Ertugrul Saatci

Disturbance in long distance gamma coherence in bipolar disorder

The aim of this study was to investigate long distance event-related gamma (28-48 Hz) coherence in mania before and after valproate monotherapy. Gamma coherence in response to visual oddball paradigm in ten medication-free, manic patients was studied before and after six weeks of valproate monotherapy in comparison to ten controls. Inter-hemispheric F(3)-F(4), C(3)-C(4), T(3)-T(4), T(5)-T(6), P(3)-P(4), O(1)-O(2) and intra-hemispheric F(3)-P(3), F(4)-P(4), F(3)-T(5), F(4)-T(6), F(3)-O(1), F(4)-O(2), C(3)-O(1), C(2)-O(4) electrode pairs were included in the analysis. Repeated measures ANOVA revealed a significant difference between groups with regard to pre-treatment coherence values (p: 0.018). The coherence to the target stimuli at the right fronto-temporal location was significantly reduced by 35.41% in the patients compared to controls (p: 0.003). Patients showed significantly lower pre-treatment coherence values in response to non-target stimuli compared to controls at the right fronto-temporal (28.51%, p: 0.004), right fronto-occipital (23.71%, p: 0.024), and right centro-occipital (25.69%, p: 0.029) locations. After six weeks of valproate monotherapy, manic symptoms improved significantly. Post-treatment change in target and non-target coherence values was statistically non-significant. EEG coherence is a measure of functional connectivity in the brain. Event-related gamma oscillations are essential for brain electrical activity. The results show that acute mania presents right sided long distance connectivity disturbance, thus pointing to the potential importance of measuring oscillatory responses in the search for consistent neurobiological markers in such a complicated condition as bipolar disorder.

An FPGA implementation Of 2-D CNN gabor-type filter

A field programmable gate array (FPGA) implementation of the Gabor-type filter is presented. The implementation uses the forward Euler approximation with optimal step size to solve the CNN cell-state equation. The FPGA is implemented on Xilinx Spartan XC3S400 device using 219 slices. An image of dimension 60 times 60 can be processed without using any external RAM only with the block RAM.

Cyclostationary Analysis of Respiratory Signals with Application of Rate Determination

Respiratory signals are periodic-like signals where the noisy periodic pattern repeats itself. Therefore, based on a stationarity assumption, autocorrelation function contains noisy cycles in time-lag with the same rate as the respiration rate. In this work, cyclostationarity test is performed on the respiratory signals in order to determine cyclic characteristics of the time varying autocorrelation function. Our specific aim is to check whether the cycle period in time corresponds to the respiration rate. Lung simulator was used to generate the respiratory signals. Time varying autocorrelation variance was computed by using both the modified windowed, and the blocked signal methods. Our simulations resulted that the cycle period was the same as the respiration period. Moreover, we observed that cyclic frequencies corresponded to the respiratory rate and its harmonics.

Determination of the minimum sampling frequency in bandpass sampling by geometric approach and geometric programming

This paper presents a simple and fast approach to find a minimum sampling frequency for multi-band signals. Instead of neighbor and boundary conditions, constraints on the sampling frequency were derived by using the geometric approach to the bandpass sampling theorem. Reformulation of the constraints on the minimum sampling frequency enabled to represent the problem as an optimization problem which was structured by the geometric programming and mixed-integer nonlinear programming methods. The convex optimization problem was then solved by the proposed algorithm applying interior point approach in the line search framework. It was demonstrated that this unified structure directly linked the geometric approach of the bandpass sampling theorem to the optimization problem. The proposed method was verified through numerical simulations in terms of the minimum sampling frequency and the computational efficiency. Results illustrated the feasibility of the geometric approach and the proposed algorithm in the determination of the minimum sampling frequency by providing the savings in the number of iterations and the decrease in the valid minimum sampling frequency.