Inter-subject alignment of human cortical anatomy using functional connectivity

Abstract

Inter-subject alignment of functional MRI (fMRI) data is necessary for group analyses. The standard approach to this problem matches anatomical features of the brain, such as major anatomical landmarks or cortical curvature. Precise alignment of functional cortical topographies, however, cannot be derived using only anatomical features. We propose a new inter-subject registration algorithm that aligns intra-subject patterns of functional connectivity across subjects. We derive functional connectivity patterns by correlating fMRI BOLD time-series, measured during movie viewing, between spatially remote cortical regions. We validate our technique extensively on real fMRI experimental data and compare our method to two state-of-the-art inter-subject registration algorithms. By cross-validating our method on independent datasets, we show that the derived alignment generalizes well to other experimental paradigms.

Keywords: Functional connectivity; Inter-subject registration; Surface-based methods.

Figure 1

Extrinsic and intrinsic systems. For reference, images of the sulcal anatomy on the inflated cortical surfaces are provided (IPS—intraparietal sulcus; LOS—lateral occipital sulcus; STS—superior temporal sulcus; CntlS—central sulcus; CingS—cingulate sulcus; CalcS—calcarine sulcus; CollS—collateral sulcus; OTS—occipitotemporal sulcus).

Figure 2

Left hemisphere plots of average inter-subject time-series correlation for the second half of the movie under various alignments. For the function-based alignments, the first half of the movie session was used as the training set. The top images show the sulcal anatomy on the inflated cortical surfaces (IPS—intraparietal sulcus; LOS—lateral occipital sulcus; STS—superior temporal sulcus; CntlS—central sulcus; CingS—cingulate sulcus; CalcS—calcarine sulcus; CollS—collateral sulcus; OTS—occipitotemporal sulcus).

Figure 3

Right hemisphere plots of average inter-subject time-series correlation for the second half of the movie under various alignments. For the function-based alignments, the first half of the movie was used as the training set. The top images show the sulcal anatomy on the inflated cortical surfaces (IPS—intraparietal sulcus; LOS—lateral occipital sulcus; STS—superior temporal sulcus; CntlS—central sulcus; CingS—cingulate sulcus; CalcS— calcarine sulcus; CollS—collateral sulcus; OTS—occipitotemporal sulcus).

Figure 4

Inter-subject correlation of time-series results restricted to different brain systems and under various alignments.

Figure 5

Left hemisphere plots of average inter-subject functional connectivity vector correlation for the second half of the movie under various alignments. For the function-based alignments, the first half of the movie was used as the training set. The top images show the sulcal anatomy on the inflated cortical surfaces (IPS—intraparietal sulcus; LOS— lateral occipital sulcus; STS—superior temporal sulcus; CntlS—central sulcus; CingS— cingulate sulcus; CalcS—calcarine sulcus; CollS—collateral sulcus; OTS—occipitotemporal sulcus).

Figure 6

Right hemisphere plots of average inter-subject functional connectivity vector correlation for the second half of the movie under various alignments. For the function-based alignments, the first half of the movie was used as the training set. The top images show the sulcal anatomy on the inflated cortical surfaces (IPS—intraparietal sulcus; LOS— lateral occipital sulcus; STS—superior temporal sulcus; CntlS—central sulcus; CingS— cingulate sulcus; CalcS—calcarine sulcus; CollS—collateral sulcus; OTS—occipitotemporal sulcus).

Figure 7

Inter-subject correlation of functional connectivity vector results restricted to different brain systems and under various alignments.

Figure 8

Category-specific between-subject classification accuracies under the various alignments. Within-subject classification accuracies are also included for reference.

Figure 9

Confusion matrices (averaged over subjects) for 7-category classification. (a) Within-subject classification (WSC); (b) Between-subject classification, anatomical alignment (BSC, Anat); (c) Between-subject classification, FTSA (BSC, FTSA); (d) Between-subject classification, FCA (BSC, FCA).

Figure 10

Warp consistency analysis between within-stimulus and across-stimulus alignments. (a) Angle between warp tangent vectors; and (b) Normalized warp consistency measure.