Ricardo José Silva Magalhães

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.

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.

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.

Abstract Computation in Schizophrenia Detection through Artificial Neural Network Based Systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

White matter changes in microstructure associated with a maladaptive response to stress in rats

In today’s society, every individual is subjected to stressful stimuli with different intensities and duration. This exposure can be a key trigger in several mental illnesses greatly affecting one’s quality of life. Yet not all subjects respond equally to the same stimulus and some are able to better adapt to them delaying the onset of its negative consequences. The neural specificities of this adaptation can be essential to understand the true dynamics of stress as well as to design new approaches to reduce its consequences. In the current work, we employed ex vivo high field diffusion magnetic resonance imaging (MRI) to uncover the differences in white matter properties in the entire brain between Fisher 344 (F344) and Sprague–Dawley (SD) rats, known to present different responses to stress, and to examine the effects of a 2-week repeated inescapable stress paradigm. We applied a tract-based spatial statistics (TBSS) analysis approach to a total of 25 animals. After exposure to stress, SD rats were found to have lower values of corticosterone when compared with F344 rats. Overall, stress was found to lead to an overall increase in fractional anisotropy (FA), on top of a reduction in mean and radial diffusivity (MD and RD) in several white matter bundles of the brain. No effect of strain on the white matter diffusion properties was observed. The strain-by-stress interaction revealed an effect on SD rats in MD, RD and axial diffusivity (AD), with lower diffusion metric levels on stressed animals. These effects were localized on the left side of the brain on the external capsule, corpus callosum, deep cerebral white matter, anterior commissure, endopiriform nucleus, dorsal hippocampus and amygdala fibers. The results possibly reveal an adaptation of the SD strain to the stressful stimuli through synaptic and structural plasticity processes, possibly reflecting learning processes.

Cognitive performance in healthy older adults relates to spontaneous switching between states of functional connectivity during rest

Growing evidence has shown that brain activity at rest slowly wanders through a repertoire of different states, where whole-brain functional connectivity (FC) temporarily settles into distinct FC patterns. Nevertheless, the functional role of resting-state activity remains unclear. Here, we investigate how the switching behavior of resting-state FC relates with cognitive performance in healthy older adults. We analyse resting-state fMRI data from 98 healthy adults previously categorized as being among the best or among the worst performers in a cohort study of >1000 subjects aged 50+ who underwent neuropsychological assessment. We use a novel approach focusing on the dominant FC pattern captured by the leading eigenvector of dynamic FC matrices. Recurrent FC patterns – or states – are detected and characterized in terms of lifetime, probability of occurrence and switching profiles. We find that poorer cognitive performance is associated with weaker FC temporal similarity together with altered switching between FC states. These results provide new evidence linking the switching dynamics of FC during rest with cognitive performance in later life, reinforcing the functional role of resting-state activity for effective cognitive processing.

The association between stress and mood across the adult lifespan on default mode network

Aging of brain structure and function is a complex process characterized by high inter- and intra-individual variability. Such variability may arise from the interaction of multiple factors, including exposure to stressful experience and mood variation, across the lifespan. Using a multimodal neuroimaging and neurocognitive approach, we investigated the association of stress, mood and their interaction, in the structure and function of the default mode network (DMN), both during rest and task-induced deactivation, throughout the adult lifespan. Data confirmed a decreased functional connectivity (FC) and task-induced deactivation of the DMN during the aging process and in subjects with lower mood; on the contrary, an increased FC was observed in subjects with higher perceived stress. Surprisingly, the association of aging with DMN was altered by stress and mood in specific regions. An increased difficulty to deactivate the DMN was noted in older participants with lower mood, contrasting with an increased deactivation in individuals presenting high stress, independently of their mood levels, with aging. Interestingly, this constant interaction across aging was globally most significant in the combination of high stress levels with a more depressed mood state, both during resting state and task-induced deactivations. The present results contribute to characterize the spectrum of FC and deactivation patterns of the DMN, highlighting the crucial association of stress and mood levels, during the adult aging process. These combinatorial approaches may help to understand the heterogeneity of the aging process in brain structure and function and several states that may lead to neuropsychiatric disorders.