| Full text | |
| Author(s): |
Sato, Joao R.
[1, 2]
;
Takahashi, Daniel Y.
[2, 3]
;
Arcuri, Silvia M.
[4]
;
Sameshima, Koichi
[2, 3]
;
Morettin, Pedro A.
[1]
;
Baccala, Luiz A.
[3, 5]
Total Authors: 6
|
| Affiliation: | [1] Univ Sao Paulo, Inst Math & Stat, Dept Stat, BR-05508 Sao Paulo - Brazil
[2] Univ Sao Paulo, Sch Med, Dept Radiol, NIF LIM44, BR-05508 Sao Paulo - Brazil
[3] Univ Sao Paulo, Bioinformat Grad Program, BR-05508 Sao Paulo - Brazil
[4] Kings Coll London, Inst Psychiat, Neuroimaging Sect, London - England
[5] Univ Sao Paulo, Escola Politecn, Dept Telecommun & Control Engn, BR-05508 Sao Paulo - Brazil
Total Affiliations: 5
|
| Document type: | Journal article |
| Source: | Human Brain Mapping; v. 30, n. 2, p. 452-461, Feb. 2009. |
| Field of knowledge: | Health Sciences - Medicine |
| Web of Science Citations: | 80 |
| Abstract | |
Functional magnetic resonance imaging (fMRI) has become an important tool in Neuroscience due to its noninvasive and high spatial resolution properties compared to other methods like PET or EEG. Characterization of the neural connectivity has been the aim of several cognitive researches, as the interactions among cortical areas lie at the heart of many brain dysfunctions and mental disorders. Several methods like correlation analysis, structural equation modeling, and dynamic causal models have been proposed to quantify connectivity strength. An important concept related to connectivity modeling is Granger causality, which is one of the most popular definitions for the measure of directional dependence between time series. In this article, we propose the application of the partial directed coherence (PDC) for the connectivity analysis of multisubject fMRI data using multivariate bootstrap. PDC is a frequency domain counterpart of Granger causality and has become a very prominent tool in EEG studies. The achieved frequency decomposition of connectivity is useful in separating interactions from neural modules from those originating in scanner noise, breath, and heart beating. Real fMRI dataset of six subjects executing a language processing protocol was used for the analysis of connectivity. (AU) | |
| FAPESP's process: | 03/10105-2 - Temporal series, analysis of dependency and applications in actuarial science and finance |
| Grantee: | Pedro Alberto Morettin |
| Support Opportunities: | PRONEX Research - Thematic Grants |
| FAPESP's process: | 05/56464-9 - Neuroscience Imaging Center at University of São Paulo Medical School |
| Grantee: | Giovanni Guido Cerri |
| Support Opportunities: | Inter-institutional Cooperation in Support of Brain Research (CINAPCE) - Thematic Grants |