The http://www.selleckchem.com/products/ABT-263.html data were high-pass filtered (cutoff, 128 s) to remove low-frequency drifts, and temporal autocorrelations were modeled using an AR(1) process. Model estimation was carried

out in two stages. First, subject-specific beta values (regression coefficients) were estimated for each time point and condition in a voxel-wise manner. From these first-level models, brain regions involved in evidence accumulation were identified by correlating fMRI activation time courses with model-based temporal profiles that estimated the amount of evidence integrating at each time point. These time series were convolved with a canonical hemodynamic response function selleck (HRF) and then used to weight each of the 14 fMRI time points for each condition of interest (three, four, and five sniffs) with its corresponding integration value, yielding a contrast image, or statistical parametric map, of temporal integration. In a second (random-effects) stage, the resulting subject-specific contrast images were entered into a one-sample t test, constituting a group-level statistical map, to identify brain

regions potentially exhibiting temporal integration. All voxels with significant activation (p < 0.001 uncorrected) were considered for further analysis. For each region identified in this manner, time series plots were computed by averaging fMRI activity across all contiguous voxels significantly activated at p < 0.005 for each of the 14 time bins. Reported significant activations in OFC were corrected for multiple comparisons using small-volume correction, based on spheres of 10 mm radius centered on previously published coordinates (Gottfried and Zald, 2005). This approach allowed us to investigate how temporal activity varied in a priori regions of interest, including

aPC, pPC, and OFC, which have been previously implicated before in fMRI studies of olfactory perceptual processing (Howard et al., 2009; Zelano et al., 2011). For this analysis, the realigned, slice-time corrected, and normalized, but unsmoothed, fMRI data were used to obtain raw time series on a voxel-by-voxel basis, thereby minimizing the influence of neighboring voxels. ROIs were structurally defined on the subject-averaged T1 structural scan using MRIcron (http://www.cabiatl.com/mricro/mricron/index.html). For the putative olfactory OFC, a sphere of 10 mm radius was drawn around the region’s locus (Gottfried and Zald, 2005), delimited to gray matter using an MRIcron filter (threshold, 90–180; arbitrary units), yielding a bilateral ROI of volume 5,184 mm3. Bilateral posterior and anterior piriform cortex ROIs were defined using prior landmarks (Howard et al., 2009; Zelano et al., 2011), yielding volumes of 2,106 and 1,485 mm3, respectively.