Functional connectivity in behavioral variant frontotemporal dementia

INTRODUCTION

Functional connectivity (FC)-which reflects relationships between neural activity in different brain regions-has been used to explore the functional architecture of the brain in neurodegenerative disorders. Although an increasing number of studies have explored FC changes in behavioral variant frontotemporal dementia (bvFTD), there is no focused, in-depth review about FC in bvFTD.

METHODS

Comprehensive literature search and narrative review to summarize the current field of FC in bvFTD.

RESULTS

(1) Decreased FC within the salience network (SN) is the most consistent finding in bvFTD; (2) FC changes extend beyond the SN and affect the interplay between networks; (3) results within the Default Mode Network are mixed; (4) the brain as a network is less interconnected and less efficient in bvFTD; (5) symptoms, functional impairment, and cognition are associated with FC; and (6) the functional architecture resembles patterns of neuropathological spread.

CONCLUSIONS

FC has potential as a biomarker, and future studies are expected to advance the field with multicentric initiatives, longitudinal designs, and methodological advances.

Mnemonic strategy training modulates functional connectivity at rest in mild cognitive impairment: Results from a randomized controlled trial

INTRODUCTION

Mnemonic strategy training (MST) has been shown to improve cognitive performance and increase brain activation in those with mild cognitive impairment (MCI). However, little is known regarding the effects of MST on functional connectivity (FC) at rest. The aim of the present study was to investigate the MST focused on face-name associations effect on resting-state FC in those with MCI.

METHODS

Twenty-six amnestic MCI participants were randomized in MST (N = 14) and Education Program (active control; N = 12). Interventions occurred twice a week over two consecutive weeks (ie, four sessions). Resting-state functional magnetic resonance imaging was collected at pre- and post-intervention. Regions of interest (ROIs) were selected based on areas that previously showed task-related activation changes after MST. Changes were examined through ROI-to-ROI analysis and significant results were corrected for multiple comparisons.

RESULTS

At post-intervention, only the MST group showed increased FC, whereas the control group showed decreased or no change in FC. After MST, there was an increased FC between the left middle temporal gyrus and right orbitofrontal cortex. In addition, a time-by-group interaction indicated that the MST group showed greater increased FC between the right inferior frontal gyrus and left brain regions, such as fusiform gyrus, temporal pole, and orbitofrontal cortex relative to controls.

DISCUSSION

MST enhanced FC in regions that are functionally relevant for the training; however, not in all ROIs investigated. Our findings suggest that MST-induced changes are reflected in task-specific conditions, as previously reported, but also in general innate connectivity. Our results both enhance knowledge about the mechanisms underlying MST effects and may provide neurophysiological evidence of training transfer.

Selecting the most relevant brain regions to discriminate Alzheimer's disease patients from healthy controls using multiple kernel learning: A comparison across functional and structural imaging modalities and atlases

BACKGROUND

Machine learning techniques such as support vector machine (SVM) have been applied recently in order to accurately classify individuals with neuropsychiatric disorders such as Alzheimer's disease (AD) based on neuroimaging data. However, the multivariate nature of the SVM approach often precludes the identification of the brain regions that contribute most to classification accuracy. Multiple kernel learning (MKL) is a sparse machine learning method that allows the identification of the most relevant sources for the classification. By parcelating the brain into regions of interest (ROI) it is possible to use each ROI as a source to MKL (ROI-MKL).

METHODS

We applied MKL to multimodal neuroimaging data in order to: 1) compare the diagnostic performance of ROI-MKL and whole-brain SVM in discriminating patients with AD from demographically matched healthy controls and 2) identify the most relevant brain regions to the classification. We used two atlases (AAL and Brodmann's) to parcelate the brain into ROIs and applied ROI-MKL to structural (T1) MRI, 18F-FDG-PET and regional cerebral blood flow SPECT (rCBF-SPECT) data acquired from the same subjects (20 patients with early AD and 18 controls). In ROI-MKL, each ROI received a weight (ROI-weight) that indicated the region's relevance to the classification. For each ROI, we also calculated whether there was a predominance of voxels indicating decreased or increased regional activity (for 18F-FDG-PET and rCBF-SPECT) or volume (for T1-MRI) in AD patients.

RESULTS

Compared to whole-brain SVM, the ROI-MKL approach resulted in better accuracies (with either atlas) for classification using 18F-FDG-PET (92.5% accuracy for ROI-MKL versus 84% for whole-brain), but not when using rCBF-SPECT or T1-MRI. Although several cortical and subcortical regions contributed to discrimination, high ROI-weights and predominance of hypometabolism and atrophy were identified specially in medial parietal and temporo-limbic cortical regions. Also, the weight of discrimination due to a pattern of increased voxel-weight values in AD individuals was surprisingly high (ranging from approximately 20% to 40% depending on the imaging modality), located mainly in primary sensorimotor and visual cortices and subcortical nuclei.

CONCLUSION

The MKL-ROI approach highlights the high discriminative weight of a subset of brain regions of known relevance to AD, the selection of which contributes to increased classification accuracy when applied to 18F-FDG-PET data. Moreover, the MKL-ROI approach demonstrates that brain regions typically spared in mild stages of AD also contribute substantially in the individual discrimination of AD patients from controls.

White matter abnormalities associated with Alzheimer's disease and mild cognitive impairment: a critical review of MRI studies

In this article, the authors aim to present a critical review of recent MRI studies addressing white matter (WM) abnormalities in Alzheimer's disease (AD) and mild cognitive impairment (MCI), by searching PubMed and reviewing MRI studies evaluating subjects with AD or MCI using WM volumetric methods, diffusion tensor imaging and assessment of WM hyperintensities. Studies have found that, compared with healthy controls, AD and MCI samples display WM volumetric reductions and diffusion tensor imaging findings suggestive of reduced WM integrity. These changes affect complex networks relevant to episodic memory and other cognitive processes, including fiber connections that directly link medial temporal structures and the corpus callosum. Abnormalities in cortico-cortical and cortico-subcortical WM interconnections are associated with an increased risk of progression from MCI to dementia. It can be concluded that WM abnormalities are detectable in early stages of AD and MCI. Degeneration of WM networks causes disconnection among neural cells and the degree of such changes is related to cognitive decline.

Clinical and demographic differences between voluntary and involuntary psychiatric admissions in a university hospital in Brazil

To assess the frequency of involuntary psychiatric hospitalizations from 2001 to 2008 and to determine associated clinical and socio-demographic characteristics, a retrospective cohort study was conducted. Adult admission data were collected from a university hospital in Brazil. Hospitalizations were classified as voluntary (VH) or involuntary (IH). Groups were compared using chi-square test for categorical variables and Mann-Whitney test for continuous non-parametric variables. The relative risk of certain events was estimated by the odds ratio statistic. Of 2,289 admissions, 13.3% were IH. The proportion of IH increased from 2.5% to 21.2% during the eight year period. IH were more frequently associated with female gender, unmarried status, unemployment, and more than 9 years of schooling. Psychotic symptoms were more common among IH. There were no differences in age, duration of hospitalization, or rate of attendance at first appointment after hospital discharge. Understanding of the characteristics associated with IH is necessary to improve the treatment of psychiatric disorders.

Resting-state functional connectivity in normal brain aging

The world is aging and, as the elderly population increases, age-related cognitive decline emerges as a major concern. Neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), allow the investigation of the neural bases of age-related cognitive changes in vivo. Typically, fMRI studies map brain activity while subjects perform cognitive tasks, but such paradigms are often difficult to implement on a wider basis. Resting-state fMRI (rs-fMRI) has emerged as an important alternative modality of fMRI data acquisition, during which no specific task is required. Due to such simplicity and the reliability of rs-fMRI data, this modality presents increased feasibility and potential for clinical application in the future. With rs-fMRI, fluctuations in regional brain activity can be detected across separate brain regions and the patterns of intercorrelation between the functioning of these regions are measured, affording quantitative indices of resting-state functional connectivity (RSFC). This review article summarizes the results of recent rs-fMRI studies that have documented a variety of aging-related RSFC changes in the human brain, discusses the neurophysiological hypotheses proposed to interpret such findings, and provides an overview of the future, highly promising perspectives in this field.

Neuroimaging in Alzheimer's disease: current role in clinical practice and potential future applications

'Alzheimer's disease is the most common cause of dementia and its prevalence is expected to increase in the coming years. Therefore, accurate diagnosis is crucial for patients, clinicians and researchers. Neuroimaging techniques have provided invaluable information about Alzheimer's disease and, owing to recent advances, these methods will have an increasingly important role in research and clinical practice. The purpose of this article is to review recent neuroimaging studies of Alzheimer's disease that provide relevant information to clinical practice, including a new modality: in vivo amyloid imaging. Magnetic resonance imaging, single photon emission computed tomography and 18F-fluorodeoxyglucose-positron emission tomography are currently available for clinical use. Patients with suspected Alzheimer's disease are commonly investigated with magnetic resonance imaging because it provides detailed images of brain structure and allows the identification of supportive features for the diagnosis. Neurofunctional techniques such as single photon emission computed tomography and 18F-fluorodeoxyglucose-positron emission tomography can also be used to complement the diagnostic investigation in cases of uncertainty. Amyloid imaging is a non-invasive technique that uses positron emission tomography technology to investigate the accumulation of the β-amyloid peptide in the brain, which is a hallmark of Alzheimer's disease. This is a promising test but currently its use is restricted to very few specialized research centers in the world. Technological innovations will probably increase its availability and reliability, which are the necessary steps to achieve robust clinical applicability. Thus, in the future it is likely that amyloid imaging techniques will be used in the clinical evaluation of patients with Alzheimer's disease.

Cardiac disorders as risk factors for Alzheimer's disease

Vascular risk factors can play an important role in determining the onset of non-genetic Alzheimer's disease (AD). Most cases of AD are sporadic and late-onset, and a complex interaction between genetic predisposition and vascular risk factors has been proposed. Vascular risk factors for AD include stroke, hypertension, diabetes, homocysteine, smoking, hypercholesterolemia, heart failure and atrial fibrillation; it is possible that these can trigger cerebrovascular dysfunction and AD pathology. Explanations for these associations include the coincidence of common disorders in the elderly where vascular and cerebrovascular disease can precipitate AD, implying that the onset of dementia disease is determined by a synergistic combination of risk factors. In this paper we review the role of cardiovascular risk factors in the pathogenesis of AD and discuss the associated brain mechanisms that can underlie the onset of AD. Cardiovascular diseases are a promising avenue of AD research because they are potentially modifiable in early adult life and provide a new perspective for the prevention of dementia.