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In this paper we use the modified and integrated version of the balloon model in the analysis of fMRI data. We propose a new state space model realization for this balloon model and represent it with the standard A,B,C and D matrices widely used in system theory. A second order Padé approximation with equal numerator and denominator degree is used for the time delay approximation in the modeling...
A new adaptive motor controller was constructed, and tested on the control of a 2-wheeled balancing robot in simulation and real world. The controller consists of a feedback (PD) controller and a cerebellar neuronal network model. The structure of the cerebellar model was configured based upon known anatomical neuronal connection in the cerebellar cortex. Namely it consists of 120 granular (Gr) cells,...
The relation between neural electrical activity and oxygen consumption is the key issue in almost all brain image modalities based on perfusion. Despite the large amount of physiological information available in the literature about the processes involved in neural activation, a practical, tractable and simultaneously accurate mathematical model to describe this relation is needed. The sodium-potassium...
The CyberWorkstation (CW) is an advanced cyber-infrastructure for Brain-Machine Interface (BMI) research. It allows the development, configuration and execution of BMI computational models using high-performance computing resources. The CW's concept is implemented using a software structure in which an “experiment engine” is used to coordinate all software modules needed to capture, communicate and...
This paper presents two alternative approaches to characterize the pharmacodynamics of propofol anesthesia in children, using State Entropy as a clinical end point. The first approach is the traditional approach where the pharmacodynamic model is described in terms of an effect-site equilibration rate constant and the Hill equation. In the second approach (the monitor-decoupled approach) the dynamics...
The identification of signal components in electroencephalographic (EEG) data originating from neural activities is a long standing problem in neuroscience. This area has regained new attention due to the possibilities of multi-dimensional signal processing. In this work we analyze measured visual-evoked potentials on the basis of the time-varying spectrum for each channel. Recently, parallel factor...
Transcranial magnetic stimulation (TMS) is a technique for brain stimulation using rapidly changing magnetic fields generated by coils. It has been established as an effective stimulation technique to treat patients suffering from damaged brain functions. Although TMS is known to be painless and noninvasive, it can also be harmful to the brain by incorrect focusing and excessive stimulation which...
The algorithm of epileptic seizure is at the core of any implantable device aimed to treat the symptoms of this disorder. A training free (on line) epileptic seizure detection algorithm for implantable device utilizing Autoregressive (AR) model parameters is developed and studied. Pre-recorded (off line) epileptic seizure data are used to estimate the internal parameters of an AR model prior and following...
Our objective is to analyze EEG signals recorded with depth electrodes during seizures in patients with drug-resistant epilepsy. Usually, different phases are observed during the seizure process, including a fast onset activity (FOA). We aim to determine how cerebral structures get involved during this FOA, in particular whether some structure can “drive” some other structures. This paper focuses...
The topologically correct and geometrically accurate reconstruction of the cerebral cortex from magnetic resonance (MR) images is an important step in quantitative analysis of the human brain structure, e.g. in cortical thickness measurement studies. Limited resolution of MR images, noise, intensity inhomogeneities, and partial volume effects can all contribute to geometrical inaccuracies and topological...
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