Regional coherence evaluation in mild cognitive impairment and Alzheimer's disease based on adaptively extracted magnetoencephalogram rhythms

This study assesses the connectivity alterations caused by Alzheimer's disease (AD) and mild cognitive impairment (MCI) in magnetoencephalogram (MEG) background activity. Moreover, a novel methodology to adaptively extract brain rhythms from the MEG is introduced. This methodology relies on the ability of empirical mode decomposition to isolate local signal oscillations and constrained blind source separation to extract the activity that jointly represents a subset of channels. Inter-regional MEG connectivity was analysed for 36 AD, 18 MCI and 26 control subjects in δ, θ, α and β bands over left and right central, anterior, lateral and posterior regions with magnitude squared coherence—c(f). For the sake of comparison, c(f) was calculated from the original MEG channels and from the adaptively extracted rhythms. The results indicated that AD and MCI cause slight alterations in the MEG connectivity. Computed from the extracted rhythms, c(f) distinguished AD and MCI subjects from controls with 69.4% and 77.3% accuracies, respectively, in a full leave-one-out cross-validation evaluation. These values were higher than those obtained without the proposed extraction methodology

Detection of temporal-lobe epilepsy with the physiological responses to fear and anxiety

Epilepsy is a neurological disease caused by an abnormal neuronal activity on a region of the brain, which provokes seizures and the loss of consciousness to its patients. Epilepsy can be very disabling, since patients do not know when crisis or seizures are going to occur. The epilepsy we will focus on is "temporal lobe epilepsy", which is caused because of an abnormal neuronal activity on the temporal lobe. Before the development of an onset, the brain's temporal lobe -and consequently, the amygdala- are activated. Once having assured the relationship between the amygdala and an onset, the project will analyse the relationship between high levels of fear and anxiety -related with amygdala functions- and the development of a seizure. After determining what the relationship between fear and anxiety and the start of the seizure is, the project aims to develop a device that can do that by itself. The device will detect the patients' heart rate -since it is the main reaction to fear- and, when the heart rate is high enough to develop into a seizure, it will warn the patient. Thanks to that, epilepsy patients will live less anxious, since they will know when a seizure is going to happen and they will be able prevent themselves from the damages which might occur

Complexity Analysis of Spontaneous Brain Activity in Attention-Deficit/Hyperactivity Disorder: Diagnostic Implications

Background: Attention-deficit/hyperactivity disorder (ADHD) is defined as the most common neurobehavioral disorder of childhood, but an objective diagnostic test is not available yet to date. Neurophychological, neuroimaging, and neurophysiological research offer ample evidence of brain and behavioral dysfunctions in ADHD, but these findings have not been useful as a diagnostic test. Methods: Whole-head magnetoencephalographic recordings were obtained from 14 diagnosed ADHD patients and 14 healthy children during resting conditions. Lempel-Ziv complexity (LZC) values were obtained for each channel and child and averaged in five sensor groups: anterior, central, left lateral, right lateral, and posterior. Results: Lempel-Ziv complexity scores were significantly higher in control subjects, with the maximum value in anterior region. Combining age and anterior complexity values allowed the correct classification of ADHD patients and control subjects with a 93% sensitivity and 79% specificity. Control subjects showed an age-related monotonic increase of LZC scores in all sensor groups, while children with ADHD exhibited a nonsignificant tendency toward decreased LZC scores. The age-related divergence resulted in a 100% specificity in children older than 9 years. Conclusions: Results support the role of a frontal hypoactivity in the diagnosis of ADHD. Moreover, the age-related divergence of complexity scores between ADHD patients and control subjects might reflect distinctive developmental trajectories. This interpretation of our results is in agreement with recent investigations reporting a delay of cortical maturation in the prefrontal corte