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For any connectivity study, it is important to determine whether correlations between two selected brain regions are statistically significant or only chance effects due to non\u2010specific correlations present throughout the data. In this report, we present a wavelet\u2010based non\u2010parametric technique for testing the null hypothesis that the correlations are typical of the data set and not unique to the regions of interest. This is achieved through spatiotemporal resampling of the data in the wavelet domain. Two functional MRI data sets were analysed: (1) Data from 8 healthy human subjects viewing a checkerboard image, and (2) \u201cNull\u201d data obtained from 3 healthy human subjects, resting with eyes closed. It was demonstrated that constrained resampling of the data in the wavelet domain allows construction of bootstrapped data with four essential properties: (1) Spatial and temporal correlations within and between slices are preserved, (2) The irregular geometry of the intracranial images is maintained, (3) There is adequate type I error control, and (4) Expected experiment\u2010induced correlations are identified. The limitations and possible extensions of the proposed technique are discussed. Hum. Brain Mapp. 23:1\u201325, 2004. \u00a9 2004 Wiley\u2010Liss, Inc.<\/jats:p>","DOI":"10.1002\/hbm.20045","type":"journal-article","created":{"date-parts":[[2004,6,16]],"date-time":"2004-06-16T22:01:06Z","timestamp":1087423266000},"page":"1-25","source":"Crossref","is-referenced-by-count":95,"title":["Spatiotemporal wavelet resampling for functional neuroimaging data"],"prefix":"10.1002","volume":"23","author":[{"given":"Michael","family":"Breakspear","sequence":"first","affiliation":[]},{"given":"Michael J.","family":"Brammer","sequence":"additional","affiliation":[]},{"given":"Ed T.","family":"Bullmore","sequence":"additional","affiliation":[]},{"given":"Pritha","family":"Das","sequence":"additional","affiliation":[]},{"given":"Leanne M.","family":"Williams","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2004,6,16]]},"reference":[{"key":"e_1_2_6_2_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.68.066202"},{"key":"e_1_2_6_3_1","doi-asserted-by":"crossref","first-page":"763","DOI":"10.1016\/S0730-725X(97)00135-5","article-title":"Generic brain activation in functional magnetic resonance imaging: A non\u2010parametric approach","volume":"15","author":"Brammer MJ","year":"1997","journal-title":"Magnet Reson Imag"},{"key":"e_1_2_6_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1388-2457(02)00051-2"},{"key":"e_1_2_6_5_1","doi-asserted-by":"publisher","DOI":"10.1006\/nimg.2002.1106"},{"key":"e_1_2_6_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-2789(03)00136-2"},{"key":"e_1_2_6_7_1","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-0193(1999)7:1<38::AID-HBM4>3.0.CO;2-Q"},{"key":"e_1_2_6_8_1","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1002\/1097-0193(200102)12:2<61::AID-HBM1004>3.0.CO;2-W","article-title":"Colored noise and computational inference in neurophysiological time series analysis: Resampling methods in time and wavelet domains","volume":"12","author":"Bullmore ET","year":"2001","journal-title":"Hum Brain Mapp"},{"key":"e_1_2_6_9_1","doi-asserted-by":"publisher","DOI":"10.1191\/0962280203sm339ra"},{"key":"e_1_2_6_10_1","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611970104"},{"key":"e_1_2_6_11_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.64.046128"},{"key":"e_1_2_6_12_1","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1038\/jcbfm.1993.4","article-title":"Functional connectivity: the principal component analysis of large (PET) data sets","volume":"13","author":"Friston KJ","year":"1993","journal-title":"J Cereb Blood Flow Metab"},{"key":"e_1_2_6_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1053-8119(03)00202-7"},{"key":"e_1_2_6_14_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0135058100"},{"key":"e_1_2_6_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1053-8119(03)00160-5"},{"key":"e_1_2_6_16_1","unstructured":"KingsburyN(2003): The 2\u2010D DWT. 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