PMC:4620161 / 62828-64279 JSONTXT

{"project":"0_colil","denotations":[{"id":"26578853-22982104-358077","span":{"begin":39,"end":43},"obj":"22982104"},{"id":"26578853-23473935-358078","span":{"begin":589,"end":593},"obj":"23473935"}],"text":"A multivariate approach (Zhang et al., 2012) was previously proposed, analogous to our method except for the following differences. It was demonstrated among the voxels within only five structurally pre-defined regions; smoothing the estimated HDR from each subject by a Gaussian kernel and imposing regularization on the smoothed HDR were performed to improve the temporal continuities of the HDR; and group analysis was run through multivariate testing of one-sample or pair-wise comparisons among conditions, equivalent to MVT (2a or 2b) discussed here. Another approach (Zhang et al., 2013) assumed that the HDR under each condition would only vary in amplitude and latency across subjects; that is, the HDR shape was presumed same across all subjects. Specifically, the HDR curve for each condition was characterized at the group level by two parameters: one was of interest (amplitude) and the other of no interest (delay). In addition, the HDR shape (fixed across subjects) was modeled by cubic splines plus their time derivatives. Once the amplitude was estimated for each subject in a one-tier model that incorporated both within- and across-subject variances, a second round of group analysis was performed only on the amplitudes (ignoring the delay) through typical one-sample or paired t-test to make inference about a condition or contrast. The approach was demonstrated among the voxels within only three structurally predefined regions."}

{"project":"TEST0","denotations":[{"id":"26578853-39-47-358077","span":{"begin":39,"end":43},"obj":"[\"22982104\"]"},{"id":"26578853-32-40-358078","span":{"begin":589,"end":593},"obj":"[\"23473935\"]"}],"text":"A multivariate approach (Zhang et al., 2012) was previously proposed, analogous to our method except for the following differences. It was demonstrated among the voxels within only five structurally pre-defined regions; smoothing the estimated HDR from each subject by a Gaussian kernel and imposing regularization on the smoothed HDR were performed to improve the temporal continuities of the HDR; and group analysis was run through multivariate testing of one-sample or pair-wise comparisons among conditions, equivalent to MVT (2a or 2b) discussed here. Another approach (Zhang et al., 2013) assumed that the HDR under each condition would only vary in amplitude and latency across subjects; that is, the HDR shape was presumed same across all subjects. Specifically, the HDR curve for each condition was characterized at the group level by two parameters: one was of interest (amplitude) and the other of no interest (delay). In addition, the HDR shape (fixed across subjects) was modeled by cubic splines plus their time derivatives. Once the amplitude was estimated for each subject in a one-tier model that incorporated both within- and across-subject variances, a second round of group analysis was performed only on the amplitudes (ignoring the delay) through typical one-sample or paired t-test to make inference about a condition or contrast. The approach was demonstrated among the voxels within only three structurally predefined regions."}

{"project":"2_test","denotations":[{"id":"26578853-22982104-38285066","span":{"begin":39,"end":43},"obj":"22982104"},{"id":"26578853-23473935-38285067","span":{"begin":589,"end":593},"obj":"23473935"}],"text":"A multivariate approach (Zhang et al., 2012) was previously proposed, analogous to our method except for the following differences. It was demonstrated among the voxels within only five structurally pre-defined regions; smoothing the estimated HDR from each subject by a Gaussian kernel and imposing regularization on the smoothed HDR were performed to improve the temporal continuities of the HDR; and group analysis was run through multivariate testing of one-sample or pair-wise comparisons among conditions, equivalent to MVT (2a or 2b) discussed here. Another approach (Zhang et al., 2013) assumed that the HDR under each condition would only vary in amplitude and latency across subjects; that is, the HDR shape was presumed same across all subjects. Specifically, the HDR curve for each condition was characterized at the group level by two parameters: one was of interest (amplitude) and the other of no interest (delay). In addition, the HDR shape (fixed across subjects) was modeled by cubic splines plus their time derivatives. Once the amplitude was estimated for each subject in a one-tier model that incorporated both within- and across-subject variances, a second round of group analysis was performed only on the amplitudes (ignoring the delay) through typical one-sample or paired t-test to make inference about a condition or contrast. The approach was demonstrated among the voxels within only three structurally predefined regions."}