Evaluación de la conectividad cerebral bajo fármacos mediante análisis no lineal del EEG

Màster Oficial en Enginyeria Biomèdica

Towards a model-based integration of co-registered electroencephalography/functional magnetic resonance imaging data with realistic neural population meshes

Brain activity can be measured with several non-invasive neuroimaging modalities, but each modality has inherent limitations with respect to resolution, contrast and interpretability. It is hoped that multimodal integration will address these limitations by using the complementary features of already available data. However, purely statistical integration can prove problematic owing to the disparate signal sources. As an alternative, we propose here an advanced neural population model implemented on an anatomically sound cortical mesh with freely adjustable connectivity, which features proper signal expression through a realistic head model for the electroencephalogram (EEG), as well as a haemodynamic model for functional magnetic resonance imaging based on blood oxygen level dependent contrast (fMRI BOLD). It hence allows simultaneous and realistic predictions of EEG and fMRI BOLD from the same underlying model of neural activity. As proof of principle, we investigate here the influence on simulated brain activity of strengthening visual connectivity. In the future we plan to fit multimodal data with this neural population model. This promises novel, model-based insights into the brain's activity in sleep, rest and task conditions.

Probabilistic ictal EEG sources and temporal lobe epilepsy surgical outcome

Objective - For patients with medication refractory medial temporal lobe epilepsy (MTLE), surgery offers the hope of a cure. However, up to 30% of patients with MTLE continue to experience disabling seizures after surgery. The reasons why some patients do not achieve seizure freedom are poorly understood. A promising theory suggests that epileptogenic networks are broadly distributed in surgically refractory MTLE, involving regions beyond the medial temporal lobe. In this retrospective study, we aimed to investigate the distribution of epileptogenic networks in MTLE using Bayesian distributed EEG source analysis from preoperative ictal onset recordings. This analysis has the advantage of generating maps of source probability, which can be subjected to voxel-based statistical analyses.Methods - We compared 10 patients who achieved post-surgical seizure freedom with 10 patients who continued experiencing seizures after surgery. Voxel-based Wilcoxon tests were employed with correction for multiple comparisons.Results - We observed that ictal EEG source intensities were significantly more likely to occur in lateral temporal and posterior medial temporal regions in patients with continued seizures post-surgery.Conclusions - Our findings support the theory of broader spatial distribution of epileptogenic networks at seizure onset in patients with surgically refractory MTLE.

Atrichia, abnormal EEG, epilepsy and mental retardation in two sisters

Two daughters of a nonconsanguineous couple are described. Both present mental retardation, epileptic seizures, congenital atrichia, histologically anomalous skin and abnormal EEG pattern. From a discussion of the literature on atrichia, the forms without involvement of teeth, nails and hidrosis, among which recessive inheritance prevails, are distinguished from each other. None of them coincide with the syndrome described here.

Effects of Methylphenidate on performance of a practical pistol shooting task: a quantitative electroencephalography (qEEG) study

Abstract Background The present study examined absolute alpha power using quantitative electroencephalogram (qEEG) in bilateral temporal and parietal cortices in novice soldiers under the influence of methylphenidate (MPH) during the preparatory aiming period in a practical pistol-shooting task. We anticipated higher bi-hemispheric cortical activation in the preparatory period relative to pre-shot baseline in the methylphenidate group when compared with the control group because methylphenidate has been shown to enhance task-related cognitive functions. Methods Twenty healthy, novice soldiers were equally distributed in control (CG; n = 10) and MPH groups 10 mg (MG; n = 10) using a randomized, double blind design. Subjects performed a pistol-shooting task while electroencephalographic activity was acquired. Results We found main effects for group and practice blocks on behavioral measures, and interactions between group and phases on electroencephalographic measures for the electrodes T3, T4, P3 and P4. Regarding the behavioral measures, the MPH group demonstrated significantly poorer in shooting performance when compared with the control and, in addition, significant increases in the scores over practice blocks were found on both groups. In addition, regarding the electroencephalographic data, we observed a significant increase in alpha power over practice blocks, but alpha power was significantly lower for the MPH group when compared with the placebo group. Moreover, we observed a significant decrease in alpha power in electrodes T4 and P4 during PTM. Conclusion Although we found no correlation between behavioral and EEG data, our findings show that MPH did not prevent the learning of the task in healthy subjects. However, during the practice blocks (PBs) it also did not favor the performance when compared with control group performance. It seems that the CNS effects of MPH demanded an initial readjustment period of integrated operations relative to the sensorimotor system. In other words, MPH seems to provoke a period of initial instability due to a possible modulation in neural activity, which can be explained by lower levels of alpha power (i.e., higher cortical activity). However, after the end of the PB1 a new stabilization was established in neural circuits, due to repetition of the task, resulting higher cortical activity during the task. In conclusion, MPH group performance was not initially superior to that of the control group, but eventually exceeded it, albeit without achieving statistical significance.

Localizing Seizure-Onset Zones in Presurgical Evaluation of Drug-Resistant Epilepsy by Electroencephalography/fMRI: Effectiveness of Alternative Thresholding Strategies

Simultaneous EEG/fMRI is an effective noninvasive tool for identifying and localizing the SOZ in patients with focal epilepsy. In this study, we evaluated different thresholding strategies in EEG/fMRI for the assessment of hemodynamic responses to IEDs in the SOZ of drug-resistant epilepsy.

Effects of verum acupuncture compared to placebo acupuncture on quantitative EEG and heart rate variability in healthy volunteers

OBJECTIVES: The aim of this single-blind randomized crossover study was to evaluate specific effects of manual acupuncture on central and vegetative nervous system activity measured by quantitative electroencephalography (qEEG) and heart rate variability (HRV). DESIGN: Twenty (20) healthy volunteers (mean: 25.2 +/- 3.6 years) were monitored simultaneously using a qEEG system and a 12-channel electrocardiogram recorder during verum acupuncture (VA) at acupuncture point Large Intestine 4 (Hegu) (LI4) or placebo acupuncture (PA) at a sham point. RESULTS: In the EEG conduction of the occipital area, needle stimulation in VA increased alpha1-frequency significantly, and the ratio alpha1/theta was shifted to the benefit of alpha1 over all electrodes. The HRV parameters showed a significant increase of the low frequency/high frequency (HF) ratio during the first minute of stimulation in VA, indicating an initial increase of sympathetic activation. However, an increase of HF power in the minute after stimulation followed by a decrease in heart rate suggests delayed vagal activation. De qi (a sensation that is typical of acupuncture needling) occurred in 16 subjects during VA and in 9 volunteers during PA (80% versus 45%). CONCLUSIONS: Manual stimulation on LI4 seems to lead to specific changes in alpha EEG-frequency and in HRV parameters. A linear relationship between the HRV parameters and the alpha EEG band might point to a specific modulation of cerebral function by vegetative effects during acupuncture.

Global, regional, and local measures of complexity of multichannel electroencephalography in acute, neuroleptic-naive, first-break schizophrenics

Background: Schizophrenic symptoms commonly are felt to indicate a loosened coordination, i.e. a decreased connectivity of brain processes. Methods: To address this hypothesis directly, global and regional multichannel electroencephalographic (EEG) complexities (omega complexity and dimensional complexity) and single channel EEG dimensional complexities were calculated from 19-channel EEG data from 9 neuroleptic-naive, first-break, acute schizophrenics and 9 age- and sex-matched controls. Twenty artifact-free 2 second EEG epochs during resting with closed eyes were analyzed (2–30 Hz bandpass, average reference for global and regional complexities, local EEG gradient time series for single channels). Results: Anterior regional Omega-Complexity was significantly increased in schizophrenics compared with controls (p < 0.001) and anterior regional Dimensional Complexity showed a trend for increase. Single channel Dimensional Complexity of local gradient waveshapes was prominently increased in the schizophrenics at the right precentral location (p = 0.003). Conclusions: The results indicate a loosened cooperativity or coordination (vice versa: an increased independence) of the active brain processes in the anterior brain regions of the schizophrenics.

Intracranial EEG reveals a time- and frequency-specific role for the right inferior frontal gyrus and primary motor cortex in stopping initiated responses.

Inappropriate response tendencies may be stopped via a specific fronto/basal ganglia/primary motor cortical network. We sought to characterize the functional role of two regions in this putative stopping network, the right inferior frontal gyrus (IFG) and the primary motor cortex (M1), using electocorticography from subdural electrodes in four patients while they performed a stop-signal task. On each trial, a motor response was initiated, and on a minority of trials a stop signal instructed the patient to try to stop the response. For each patient, there was a greater right IFG response in the beta frequency band ( approximately 16 Hz) for successful versus unsuccessful stop trials. This finding adds to evidence for a functional network for stopping because changes in beta frequency activity have also been observed in the basal ganglia in association with behavioral stopping. In addition, the right IFG response occurred 100-250 ms after the stop signal, a time range consistent with a putative inhibitory control process rather than with stop-signal processing or feedback regarding success. A downstream target of inhibitory control is M1. In each patient, there was alpha/beta band desynchronization in M1 for stop trials. However, the degree of desynchronization in M1 was less for successfully than unsuccessfully stopped trials. This reduced desynchronization on successful stop trials could relate to increased GABA inhibition in M1. Together with other findings, the results suggest that behavioral stopping is implemented via synchronized activity in the beta frequency band in a right IFG/basal ganglia network, with downstream effects on M1.

TETRA mobile radios interfere with electroencephalography recording equipment

We observed an anomaly in the human electroencephalogram (EEG) associated with exposure to terrestrial trunked radio (TETRA) Radiofrequency Fields (RF). Here, we characterize the time and frequency components of the anomaly and demonstrate that it is an artefact caused by TETRA RF interfering with the EEG recording equipment and not by any direct or indirect effect on the brain.

An approach to emotion recognition in single-channel EEG signals: a mother child interaction

In this work, we perform a first approach to emotion recognition from EEG single channel signals extracted in four (4) mother-child dyads experiment in developmental psychology -- Single channel EEG signals are analyzed and processed using several window sizes by performing a statistical analysis over features in the time and frequency domains -- Finally, a neural network obtained an average accuracy rate of 99% of classification in two emotional states such as happiness and sadness