"2014-09-08+02:00"^^ . "2014-12-31+01:00"^^ . . . . "Funk\u010Dn\u00ED magnetick\u00E1 rezonance (fMRI) je metoda, kter\u00E1 umo\u017E\u0148uje studovat vztahy mezi aktivovan\u00FDmi oblastmi mozku, tzv. konektivitu. Jednou z nejpokro\u010Dilej\u0161\u00EDch metod vyvinut\u00FDch k anal\u00FDze efektivn\u00ED konektivity ve fMRI je dynamick\u00E9 kauz\u00E1ln\u00ED modelov\u00E1n\u00ED (DCM), kter\u00E9 kombinuje neurobiologicky p\u0159ijateln\u00FD model dynamiky neur\u00E1ln\u00EDch populac\u00ED a biofyzik\u00E1ln\u011B v\u011Brohodn\u00FD dop\u0159edn\u00FD model, popisuj\u00EDc\u00ED transformaci neur\u00E1ln\u00ED aktivity na m\u011B\u0159en\u00FD sign\u00E1l. K validn\u00EDmu pou\u017Eit\u00ED v\u0161ak DCM vy\u017Eaduje velmi konkr\u00E9tn\u00ED definici hypot\u00E9zy. C\u00EDlem projektu je vyvinout metodiku, kter\u00E1 usnadn\u00ED specifikaci DCM model\u016F a zkvalitn\u00ED interpretaci v\u00FDsledk\u016F. K tomu vyu\u017Eijeme dopl\u0148uj\u00EDc\u00ED informace z\u00EDskan\u00E9 pomoc\u00ED anal\u00FDzy nez\u00E1visl\u00FDch komponent a Grangerovy kauzality. Projekt tak\u00E9 p\u0159isp\u011Bje k lep\u0161\u00EDmu pochopen\u00ED souvislost\u00ED mezi koncepty funk\u010Dn\u00ED a efektivn\u00ED konektivity. Efektivn\u011Bj\u0161\u00ED (a snadn\u011Bj\u0161\u00ED a validn\u011Bj\u0161\u00ED) pou\u017E\u00EDv\u00E1n\u00ED DCM umo\u017En\u00ED neurov\u011Bdc\u016Fm vy\u0159e\u0161it v\u00EDce (a l\u00E9pe) neurov\u011Bdn\u00EDch ot\u00E1zek a m\u016F\u017Ee p\u0159isp\u011Bt k v\u00FDvoji neurov\u011Bd jako takov\u00FDch." . . . . . . "Comparison and inference of methods for evaluation of functional and effective connectivity in fMRI"@en . . "0"^^ . "23"^^ . "23"^^ . "http://www.isvav.cz/projectDetail.do?rowId=GAP103/12/0552"^^ . . "Functional magnetic resonance imaging (fMRI) gives us the possibility to study relations between activated brain areas, i.e. brain connectivity. The most advanced method for investigation of effective connectivity is dynamic causal modeling (DCM), which combines neurobiologically plausible model of neural population dynamics and a biophysically plausible forward model that describes the transformation from neural activity to the measured signal. However, DCM requires very specific hypothesis to valid use. Therefore, the aim of the proposed project is to develop procedure that will guide specification of DCM models and improve subsequent inference. For this purpose, additional information obtained by independent component analysis and Granger causality modeling will be used. The project will contribute to better understanding the relations between concepts of functional and effective connectivity. More effective (and easy and valid) use of DCM will enable neuroscientists to resolve more (and better) experimental questions and could enhance neuroscience research."@en . "2013-06-12+02:00"^^ . "1"^^ . . "1"^^ . . . . . . "Srovn\u00E1n\u00ED a inference metod hodnocen\u00ED funk\u010Dn\u00ED a efektivn\u00ED konektivity ve fMRI" . "functional MRI cognitive neuroscience dynamic causal modelling functional connectivity effective connectivity independent component analysis Granger causality"@en . . "GAP103/12/0552" . . . "2012-01-01+01:00"^^ .