An individual is typically considered an adult at age 18, although the age of adulthood varies for different legal and social policies. A key question is how cognitive capacities relevant to these policies change with development. The current study used an emotional go/no-go paradigm and functional neuroimaging to assess cognitive control under sustained states of negative and positive arousal in a community sample of one hundred ten 13- to 25-year-olds from New York City and Los Angeles. The results showed diminished cognitive performance under brief and prolonged negative emotional arousal in 18- to 21-year-olds relative to adults over 21. This reduction in performance was paralleled by decreased activity in fronto-parietal circuitry, implicated in cognitive control, and increased sustained activity in the ventromedial prefrontal cortex, involved in emotional processes. The findings suggest a developmental shift in cognitive capacity in emotional situations that coincides with dynamic changes in prefrontal circuitry. These findings may inform age-related social policies.
BonnieR. J.ScottE. S. (2013). The teenage brain: Adolescent brain research and the law. Current Directions in Psychological Science, 22, 158–161.
2.
BotvinickM.NystromL. E.FissellK.CarterC. S.CohenJ. D. (1999). Conflict monitoring versus selection-for-action in anterior cingulate cortex. Nature, 402, 179–181.
3.
CaseyB. J. (2015). Beyond simple models of self-control to circuit-based accounts of adolescent behavior. Annual Review of Psychology, 66, 295–319.
4.
CaseyB JGalvánA.SomervilleL. (2015). Beyond simple models of adolescence to an integrated circuit-based account: A commentary. Developmental Cognitive Neuroscience. Advance online publication. doi:10.1016/j.dcn.2015.12.006
5.
CaseyB. J.GetzS.GalvanA. (2008). The adolescent brain. Developmental Review, 28, 62–77.
6.
CheinJ.AlbertD.O’BrienL.UckertK.SteinbergL. (2011). Peers increase adolescent risk taking by enhancing activity in the brain’s reward circuitry. Developmental Science, 14, F1–F10.
7.
ChenG.SaadZ. S.BrittonJ. C.PineD. S.CoxR. W. (2013). Linear mixed-effects modeling approach to FMRI group analysis. NeuroImage, 73, 176–190.
8.
CohenA. O.CaseyB. J. (2014). Rewiring juvenile justice: The intersection of developmental neuroscience and legal policy. Trends in Cognitive Sciences, 18, 63–65.
9.
CohenA. O.DellarcoD. V.BreinerK.HelionC.RahdarA.PedersenG.. . . CaseyB. J. (2016). The impact of emotional states on cognitive control circuitry and function. Journal of Cognitive Neuroscience28, 446–459.
10.
Cohen-GilbertJ. E.KillgoreW. D. S.WhiteC. N.SchwabZ. J.CrowleyD. J.CovellM. J.. . . SilveriM. M. (2014). Differential influence of safe versus threatening facial expressions on decision-making during an inhibitory control task in adolescence and adulthood. Developmental Science, 17, 212–223.
11.
Cohen-GilbertJ. E.ThomasK. M. (2013). Inhibitory control during emotional distraction across adolescence and early adulthood. Child Development, 84, 1954–1966.
12.
CoxR. W. (1996). AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages. Computers and Biomedical Research, 29, 162–173.
13.
DosenbachN. U. F.NardosB.CohenA. L.FairD. A.PowerD.ChurchJ. A.. . . SchlaggarB. L. (2011). Prediction of individual brain maturity using fMRI. Science, 329, 1358–1361.
14.
DreyfussM.CaudleK.DrysdaleA. T.JohnstonN. E.CohenA. O.SomervilleL. H.. . . CaseyB. J. (2014). Teens impulsively react rather than retreat from threat. Developmental Neuroscience, 36, 220–227.
15.
ErnstM.PineD. S.HardinM. (2006). Triadic model of the neurobiology of motivated behavior in adolescence. Psychological Medicine, 36, 299–312.
16.
FairD. A.CohenA. L.PowerJ. D.DosenbachN. U.ChurchJ. A.MiezinF. M.. . . PetersenS. E. (2009). Functional brain networks develop from a “local to distributed” organization. PLoS Computational Biology, 5(5), Article 381. doi:10.1371/journal.pcbi.1000381
17.
FoerdeK.SteinglassJ. E.ShohamyD.WalshB. T. (2015). Neural mechanisms supporting maladaptive food choices in anorexia nervosa. Nature Neuroscience, 18, 1571–1573. doi:10.1038/nn.4136
18.
GalvanA.HareT. A.ParraC. E.PennJ.VossH.GloverG.CaseyB. J. (2006). Earlier development of the accumbens relative to orbitofrontal cortex might underlie risk-taking behavior in adolescents. The Journal of Neuroscience, 26, 6885–6892. doi:10.1523/JNEUROSCI.1062-06.2006
19.
GardnerM.SteinbergL. (2005). Peer influence on risk taking, risk preference, and risky decision making in adolescence and adulthood: An experimental study. Developmental Psychology, 41, 625–635.
20.
GeierC. F.TerwilligerR.TeslovichT.VelanovaK.LunaB. (2010). Immaturities in reward processing and its influence on inhibitory control in adolescence. Cerebral Cortex, 20, 1613–1629.
21.
GogtayN.GieddJ. N.LuskL.HayashiK. M.GreensteinD.VaituzisA. C.. . . ThompsonP. M. (2004). Dynamic mapping of human cortical development during childhood through early adulthood. Proceedings of the National Academy of Sciences, USA, 101, 8174–8179.
22.
Grose-FiferJ.RodriguesA.HooverS.ZottoliT. (2013). Attentional capture by emotional faces in adolescence. Advances in Cognitive Psychology, 9, 81–91.
23.
HareT. A.TottenhamN.GalvanA.VossH. U.GloverG. H.CaseyB. J. (2008). Biological substrates of emotional reactivity and regulation in adolescence during an emotional go-nogo task. Biological Psychiatry, 63, 927–934.
24.
Institute of Medicine & National Research Council. (2014). Investing in the health and well-being of young adults (R. J. Bonnie, C. Stroud, & H. Breiner, Eds.). Washington, DC: The National Academies Press.
25.
JovicichJ.CzannerS.GreveD.HaleyE.van der KouweA.GollubR.. . . DaleA. (2006). Reliability in multi-site structural MRI studies: Effects of gradient non-linearity correction on phantom and human data. NeuroImage, 30, 436–443.
26.
LunaB.MarekS.LarsenB.Tervo-ClemmensB.ChahalR. (2015). An integrative model of the maturation of cognitive control. Annual Review of Neuroscience, 38, 151–170.
27.
MacmillanN. A.CreelmanC. D. (2004). Detection theory: A user’s guide (2nd ed.). Mahwah, NJ: Erlbaum.
28.
MastenA. S.CicchettiD. (2010). Developmental cascades. Development and Psychopathology, 22, 491–495.
29.
McLarenD. G.RiesM. L.XuG.JohnsonS. C. (2012). A generalized form of context-dependent psychophysiological interactions (gPPI): A comparison to standard approaches. NeuroImage, 61, 1277–1286.
30.
MillsK. L.GoddingsA.-L.ClasenL. S.GieddJ. N.BlakemoreS.-J. (2014). The developmental mismatch in structural brain maturation during adolescence. Developmental Neuroscience, 36, 147–160.
31.
PlattM. L.GlimcherP. W. (1999). Neural correlates of decision variables in parietal cortex. Nature, 400, 233–238.
RaznahanA.ShawP. W.LerchJ. P.ClasenL. S.GreensteinD.BermanR.. . . GieddJ. N. (2014). Longitudinal four-dimensional mapping of subcortical anatomy in human development. Proceedings of the National Academy of Sciences, USA, 111, 1592–1597.
34.
RoyM.ShohamyD.WagerT. D. (2012). Ventromedial prefrontal-subcortical systems and the generation of affective meaning. Trends in Cognitive Sciences, 16, 147–156.
35.
ScottE. S. (2013). “Children are different”: Constitutional values and justice policy. Ohio State Journal of Criminal Law, 11, 71–105.
36.
SilvaK.ShulmanE. P.CheinJ.SteinbergL. (2015). Peers increase late adolescents’ exploratory behavior and sensitivity to positive and negative feedback. Journal of Research on Adolescence. Advance online publication. doi:10.1111/jora.12219
37.
SilversJ. A.WeberJ.WagerT. D.OchsnerK. N. (2015). Bad and worse: Neural systems underlying reappraisal of high- and low-intensity negative emotions. Social Cognitive and Affective Neuroscience, 10, 172–179.
38.
SmithS. M.JenkinsonM.WoolrichM. W.BeckmannC. F.BehrensT. E. J.Johansen-BergH.. . . MatthewsP. M. (2004). Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage, 23, 208–219.
39.
SomervilleL. H.HareT.CaseyB. J. (2011). Frontostriatal maturation predicts cognitive control failure to appetitive cues in adolescents. Journal of Cognitive Neuroscience, 23, 2123–2134.
40.
SowellE. R.ThompsonP. M.LeonardC. M.WelcomeS. E.KanE.TogaA. W. (2004). Longitudinal mapping of cortical thickness and brain growth in normal children. The Journal of Neuroscience, 24, 8223–8231.
41.
SteinbergL. (2010). A dual systems model of adolescent risk-taking. Developmental Psychobiology, 52, 216–224.
42.
SteinbergL. (2013). The influence of neuroscience on U.S. Supreme Court decisions involving adolescents’ criminal culpability. Nature Reviews Neuroscience, 14, 513–518.
43.
SteinbergL.GrahamS. J.O’BrienL.WoolardJ.CauffmanE.BanichM. (2009). Age differences in future orientation and delay discounting. Child Development, 80, 28–44.
44.
Taylor-ThompsonK. (2014). Minority rule: Redefining the age of criminality. N.Y.U. Review of Law & Social Change, 38, 143–200.
45.
Van LeijenhorstL.ZanolieK.Van MeelC. S.WestenbergP. M.RomboutsS. A. R. B.CroneE. A. (2010). What motivates the adolescent? Brain regions mediating reward sensitivity across adolescence. Cerebral Cortex, 20, 61–69.
46.
VincentJ. L.KahnI.SnyderA. Z.RaichleM. E.BucknerR. L.PhilippiC. L.. . . RaichleM. E. (2008). Evidence for a frontoparietal control system revealed by intrinsic functional connectivity. Journal of Neurophysiology, 100, 3328–3342.
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