Special Session on Neural Signals of Brain Disorders 2010 Abstracts
Short Papers
| Paper Nr: | 1 |
| Title: | SPARSE BUMP MODELING OF MILDAD PATIENTS - Modeling Transient Oscillations in the EEG of Patients with Mild Alzheimer’s Disease |
| Authors: | François-Benoit Vialatte, Charles François Vincent Latchoumane, Nigel Hudson, Sunil Wimalaratna, Jordi Solé-Casals, Jaeseung Jeong and Andrzej Cichocki |
| Abstract: | We explore the potential of bump modeling to extract transient local synchrony in EEG, as a marker for mildAD (mild Alzheimer’s disease). EEG signals of patients with mildAD are transformed to a wavelet timefrequency representation, and afterwards a sparsification process (bump modeling) extracts time-frequency oscillatory bursts. We observed that organized oscillatory events contain stronger discriminative signatures than averaged spectral EEG statistics for patients in a probable early stage of Alzheimer’s disease. Specifically, bump modeling enhanced the difference between mildAD patients and age-matched control subjects in the θ and β frequency ranges.This effect is consistent with previous results obtained on other databases. |
| Paper Nr: | 3 |
| Title: | ICA CLEANING PROCEDURE FOR EEG SIGNALS ANALYSIS - Application to Alzheimer's Disease Detection |
| Authors: | J. Solé-Casals, F. Vialatte, J. Pantel, D. Prvulovic, C. Haenschel and A. Cichocki |
| Abstract: | To develop systems in order to detect Alzheimer’s disease we want to use EEG signals. Available database is raw, so the first step must be to clean signals properly. We propose a new way of ICA cleaning on a database recorded from patients with Alzheimer's disease (mildAD, early stage). Two researchers visually inspected all the signals (EEG channels), and each recording's least corrupted (artefact-clean) continuous 20 sec interval were chosen for the analysis. Each trial was then decomposed using ICA. Sources were ordered using a kurtosis measure, and the researchers cleared up to seven sources per trial corresponding to artefacts (eye movements, EMG corruption, EKG, etc), using three criteria: (i) Isolated source on the scalp (only a few electrodes contribute to the source), (ii) Abnormal wave shape (drifts, eye blinks, sharp waves, etc.), (iii) Source of abnormally high amplitude (≥100 μV). We then evaluated the outcome of this cleaning by means of the classification of patients using multilayer perceptron neural networks. Results are very satisfactory and performance is increased from 50.9% to 73.1% correctly classified data using ICA cleaning procedure. |
| Paper Nr: | 5 |
| Title: | CEREBRAL CORRELATES OF THE CONTINOUS PERFORMANCE TEST-IDENTICAL PAIRS VERSION - An fMRI Study |
| Authors: | J. M. Serra-Grabulosa, A. Adan, C. Falcón, N. Bargalló and J. Solé-Casals |
| Abstract: | One of the most used paradigms in the study of the attention is the Continuous Performance Test (CPT). The Identical Pairs version of the CPT (CPT-IP) has been used to evaluate attention deficits in developmental, neurological and psychiatric disorders. Since both dyscalculia and ADHD (attention deficit hyperactivity disorder) show attentional and numerical processing deficits, it would be interesting to evaluate functional brain patterns related to the CPT-IP in a task which uses numerical stimuli. In this sense, the aim of our study was to design a task to evaluate sustained attention using functional magnetic resonance imaging. This task has to be sensitive to evaluate later dyscalculic and ADHD subjects. Forty right-handed, healthy subjects (20 women; age range 18–25) were recruited to participate in the study. A CPT-IP implemented as a block design was used to assess sustained attention in the fMRI session. Results showed the CPT-IP task used activates a network of frontal, parietal and occipital areas and could be related to executive, attentional and numerical processing functions. |