence on protection of brain even in aMCI CSF biomarker, a high-risk population to convert to AD.

Neuropsychological and psychiatric disorders represent a major concern and cause of disabilities after the trauma, contributing to worse recovery after traumatic brain injury (TBI). However, the lack of well-defined parameters to evaluate patient’s psychiatric disorders leads to a wide range of diagnoses and symptoms. The aim of this study was to perform a review of literature in order to gather data of the most common scales and inventories used to assess and diagnose depression, anxiety, and posttraumatic stress disorder (PTSD) after TBI. We conducted a literature search via MEDLINE, PubMed, and Web of Science. We included reviews, systematic reviews, and meta-analysis studies, and we used the following keywords: “traumatic brain injury OR TBI,” “depression OR depressive disorder,” “anxiety,” and “posttraumatic stress disorder OR PTSD.” From 610 titles, a total of 68 systematic reviews or meta-analysis were included in the section “Results” of this review: depression (n = 32), anxiety (n = 9), and PTSD (n = 27). Depression after TBI is a more established condition, with more homogeneous studies. Anxiety and PTSD disorders have been studied in a heterogeneous way, usually as comorbidity with other psychiatric disorders. Some scales and inventories designed for the general community may not be appropriate for patients with TBI.