Search results for "default mode"

Comparison of Functional Network Connectivity and Granger Causality for Resting State fMRI Data

2017

Functional network connectivity (FNC) and Granger causality have been widely used to identify functional and effective connectivity for resting functional magnetic resonance imaging (fMRI) data. However, the relationship between these two approaches is still unclear, making it difficult to compare results. In this study, we investigate the relationship by constraining the FNC lags and the causality coherences for analyzing resting state fMRI data. The two techniques were applied respectively to examine the connectivity within default mode network related components extracted by group independent component analysis. The results show that FNC and Granger causality provide complementary result…

Neurobiological foundations of multisensory processing integration in people with autism spectrum disorders: The role of the medial prefrontal cortex

2014

This review aims to relate the sensory processing problems in people with Autism spectrum disorders (ASD), especially Multisensory interaction (MSI), to the role of the medial prefrontal cortex (mPFC) by exploring neuroanatomical findings; brain connectivity and Default Network (DN); global or locally directed attention; and temporal multisensory binding. The mPFC is part of the brain’s DN, which is deactivated when attention is focused on a particular task and activated on rest when spontaneous cognition emerges. In those with ASD, it is hypoactive and the higher the social impairment the greater the atypical activity. With an immature DN, cross-modal integration is impaired, resulting in …

Questions and controversies in the study of time-varying functional connectivity in resting fMRI.

2020

The brain is a complex, multiscale dynamical system composed of many interacting regions. Knowledge of the spatiotemporal organization of these interactions is critical for establishing a solid understanding of the brain’s functional architecture and the relationship between neural dynamics and cognition in health and disease. The possibility of studying these dynamics through careful analysis of neuroimaging data has catalyzed substantial interest in methods that estimate time-resolved fluctuations in functional connectivity (often referred to as “dynamic” or time-varying functional connectivity; TVFC). At the same time, debates have emerged regarding the application of TVFC analyses to re…

Effects of Transcranial Direct Current Stimulation on Brain Networks Related to Creative Thinking

2020

AbstractHuman creative thinking is unique and capable of generating novel and valuable ideas. Recent research has clarified the contribution of different brain networks (default mode network, DN; executive control network; salience network) to creative thinking. However, the effects of brain stimulation on brain networks during creative thinking and on creative performance have not been clarified. The present study was designed to examine the changes in functional connectivity (FC) and effective connectivity (EC) of the large-scale brain network, and the ensuing changes in creative performance, induced by transcranial direct current stimulation (tDCS). Fourteen healthy male students underwe…

DEFAULT MODE NETWORK AND WORKING MEMORY NETWORK DURING AN FMRI WORKING MEMORY TASK: DIFFERENCES AND CORRELATIONS WITH BEHAVIORAL PERFORMANCE

2013

INTRODUCTION Previous neuroimaging studies have shown that working memory load has marked effects on regional neural activation[1-5]. However, the mechanism through which working memory load modulates brain connectivity is still unclear. During a working memory task, two of the most involved networks are the default mode network (DMN) and the working memory network (WMN)[6-7]: the selective focus on these networks can be useful in better understanding the load effects. Spatial independent component analysis (ICA)[8] has becomes a reliable technique to investigate the networks involved during an fMRI task, as it extracts spatiotemporal patterns of neural activity maximizing spatial independe…

Classification of Schizophrenia Patients and Healthy Controls Using ICA of Complex-Valued fMRI Data and Convolutional Neural Networks

2019

Deep learning has contributed greatly to functional magnetic resonance imaging (fMRI) analysis, however, spatial maps derived from fMRI data by independent component analysis (ICA), as promising biomarkers, have rarely been directly used to perform individualized diagnosis. As such, this study proposes a novel framework combining ICA and convolutional neural network (CNN) for classifying schizophrenia patients (SZs) and healthy controls (HCs). ICA is first used to obtain components of interest which have been previously implicated in schizophrenia. Functionally informative slices of these components are then selected and labelled. CNN is finally employed to learn hierarchical diagnostic fea…

2014

Bipolar disorder is characterized by a functional imbalance between hyperactive ventral/limbic areas and hypoactive dorsal/cognitive brain regions potentially contributing to affective and cognitive symptoms. Resting-state studies in bipolar disorder have identified abnormal functional connectivity between these brain regions. However, most of these studies used a seed-based approach, thus restricting the number of regions that were analyzed. Using data-driven approaches, researchers identified resting state networks whose spatial maps overlap with frontolimbic areas such as the default mode network, the frontoparietal networks, the salient network, and the meso/paralimbic network. These ne…

Cognitive benefits of exercise interventions: an fMRI activation likelihood estimation meta-analysis.

2021

Despite a growing number of functional MRI studies reporting exercise-induced changes during cognitive processing, a systematic determination of the underlying neurobiological pathways is currently lacking. To this end, our neuroimaging meta-analysis included 20 studies and investigated the influence of physical exercise on cognition-related functional brain activation. The overall meta-analysis encompassing all experiments revealed physical exercise-induced changes in the left parietal lobe during cognitive processing. Subgroup analysis further revealed that in the younger-age group (< 35 years old) physical exercise induced more widespread changes in the right hemisphere, whereas in th…

Neural Mechanisms of Acceptance and Commitment Therapy for Chronic Pain: A Network-Based fMRI Approach

2021

AbstractOver 100 million Americans suffer from chronic pain (CP), which causes more disability than any other medical condition in the U.S. at a cost of $560-$635 billion per year (IOM, 2011). Opioid analgesics are frequently used to treat CP. However, long term use of opioids can cause brain changes such as opioid-induced hyperalgesia that, over time, increase pain sensation. Also, opioids fail to treat complex psychological factors that worsen pain-related disability, including beliefs about and emotional responses to pain. Cognitive behavioral therapy (CBT) can be efficacious for CP. However, CBT generally does not focus on important factors needed for long-term functional improvement, i…

Spatial source phase : A new feature for identifying spatial differences based on complex-valued resting-state fMRI data

2019

Spatial source phase, the phase information of spatial maps extracted from functional magnetic resonance imaging (fMRI) data by data‐driven methods such as independent component analysis (ICA), has rarely been studied. While the observed phase has been shown to convey unique brain information, the role of spatial source phase in representing the intrinsic activity of the brain is yet not clear. This study explores the spatial source phase for identifying spatial differences between patients with schizophrenia (SZs) and healthy controls (HCs) using complex‐valued resting‐state fMRI data from 82 individuals. ICA is first applied to preprocess fMRI data, and post‐ICA phase de‐ambiguity and den…