Neurodegenerative diseases target large-scale human brain networks

Abstract

During development, the healthy human brain constructs a host of large-scale, distributed, function-critical neural networks. Neurodegenerative diseases have been thought to target these systems, but this hypothesis has not been systematically tested in living humans. We used network-sensitive neuroimaging methods to show that five different neurodegenerative syndromes cause circumscribed atrophy within five distinct, healthy, human intrinsic functional connectivity networks. We further discovered a direct link between intrinsic connectivity and gray matter structure. Across healthy individuals, nodes within each functional network exhibited tightly correlated gray matter volumes. The findings suggest that human neural networks can be defined by synchronous baseline activity, a unified corticotrophic fate, and selective vulnerability to neurodegenerative illness. Future studies may clarify how these complex systems are assembled during development and undermined by disease.

Figure 1. Study design schematic

Patient groups were compared to HC1 subjects to determine syndromic atrophy patterns. From these maps, distinct seed ROIs were extracted (see Table S2) and used in functional (HC2) and structural (HC1) correlation analyses. These experiments determined the functional intrinsic connectivity networks (ICNs 1-5) and structural covariance networks (SCNs 1-5) associated with each of the five syndrome-related seeds. ICN and SCN maps were then compared to all five syndromic atrophy maps to derive GOF scores, yielding 50 total scores ((5 ICN maps×5 atrophy maps) + (5 SCN maps×5 atrophy maps)), which are summarized in Figure 5.

Figure 2. Convergent syndromic atrophy, healthy ICN, and healthy structural covariance patterns

(A) Five distinct clinical syndromes showed dissociable atrophy patterns, whose cortical maxima (circled) provided seed ROIs for ICN and SC analyses. (B) ICN mapping experiments identified five distinct networks anchored by the five syndromic atrophy seeds. (C) Healthy subjects further showed gray matter volume covariance patterns that recapitulated results shown in (A) and (B). For visualization purposes, results are shown at P < 0.00001 uncorrected (A & C) and P < 0.001 corrected height and extent thresholds (B). In A-C, results are displayed on representative sections of the MNI template brain. In coronal and axial images, the left side of the image corresponds to the left side of the brain. ANG = angular gyrus; FI = frontoinsula; IFGoper = inferior frontal gyrus, pars opercularis; PMC = premotor cortex; TPole = temporal pole.

Figure 3. Detailed network mapping of the right frontal insula, a focus of neurodegeneration in bvFTD

(A) Reduced gray matter volume in bvFTD vs. controls (P < 0.05, whole brain FWE corrected) occurs within regions showing (B) intrinsically correlated BOLD signals in controls (P < 0.001, whole-brain corrected height and extent thresholds) and (C) structural covariance in controls (P < 0.05, whole brain FWE corrected). These distributed spatial maps overlap (D) within a “network” that reflects known primate neuroanatomical connections. AI = anterior insula, dACC = dorsal anterior cingulate cortex, dlPFC = dorsolateral prefrontal cortex, dPI = dorsal posterior insula, FO = frontal operculum, MDthal = mediodorsal thalamus, SLEA = sublenticular extended amygdala, vlPFC = ventrolateral prefrontal cortex, vmStr = ventromedial striatum.

Figure 4. Relationship between intrinsic functional connectivity and structural covariance in the healthy human brain

(A) The bvFTD-associated group-level ICA map (parent seed = right FI) was used to extract ROI BOLD signal timeseries from a single representative control subject (B). These timeseries reveal the correlated functional signals arising from the right and left FI and the right dACC, primary neurodegeneration foci in bvFTD. These same ROIs were applied to each of the 65 HC1 subjects to extract and plot local gray matter intensities for each ROI against the subject pool, randomly ordered on the x-axis to illustrate the structural covariance (C). Plots of R FI gray matter intensity against L FI and dACC intensities reveal the strength of within-network gray matter correlations (D). a.u. = arbitrary units.

Figure 5. Quantitative spatial similarity of each ICN and structural covariance map with the five syndromic atrophy maps

Binary spatial templates derived from the five atrophy maps were used to generate “goodness-of-fit” (GOF) scores that reflect how well the healthy intrinsic functional (A, B) and structural (C) correlation maps fit each syndrome's atrophy pattern. GOF was defined as the difference between the t-score mean within vs. outside each atrophy template, such that each ICN or structural correlation map had one “source” GOF score, for the atrophy map used to derive its seed, and four “other” scores for the four remaining atrophy templates. This procedure revealed higher GOF for source vs. other maps for each seed at the group level (A, C). At the single-subject level (B), all ICNs showed significantly greater GOF to source vs. other atrophy maps. Data are shown as mean +/- s.e.m (where applicable). * P < 0.05. ** P < 0.0005.

Figure 6. Neurodegenerative syndromes target anatomically dissociable brain systems

Colored regions highlight voxels found within associated maps of syndromic atrophy (p < 0.0001, uncorrected; patients vs. controls), intrinsic functional connectivity (ICA-derived; p < 0.01, corrected; healthy controls only), and structural covariance (p < 0.0001, uncorrected; healthy controls only). The color code (bottom) refers to the atrophy map used to derive the relevant seed ROI. These results, statistically thresholded to inflate potential overlap across the five 3-map datasets, illustrate the dissociable nature of the targeted brain systems.