Adolescent brain development and depression: A case for the importance of connectivity of the anterior cingulate cortex

Abstract

We propose that structural and functional connectivity of the anterior cingulate cortex (ACC) represents a critical component of adolescent developmental psychopathology. We hypothesize that connectivity of the ACC, a hub for integrating cognitive, affective, and social information to guide self-regulation across domains, supports adaptive development of self-regulation during adolescence and that, conversely, disrupted maturation of ACC connectivity contributes to the development of depression. To integrate findings on typical development, we report results of a meta-analysis of diffusion imaging findings of typical adolescent development of the cingulum and anterior thalamic radiations, the tracts most relevant to ACC connectivity, and provide a critical review of the literature on ACC functional connectivity. Finally, we review the evidence for altered structural and functional connectivity in adolescents with depression. Although the evidence for our claim is persuasive, a more comprehensive understanding of the ACC's role depends upon future investigations with sophisticated modeling of networks, prospective and longitudinal designs, and examination of structure-function associations.

Keywords: Adolescence; Affect regulation; Anterior cingulate cortex; Connectivity; Depression; Development.

Figure 1

Illustration of the (a) cingulum and (b) anterior thalamic radiations (ATR). Original figure generated to illustrate the pathways of interest in the current review. Deterministic tractography was used to track the cingulum and ATR using diffusion spectrum imaging data from an atlas generated from a sample of 60 neurologically healthy participants (the sample and atlas generation process are described in (Jarbo and Verstynen, 2015; Yeh et al., 2016). Color-coded images show the orientation of the principal direction of diffusion of each streamline, with red, blue, and green representing diffusion along x-, y-, and z-axes, respectively.

Figure 2

Illustration of meta-analysis methods. Regression models reported for each pathway were used to simulate fractional anisotropy (FA) data for each age within the range included in each study. FA values were converted to z-scores in order to standardize across studies, producing an estimate of the predicted direction and magnitude of change in FA at each age for each pathway. Blue lines represent regression models of developmental change in FA of the cingulum. Red lines represent regression models for age effects on FA in the anterior thalamic radiations.

Figure 3

Developmental trajectories of cingulum and ATR fractional anisotropy. A) Lifetime developmental trajectory of FA from age 0–90. B) Trajectory of FA across adolescence, age 10–20. Lines represent mean FA z-scores from all models included. Because the composite model predictions combine both linear and quadratic effects, both linear and quadratic models are displayed. Error bars depict standard deviations.

Figure 4

Developmental trajectories of cingulum and ATR MD, RD, and AD. A) Lifetime developmental trajectory of MD, RD and AD from age 0–70. B) Trajectory of MD, RD, and AD across adolescence, age 10–20. Lines represent mean z-scores for each measure across all models included. Both linear and quadratic effects are displayed. Error bars depict standard deviations. MD: mean diffusivity; AD: axial diffusivity; RD: radial diffusivity.