[Show abstract][Hide abstract] ABSTRACT: This retrospective study examined the demographic, clinical and pharmacological factors associated with aggressive behaviour after abrupt discontinuation of medication in schizophrenic patients.
The study reports on a survey of 402 schizophrenic patients, who had abruptly discontinued their medication and had been involuntarily hospitalized to Psychiatric Hospital of Attika. The survey utilized the Discontinuation-Emergent Signs and Symptoms Checklist (DESS) to assess the signs and symptoms that patients exhibited (Rosenbaum et al., Biol Psychiatry 1998;44:77), as well the Aggression Scale (Delgado-Escueta et al., New England J Med 1981;305:711) to estimate the aggressive behaviour. Demographic and clinical variables as well as variables related to pharmacological treatment have been also investigated.
Analyses revealed that the presence of aggressive behaviour after abrupt drug discontinuation was associated positively with previous history of aggression, male gender , abrupt discontinuation of anticholinergics, delusions, nervousness or anxiety, elevated mood, irritability and negatively with negative symptoms. These predictors can correctly classify 76.3% of patients with aggressive behaviour and 64.0% of patients without aggressive behaviour.
These findings suggest that abrupt discontinuation of medication in schizophrenic patients may lead to aggressive behaviour, being connected at least in the acute phase with particular demographic, clinical and pharmacological parameters.
International Journal of Psychiatry in Clinical Practice 11/2011; 15(4):296-302. DOI:10.3109/13651501.2011.589517 · 1.31 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Due to their non-stationarity, ERP signals are difficult to study. The concept of cointegration might overcome this problem and allow for the study of the co-variability between whole ERP signals. In this context cointegration factor is defined as the ability of an ERP signal to co-vary with other ERP signals. The aim of the present study was to investigate whether the cointegra- tion factor is dependent on different EMF condi- tions and gender, as well as the locations of the electrodes on the scalp. The findings revealed that women have a significantly higher cointe- gration factor than men, while all subjects have increased cointegration factors in the presence of EMF. The cointegration factor is location de- pendent, creating a distinct cluster of high coin- tegration capacity at the central and lateral electrodes of the scalp, in contrast to clusters of low cointegration capacity at the anterior and posterior electrodes There seem to be distinct similarities of the present findings with those from standard methodologies of the ERPs. In conclusion cointegration is a promising tool towards the study of functional interactions bet- ween different brain locations.
[Show abstract][Hide abstract] ABSTRACT: In this paper, subband spectral entropy (SSE) and its relative form was used for the analysis of rest electroencephalogram (EEG) and event related potentials (ERP). The recorded signals were taken from control children and children with dyslexia. Adaptive-optimal-kernel (AOK) time-frequency representation was used to produce high resolution spectrogram. Then, SSE and relative subband spectral entropy (RSSE) were calculated. The entropic patterns of both controls and dyslexics were investigated showing differences in specific electrode recordings.
Digital Signal Processing, 2009 16th International Conference on; 08/2009
[Show abstract][Hide abstract] ABSTRACT: The main purpose of this paper is to study energy differentiations of electroencephalogram (EEG) and event related potentials (ERP) of normal subjects and subjects with dyslexia. As ERP is considered to be nonstationary signal, traditional spectral analysis is not recommended. A most appropriate approach is time-frequency representation (TFR) which reveals temporal evolution of frequency components. In this study a non-orthogonal, iterative method for adaptive time-frequency approximation of signals called matching pursuit is used. This method decomposes the signal piece by piece using a dictionary of basis functions. At each step the best fitting analyzing function is adapted to an intrinsic structure of the signal, thus providing flexible signal representation. The major advantages of the matching pursuit are the good localization of transients, the robust universal estimate of the time-frequency energy density which is resistant to the existence of noise and the fact that the dictionary set of waveforms is not limited to a single basis. Time frequency statistics reveal statistical differences on energy distribution of specific time intervals and frequency components over time-frequency plane. Possible non-normal distributions of the energy values are taken into account and a normalization transform is used in order to be able to use robust parametric tests. According to this analysis, dyslexics appear to have statistically reduced energy compared to controls for frequency regions 5-20Hz and for time around the ERP component N100. Introduction In the present paper, the matching pursuit algorithm, which was first proposed by Mallat and Zhang  is applied in order to estimate the energy of EEG signals in time-frequency plane. The use of matching pursuit algorithm leads to a decomposition of each EEG signal into a linear expansion of Gabor atoms. The time-frequency estimation of EEG signal energy is the result of pseudo Wigner-Ville distribution of Hilbert transform of these Gabor atoms. In previous works have been used some other methods in estimation of EEG signal energy in time-frequency plane like spectrogram , scalogram , bandpass filtering in overlapping bands .The approximation of a signal using nonorthogonal functions is a "nonpolynomial" problem (computational complexity grows exponentially with the dimension of signal). The matching pursuit algorithm is a sub-optimal solution but as the heuristic give relatively small error this can't be considered as drawback. The major advantages of matching pursuit in contrary to the other time-frequency methods is that provides an optimal non-orthogonal selection of basis atoms and full parametrization of these atoms. The above features of matching pursuit is very important in time-frequency analysis of non-stationary signal like EEG/ERP, whose temporal changes in energy are significant as they are associated with functional brain activation. No other methods possess these properties. For example, the Fourier analysis which used in spectrogram localization in time and frequency depends on epoch length (the STFT spectrogram divides the analyzed signal into overlapping epochs). Continuous wavelet transform or Cohen's class transforms do not provide parametric description. Moreover Cohen's class transforms are biased by cross-terms. Discrete wavelet transforms, which used in scalogram give parametric descriptions, but their time-frequency resolution is severely limited as it has high temporal resolution and low frequency resolution at high frequencies, and low temporal resolution and high frequency resolution at low frequencies . According to earlier works the matching pursuit algorithm provides a unified parametrization of EEG, applicable in a variety of several standard research and clinical problems, encountered in analysis of evoked potentials , automatic detection and analysis of sleep spindles in overnight EEG recordings , ERD/ERS , pharmaco-EEG  and epileptic seizures .
[Show abstract][Hide abstract] ABSTRACT: We evaluated cross-sectionally the associations of depression and anxiety with age, sex, duration of illness, educational level, degree of disability and treatment with interferon-beta in outpatients with relapsing-remitting multiple sclerosis (RRMS) during a clinically stable phase of their illness.
The depression status scored on the Beck Depression Inventory (BDI), the symptoms of anxiety assessed using the State Trait Anxiety Inventory (STAI) and the level of disability measured by the Expanded Disability Status Scale (EDSS) were quantified in 86 consecutive RRMS patients.
Linear regression analyses indicated that EDSS was independently (P < 0.001) associated with BDI and STAI and accounted for 15.7% and 18.5% of the variance in BDI and STAI respectively. The former association retained its statistical significance in multiple regression models adjusting for demographic and clinical characteristics.
Disability status is an independent but moderate determinant of depression and anxiety in MS patients.
[Show abstract][Hide abstract] ABSTRACT: Twenty-two patients with major depressive disorder, 11 of them with melancholic features, and 11 controls were investigated with CANTAB subtests focusing in visual memory/learning and executive functions. Melancholic patients performed worse than the other groups in all tasks and manifested a significant impairment in set shifting. The results are discussed in association with prefrontal dysfunction.
European Psychiatry 10/2006; 21(6):361-3. DOI:10.1016/j.eurpsy.2006.03.008 · 3.44 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: In the present paper, a new methodological approach, for the classification of first episode schizophrenic patients (FES) against normal controls, is proposed. The first step of the methodology applied is the feature extraction, which is based on the combination of the multivariate autoregressive model with the simulated annealing technique, in order to extract optimum features, in terms of classification rate. The classification, as the second step of the methodology, is implemented by means of an artificial neural network (ANN) trained with the back-propagation algorithm under "leave-one-out cross-validation". The ANN is a multi-layer perceptron, the architecture of which, is selected after a detailed search. The proposed methodology has been applied for the classification of FES patients and normal controls using as input signals the Intracranial current sources obtained by the inversion of ERPs using an algebraic reconstruction technique. Results by implementing the proposed methodology provide classification rates of up to 93.1%
[Show abstract][Hide abstract] ABSTRACT: In the present study an attempt was made to focus in the differences between Obsessive-Compulsive Disorder (OCD) patients and healthy controls, as reflected by the P600 component of event-related potential (ERP) signals, to locate brain areas that may be related to Working Memory (WM) deficits. Neuropsychological research has yielded contradicting results regarding WM in OCD. Eighteen patients with OCD symptomatology and 20 normal controls (age and sex matched) were subjected to a computerized version of the digit span Wechsler test. EEG activity was recorded from 15 scalp electrodes (leads). A dedicated computer software was developed to read the ERP signals and to calculate features related to the ERP P600 component (500-800 ms). Nineteen features were generated, from each ERP-signal and each lead, and were employed in the design of the Probabilistic Neural Network (PNN) classifier. Highest single-lead precision (86.8%) was found at the Fp2 and C6 leads. When the output from all single-lead PNN classifiers fed a Majority Vote Engine (MVE), the system classified correctly all subjects, providing a powerful classification scheme. Findings indicated that OCD patients differed from normal controls at the prefrontal and temporo-central brain regions.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 02/2005; 4:3994-7. DOI:10.1109/IEMBS.2005.1615337
[Show abstract][Hide abstract] ABSTRACT: The analysis of the P600 component of Event-related Potentials (ERPs) has attracted attention due to its relation to covert cognitive mechanisms, in connection to memory processes. The component may often be low-amplitude, compared to other components such as the P300. Independent component analysis (ICA) techniques have been successfully applied in ERP processing, in the framework of blind source separation (BSS) for unmixing recorded potentials into a sum of temporally independent and spatially fixed components. In the present work ICA was used for reconstructing averaged ERPs in the time window of the P600 component, selecting a subset of independent components' projections to the original electrode recording positions. The selection is based on two empirical criteria, selecting the projection that reconstructs a P600 nearest temporally to the original P600, or selecting the projection combination - up to a preselected maximum number of combined projections providing maximum reconstructed P600 amplitude. The techniques are tested on ERPs recorded from healthy subjects and psychiatric patients, notably improving the differentiation of the two groups, based on either the amplitude or the latency of the reconstructed P600 component, in comparison to results achieved using the original ERPs.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 02/2004; 1:80-3. DOI:10.1109/IEMBS.2004.1403095
[Show abstract][Hide abstract] ABSTRACT: Oxidative stress is an important mechanism of cell death in Parkinson's disease (PD) and brain ischemia. Vitamins C, E and A are important antioxidants and deficiency of these agents has been implicated in the mechanisms of atherosclerosis. We measured the levels of the above antioxidant vitamins in 44 patients with PD, 12 patients with vascular parkinsonism (VP), 11 patients with other parkinsonism syndromes of various causes and 39 controls. Vitamin A levels did not differ between groups. Vitamins C and E were found decreased in VP, while they were normal in PD indicating low levels of antioxidant vitamins in VP and stressing the necessity of maintaining sufficient dietary intake of these agents in the elderly.
Journal of the Neurological Sciences 11/2003; 215(1-2):51-5. DOI:10.1016/S0022-510X(03)00184-9 · 2.26 Impact Factor