Search results for "network"
showing 10 items of 7718 documents
pBrain: A novel pipeline for Parkinson related brain structure segmentation
2020
[EN] Parkinson is a very prevalent neurodegenerative disease impacting the life of millions of people worldwide. Although its cause remains unknown, its functional and structural analysis is fundamental to advance in the search of a cure or symptomatic treatment. The automatic segmentation of deep brain structures related to Parkinson's disease could be beneficial for the follow up and treatment planning. Unfortunately, there is not broadly available segmentation software to automatically measure Parkinson related structures. In this paper, we present a novel pipeline to segment three deep brain structures related to Parkinson's disease (substantia nigra, subthalamic nucleus and red nucleus…
Neural net classification of REM sleep based on spectral measures as compared to nonlinear measures
2001
In various studies the implementation of nonlinear and nonconventional measures has significantly improved EEG (electroencephalogram) analyses as compared to using conventional parameters alone. A neural network algorithm well approved in our laboratory for the automatic recognition of rapid eye movement (REM) sleep was investigated in this regard. Originally based on a broad range of spectral power inputs, we additionally supplied the nonlinear measures of the largest Lyapunov exponent and correlation dimension as well as the nonconventional stochastic measures of spectral entropy and entropy of amplitudes. No improvement in the detection of REM sleep could be achieved by the inclusion of …
Task-induced deactivation in diverse brain systems correlates with interindividual differences in distinct autonomic indices
2018
AbstractNeuroimaging research has shown that different cognitive tasks induce relatively specific activation patterns, as well as less task-specific deactivation patterns. Here we examined whether individual differences in Autonomic Nervous System (ANS) activity during task performance correlate with the magnitude of task-induced deactivation. In an fMRI study, participants performed a continuous mental arithmetic task in a task/rest block design, while undergoing combined fMRI and heart / respiration rate acquisitions using photoplethysmograph and respiration belt. As expected, task performance increased heart-rate and reduced the RMSSD, a cardiac index related to vagal tone. Across partic…
Money, Social Relationships and the Sense of Self: The Consequences of an Improved Financial Situation for Persons Suffering from Serious Mental Illn…
2017
During a 9-month period, 100 persons with SMI were given approx. 73 USD per month above their normal income. Sixteen of the subjects were interviewed. The interviews were analysed according to the methods of thematic analysis. The money was used for personal pleasure and to re-establish reciprocal relations to others. The ways in which different individuals used the money at their disposal impacted their sense of self through experiences of mastery, agency, reciprocity, recognition and security. The findings underline the importance of including social circumstances in our understanding of mental health problems, their trajectories and the recovery process.
The facilitative effect of gestures on the neural processing of semantic complexity in a continuous narrative
2019
© 2019 Elsevier Inc. Gestures are elemental components of social communication and aid comprehension of verbal messages; however, little is known about the potential role of gestures in facilitating processing of semantic complexity in an ecologically valid setting. The goal of this study was to investigate whether cognitive load, as indexed by semantic complexity, is modulated by the presentation of gestures accompanying speech. Twenty healthy participants watched 16 video clips of a short narrative while instructed to carefully listen to and watch the narrator while functional magnetic resonance imaging (fMRI) data were acquired. The videos contained passages with and without various co-s…
Epoch versus impulse models in the analysis of parametric fMRI studies
2013
Abstract Objective In parametric fMRI studies the relationship between the amplitude of the hemodynamic response and electrophysiological or behavioral parameters is commonly analyzed using the general linear model (GLM). We examined ways of using single-trial response time (RT) in the analysis of a decision-making task to better isolate task-specific activation. Methods fMRI and RT data were recorded in twenty-one subjects performing a visual-oddball-task. Four explanatory variables (EVs) were generated for the GLM-analysis: A conventional (constant impulse) EV, a constant epoch EV informed using subjects’ average RT, a variable impulse EV and a variable epoch EV both informed using single…
Decoding attentional states for neurofeedback Mindfulness vs. wandering thoughts
2018
Abstract Neurofeedback requires a direct translation of neuronal brain activity to sensory input given to the user or subject. However, decoding certain states, e.g., mindfulness or wandering thoughts, from ongoing brain activity remains an unresolved problem. In this study, we used magnetoencephalography (MEG) to acquire brain activity during mindfulness meditation and thought-inducing tasks mimicking wandering thoughts. We used a novel real-time feature extraction to decode the mindfulness, i.e., to discriminate it from the thought-inducing tasks. The key methodological novelty of our approach is usage of MEG power spectra and functional connectivity of independent components as features …
Functional connectivity analysis using whole brain and regional network metrics in MS patients
2016
In the present study we investigated brain network connectivity differences between patients with relapsing-remitting multiple sclerosis (RRMS) and healthy controls (HC) as derived from functional resonance magnetic imaging (fMRI) using graph theory. Resting state fMRI data of 18 RRMS patients (12 female, mean age ± SD: 42 ± 12.06 years) and 25 HC (8 female, 29.2 ± 5.38 years) were analyzed. In order to obtain information of differences in entire brain network, we focused on both, local and global network connectivity parameters. And the regional connectivity differences were assessed using regional network parameters. RRMS patients presented a significant increase of modularity in comparis…
Discovering dynamic task-modulated functional networks with specific spectral modes using MEG.
2019
Efficient neuronal communication between brain regions through oscillatory synchronization at certain frequencies is necessary for cognition. Such synchronized networks are transient and dynamic, established on the timescale of milliseconds in order to support ongoing cognitive operations. However, few studies characterizing dynamic electrophysiological brain networks have simultaneously accounted for temporal non-stationarity, spectral structure, and spatial properties. Here, we propose an analysis framework for characterizing the large-scale phase-coupling network dynamics during task performance using magnetoencephalography (MEG). We exploit the high spatiotemporal resolution of MEG to m…
Quantification of cortical proprioceptive processing through a wireless and miniaturized EEG amplifier.
2022
Corticokinematic coherence (CKC) is computed between limb kinematics and cortical activity (e.g. MEG, EEG), and it can be used to detect, quantify and localize the cortical processing of proprioceptive afference arising from the body. EEG-based studies on CKC have been limited to lab environments due to bulky, non-portable instrumentations. We recently proposed a wireless and miniaturized EEG acquisition system aimed at enabling EEG studies outside the laboratory. The purpose of this work is to compare the EEG-based CKC values obtained with this device with a conventional wired-EEG acquisition system to validate its use in the quantification of cortical proprioceptive processing. Eleven hea…