Search results for "fMRI"

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…

Supramodal neural processing of abstract information conveyed by speech and gesture

2013

Abstractness and modality of interpersonal communication have a considerable impact on comprehension. They are relevant for determining thoughts and constituting internal models of the environment. Whereas concrete object-related information can be represented in mind irrespective of language, abstract concepts require a representation in speech. Consequently, modality-independent processing of abstract information can be expected. Here we investigated the neural correlates of abstractness (abstract vs. concrete) and modality (speech vs. gestures), to identify an abstractness-specific supramodal neural network. During fMRI data acquisition 20 participants were presented with videos of an ac…

2014

Due to its millisecond-scale temporal resolution, EEG allows to assess neural correlates with precisely defined temporal relationship relative to a given event. This knowledge is generally lacking in data from functional magnetic resonance imaging (fMRI) which has a temporal resolution on the scale of seconds so that possibilities to combine the two modalities are sought. Previous applications combining event-related potentials (ERPs) with simultaneous fMRI BOLD generally aimed at measuring known ERP components in single trials and correlate the resulting time series with the fMRI BOLD signal. While it is a valuable first step, this procedure cannot guarantee that variability of the chosen …

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…

Data-driven analysis for fMRI during naturalistic music listening

2017

Interest towards higher ecological validity in functional magnetic resonance imaging (fMRI) experiments has been steadily growing since the turn of millennium. The trend is reflected in increasing amount of naturalistic experiments, where participants are exposed to the real-world complex stimulus and/or cognitive tasks such as watching movie, playing video games, or listening to music. Multifaceted stimuli forming parallel streams of input information, combined with reduced control over experimental variables introduces number of methodological challenges associated with isolating brain responses to individual events. This exploratory work demonstrated some of those methodological challeng…

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.

Generation of stimulus features for analysis of FMRI during natural auditory experiences

2014

In contrast to block and event-related designs for fMRI experiments, it becomes much more difficult to extract events of interest in the complex continuous stimulus for finding corresponding blood-oxygen-level dependent (BOLD) responses. Recently, in a free music listening fMRI experiment, acoustic features of the naturalistic music stimulus were first extracted, and then principal component analysis (PCA) was applied to select the features of interest acting as the stimulus sequences. For feature generation, kernel PCA has shown its superiority over PCA in various applications, since it can implicitly exploit nonlinear relationship among features and such relationship seems to exist genera…

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…