A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

Selectively and progressively disrupted structural connectivity of functional brain networks in Alzheimer's disease - revealed by a novel framework to analyze edge distributions of networks detecting disruptions with strong statistical evidence. | LitMetric

Alzheimer's disease (AD) disrupts selectively and progressively (increasing with severity) functional connectivity of intrinsic brain networks (IBNs), most prominent in the default mode network. Given that IBNs' functional connectivity depends on structural connectivity, we hypothesize for our study selective and progressive changes of IBN based structural connectivity in AD. To achieve strong statistical evidence, we introduce a novel statistical method based on the edge frequency distributions of structural connectivity networks. Such non-Gaussian distributions are compared in a multiple testing scheme, combining a flexible nonparametric test statistic with permutation based strong control of the family wise error rate. We assessed 26 healthy elderly, 23 patients with AD-dementia, and 28 patients with mild cognitive impairment (MCI) by resting-state functional MRI, diffusion tensor imaging, and clinical-neuropsychological testing including annual follow-up assessment. After 3years, 50% of the patients with MCI converted to AD. Tractography of diffusion tensor data identifies structural connectivity networks between regions of IBNs, which are detected by an independent component analysis of resting state fMRI data. We find that IBNs' structural connectivity is selectively and progressively disrupted with primary changes in the default mode network. Correspondent results are found for IBNs' functional connectivity. In addition, structural connectivity across the nodes of all IBNs separated individual MCI patients converting to AD from non-converters. Conclusively, our study provides a new approach to analyze connectivity networks by their non-Gaussian edge frequency distributions and achieves strong statistical evidence by application of the family wise error rate. Data analysis provides selective and progressive disruptions of IBN's structural connectivity in AD and demonstrates the increased power of our method compared to recent studies.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.neuroimage.2013.05.011DOI Listing

Publication Analysis

Top Keywords

structural connectivity
32
selectively progressively
12
connectivity
12
strong statistical
12
statistical evidence
12
functional connectivity
12
connectivity networks
12
progressively disrupted
8
structural
8
brain networks
8

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!