The alteration landscape of the cerebral cortex

Abstract

Growing evidence is challenging the assumption that brain disorders are diagnostically clear-cut categories. Transdiagnostic studies show that a set of cerebral areas is frequently altered in a variety of psychiatric as well as neurological syndromes. In order to provide a map of the altered areas in the pathological brain we devised a metric, called alteration entropy (A-entropy), capable of denoting the "structural alteration variety" of an altered region. Using the whole voxel-based morphometry database of BrainMap, we were able to differentiate the brain areas exhibiting a high degree of overlap between different neuropathologies (or high value of A-entropy) from those exhibiting a low degree of overlap (or low value of A-entropy). The former, which are parts of large-scale brain networks with attentional, emotional, salience, and premotor functions, are thought to be more vulnerable to a great range of brain diseases; while the latter, which include the sensorimotor, visual, inferior temporal, and supramarginal regions, are thought to be more informative about the specific impact of brain diseases. Since low A-entropy areas appear to be altered by a smaller number of brain disorders, they are more informative than the areas characterized by high values of A-entropy. It is also noteworthy that even the areas showing low values of A-entropy are substantially altered by a variety of brain disorders. In fact, no cerebral area appears to be only altered by a specific disorder. Our study shows that the overlap of areas with high A-entropy provides support for a transdiagnostic approach to brain disorders but, at the same time, suggests that fruitful differences can be traced among brain diseases, as some areas can exhibit an alteration profile more specific to certain disorders than to others.

Keywords: Alteration entropy; Brain alterations; Brain disorders; Brain networks; Voxel-based morphometry.

Figure 1.

2D and 3D (fine-grained) visualizations of disease-related alteration entropy maps. The radar graph illustrates the mean alteration entropy values of the principal large-scale brain networks: premotor (PreMOT), dorsal attentional (DAN), ventral attentional right and left (VAN R and L), thalamus and basal ganglia (TH-Ganglia), default mode network (DMN), salience network (Salience), motor network (Motor), sensorimotor network (SensMOT), Cerebellum, auditory network (Auditory), visual network (V1, V2, V3).

Figure 2.

Comparison between the alteration entropy calculated on the basis of a fine-grained neuropathological subdivision (ICD pathological categories, upper panel first row) and the alteration entropy calculated on the basis of a coarser subdivision (ICD pathological blocks, upper panel second row). The middle panel illustrates a map of the probability for each brain area to be altered (derived from an unthresholded ALE map of all the disease-related gray matter (GM) alterations detected with VBM and included in the BrainMap database). The lower panel (row before the last) shows a winner takes all (WTA) comparison between the ALE map and the A-entropy map (fine-grained). Regions showing a prevalence of the A-entropy values (i.e., with high A-entropy values but less frequently altered) are highlighted in blue. Regions showing a prevalence of the ALE values (frequently altered but proportionally with lower A-entropy values) are highlighted in blue. The lower panel (last row) shows a comparison between the thresholded ALE map and the A-entropy map (fine-grained, thresholded to show only the voxels with values >0.5). Regions with high A-entropy values but not frequently altered (and thereby not overlapping with significant areas in the ALE map) are highlighted in red. Regions with both high A-entropy and significant ALE values are highlighted in green. No areas with significant ALE values and low A-entropy were found. All the significant ALE values characterize areas that also show high A-entropy.

Figure 3.

Comparison between the insular areas that were most frequently reported as being altered in our sample (upper panels) and the brain areas showing the highest A-entropy values (lower panels).

Figure 4.

Bidimensional view of the areas exhibiting 100% of overlap between the thresholded ALE map of the most frequently altered brain regions and the A-entropy map (50% of the regions having the highest A-entropy values).

Figure 5.

Diagram depicting the model proposed by Buckholtz and Meyer-Lindenberg (2012).