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, 113 (2), 428-33

Metabolic Connectivity Mapping Reveals Effective Connectivity in the Resting Human Brain

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Metabolic Connectivity Mapping Reveals Effective Connectivity in the Resting Human Brain

Valentin Riedl et al. Proc Natl Acad Sci U S A.

Abstract

Directionality of signaling among brain regions provides essential information about human cognition and disease states. Assessing such effective connectivity (EC) across brain states using functional magnetic resonance imaging (fMRI) alone has proven difficult, however. We propose a novel measure of EC, termed metabolic connectivity mapping (MCM), that integrates undirected functional connectivity (FC) with local energy metabolism from fMRI and positron emission tomography (PET) data acquired simultaneously. This method is based on the concept that most energy required for neuronal communication is consumed postsynaptically, i.e., at the target neurons. We investigated MCM and possible changes in EC within the physiological range using "eyes open" versus "eyes closed" conditions in healthy subjects. Independent of condition, MCM reliably detected stable and bidirectional communication between early and higher visual regions. Moreover, we found stable top-down signaling from a frontoparietal network including frontal eye fields. In contrast, we found additional top-down signaling from all major clusters of the salience network to early visual cortex only in the eyes open condition. MCM revealed consistent bidirectional and unidirectional signaling across the entire cortex, along with prominent changes in network interactions across two simple brain states. We propose MCM as a novel approach for inferring EC from neuronal energy metabolism that is ideally suited to study signaling hierarchies in the brain and their defects in brain disorders.

Keywords: directional signaling; effective connectivity; energy metabolism; resting state; simultaneous PET/fMRI.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
MCM reveals EC in the human brain. (A) FC reveals undirected pathways of synchronous fMRI signal fluctuations between two regions, X and Y. For each subject, FC is calculated as the temporal correlation, [r] between the cluster time series. In our example, we identified FC pathways during conditions of eyes closed and eyes open. (B) In a next step, we identified EC (i.e., the directionality of signaling) in a given functional pathway. For each region, we calculated the spatial correlation, [r], between voxel FC and FDG values of simultaneously acquired fMRI and PET data. According to cellular recordings (see text), the majority of signaling-related energy is consumed postsynaptically, i.e., at the target region. Thus, MCM identifies afferent EC in the signaling pathway between region X and region Y.
Fig. 2.
Fig. 2.
Brain regions belonging to visual stream and prefrontal association networks. Spatial maps (P < 0.05, corrected) are projected onto the inflated cortical surface of a standard brain. Major networks of a recent 1,000-subject analysis are illustrated in the middle panel (top, lateral surface; bottom, medial surface) using different colors and serve as a reference for the assignment of each of our ROIs to its closest match. Reprinted from ref. . Ventral/dorsal visual stream ROIs include the CaS, StC, ExC, ITG, and SPL. Prefrontal association network ROIs include the PFCa, INS, PFCdl, MCC, and PFCvm. Table 1 lists the anatomic structures covered by each ROI. The CaS was chosen as the early visual region for further analyses, because it fully covers the cluster of greatest increase in metabolic activity during the eyes open condition from an earlier analysis (10).
Fig. 3.
Fig. 3.
FC pathways during the eyes closed and eyes open conditions. (A) Stable FC is seen between the CaS (image to the right of the graph) and all other visual regions (StC, ExC, ITG, and SPL) independent of condition (results of one-sample t tests; see text). (B) FC between the CaS and all regions of the salience network (purple) increases only during the eyes open condition (two-sample t tests; PFCa: P < 0.05; INS: P < 0.0005; MCC: P < 0.005). The two other regions (PFCdl and PFCvm) show no FC with the CaS (P > 0.1). Note that only salience regions INS and MCC show increased FC when a stringent Bonferroni correction is applied for possibly nine two-sample t tests in this FC analysis. Boxplots indicate median, 25th–75th percentiles (box), and extreme data points (whiskers).
Fig. 4.
Fig. 4.
EC between regions using MCM. (A) Stable bidirectional (bottom-up/top-down) signaling between the CaS and all other visual regions (StC, ExC, ITG, and SPL) and top-down modulation from the SPL (P < 0.0005) independent of condition. (B) All frontal regions of the salience network (purple) exert top-down modulation of the CaS only during the eyes open condition (PFCa: P < 0.0005; INS: P < 0.005; MCC: P < 0.05). Boxplots indicate median, 25th–75th percentiles (box), and extreme data points (whiskers).
Fig. S1.
Fig. S1.
Illustration of alignment between individual EPI and FDG-PET images in four subjects. Shown is the alignment between FDG-PET (gray) and EPI (red overlay) images in individual subject space after rigid-body coregistration. Note the full overlap between both imaging modalities in regions analyzed in this study, particularly occipital (axial slice), insular (coronal slice), and cingulate (saggital) cortices; however, typical signal dropouts owing to field inhomogeneity can be found in the medial inferior frontal cortex of the EPI images. Voxel coordinates: 50, 63, and 32.
Fig. S2.
Fig. S2.
Influence of voxel and ROI size on MCM results. (A) Varying ROI size of the target region during MCM calculation using an increasing z-value threshold (z > 3–7; light-blue to dark-blue bars) from initial ICA maps (2 × 2 × 2 mm). For comparison, we also calculated MCM on a larger voxel size (3 × 3 × 3 mm) at z > 3 (green bars). (B) Results of MCM calculation on 3 × 3 × 3 voxel size between the CaS and all other regions, corresponding to Fig. 4. Color coding: light green, bottom-up EC; dark green, top-down EC. Note that the directionality of all connections matches the results presented in Fig. 4. (C) Results of MCM calculation with varying target ROI sizes (see A) between the VISa and all other regions, corresponding to Fig. 4. Color coding: light-green to dark-green bars, z > 3–7. Note that the results correspond to MCM calculations presented in Fig. 4 up to z > 6, corresponding to approximately one-quarter of the original ROI size. Increasing variability of MCM occurs only at z > 7.

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