NeuroImage
-
Randomized Controlled Trial
The impact of "physiological correction" on functional connectivity analysis of pharmacological resting state fMRI.
Growing interest in pharmacological resting state fMRI (RSfMRI) necessitates developing standardized and robust analytical approaches that are insensitive to spurious correlated physiological signals. However, in pharmacological experiments physiological variations constitute an important aspect of the pharmacodynamic/pharmacokinetic profile of drug action; therefore retrospective corrective methods that discard physiological signals as noise may not be suitable. Previously, we have shown that template-based dual regression analysis is a sensitive method for model-free and objective detection of drug-specific effects on functional brain connectivity. ⋯ The impact of RVHRCOR on statistical tests was limited to elimination of both morphine and alcohol effects related to the somatosensory network that consists of insula and cingulate cortex-important structures for autonomic regulation. Although our data do not warrant speculations about neuronal or vascular origins of these effects, these observations raise caution about the implications of physiological 'noise' and the risks of introducing false positives (e.g. increased white matter connectivity) by using generalized physiological correction methods in pharmacological studies. The obvious sensitivity of the posterior part of the default mode network to different correction schemes, underlines the importance of controlling for physiological fluctuations in seed-based functional connectivity analyses.
-
Current resting-state network analysis often looks for coherent spontaneous BOLD signal fluctuations at frequencies below 0.1 Hz in a multiple-minutes scan. However hemodynamic signal variation can occur at a faster rate, causing changes in functional connectivity at a smaller time scale. In this study we proposed to use MREG technique to increase the temporal resolution of resting-state fMRI. ⋯ The aim of the study paradigm was to specifically observe visual and motor resting-state networks. Preliminary results have found corresponding networks at frequencies above 0.1 Hz. These networks at higher frequencies showed better stability in both spatial and temporal dimensions from the sliding-window analysis of the time series, which suggests the potential of using high temporal resolution MREG sequences to track dynamic resting-state networks at sub-minute time scale.
-
Quantitative magnetic susceptibility mapping (QSM) has recently been introduced to provide a novel quantitative and local MRI contrast. However, the anatomical contrast represented by in vivo susceptibility maps has not yet been compared systematically and comprehensively with gradient (recalled) echo (GRE) magnitude, frequency, and R(2)(*) images. Therefore, this study compares high-resolution quantitative susceptibility maps with conventional GRE imaging approaches (magnitude, frequency, R(2)(*)) in healthy individuals at 7 T with respect to anatomic tissue contrast. ⋯ Regression analysis between magnetic susceptibility and R(2)(*) values of WM and GM structures suggested that variations in myelin content cause the overall contrast between gray and white matter on susceptibility maps and that both R(2)(*) and susceptibility values provide linear measures for iron content in GM. In conclusion, quantitative magnetic susceptibility mapping provides a non-invasive and spatially specific contrast that opens the door to the assessment of diseases characterized by variation in iron and/or myelin concentrations. Its ability to reflect anatomy of deep GM structures with superb delineation may be useful for neurosurgical applications.
-
There have been many interpretations of functional connectivity and proposed measures of temporal correlations between BOLD signals across different brain areas. These interpretations yield from many studies on functional connectivity using resting-state fMRI data that have emerged in recent years. However, not all of these studies used the same metrics for quantifying the temporal correlations between brain regions. ⋯ For the present data set, we found greater stability in FC between the second and third sessions (one hour between sessions) compared to the first and second sessions (approximately 11months between sessions). Finally, we report that some of the metrics showed a positive association between strength and stability. In summary, the results presented in this paper suggest important implications when choosing metrics for quantifying and assessing various types of functional connectivity for resting-state fMRI studies.
-
Near-infrared spectroscopy (NIRS) is a promising neuroimaging tool for the study of human cognition. Here, we show that event-related NIRS is able to detect age-related differences in the neural processing in a simple visual Go/NoGo task using a relatively fast (stimulus onset asynchrony approx. 1.4s) event-related design together with a model-based analysis approach. Subjects were healthy young (<30 years) and elderly (>60 years) adults. ⋯ The present study successfully separated the neural correlates of response inhibition from errors of commission/omission and provides data from multiple simultaneously recorded optodes. Furthermore, these results demonstrate the feasibility of using NIRS to investigate neural processes related to aging and dementia, in particular in patients for which other neuroimaging techniques are contraindicated. In the future, functional phenotyping of successful aging in respect to executive performance may be feasible.