116 research outputs found
Cross-Frequency Power-Power Coupling Analysis:A Useful Cross-Frequency Measure to Classify ICA-Decomposed EEG
Central neuropathic pain in paraplegia alters movement related potentials
Objectives:
Spinal Cord Injured (SCI) persons with and without Central Neuropathic Pain (CNP) show different oscillatory brain activities during imagination of movement. This study investigates whether they also show differences in movement related cortical potentials (MRCP).
Methods:
SCI paraplegic patients with no CNP (n = 8), with CNP in their lower limbs (n = 8), and healthy control subjects (n = 10) took part in the study. EEG clustering involved independent component analysis, equivalent current dipole fitting, and Measure Projection to define cortical domains that have functional modularity during the motor imagery task.
Results:
Three domains were identified: limbic system, sensory-motor cortex and visual cortex. The MRCP difference between the groups of SCI with and without CNP was reflected in a domain located in the limbic system, while the difference between SCI patients and control subjects was in the sensorimotor domain. Differences in MRCP morphology between patients and healthy controls were visible for both paralysed and non paralysed limbs.
Conclusion:
SCI but not CNP affects the movement preparation, and both SCI and CNP affect sensory processes.
Significance:
Rehabilitation strategies of SCI patients based on MRCP should take into account the presence of CNP
Public Expenditure Composition and Economic Growth : Optimal Adjustment by Using Gradient Method
Parieto-Occipital Alpha and Low-Beta EEG Power Reflect Sense of Agency
The sense of agency (SoA) is part of psychophysiological modules related to the self. Disturbed SoA is found in several clinical conditions, hence understanding the neural correlates of the SoA is useful for the diagnosis and determining the proper treatment strategies. Although there are several neuroimaging studies on SoA, it is desirable to translate the knowledge to more accessible and inexpensive EEG-based biomarkers for the sake of applicability. However, SoA has not been widely investigated using EEG. To address this issue, we designed an EEG experiment on healthy adults (n = 15) to determine the sensitivity of EEG on the SoA paradigm using hand movement with parametrically delayed visual feedback. We calculated the power spectral density over the traditional EEG frequency bands for ten delay conditions relative to no delay condition. Independent component analysis and equivalent current dipole modeling were applied to address artifact rejection, volume conduction, and source localization to determine the effect of interest. The results revealed that the alpha and low-beta EEG power increased in the parieto-occipital regions in proportion to the reduced SoA reported by the subjects. We conclude that the parieto-occipital alpha and low-beta EEG power reflect the sense of agency
Hierarchical Event Descriptors (HED): Semi-Structured Tagging for Real-World Events in Large-Scale EEG.
Real-world brain imaging by EEG requires accurate annotation of complex subject-environment interactions in event-rich tasks and paradigms. This paper describes the evolution of the Hierarchical Event Descriptor (HED) system for systematically describing both laboratory and real-world events. HED version 2, first described here, provides the semantic capability of describing a variety of subject and environmental states. HED descriptions can include stimulus presentation events on screen or in virtual worlds, experimental or spontaneous events occurring in the real world environment, and events experienced via one or multiple sensory modalities. Furthermore, HED 2 can distinguish between the mere presence of an object and its actual (or putative) perception by a subject. Although the HED framework has implicit ontological and linked data representations, the user-interface for HED annotation is more intuitive than traditional ontological annotation. We believe that hiding the formal representations allows for a more user-friendly interface, making consistent, detailed tagging of experimental, and real-world events possible for research users. HED is extensible while retaining the advantages of having an enforced common core vocabulary. We have developed a collection of tools to support HED tag assignment and validation; these are available at hedtags.org. A plug-in for EEGLAB (sccn.ucsd.edu/eeglab), CTAGGER, is also available to speed the process of tagging existing studies
Regional optimum frequency analysis of resting-state fMRI data for early detection of Alzheimer’s disease biomarkers
Regional optimum frequency analysis of resting-state fMRI data for early detection of Alzheimer’s disease biomarkers
The blood-oxygen label dependent (BOLD) signal obtained from functional magnetic resonance images (fMRI) varies significantly among populations. Yet, there is some agreement among researchers over the pace of the blood flow within several brain regions relative to the subject’s age and cognitive ability. Our analysis further suggested that regional coherence among the BOLD fMRI voxels belonging to the individual region of the brain has some correlation with underlying pathology as well as cognitive performance, which can suggest potential biomarkers to the early onset of the disease. To capitalise on this we propose a method, called Regional Optimum Frequency Analysis (ROFA), which is based on finding the optimum synchrony frequency observed at each brain region for each of the resting-state BOLD frequency bands (Slow 5 (0.01–0.027 Hz), Slow 4 (0.027–0.073 Hz) and slow 3 (0.073 to 0.198 Hz)), and the whole frequency band (0.01–0.167 Hz) respectively. The ROFA is carried out on fMRI data of total 310 scans, i.e., 26, 175 and 109 scans from 21 young-healthy (YH), 69 elderly-healthy (EH) and 33 Alzheimer’s disease (AD) patients respectively, where these scans include repeated scans from some subjects acquired at 3 to 6 months intervals. A 10-fold cross-validation procedure evaluated the performance of ROFA for classification between the YH vs EH, YH vs AD and EH vs AD subjects. Based on the confusion-matrix parameters; accuracy, precision, sensitivity and Matthew’s correlation coefficient (MCC), the proposed ROFA classification outperformed the state-of-the-art Group-independent component analysis (Group-ICA), Functional-connectivity, Graph metrics, Eigen-vector centrality, Amplitude of low-frequency fluctuation (ALFF) and fractional amplitude of low-frequency fluctuations (fALFF) based methods with more than 94.99% precision and 95.67% sensitivity for different subject groups. The results demonstrate the effectiveness of the proposed ROFA parameters (frequencies) as adequate biomarkers of Alzheimer’s disease
Phaseâ amplitude coupling between interictal highâ frequency activity and slow waves in epilepsy surgery
ObjectiveWe hypothesized that the modulation index (MI), a summary measure of the strength of phaseâ amplitude coupling between highâ frequency activity (>150Â Hz) and the phase of slow waves (3â 4Â Hz), would serve as a useful interictal biomarker for epilepsy presurgical evaluation.MethodsWe investigated 123 patients who underwent focal cortical resection following extraoperative electrocorticography recording and had at least 1 year of postoperative followâ up. We examined whether consideration of MI would improve the prediction of postoperative seizure outcome. MI was measured at each intracranial electrode site during interictal slowâ wave sleep. We compared the accuracy of prediction of patients achieving International League Against Epilepsy class 1 outcome between the full multivariate logistic regression model incorporating MI in addition to conventional clinical, seizure onset zone (SOZ), and neuroimaging variables, and the reduced logistic regression model incorporating all variables other than MI.ResultsNinety patients had class 1 outcome at the time of most recent followâ up (mean followâ up = 5.7Â years). The full model had a noteworthy outcome predictive ability, as reflected by regression model fit R2 of 0.409 and area under the curve (AUC) of receiver operating characteristic plot of 0.838. Incomplete resection of SOZ (PÂ <Â 0.001), larger number of antiepileptic drugs at the time of surgery (PÂ =Â 0.007), and larger MI in nonresected tissues relative to that in resected tissue (PÂ =Â 0.020) were independently associated with a reduced probability of class 1 outcome. The reduced model had a lower predictive ability as reflected by R2 of 0.266 and AUC of 0.767. Anatomical variability in MI existed among nonepileptic electrode sites, defined as those unaffected by magnetic resonance imaging lesion, SOZ, or interictal spike discharges. With MI adjusted for anatomical variability, the full model yielded the outcome predictive ability of R2 of 0.422, AUC of 0.844, and sensitivity/specificity of 0.86/0.76.SignificanceMI during interictal recording may provide useful information for the prediction of postoperative seizure outcome.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146440/1/epi14544_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146440/2/epi14544.pd
ERPs and their brain sources in perceptual and conceptual prospective memory tasks: commonalities and differences between the two tasks
The present study examined whether Event-Related Potential (ERP) components and their neural generators are common to perceptual and conceptual prospective memory (PM) tasks or specific to the form of PM cue involved. We used Independent Component Analysis (ICA) to study the contributions of brain source activities to scalp ERPs across the different phases of two event-based PM-tasks: (1) holding intentions during a delay (monitoring) (2) detecting the correct context to perform the delayed intention (cue detection) and (3) carrying out the action (realisation of delayed intentions). Results showed that monitoring for both perceptual and conceptual PM-tasks was characterised by an enhanced early occipital negativity (N200). In addition the conceptual PM-task showed a long-lasting effect of monitoring significant around 700 ms. Perceptual PM-task cues elicited an N300 enhancement associated with cue detection, whereas a midline N400-like response was evoked by conceptual PM-task cues. The Prospective Positivity associated with realisation of delayed intentions was observed in both conceptual and perceptual tasks. A common frontal-midline brain source contributed to the Prospective Positivity in both tasks and a strong contribution from parieto-frontal brain sources was observed only for the perceptually cued PM-task. These findings support the idea that: (1) The enhanced N200 can be understood as a neural correlate of a ‘retrieval mode’ for perceptual and conceptual PM-tasks, and additional strategic monitoring is implemented according the nature of the PM task; (2) ERPs associated with cue detection are specific to the nature of the PM cues; (3) Prospective Positivity reflects a general PM process, but the specific brain sources contributing to it depend upon the nature of the PM task
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