IEEE transactions on bio-medical engineering
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IEEE Trans Biomed Eng · Aug 2007
Predictions of psychophysical measurements for sinusoidal amplitude modulated (SAM) pulse-train stimuli from a stochastic model.
Two approaches have been proposed to reduce the synchrony of the neural response to electrical stimuli in cochlear implants. One approach involves adding noise to the pulse-train stimulus, and the other is based on using a high-rate pulse-train carrier. Hypotheses regarding the efficacy of the two approaches can be tested using computational models of neural responsiveness prior to time-intensive psychophysical studies. ⋯ Changes in dynamic range (DR) and intensity discrimination are compared with that observed for noise-modulated pulse-train stimuli. Modulation frequency discrimination is also studied as a function of stimulus level and pulse rate. Results suggest that high rate carriers may positively impact such psychophysical measures.
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IEEE Trans Biomed Eng · Aug 2007
Estimation of the hemodynamic response of fMRI Data using RBF neural network.
Functional magnetic resonance imaging (fMRI) is an important technique for neuroimaging. The conventional system identification methods used in fMRI data analysis assume a linear time-invariant system with the impulse response described by the hemodynamic responses (HDR). However, the measured blood oxygenation level-dependent (BOLD) signals to a particular processing task (for example, rapid event-related fMRI design) show nonlinear properties and vary with different brain regions and subjects. ⋯ The equivalence of the proposed method to the existing Volterra series method has been demonstrated. It is shown that the first- and second-order Volterra kernels could be deduced from the parameters of the RBF neural network. Studies on both simulated (using Balloon model) as well as real event-related fMRI data show that the proposed method can accurately estimate the HDR of the brain and capture the variations of the HDRs as a function of the brain regions and subjects.