Fernández A

Automatic mapping of surfaces affected by forest fires in Spain using AVHRR NDVI composite image data

Abstract In this work, we describe the statistical techniques used to analyze images from the National Oceanic and Atmospheric Administrations advanced very high resolution radiometer for the calculation and mapping of surfaces affected by large forest fires in Spain in 1993 and 1994. Maximum value normalized difference vegetation index (NDVI) composites (MVCs) were generated for every ten-day period over the two years of the study. Two techniques, one regression analysis and the other differencing, were applied to the NDVI-MVCs both before and after each fire event to determine detection thresholds of change and to delineate and objectively evaluate the burned surfaces. The comparison between the single-fires burned areas predicted by the techniques and that provided by the Spanish Forestry Service (ground based) showed that the regression algorithm was more reliable, giving rise to virtually no bias (−0.9%) and a root mean square error (RMS) of 20.3%, both calculated as a percentage of the mean burned area of the whole sample. The technique of differencing provided worse results with a 3.2% bias and a 23.5% RMS error. Likewise, a comparison between. the perimeters of the large fires supplied by official data (GPS-based) and those obtained by the regression method confirmed the validity of the technique not only for calculating fire size, but also for mapping of large forest fires.

Magnetoencephalographic pattern of epileptiform activity in children with early-onset autism spectrum disorders.

OBJECTIVE To provide further data around magnetoencephalographic (MEG) findings in early-onset autism spectrum disorders (ASD). METHODS Thirty-six children (mean age 7 years) diagnosed of PDD (DSM-IV, ICD-10) were studied. There were 22 children with autistic disorder, 9 with Aspergers syndrome, and 5 with pervasive developmental disorder not otherwise specified (PDD-NOS). According to the Childhood Autism Rating Scale (CARS), the autistic disorder was mild to moderate in 11, and severe in 11. Neuroimaging studies using three-dimensional MRI as well as simultaneous MEG-EEG and fusion techniques through magnetic source imaging (MSI) were performed, with the aid of anesthesia in non-cooperative patients. RESULTS Most patients had no EEG abnormalities. All ASD children showed common specific abnormalities in the shape of low amplitude monophasic and biphasic spikes (isolated or short bursts) as well as acute waves, predominantly distributed in the perisylvian areas. In Aspergers syndrome, epileptiform spikes were mostly found in the right hemisphere. No lateralized epileptiform activity was observed in non-Aspergers autistic patients. CONCLUSIONS MEG epileptiform activity is frequently documented in children with early-onset ASD. SIGNIFICANCE Subclinical epileptiform activity is present especially in the perisylvian regions for many patients with ASD.

Quantitative magnetoencephalography of spontaneous brain activity in Alzheimer disease : An exhaustive frequency analysis

Quantitative magnetoencephalography (qMEG) was used to investigate differences in the 2 to 60 Hz spectral power, between Alzheimer disease (AD) patients and control subjects. Twenty-two AD patients and 21 age-matched control subjects participated in this study. MEG signal analysis comprised the division of the entire 2 to 60 Hz spectrum in 2 Hz-width subbands. Both the relative power and the contribution of each subband to the correct classification of AD patients and controls were calculated. The relative power in 2 bands comprised between 2 to 4 Hz and 16 to 28 Hz was selected by a restrictive multiple-comparison test, among the entire 2 to 60 Hz spectrum. Using 2 to 4 Hz values it is possible to choose a classification rule with an estimate sensitivity and specificity given by 68% and 76% respectively. Alternatively, when 16 to 28 Hz values are used, it is possible to obtain a better classification rule with an estimate sensitivity and specificity given by 81% and 80%, respectively. To the best of our knowledge, this is the first electroencephalography or MEG study where a so exhaustive analysis of the magneto-electric spectrum has been performed. This study supports the notion that more attention should be devoted to the study of β band in AD.

18. Complexity analysis of the magnetoencephalogram background activity in Alzheimer disease

neous activity, abnormalities in NCS, and EMG responses to electrical stimulation of the peripheral nerve. Only three patients were classified as central CMAS, they had continuous discharge of normal motor unit potentials. Two teen aged brothers complaining from cramps in legs and hands met the criteria for Isaacs syndrome, with myokymic discharges and spontaneous neuromyotonia, the electric stimulation of the peripheral nerve evoked after-discharges in the EMG. One patient with acquired neuromyotonia had a peripheral neuropathy secondary to a hypothyroidism. In the remaining four patients neuromyotonia was secondary to peripheral neuropathy of unknown etiology; fibrillation or positive sharp wave were observed at rest, and also neuromyotonia and myokymic discharges; but the presence of abnormalities in NCS was the main finding. CMAS includes a wide range of pathologies, some of them with a peripheral cause and for its differential diagnosis is essential the electrophysiological study.