Search results for " fMRI"
showing 10 items of 83 documents
Action expertise reduces brain activity for audiovisual matching actions: An fMRI study with expert drummers
2011
When we observe someone perform a familiar action, we can usually predict what kind of sound that action will produce. Musical actions are over-experienced by musicians and not by non-musicians, and thus offer a unique way to examine how action expertise affects brain processes when the predictability of the produced sound is manipulated. We used functional magnetic resonance imaging to scan 11 drummers and 11 age- and gender-matched novices who made judgments on point-light drumming movements presented with sound. In Experiment 1, sound was synchronized or desynchronized with drumming strikes, while in Experiment 2 sound was always synchronized, but the natural covariation between sound in…
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…
The obsessions of the green-eyed monster: jealousy and the female brain
2019
The present brain-imaging study assessed neural correlates of romantic jealousy in women who had suffered real infidelity by their partner. We predicted to find activation across different brain st...
Resting-state EEG reveals four subphenotypes of amyotrophic lateral sclerosis
2021
Abstract Amyotrophic lateral sclerosis is a devastating disease characterized primarily by motor system degeneration, with clinical evidence of cognitive and behavioural change in up to 50% of cases. Amyotrophic lateral sclerosis is both clinically and biologically heterogeneous. Subgrouping is currently undertaken using clinical parameters, such as site of symptom onset (bulbar or spinal), burden of disease (based on the modified El Escorial Research Criteria) and genomics in those with familial disease. However, with the exception of genomics, these subcategories do not take into account underlying disease pathobiology, and are not fully predictive of disease course or prognosis. Recently…
Frequency-specific network activity predicts bradykinesia severity in Parkinson’s disease
2021
Highlights • Parallel subnetworks are affected in bradykinesia. • The primary motor and the premotor cortex are common nodes with task-specificity. • Beta activity decreases, gamma activity increases with improvement of bradykinesia. • Subthalamic stimulation reduces beta, increases gamma power in ipsilateral cortex. • Subnetworks act with frequency-specific oscillations.
Altered cerebral blood flow velocity features in fibromyalgia patients in resting-state conditions
2017
[EN] The aim of this study is to characterize in resting-state conditions the cerebral blood flow velocity (CBFV) signals of fibromyalgia patients. The anterior and middle cerebral arteries of both hemispheres from 15 women with fibromyalgia and 15 healthy women were monitored using Transcranial Doppler (TCD) during a 5-minute eyes-closed resting period. Several signal processing methods based on time, information theory, frequency and time-frequency analyses were used in order to extract different features to characterize the CBFV signals in the different vessels. Main results indicated that, in comparison with control subjects, fibromyalgia patients showed a higher complexity of the envel…
Low-Rank Tucker-2 Model for Multi-Subject fMRI Data Decomposition with Spatial Sparsity Constraint
2022
Tucker decomposition can provide an intuitive summary to understand brain function by decomposing multi-subject fMRI data into a core tensor and multiple factor matrices, and was mostly used to extract functional connectivity patterns across time/subjects using orthogonality constraints. However, these algorithms are unsuitable for extracting common spatial and temporal patterns across subjects due to distinct characteristics such as high-level noise. Motivated by a successful application of Tucker decomposition to image denoising and the intrinsic sparsity of spatial activations in fMRI, we propose a low-rank Tucker-2 model with spatial sparsity constraint to analyze multi-subject fMRI dat…
Brain Synchrony in Competition and Collaboration During Multiuser Neurofeedback-Based Gaming
2021
EEG hyperscanning during multiuser gaming offers opportunities to study brain characteristics of social interaction under various paradigms. In this study, we aimed to characterize neural signatures and phase-based functional connectivity patterns of gaming strategies during collaborative and competitive alpha neurofeedback games. Twenty pairs of participants with no close relationship took part in three sessions of collaborative or competitive multiuser neurofeedback (NF), with identical graphical user interface, using Relative Alpha (RA) power as a control signal. Collaborating dyads had to keep their RA within 5% of each other for the team to be awarded a point, while members of competit…
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…