Search results for "default mode network"
showing 10 items of 29 documents
Testing different ICA algorithms and connectivity analyses on MS patients.
2015
Multiple sclerosis (MS) is a progressive neurological disorder that affects the central nervous system. Functional magnetic resonance imaging (fMRI) has been employed to track the course and disease progression in patients with MS. The two main aims of this study were to apply in a data-driven approach the independent component analysis (ICA) in the spatial domain to depict the active sources and to look at the effective connectivity between the identified spatial sources. Several ICA algorithms have been proposed for fMRI data analysis. In this study, we aimed to test two well characterized algorithms, namely, the fast ICA and the complex infomax algorithms, followed by two effective conne…
Rethinking clinical decision-making to improve clinical reasoning
2022
Improving clinical reasoning techniques is the right way to facilitate decision-making from prognostic, diagnostic, and therapeutic points of view. However, the process to do that is to fill knowledge gaps by studying and growing experience and knowing some cognitive aspects to raise the awareness of thinking mechanisms to avoid cognitive errors through correct educational training. This article examines clinical approaches and educational gaps in training medical students and young doctors. The authors explore the core elements of clinical reasoning, including metacognition, reasoning errors and cognitive biases, reasoning strategies, and ways to improve decision-making. The article addres…
Comparison of Different Hypotheses Regarding the Spread of Alzheimer’s Disease Using Markov Random Fields and Multimodal Imaging
2018
Alzheimer’s disease (AD) is characterized by a cascade of pathological processes that can be assessed in vivo using different neuroimaging methods. Recent research suggests a systematic sequence of pathogenic events on a global biomarker level, but little is known about the associations and dependencies of distinct lesion patterns on a regional level. Markov random fields are a probabilistic graphical modeling approach that represent the interaction between individual random variables by an undirected graph. We propose the novel application of this approach to study the interregional associations and dependencies between multimodal imaging markers of AD pathology and to compare different hy…
Cognitive reserve impacts on inter-individual variability in resting-state cerebral metabolism in normal aging
2012
There is a great deal of heterogeneity in the impact of aging on cognition and cerebral functioning. One potential factor contributing to individual differences among the elderly is the cognitive reserve, which designates the partial protection from the deleterious effects of aging that lifetime experience provides. Neuroimaging studies examining task-related activation in elderly people suggested that cognitive reserve takes the form of more efficient use of brain networks and/or greater ability to recruit alternative networks to compensate for age-related cerebral changes. In this exploratory multi-center study, we examined the relationships between cognitive reserve, as measured by educa…
The default mode network and the working memory network are not anti-correlated during all phases of a working memory task
2015
INTRODUCTION:\ud \ud The default mode network and the working memory network are known to be anti-correlated during sustained cognitive processing, in a load-dependent manner. We hypothesized that functional connectivity among nodes of the two networks could be dynamically modulated by task phases across time.\ud METHODS:\ud \ud To address the dynamic links between default mode network and the working memory network, we used a delayed visuo-spatial working memory paradigm, which allowed us to separate three different phases of working memory (encoding, maintenance, and retrieval), and analyzed the functional connectivity during each phase within and between the default mode network and the …
Distributed analysis of simultaneous EEG-fMRI time-series: modeling and interpretation issues
2009
Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) represent brain activity in terms of a reliable anatomical localization and a detailed temporal evolution of neural signals. Simultaneous EEG-fMRI recordings offer the possibility to greatly enrich the significance and the interpretation of the single modality results because the same neural processes are observed from the same brain at the same time. Nonetheless, the different physical nature of the measured signals by the two techniques renders the coupling not always straightforward, especially in cognitive experiments where spatially localized and distributed effects coexist and evolve temporally at different …
The chronnectome of musical beat
2020
Keeping time is fundamental for our everyday existence. Various isochronous activities, such as locomotion, require us to use internal timekeeping. This phenomenon comes into play also in other human pursuits such as dance and music. When listening to music, we spontaneously perceive and predict its beat. The process of beat perception comprises both beat inference and beat maintenance, their relative importance depending on the salience of beat in the music. To study functional connectivity associated with these processes in a naturalistic situation, we used functional magnetic resonance imaging to measure brain responses of participants while they were listening to a piece of music contai…
Large-scale brain networks emerge from dynamic processing of musical timbre, key and rhythm
2012
We investigated the neural underpinnings of timbral, tonal, and rhythmic features of a naturalistic musical stimulus. Participants were scanned with functional Magnetic Resonance Imaging (fMRI) while listening to a stimulus with a rich musical structure, a modern tango. We correlated temporal evolutions of timbral, tonal, and rhythmic features of the stimulus, extracted using acoustic feature extraction procedures, with the fMRI time series. Results corroborate those obtained with controlled stimuli in previous studies and highlight additional areas recruited during musical feature processing. While timbral feature processing was associated with activations in cognitive areas of the cerebel…
Default Mode Network Efficiency Is Correlated With Deficits in Inhibition in Adolescents With Inhalant Use Disorder
2020
It is well established that alterations in cognitive function and damage to brain structures are often found in adolescents who have substance use disorder (SUD). However, deficits in executive cognitive functioning in adolescents related to the vulnerability and consumption of such substances are not well known. In this study, we use graph theoretic analysis to compare the network efficiency in the resting state for three networks---default mode network (DMN), salience network (SN) and fronto-parietal network (FPN)---between inhalant-consuming adolescents and a control group (12 to 17 years old). We analysed whether the efficiency of these functional networks was related to working memory,…
Adaptive independent vector analysis for multi-subject complex-valued fMRI data.
2017
Abstract Background Complex-valued fMRI data can provide additional insights beyond magnitude-only data. However, independent vector analysis (IVA), which has exhibited great potential for group analysis of magnitude-only fMRI data, has rarely been applied to complex-valued fMRI data. The main challenges in this application include the extremely noisy nature and large variability of the source component vector (SCV) distribution. New method To address these challenges, we propose an adaptive fixed-point IVA algorithm for analyzing multiple-subject complex-valued fMRI data. We exploited a multivariate generalized Gaussian distribution (MGGD)- based nonlinear function to match varying SCV dis…