Uniwersytet Jagielloński Collegium Medicum Zakład bioinformatyki i telemedycyny

COST

COST(2008-2011).

The COST BM0601 NeuroMath in the Department of Bioinformatics and Telemedicine was implemented the project “The role of dorsolateral prefrontal cortex in saccadic eye movement. Multiresolution analysis of event-related potentials using wavelet transform.” The main objective of the COST Action BM0601: Advanced Methods for the Estimate of Human Brain Activity and Conectivity (NeuroMath) is to increase the knowledge on the mathematical methods able to estimate the cortical activity and connectivity in the human brain from non invasive neuroelectric and hemodynamic measurements. Additional objectives include the developing of new techniques for the multimodal integration of neuroelectromagnetic and hemodynamic measurements, and their application in several contexts, from the study of human cortical activity during cognitive tasks to the field of the brain computer interface. Studies on voluntary eye movements have been largely focused on the relation between the dorsolateral prefrontal cortex, caudate nucleus, globus pallidus, substantia nigra pars reticulate and superior colliculus. This neuroanatomical circuit by serial inhibitory connections controls the oculomotor function of the saccadic omnipause and burst neurons (caudate inhibits the substantia nigra pars reticulata, which in turn inhibits the superior colliculus). Neuroanatomical studies measured cerebral blood flow has documented abnormalities in brain regions such as dorsolateral prefrontal cortex, caudate nucleus, globus pallidus for adults and children with ADHD. We analyzed such parameters of saccades as duration, amplitude, fixation, peak velocity, slope, sharpness, position profile, velocity profile, phase profile and relation between peak velocity and amplitude. In present research we analyzed event-related potentials by wavelet decomposition. We used the discrete wavelet transform DWT (Daubechies with 20 coefficients, i.e., Daub20, and Haar). The discrete wavelet transform (DWT) is an implementation of the wavelet transform using a discrete set of the wavelet scales and translations obeying some defined rules. In other words, this transform decomposes the signal into mutually orthogonal set of wavelets, which is the main difference from the continuous wavelet transform (CWT), or its implementation for the discrete time series sometimes called discrete-time continuous wavelet transform (DT-CWT). The NEUROMATH Action aimed to develop an European networks in the neuroscience field which, if possible, should become reference in Europe and contribute to the scientific development of the domain. Scientific research will address questions in the areas listed below. 1. Development of new techniques for the estimation of brain activity and connectivity One of the main objective of this area of research is to increase the knowledge about the accuracy that is possible to obtain for the estimation of brain activity from separate neuroelectric and hemodynamic non invasive recordings. In particular, the possibility is addressed to estimate the cortical activity in selected cortical regions of interest from non invasive scalp EEG recordings. This objective is fundamental since the activity of the brain is generated from the brain and not from the scalp, where it is usually represented. Definitive measure of estimation errors for cortical estimation from non-invasive EEG measurements are to be obtained. Another important goal of this area of research is to increase the knowledge about the estimation of the functional brain connectivity, i.e. how and how much particular regions of the brain cooperate together during cognitive and motor tasks.

We also participated in:

COST Action Action B27: Electric Neuronal Oscillations and Cognition (ENOC)

COST Action BM0605: Consciousness: A Transdisciplinary, Integrated Approach