Dual systems model

Not to be confused with Dual process theory.

The dual systems model, also known as the maturational imbalance model,[1] is a theory arising from developmental cognitive neuroscience which posits that increased risk-taking during adolescence is a result of a combination of heightened reward sensitivity and immature impulse control.[2][3] In other words, the appreciation for the benefits arising from the success of an endeavor is heightened, but the appreciation of the risks of failure lags behind.

The dual systems model hypothesizes that early maturation of the socioemotional system (including brain regions like the striatum) increases adolescents' attraction for exciting, pleasurable, and novel activities during a time when cognitive control systems (including brain regions like the prefrontal cortex) are not fully developed and thus cannot regulate these appetitive, and potentially hazardous, impulses. The temporal gap in the development of the socioemotional and cognitive control systems creates a period of heightened vulnerability to risk-taking during mid-adolescence. In the dual systems model, "reward sensitivity" and "cognitive control" refer to neurobiological constructs that are measured in studies of brain structure and function. Other models similar to the dual systems model are the maturational imbalance model,[4] the driven dual systems model,[5] and the triadic model.[6]

The dual systems model is not free from controversy, however. It is highly contested and debated within developmental psychology and neuroscientific fields whether or not when the prefrontal cortex is said to be fully or efficiently developed. Most longitudinal evidence suggests that myelination of gray matter in the frontal lobe is a very long process and may be continuing until well into middle age or greater, and major facets of the brain are recorded to reach mature levels in one's mid-teens, including the parts that are responsible for response inhibition and impulse control, suggesting that many later age markers may ultimately be arbitrary.[7]

  1. ^ Casey, B. J.; Jones, Rebecca M.; Somerville, Leah H. (March 2011). "Braking and Accelerating of the Adolescent Brain". Journal of Research on Adolescence. 21 (1): 21–33. doi:10.1111/j.1532-7795.2010.00712.x. PMC 3070306. PMID 21475613.
  2. ^ Steinberg, Laurence (2010). "A dual systems model of adolescent risk-taking". Developmental Psychobiology. 52 (3): 216–224. doi:10.1002/dev.20445. PMID 20213754.
  3. ^ Somerville, Leah H.; Jones, Rebecca M.; Casey, B.J. (February 2010). "A time of change: Behavioral and neural correlates of adolescent sensitivity to appetitive and aversive environmental cues". Brain and Cognition. 72 (1): 124–133. doi:10.1016/j.bandc.2009.07.003. PMC 2814936. PMID 19695759.
  4. ^ Casey, B.J.; Jones, Rebecca M.; Hare, Todd A. (March 2008). "The Adolescent Brain". Annals of the New York Academy of Sciences. 1124 (1): 111–126. Bibcode:2008NYASA1124..111C. doi:10.1196/annals.1440.010. PMC 2475802. PMID 18400927.
  5. ^ Luna, Beatriz; Wright, Catherine (2016). "Adolescent brain development: Implications for the juvenile criminal justice system". APA handbook of psychology and juvenile justice. pp. 91–116. doi:10.1037/14643-005. ISBN 978-1-4338-1967-4.
  6. ^ Ernst, Monique (August 2014). "The triadic model perspective for the study of adolescent motivated behavior". Brain and Cognition. 89: 104–111. doi:10.1016/j.bandc.2014.01.006. PMC 4248307. PMID 24556507.
  7. ^ Cazard, P; Ricard, F; Facchetti, L (1992). "Dépression et asymétrie fonctionnelle" [Depression and functional EEG asymmetry]. Annales médico-psychologiques (in French). 150 (2–3): 230–239. OCLC 118095174. PMID 1343525.