Javascript must be enabled to continue!
Graph analysis uncovers an opposing impact of methylphenidate on connectivity patterns within default mode network sub-divisions
View through CrossRef
Abstract
Background
The Default Mode Network (DMN) is a central neural network, with recent evidence indicating that it is composed of functionally distinct sub-networks. Methylphenidate (MPH) administration has been shown before to modulate impulsive behavior, though it is not yet clear whether these effects relate to MPH-induced changes in DMN connectivity. To address this gap, we assessed the impact of MPH administration on functional connectivity patterns within and between distinct DMN sub-networks and tested putative relations to variability in sub-scales of impulsivity.
Methods
Fifty-five right-handed healthy adults underwent two resting-state functional MRI (rs-fMRI) scans, following acute administration of either MPH (20 mg) or placebo, via a randomized double-blind placebo-controlled design. Graph modularity analysis was implemented to fractionate the DMN into distinct sub-networks based on the impact of MPH (vs. placebo) on DMN connectivity patterns with other neural networks.
Results
MPH administration led to an overall decreased DMN connectivity, particularly with the auditory, cinguloopercular, and somatomotor networks, and increased connectivity with the parietomedial network. Graph analysis revealed that the DMN could be fractionated into two distinct sub-networks, with one exhibiting MPH-induced increased connectivity and the other decreased connectivity. Decreased connectivity of the DMN sub-network with the cinguloopercular network following MPH administration was associated with elevated impulsivity and non-planning impulsiveness.
Conclusion
Current findings highlight the intricate effects of MPH administration on DMN rs-fMRI connectivity, uncovering its opposing impact on distinct DMN sub-divisions. MPH-induced dynamics in DMN connectivity patterns with other neural networks may account for some of the effects of MPH administration on impulsive behavior.
Springer Science and Business Media LLC
Title: Graph analysis uncovers an opposing impact of methylphenidate on connectivity patterns within default mode network sub-divisions
Description:
Abstract
Background
The Default Mode Network (DMN) is a central neural network, with recent evidence indicating that it is composed of functionally distinct sub-networks.
Methylphenidate (MPH) administration has been shown before to modulate impulsive behavior, though it is not yet clear whether these effects relate to MPH-induced changes in DMN connectivity.
To address this gap, we assessed the impact of MPH administration on functional connectivity patterns within and between distinct DMN sub-networks and tested putative relations to variability in sub-scales of impulsivity.
Methods
Fifty-five right-handed healthy adults underwent two resting-state functional MRI (rs-fMRI) scans, following acute administration of either MPH (20 mg) or placebo, via a randomized double-blind placebo-controlled design.
Graph modularity analysis was implemented to fractionate the DMN into distinct sub-networks based on the impact of MPH (vs.
placebo) on DMN connectivity patterns with other neural networks.
Results
MPH administration led to an overall decreased DMN connectivity, particularly with the auditory, cinguloopercular, and somatomotor networks, and increased connectivity with the parietomedial network.
Graph analysis revealed that the DMN could be fractionated into two distinct sub-networks, with one exhibiting MPH-induced increased connectivity and the other decreased connectivity.
Decreased connectivity of the DMN sub-network with the cinguloopercular network following MPH administration was associated with elevated impulsivity and non-planning impulsiveness.
Conclusion
Current findings highlight the intricate effects of MPH administration on DMN rs-fMRI connectivity, uncovering its opposing impact on distinct DMN sub-divisions.
MPH-induced dynamics in DMN connectivity patterns with other neural networks may account for some of the effects of MPH administration on impulsive behavior.
Related Results
Searching for the representation of fatigue in the brain
Searching for the representation of fatigue in the brain
This research project was aimed at improving our understanding of the neuronal
mechanism that causes fatigue in patients with a brain tumor.
In chapter one, we aimed to better und...
Methylphenidate-Induced Menorrhagia in Twin Girls
Methylphenidate-Induced Menorrhagia in Twin Girls
Objective: Methylphenidate, a psychostimulant agent, is used in first-line psychopharmacological treatment in children and adolescents with attention-deficit/hyperactivity disorder...
Increased life expectancy of heart failure patients in a rural center by a multidisciplinary program
Increased life expectancy of heart failure patients in a rural center by a multidisciplinary program
Abstract
Funding Acknowledgements
Type of funding sources: None.
INTRODUCTION Patients with heart failure (HF)...
Graph convolutional neural networks for 3D data analysis
Graph convolutional neural networks for 3D data analysis
(English) Deep Learning allows the extraction of complex features directly from raw input data, eliminating the need for hand-crafted features from the classical Machine Learning p...
Pathogenesis-directed therapy of methylphenidate-induced oxidative heart damage in rats
Pathogenesis-directed therapy of methylphenidate-induced oxidative heart damage in rats
AimThe current study aimed to investigate the protective effects of adenosine triphosphate (ATP), metyrosine, and melatonin on possible methylphenidate cardiotoxicity in rats using...
Graph data warehousing
Graph data warehousing
Over the last decade, we have witnessed the emergence of networks in a wide spectrum of application domains, ranging from social and information networks to biological and transpor...
Structure can predict function in the human brain: a graph neural network deep learning model of functional connectivity and centrality based on structural connectivity
Structure can predict function in the human brain: a graph neural network deep learning model of functional connectivity and centrality based on structural connectivity
Abstract
Although functional connectivity and associated graph theory measures (e.g., centrality; how centrally important to the network a region is) are widely u...
Age-dependent effects of methylphenidate in the prefrontal cortex: evidence from electrophysiological and Arc gene expression measurements
Age-dependent effects of methylphenidate in the prefrontal cortex: evidence from electrophysiological and Arc gene expression measurements
Methylphenidate, a drug widely used for attention deficit hyperactivity disorder in children, may affect neuronal function differently in young and adult subjects, particularly in ...

