Unraveling the miswired connectome: a developmental perspective

Abstract

The vast majority of mental illnesses can be conceptualized as developmental disorders of neural interactions within the connectome, or developmental miswiring. The recent maturation of pediatric in vivo brain imaging is bringing the identification of clinically meaningful brain-based biomarkers of developmental disorders within reach. Even more auspicious is the ability to study the evolving connectome throughout life, beginning in utero, which promises to move the field from topological phenomenology to etiological nosology. Here, we scope advances in pediatric imaging of the brain connectome as the field faces the challenge of unraveling developmental miswiring. We highlight promises while also providing a pragmatic review of the many obstacles ahead that must be overcome to significantly impact public health.

Figure 1. Miswired Developmental Trajectories

Different categories of abnormal developmental trajectories can be identified. Abnormalities in timing may reflect precocious (A) or delayed (immature; B) development with respect to typical development. Other scenarios may involve halted development (C; when development stops after initially following typical trajectories), failure to mature (D; when the maturation trajectory does not follow/attain the normative curve) or ectopic development (E; when developmental changes occur in atypical but not in typical development). Blue and red dashed lines: typical and atypical development, respectively.

Figure 2. Age-Related Connectomics Studies in Selected Neurodevelopmental Disorders

Among the most studied disorders in clinical connectomics (Craddock et al, 2013), we selected four examples of either early or later clinical onset in youth (Autism [blue]; ADHD [green]); schizophrenia [pink]; depression [yellow]). For each disorder, we counted the total number of connectomic empirical studies that included task-fMRI, R-fMRI and/or diffusion-based MRI. Amongst them, we then counted the studies examining age-related effects (excluding aging). As the pie charts show, few studies have addressed developmental effects. The largest proportion was in autism (10% of autism papers) and ADHD (8% of ADHD papers) followed by a negligible number in schizophrenia (1%) with no such studies in depression. Notably, none of the age-related studies identified used a longitudinal design. Our searches were conducted in July 2014 with PubMed combining the key words “connectivity” and the name of each of the above disorders.

Figure 3. Connectome graph

This sketch depicts a graph whereby nodes (solid black circles) are connected by edges (solid lines); a highly connected node is illustrated as solid blue circle. Community detection algorithms identify subsets of nodes that are more densely (colored clouds) connected internally than with the remainder of the graph - i.e., modules. Figure modified from Fair et al., 2012; PNAS.