Paulo Marques

A hitchhiker's guide to diffusion tensor imaging

Diffusion Tensor Imaging (DTI) studies are increasingly popular among clinicians and researchers as they provide unique insights into brain network connectivity. However, in order to optimize the use of DTI, several technical and methodological aspects must be factored in. These include decisions on: acquisition protocol, artifact handling, data quality control, reconstruction algorithm, and visualization approaches, and quantitative analysis methodology. Furthermore, the researcher and/or clinician also needs to take into account and decide on the most suited software tool(s) for each stage of the DTI analysis pipeline. Herein, we provide a straightforward hitchhikers guide, covering all of the workflows major stages. Ultimately, this guide will help newcomers navigate the most critical roadblocks in the analysis and further encourage the use of DTI.

Stress Impact on Resting State Brain Networks.

Resting state brain networks (RSNs) are spatially distributed large-scale networks, evidenced by resting state functional magnetic resonance imaging (fMRI) studies. Importantly, RSNs are implicated in several relevant brain functions and present abnormal functional patterns in many neuropsychiatric disorders, for which stress exposure is an established risk factor. Yet, so far, little is known about the effect of stress in the architecture of RSNs, both in resting state conditions or during shift to task performance. Herein we assessed the architecture of the RSNs using functional magnetic resonance imaging (fMRI) in a cohort of participants exposed to prolonged stress (participants that had just finished their long period of preparation for the medical residence selection exam), and respective gender- and age-matched controls (medical students under normal academic activities). Analysis focused on the pattern of activity in resting state conditions and after deactivation. A volumetric estimation of the RSNs was also performed. Data shows that stressed participants displayed greater activation of the default mode (DMN), dorsal attention (DAN), ventral attention (VAN), sensorimotor (SMN), and primary visual (VN) networks than controls. Importantly, stressed participants also evidenced impairments in the deactivation of resting state-networks when compared to controls. These functional changes are paralleled by a constriction of the DMN that is in line with the pattern of brain atrophy observed after stress exposure. These results reveal that stress impacts on activation-deactivation pattern of RSNs, a finding that may underlie stress-induced changes in several dimensions of brain activity.

The Functional Connectome of Cognitive Reserve

Cognitive Reserve (CR) designates the brains capacity to actively cope with insults through a more efficient use of its resources/networks. It was proposed in order to explain the discrepancies between the observed cognitive ability and the expected capacity for an individual. Typical proxies of CR include education and Intelligence Quotient but none totally account for the variability of CR and no study has shown if the brains greater efficiency associated with CR can be measured. We used a validated model to estimate CR from the residual variance in memory and general executive functioning, accounting for both brain anatomical (i.e., gray matter and white matter signal abnormalities volume) and demographic variables (i.e., years of formal education and sex). Functional connectivity (FC) networks and topological properties were explored for associations with CR. Demographic characteristics, mainly accounted by years of formal education, were associated with higher FC, clustering, local efficiency and strength in parietal and occipital regions and greater network transitivity. Higher CR was associated with a greater FC, local efficiency and clustering of occipital regions, strength and centrality of the inferior temporal gyrus and higher global efficiency. Altogether, these findings suggest that education may facilitate the brains ability to form segregated functional groups, reinforcing the view that higher education level triggers more specialized use of neural processing. Additionally, this study demonstrated for the first time that CR is associated with more efficient processing of information in the human brain and reinforces the existence of a fine balance between segregation and integration. Hum Brain Mapp 37:3310–3322, 2016..

A Hitchhiker's guide to functional magnetic resonance imaging

Functional Magnetic Resonance Imaging (fMRI) studies have become increasingly popular both with clinicians and researchers as they are capable of providing unique insights into brain functions. However, multiple technical considerations (ranging from specifics of paradigm design to imaging artifacts, complex protocol definition, and multitude of processing and methods of analysis, as well as intrinsic methodological limitations) must be considered and addressed in order to optimize fMRI analysis and to arrive at the most accurate and grounded interpretation of the data. In practice, the researcher/clinician must choose, from many available options, the most suitable software tool for each stage of the fMRI analysis pipeline. Herein we provide a straightforward guide designed to address, for each of the major stages, the techniques, and tools involved in the process. We have developed this guide both to help those new to the technique to overcome the most critical difficulties in its use, as well as to serve as a resource for the neuroimaging community.

Plasticity of resting state brain networks in recovery from stress

Chronic stress has been widely reported to have deleterious impact in multiple biological systems. Specifically, structural and functional remodeling of several brain regions following prolonged stress exposure have been described; importantly, some of these changes are eventually reversible. Recently, we showed the impact of stress on resting state networks (RSNs), but nothing is known about the plasticity of RSNs after recovery from stress. Herein, we examined the “plasticity” of RSNs, both at functional and structural levels, by comparing the same individuals before and after recovery from the exposure to chronic stress; results were also contrasted with a control group. Here we show that the stressed individuals after recovery displayed a decreased resting functional connectivity in the default mode network (DMN), ventral attention network (VAN), and sensorimotor network (SMN) when compared to themselves immediately after stress; however, this functional plastic recovery was only partial as when compared with the control group, as there were still areas of increased connectivity in dorsal attention network (DAN), SMN and primary visual network (VN) in participants recovered from stress. Data also shows that participants after recovery from stress displayed increased deactivations in DMN, SMN, and auditory network (AN), to levels similar to those of controls, showing a normalization of the deactivation pattern in RSNs after recovery from stress. In contrast, structural changes (volumetry) of the brain areas involving these networks are absent after the recovery period. These results reveal plastic phenomena in specific RSNs and a functional remodeling of the activation-deactivation pattern following recovery from chronic-stress, which is not accompanied by significant structural plasticity.

The Bounds Of Education In The Human Brain Connectome

Inter-individual heterogeneity is evident in aging; education level is known to contribute for this heterogeneity. Using a cross-sectional study design and network inference applied to resting-state fMRI data, we show that aging was associated with decreased functional connectivity in a large cortical network. On the other hand, education level, as measured by years of formal education, produced an opposite effect on the long-term. These results demonstrate the increased brain efficiency in individuals with higher education level that may mitigate the impact of age on brain functional connectivity.

BrainCAT - a tool for automated and combined functional magnetic resonance imaging and diffusion tensor imaging brain connectivity analysis

Multimodal neuroimaging studies have recently become a trend in the neuroimaging field and are certainly a standard for the future. Brain connectivity studies combining functional activation patterns using resting-state or task-related functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) tractography have growing popularity. However, there is a scarcity of solutions to perform optimized, intuitive, and consistent multimodal fMRI/DTI studies. Here we propose a new tool, brain connectivity analysis tool (BrainCAT), for an automated and standard multimodal analysis of combined fMRI/DTI data, using freely available tools. With a friendly graphical user interface, BrainCAT aims to make data processing easier and faster, implementing a fully automated data processing pipeline and minimizing the need for user intervention, which hopefully will expand the use of combined fMRI/DTI studies. Its validity was tested in an aging study of the default mode network (DMN) white matter connectivity. The results evidenced the cingulum bundle as the structural connector of the precuneus/posterior cingulate cortex and the medial frontal cortex, regions of the DMN. Moreover, mean fractional anisotropy (FA) values along the cingulum extracted with BrainCAT showed a strong correlation with FA values from the manual selection of the same bundle. Taken together, these results provide evidence that BrainCAT is suitable for these analyses.

The neural correlates of obsessive-compulsive disorder: a multimodal perspective

Obsessive-compulsive disorder (OCD) is one of the most debilitating psychiatric conditions. An extensive body of the literature has described some of the neurobiological mechanisms underlying the core manifestations of the disorder. Nevertheless, most reports have focused on individual modalities of structural/functional brain alterations, mainly through targeted approaches, thus possibly precluding the power of unbiased exploratory approaches. Eighty subjects (40 OCD and 40 healthy controls) participated in a multimodal magnetic resonance imaging (MRI) investigation, integrating structural and functional data. Voxel-based morphometry analysis was conducted to compare between-group volumetric differences. The whole-brain functional connectome, derived from resting-state functional connectivity (FC), was analyzed with the network-based statistic methodology. Results from structural and functional analysis were integrated in mediation models. OCD patients revealed volumetric reductions in the right superior temporal sulcus. Patients had significantly decreased FC in two distinct subnetworks: the first, involving the orbitofrontal cortex, temporal poles and the subgenual anterior cingulate cortex; the second, comprising the lingual and postcentral gyri. On the opposite, a network formed by connections between thalamic and occipital regions had significantly increased FC in patients. Integrative models revealed direct and indirect associations between volumetric alterations and FC networks. This study suggests that OCD patients display alterations in brain structure and FC, involving complex networks of brain regions. Furthermore, we provided evidence for direct and indirect associations between structural and functional alterations representing complex patterns of interactions between separate brain regions, which may be of upmost relevance for explaining the pathophysiology of the disorder.

Structural laterality is associated with cognitive and mood outcomes: An assessment of 105 healthy aged volunteers

Abstract The human brain presents multiple asymmetries that dynamically change throughout life. These phenomena have been associated with cognitive impairments and psychiatric disorders although possible associations with specific patterns of cognitive aging are yet to be determined. We have therefore mapped and quantified morphological asymmetries in a heterogeneous and aged population (65.2±8.0 years old, 52 male and 53 female) to explore potential associations between the asymmetries in specific brain regions and cognitive performance. The sample was characterized in a battery of neuropsychological tests and in terms of brain structural asymmetries using a ROI‐based approach. A substantial number of brain areas presented some degree of asymmetry. Such biases survived a stringent statistical correction and were largely confirmed in a voxel‐based analysis. In specific brain areas, like the thalamus and insula, asymmetry was correlated with cognition and mood descriptors as the Stroop words/colors test or depressive mood scale, respectively. Curiously in the latter, the association was independent of its left/right direction. Altogether, results reveal that asymmetry is widespread in the aged brain and that area‐specific biases (degree and direction) associate with the functional profile of the individual. Graphical abstract Figure. No caption available. HighlightsThe aged brain presents ubiquitous structural asymmetries.Age, education and cognitive performance group do not influence asymmetries.Sex affects laterality only in the fusiform gyrus.In specific brain areas (a)symmetry associates with cognitive and mood outcomes.Cognition is better explained by laterality than by absolute left or right volumes.

Central autonomic nervous system response to autonomic challenges is altered in patients with a previous episode of Takotsubo Cardiomyopathy

Aims: Takotsubo cardiomyopathy is an intriguing disease characterized by acute transient left ventricular dysfunction usually triggered by an episode of severe stress. The excessive levels of catecholamines and the overactivation of the sympathetic system are believed to be the main pathophysiologic mechanisms of Takotsubo cardiomyopathy, but it is unclear whether there is a structural or functional signature of the disease. In this sense, our aim was to characterize the central autonomic system response to autonomic challenges in patients with a previous episode of Takotsubo cardiomyopathy when compared with a control group of healthy volunteers. Methods and results: Functional magnetic resonance imaging (fMRI) was performed in four patients with a previous episode of Takotsubo cardiomyopathy (average age of 67±12 years) and in eight healthy volunteers (average age of 66±5 years) while being submitted to different autonomic challenges (cold exposure and Valsalva manoeuvre). The fMRI analysis revealed a significant variation of the blood oxygen level dependent signal triggered by the Valsalva manoeuvre in specific areas of the brain involved in the cortical control of the autonomic system and significant differences in the pattern of activation of the insular cortex, amygdala and the right hippocampus between patients with Takotsubo cardiomyopathy and controls, even though these regions did not present significant volumetric changes. Conclusion: The central autonomic response to autonomic challenges is altered in patients with Takotsubo cardiomyopathy, thus suggesting a dysregulation of the central autonomic nervous system network. Subsequent studies are needed to unveil whether these alterations are causal or predisposing factors to Takotsubo cardiomyopathy.