Name
Title | ||
|---|---|---|
Statistical parametric mapping applied to an autoradiographic study of cerebral activation during treadmill walking in rats. |
Abstract | ||
|---|---|---|
Autoradiographs are conventionally analyzed by a region-of-interest (ROI) analysis. However, definition of ROIs on an image set is labor intensive, is subject to potential inter-rater bias, and is not well suited for anatomically variable structures that may not consistently correspond to specific ROIs. Most importantly, the ROI method is poorly suited for whole-brain analysis, where one wishes to detect all activations resulting from an experimental paradigm. A system developed for analysis of imaging data in humans, Statistical Parametric Mapping (SPM), avoids some of these limitations but has not previously been adapted as a tool for the analysis of autoradiographs. Here, we describe the application of SPM to an autoradiographic data set mapping cerebral activation in rats during treadmill walking. We studied freely moving, non-tethered rats that received injections of the cerebral blood flow tracer [14C]-iodoantipyrine, while they were performing a treadmill task (n = 7) or during a quiescent control condition (n = 6). Results obtained with SPM were compared to those previously reported using a standard ROI-based method of analysis [J. Cereb. Blood Flow Metab. 23(2003) 925]. The SPM method confirmed most areas detected as significant using the ROI approach. However, in the subcortex, SPM detected additional significant regions that, because of their irregular structures, fell short of statistical significance when analyzed by ROI. The SPM approach offers the ability to perform a semi-automated whole-brain analysis, and coupled with autoradiography, provides an effective means to globally localize functional activity in small animals. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1016/j.neuroimage.2004.05.014 | NeuroImage |
Keywords | DocType | Volume |
Statistical parametric mapping,Autoradiography,Cerebral blood flow,Rats | Journal | 23 |
Issue | ISSN | Citations |
1 | 1053-8119 | 10 |
PageRank | References | Authors |
1.02 | 1 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peter T. Nguyen | 1 | 10 | 1.02 |
| Daniel P Holschneider | 2 | 12 | 1.40 |
| Jean-Michel I. Maarek | 3 | 10 | 1.02 |
| Jun Yang | 4 | 10 | 1.02 |
| Mark A. Mandelkern | 5 | 10 | 1.02 |