63 research outputs found
Clusterwise Independent Component Analysis (C-ICA):An R package for clustering subjects based on ICA patterns underlying three-way (brain) data
In many areas of science, like neuroscience, genomics and text mining, several important and challenging research questions imply the study of (subject) heterogeneity present in three-way data. In clinical neuroscience, for example, disclosing differences or heterogeneity between subjects in resting state networks (RSNs) underlying multi-subject fMRI data (i.e., time by voxel by subject three-way data) may advance the subtyping of psychiatric and mental diseases. Recently, the Clusterwise Independent Component Analysis (C-ICA) method was proposed that enables the disclosure of heterogeneity between subjects in RSNs that is present in multi-subject rs-fMRI data [1]. Up to now, however, no publicly available software exists that allows to fit C-ICA to empirical data at hand. The goal of this paper, therefore, is to present the CICA R package, which contains the necessary functions to estimate the C-ICA parameters and to interpret and visualize the analysis output. Further, the package also includes functions to select suitable initial values for the C-ICA model parameters and to determine the optimal number of clusters and components for a given empirical data set (i.e., model selection). The use of the main functions of the package is discussed and demonstrated with simulated data. Herewith, the necessary analytical choices that have to be made by the user (e.g., starting values) are explained and showed step by step. The rich functionality of the package is further illustrated by applying C-ICA to empirical rs-fMRI data from a group of Alzheimer patients and elderly control subjects and to multi-country stock market data. Finally, extensions regarding the C-ICA algorithm and procedures for model selection that could be implemented in future releases of the package are discussed
When I relive a positive me: Vivid autobiographical memories facilitate autonoetic brain activation and enhance mood
Autobiographical memory is vital for our well-being and therefore used in therapeutic interventions. However, not much is known about the (neural) processes by which reliving memories can have beneficial effects. This study investigates what brain activation patterns and memory characteristics facilitate the effectiveness of reliving positive autobiographical memories for mood and sense of self. Particularly, the role of vividness and autonoetic consciousness is studied. Participants (N= 47) with a wide range of trait self-esteem relived neutral and positive memories while their bold responses, experienced vividness of the memory, mood, and state self-esteem were recorded. More vivid memories related to better mood and activation in amygdala, hippocampus and insula,indicative of increased awareness of oneself (i.e., prereflective aspect of autonoetic con-sciousness). Lower vividness was associated with increased activation in the occipital lobe, PCC, and precuneus, indicative of a more distant mode of reliving. While individuals with lower trait self-esteem increased in state self-esteem, they showed less deacti-vation of the lateral occipital cortex during positive memories. In sum, the vividness of the memory seemingly distinguished a more immersed and more distant manner of memory reliving. In particular, when reliving positive memories higher vividness facilitated increased prereflective autonoetic consciousness, which likely is instrumental in boosting mood
Loss of ‘Small-World’ Networks in Alzheimer's Disease: Graph Analysis of fMRI Resting-State Functional Connectivity
BACKGROUND: Local network connectivity disruptions in Alzheimer's disease patients have been found using graph analysis in BOLD fMRI. Other studies using MEG and cortical thickness measures, however, show more global long distance connectivity changes, both in functional and structural imaging data. The form and role of functional connectivity changes thus remains ambiguous. The current study shows more conclusive data on connectivity changes in early AD using graph analysis on resting-state condition fMRI data. METHODOLOGY/PRINCIPAL FINDINGS: 18 mild AD patients and 21 healthy age-matched control subjects without memory complaints were investigated in resting-state condition with MRI at 1.5 Tesla. Functional coupling between brain regions was calculated on the basis of pair-wise synchronizations between regional time-series. Local (cluster coefficient) and global (path length) network measures were quantitatively defined. Compared to controls, the characteristic path length of AD functional networks is closer to the theoretical values of random networks, while no significant differences were found in cluster coefficient. The whole-brain average synchronization does not differ between Alzheimer and healthy control groups. Post-hoc analysis of the regional synchronization reveals increased AD synchronization involving the frontal cortices and generalized decreases located at the parietal and occipital regions. This effectively translates in a global reduction of functional long-distance links between frontal and caudal brain regions. CONCLUSIONS/SIGNIFICANCE: We present evidence of AD-induced changes in global brain functional connectivity specifically affecting long-distance connectivity. This finding is highly relevant for it supports the anterior-posterior disconnection theory and its role in AD. Our results can be interpreted as reflecting the randomization of the brain functional networks in AD, further suggesting a loss of global information integration in disease
Linkage disequilibrium analysis to enable more efficient gene and QTL mapping in apple
BACKGROUND/OBJECTIVE: Overlapping clinical symptoms often complicate differential diagnosis between patients with Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD). Magnetic resonance imaging (MRI) reveals disease specific structural and functional differences that aid in differentiating AD from bvFTD patients. However, the benefit of combining structural and functional connectivity measures to-on a subject-basis-differentiate these dementia-types is not yet known. METHODS: Anatomical, diffusion tensor (DTI), and resting-state functional MRI (rs-fMRI) of 30 patients with early stage AD, 23 with bvFTD, and 35 control subjects were collected and used to calculate measures of structural and functional tissue status. All measures were used separately or selectively combined as predictors for training an elastic net regression classifier. Each classifier's ability to accurately distinguish dementia-types was quantified by calculating the area under the receiver operating characteristic curves (AUC). RESULTS: Highest AUC values for AD and bvFTD discrimination were obtained when mean diffusivity, full correlations between rs-fMRI-derived independent components, and fractional anisotropy (FA) were combined (0.811). Similarly, combining gray matter density (GMD), FA, and rs-fMRI correlations resulted in highest AUC of 0.922 for control and bvFTD classifications. This, however, was not observed for control and AD differentiations. Classifications with GMD (0.940) and a GMD and DTI combination (0.941) resulted in similar AUC values (p = 0.41). CONCLUSION: Combining functional and structural connectivity measures improve dementia-type differentiations and may contribute to more accurate and substantiated differential diagnosis of AD and bvFTD patients. Imaging protocols for differential diagnosis may benefit from also including DTI and rs-fMRI
Glucocorticoids Decrease Hippocampal and Prefrontal Activation during Declarative Memory Retrieval in Young Men
Glucocorticoids (GCs, cortisol in human) are associated with impairments in declarative memory retrieval. Brain regions hypothesized to mediate these effects are the hippocampus and prefrontal cortex (PFC). Our aim was to use fMRI in localizing the effects of GCs during declarative memory retrieval. Therefore, we tested memory retrieval in 21 young healthy males in a randomized placebo-controlled crossover design. Participants encoded word lists containing neutral and emotional words 1Â h prior to ingestion of 20Â mg hydrocortisone. Memory retrieval was tested using an old/new recognition paradigm in a rapid event-related design. It was found that hydrocortisone decreased brain activity in both the hippocampus and PFC during successful retrieval of neutral words. These observations are consistent with previous animal and human studies suggesting that glucocorticoids modulate both hippocampal and prefrontal brain regions that are crucially involved in memory processing
Presymptomatic cognitive and neuroanatomical changes in genetic frontotemporal dementia in the Genetic Frontotemporal dementia Initiative (GENFI) study: A cross-sectional analysis
Background: Frontotemporal dementia is a highly heritable neurodegenerative disorder. In about a third of patients, the disease is caused by autosomal dominant genetic mutations usually in one of three genes: progranulin (. GRN), microtubule-associated protein tau (. MAPT), or chromosome 9 open reading frame 72 (. C9orf72). Findings from studies of other genetic dementias have shown neuroimaging and cognitive changes before symptoms onset, and we aimed to identify whether such changes could be shown in frontotemporal dementia. Methods: We recruited participants to this multicentre study who either were known carriers of a pathogenic mutation in GRN, MAPT, or C9orf72, or were at risk of carrying a mutation because a first-degree relative was a known symptomatic carrier. We calculated time to expected onset as the difference between age at assessment and mean age at onset within the family. Participants underwent a standardised clinical assessment and neuropsychological battery. We did MRI and generated cortical and subcortical volumes using a parcellation of the volumetric T1-weighted scan. We used linear mixed-effects models to examine whether the association of neuropsychology and imaging measures with time to expected onset of symptoms differed between mutation carriers and non-carriers. Findings: Between Jan 30, 2012, and Sept 15, 2013, we recruited participants from 11 research sites in the UK, Italy, the Netherlands, Sweden, and Canada. We analysed data from 220 participants: 118 mutation carriers (40 symptomatic and 78 asymptomatic) and 102 non-carriers. For neuropsychology measures, we noted the earliest significant differences between mutation carriers and non-carriers 5 years before expected onset, when differences were significant for all measures except for tests of immediate recall and verbal fluency. We noted the largest Z score differences between carriers and non-carriers 5 years before expected onset in tests of naming (Boston Naming Test -0·7; SE 0·3) and executive function (Trail Making Test Part B, Digit Span backwards, and Digit Symbol Task, all -0·5, SE 0·2). For imaging measures, we noted differences earliest for the insula (at 10 years before expected symptom onset, mean volume as a percentage of total intracranial volume was 0·80% in mutation carriers and 0·84% in non-carriers; difference -0·04, SE 0·02) followed by the temporal lobe (at 10 years before expected symptom onset, mean volume as a percentage of total intracranial volume 8·1% in mutation carriers and 8·3% in non-carriers; difference -0·2, SE 0·1). Interpretation: Structural imaging and cognitive changes can be identified 5-10 years before expected onset of symptoms in asymptomatic adults at risk of genetic frontotemporal dementia. These findings could help to define biomarkers that can stage presymptomatic disease and track disease progression, which will be important for future therapeutic trials. Funding: Centres of Excellence in Neurodegenerati
Presymptomatic white matter integrity loss in familial frontotemporal dementia in the GENFI cohort
Objective: We aimed to investigate mutation-specific white matter (WM) integrity changes in presymptomatic and symptomatic mutation carriers of the C9orf72, MAPT, and GRN mutations by use of diffusion-weighted imaging within the Genetic Frontotemporal dementia Initiative (GENFI) study. Methods: One hundred and forty mutation carriers (54 C9orf72, 30 MAPT, 56 GRN), 104 presymptomatic and 36 symptomatic, and 115 noncarriers underwent 3T diffusion tensor imaging. Linear mixed effects models were used to examine the association between diffusion parameters and years from estimated symptom onset in C9orf72, MAPT, and GRN mutation carriers versus noncarriers. Post hoc analyses were performed on presymptomatic mutation carriers only, as well as left–right asymmetry analyses on
Maintenance versus manipulation in verbal working memory revisited: an fMRI study
Working memory (WM) is the ability to keep a limited amount of information "on line" for immediate use during short intervals. Verbal WM has been hypothesized to consist of neuroanatomically segregated components, i.e., maintenance (storage, rehearsal, and matching) and manipulation (reordering or updating), corresponding to ventrolateral and dorsolateral prefrontal cortex. Previous imaging studies of maintenance vs manipulation processes in WM have produced inconsistent results, which may have been due to methodological issues such as low statistical power and the use of insertion (subtraction) designs. In the present functional magnetic resonance imaging study we used parametric versions of both a prototypical maintenance task (Sternberg) and a prototypical manipulation task (n-letter back task) in 21 healthy subjects. Increased signal correlated with load common for both tasks was found in bilateral dorsolateral and anterior prefrontal, left ventrolateral prefrontal, and bilateral parietal regions. Workload x task interactions were found in bilateral dorsolateral prefrontal cortex for manipulation vs maintenance, but also for responding vs encoding (storage) in the maintenance task. Therefore, our data support a functional rather than a neuroanatomical distinction between maintenance and manipulation, given our finding that these tasks differentially activate virtually identical system
Delayed rather than decreased BOLD response as a marker for early Alzheimer's disease
Functional MRI (fMRI) in established Alzheimer's disease (AD) shows regionally altered blood oxygenation level dependent (BOLD) responses. Mild cognitive impairment (MCI) is thought to represent an intermediate state between health and early Alzheimer's disease. To study this probable early dementia stage pathology, we studied in detail the BOLD response in MCI during visual encoding. 28 MCI patients, 18 AD patients, and 41 healthy elderly controls performed a face encoding task during fMRI scanning. Data were analyzed using orthogonal regressors, each representing different phases of the BOLD response (from slow to fast). Using a mixed effects model, regressor x group interactions were analyzed applying P < 0.05, corrected. In occipital regions, MCI patients could be distinguished significantly better from controls and AD patients with a regressor of the early phase of the (fast) BOLD response than with the regressor of the late (slow) BOLD phase. Occipitally, the early phase BOLD response was significantly diminished in MCI patients compared to controls, and significantly increased when compared to AD. AD patients showed diminished early phase activation in widespread regions throughout the brain when compared to controls. There were no differences in the late (slow) phase of the BOLD response. This study stresses the importance of analyzing early phase BOLD responses and not only using one model of the BOLD response in neurodegenerative diseases. The increasing delay of the BOLD response from controls to MCI to AD may be consistent with the idea that MCI is a transitional state between healthy aging and dementia. Analyzing differences in different phases of the BOLD response introduces new opportunities to understand changes in regional brain dynamics in MCI and how well this may serve as an early marker of AD pathology
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