Neurodevelopment of the incentive network facilitates motivated behaviour from adolescence to adulthood

The ability to enhance motivated performance through incentives is crucial to guide and ultimately optimize the outcome of goal-directed behaviour. It remains largely unclear how motivated behaviour and performance develops particularly across adolescence. Here, we used computational fMRI to assess how response speed and its underlying neural circuitry are modulated by reward and loss in a monetary incentive delay paradigm. We demonstrate that maturational fine-tuning of functional coupling within the cortico-striatal incentive circuitry from adolescence to adulthood facilitates the ability to enhance performance selectively for higher subjective values. Additionally, during feedback, we found developmental sex differences of striatal representations of reward prediction errors in an exploratory analysis. Our findings suggest that a reduced capacity to utilize subjective value for motivated behaviour in adolescence is rooted in immature information processing in the incentive system. This indicates that the neurocircuitry for coordination of incentivised, motivated cognitive control acts as a bottleneck for behavioural adjustments in adolescence.

[1]  Matthew L. Dixon,et al.  The Neural Basis of Motivational Influences on Cognitive Control , 2017, bioRxiv.

[2]  Ryan D Ward,et al.  Inhibition of Mediodorsal Thalamus Disrupts Thalamofrontal Connectivity and Cognition , 2013, Neuron.

[3]  Sven Bestmann,et al.  The Role of Dopamine in Motor Flexibility , 2014, Journal of Cognitive Neuroscience.

[4]  Adeel Razi,et al.  Bayesian model reduction and empirical Bayes for group (DCM) studies , 2016, NeuroImage.

[5]  M. Husain,et al.  Reward Pays the Cost of Noise Reduction in Motor and Cognitive Control , 2015, Current Biology.

[6]  Ulrik R Beierholm,et al.  Dopamine Modulates Reward-Related Vigor , 2013, Neuropsychopharmacology.

[7]  Jane E. Joseph,et al.  Modulation of meso-limbic reward processing by motivational tendencies in young adolescents and adults , 2016, NeuroImage.

[8]  Aditya Gilra,et al.  Thalamic regulation of switching between cortical representations enables cognitive flexibility , 2018, Nature Neuroscience.

[9]  M. Pessiglione,et al.  Critical Roles for Anterior Insula and Dorsal Striatum in Punishment-Based Avoidance Learning , 2012, Neuron.

[10]  L. Uddin Salience processing and insular cortical function and dysfunction , 2014, Nature Reviews Neuroscience.

[11]  Adeel Razi,et al.  A guide to group effective connectivity analysis, part 1: First level analysis with DCM for fMRI , 2019, NeuroImage.

[12]  Ulrik R Beierholm,et al.  Opposing effects of reward and punishment on human vigor , 2017, Scientific Reports.

[13]  M. Botvinick,et al.  Motivation and cognitive control: from behavior to neural mechanism. , 2015, Annual review of psychology.

[14]  S. Walitza,et al.  Maladaptive avoidance learning in the orbitofrontal cortex in adolescents with major depression , 2021, medRxiv.

[15]  Monique Ernst,et al.  Nucleus accumbens, thalamus and insula connectivity during incentive anticipation in typical adults and adolescents , 2013, NeuroImage.

[16]  Kimberly S. Chiew,et al.  Reward favors the prepared: Incentive and task-informative cues interact to enhance attentional control. , 2016, Journal of experimental psychology. Human perception and performance.

[17]  S. Kapur,et al.  Direct Activation of the Ventral Striatum in Anticipation of Aversive Stimuli , 2003, Neuron.

[18]  S. Pollak,et al.  Developmental continuity in reward-related enhancement of cognitive control , 2014, Developmental Cognitive Neuroscience.

[19]  L. Pessoa,et al.  Network Analysis Reveals Increased Integration during Emotional and Motivational Processing , 2012, The Journal of Neuroscience.

[20]  L. Somerville,et al.  Development of corticostriatal connectivity constrains goal-directed behavior during adolescence , 2017, Nature Communications.

[21]  M. Ernst,et al.  A systematic review of fMRI reward paradigms used in studies of adolescents vs. adults: The impact of task design and implications for understanding neurodevelopment , 2013, Neuroscience & Biobehavioral Reviews.

[22]  L. Whitten Translational Neuroscience and Potential Contributions of Functional Magnetic Resonance Imaging (fMRI) to the Prevention of Substance Misuse and Antisocial Behavior , 2013, Prevention Science.

[23]  N. Bunzeck,et al.  Absolute Coding of Stimulus Novelty in the Human Substantia Nigra/VTA , 2006, Neuron.

[24]  B. Balleine,et al.  Ventral Pallidal Projections to Mediodorsal Thalamus and Ventral Tegmental Area Play Distinct Roles in Outcome-Specific Pavlovian-Instrumental Transfer , 2015, The Journal of Neuroscience.

[25]  L. Felix,et al.  Systematic review of strategies to increase access to health services among children over five in low‐ and middle‐income countries , 2018, Tropical medicine & international health : TM & IH.

[26]  C. Büchel,et al.  Predicting development of adolescent drinking behaviour from whole brain structure at 14 years of age , 2019, eLife.

[27]  Beatriz Luna,et al.  Incentives facilitate developmental improvement in inhibitory control by modulating control-related networks , 2018, NeuroImage.

[28]  R. Dahl,et al.  Neural systems underlying reward cue processing in early adolescence: The role of puberty and pubertal hormones , 2019, Psychoneuroendocrinology.

[29]  H. Flor,et al.  Activation of the ventral striatum during aversive contextual conditioning in humans , 2012, Biological Psychology.

[30]  Anna S. Mitchell,et al.  Critical role for the mediodorsal thalamus in permitting rapid reward-guided updating in stochastic reward environments , 2016, eLife.

[31]  Jason Tucciarone,et al.  The Mediodorsal Thalamus Drives Feedforward Inhibition in the Anterior Cingulate Cortex via Parvalbumin Interneurons , 2015, The Journal of Neuroscience.

[32]  P. Dayan,et al.  The habenula encodes negative motivational value associated with primary punishment in humans , 2014, Proceedings of the National Academy of Sciences.

[33]  E. Crone,et al.  Understanding adolescence as a period of social–affective engagement and goal flexibility , 2012, Nature Reviews Neuroscience.

[34]  Jean-Luc Anton,et al.  Pros and Cons of Using the Informed Basis Set to Account for Hemodynamic Response Variability with Developmental Data , 2016, Front. Neurosci..

[35]  M. Ernst,et al.  Longitudinal study of striatal activation to reward and loss anticipation from mid-adolescence into late adolescence/early adulthood , 2014, Brain and Cognition.

[36]  S. Haber,et al.  The Reward Circuit: Linking Primate Anatomy and Human Imaging , 2010, Neuropsychopharmacology.

[37]  Brian Knutson,et al.  FMRI Visualization of Brain Activity during a Monetary Incentive Delay Task , 2000, NeuroImage.

[38]  M. Phillips,et al.  Healthy adolescents' neural response to reward: associations with puberty, positive affect, and depressive symptoms. , 2010, Journal of the American Academy of Child and Adolescent Psychiatry.

[39]  Leah H. Somerville,et al.  Adolescent Development of Value-Guided Goal Pursuit , 2018, Trends in Cognitive Sciences.

[40]  R. Chan,et al.  Anticipatory pleasure predicts effective connectivity in the mesolimbic system , 2015, Front. Behav. Neurosci..

[41]  J. Krakauer,et al.  The basal ganglia: from motor commands to the control of vigor , 2016, Current Opinion in Neurobiology.

[42]  J L Collins,et al.  Youth risk behavior surveillance--United States, 1993. , 1995, The Journal of school health.

[43]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[44]  P. Dayan Instrumental vigour in punishment and reward , 2012, The European journal of neuroscience.

[45]  R. Wilcox The percentage bend correlation coefficient , 1994 .

[46]  Y. Liu,et al.  Resting-state functional connectivity between the dorsal anterior cingulate cortex and thalamus is associated with risky decision-making in nicotine addicts , 2016, Scientific Reports.

[47]  Sabine Peters,et al.  Gambling for self, friends, and antagonists: Differential contributions of affective and social brain regions on adolescent reward processing , 2014, NeuroImage.

[48]  P. Dayan,et al.  Behavioral/systems/cognitive Action Dominates Valence in Anticipatory Representations in the Human Striatum and Dopaminergic Midbrain , 2010 .

[49]  P. Glimcher,et al.  Midbrain Dopamine Neurons Encode a Quantitative Reward Prediction Error Signal , 2005, Neuron.

[50]  Viola S. Störmer,et al.  Reward speeds up and increases consistency of visual selective attention: a lifespan comparison , 2014, Cognitive, affective & behavioral neuroscience.

[51]  Todd A. Hare,et al.  Frontostriatal Maturation Predicts Cognitive Control Failure to Appetitive Cues in Adolescents , 2011, Journal of Cognitive Neuroscience.

[52]  R. Rescorla,et al.  A theory of Pavlovian conditioning : Variations in the effectiveness of reinforcement and nonreinforcement , 1972 .

[53]  M. Frank,et al.  Frontal theta as a mechanism for cognitive control , 2014, Trends in Cognitive Sciences.

[54]  Vanessa Johnston,et al.  Incentives for preventing smoking in children and adolescents. , 2012, The Cochrane database of systematic reviews.

[55]  M. Yücel,et al.  The anticipation and outcome phases of reward and loss processing: A neuroimaging meta‐analysis of the monetary incentive delay task , 2018, Human brain mapping.

[56]  E. Koechlin,et al.  Motivation and cognitive control in the human prefrontal cortex , 2009, Nature Neuroscience.

[57]  L. Somerville,et al.  Braking and Accelerating of the Adolescent Brain. , 2011, Journal of research on adolescence : the official journal of the Society for Research on Adolescence.

[58]  A. Galván,et al.  Neural representation of expected value in the adolescent brain , 2014, Proceedings of the National Academy of Sciences.

[59]  Herman Aguinis,et al.  Appraisal of the Homogeneity of Error Variance Assumption and Alternatives to Multiple Regression for Estimating Moderating Effects of Categorical Variables , 1999 .

[60]  R. Dolan,et al.  How the Brain Translates Money into Force: A Neuroimaging Study of Subliminal Motivation , 2007, Science.

[61]  Boris Suchan,et al.  The Regulatory Role of the Human Mediodorsal Thalamus , 2018, Trends in Cognitive Sciences.

[62]  Vincent D Costa,et al.  Motivational neural circuits underlying reinforcement learning , 2017, Nature Neuroscience.

[63]  Ilya E. Monosov,et al.  Anterior cingulate is a source of valence-specific information about value and uncertainty , 2016, Nature Communications.

[64]  Amirsaman Sajad,et al.  Cortical Microcircuitry of Performance Monitoring , 2018, Nature Neuroscience.

[65]  Michael X. Cohen,et al.  Striatum-medial prefrontal cortex connectivity predicts developmental changes in reinforcement learning. , 2012, Cerebral cortex.

[66]  Thomas F. Nugent,et al.  Dynamic mapping of human cortical development during childhood through early adulthood. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[67]  Daniel Brandeis,et al.  Cognitive flexibility in adolescence: Neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development , 2015, NeuroImage.

[68]  Mark J. Edwards,et al.  Motivation and movement: the effect of monetary incentive on performance speed , 2011, Experimental Brain Research.

[69]  Michael X. Cohen,et al.  Different neural systems adjust motor behavior in response to reward and punishment , 2007, NeuroImage.

[70]  Gang Chen,et al.  Adolescents, Adults and Rewards: Comparing Motivational Neurocircuitry Recruitment Using fMRI , 2010, PloS one.

[71]  P. Dayan,et al.  Tonic dopamine: opportunity costs and the control of response vigor , 2007, Psychopharmacology.

[72]  Timothy E. Ham,et al.  Extrinsic and Intrinsic Brain Network Connectivity Maintains Cognition across the Lifespan Despite Accelerated Decay of Regional Brain Activation , 2016, The Journal of Neuroscience.

[73]  Adriana Galvan,et al.  Enhanced Striatal Sensitivity to Aversive Reinforcement in Adolescents versus Adults , 2013, Journal of Cognitive Neuroscience.

[74]  Claus Lamm,et al.  P300 amplitude variation is related to ventral striatum BOLD response during gain and loss anticipation: An EEG and fMRI experiment , 2014, NeuroImage.

[75]  L. Steinberg A dual systems model of adolescent risk-taking. , 2010, Developmental psychobiology.

[76]  Hannah S. Locke,et al.  Motivational influences on cognitive control: Behavior, brain activation, and individual differences , 2008, Cognitive, affective & behavioral neuroscience.

[77]  E. Crone,et al.  Sex steroids and brain structure in pubertal boys and girls: a mini-review of neuroimaging studies , 2011, Neuroscience.

[78]  Raymond J. Dolan,et al.  Multiple value signals in dopaminergic midbrain and their role in avoidance contexts , 2016, NeuroImage.

[79]  Karl J. Friston,et al.  Temporal Difference Models and Reward-Related Learning in the Human Brain , 2003, Neuron.

[80]  Christian A. Rodriguez,et al.  Adolescent impatience decreases with increased frontostriatal connectivity , 2015, Proceedings of the National Academy of Sciences.

[81]  Hiroshi Yamada,et al.  Preferential Representation of Past Outcome Information and Future Choice Behavior by Putative Inhibitory Interneurons Rather Than Putative Pyramidal Neurons in the Primate Dorsal Anterior Cingulate Cortex. , 2019, Cerebral cortex.

[82]  Martijn P. van den Heuvel,et al.  Glutamate changes in healthy young adulthood , 2013, European Neuropsychopharmacology.

[83]  Michael M. Halassa,et al.  Prefrontal Cortex Regulates Sensory Filtering through a Basal Ganglia-to-Thalamus Pathway , 2019, Neuron.

[84]  Thorsten Kahnt,et al.  Reward, Value, and Salience , 2017 .

[85]  Peter B. Jones,et al.  Compulsivity and impulsivity traits linked to attenuated developmental fronto-striatal myelination trajectories , 2019, Nature Neuroscience.

[86]  Abraham Z. Snyder,et al.  Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion , 2012, NeuroImage.

[87]  K. Ethier,et al.  Youth Risk Behavior Surveillance — United States, 2017 , 2018, Morbidity and mortality weekly report. Surveillance summaries.

[88]  A. Galván,et al.  Behavioral and neural correlates of loss aversion and risk avoidance in adolescents and adults , 2013, Developmental Cognitive Neuroscience.

[89]  Viktor Müller,et al.  Life Span Differences in Electrophysiological Correlates of Monitoring Gains and Losses during Probabilistic Reinforcement Learning , 2011, Journal of Cognitive Neuroscience.

[90]  Pete Wegier,et al.  Neural responses to monetary incentives in younger and older adults , 2015, Brain Research.

[91]  Russell A. Poldrack,et al.  A unique adolescent response to reward prediction errors , 2010, Nature Neuroscience.

[92]  David J. Paulsen,et al.  Effects of incentives, age, and behavior on brain activation during inhibitory control: A longitudinal fMRI study , 2014, Developmental Cognitive Neuroscience.

[93]  C. Büchel,et al.  Mapping adolescent reward anticipation, receipt, and prediction error during the monetary incentive delay task , 2018, Human brain mapping.

[94]  Wouter Kool,et al.  Cost-Benefit Arbitration Between Multiple Reinforcement-Learning Systems , 2017, Psychological science.

[95]  Michael G. Hardin,et al.  Triadic model of the neurobiology of motivated behavior in adolescence , 2005, Psychological Medicine.

[96]  Brian Knutson,et al.  Affective traits link to reliable neural markers of incentive anticipation , 2014, NeuroImage.

[97]  The Behavioralist Goes to School: Leveraging Behavioral Economics to Improve Educational Performance. NBER Working Paper No. 18165. , 2012 .

[98]  Ian C. Ballard,et al.  Dorsolateral Prefrontal Cortex Drives Mesolimbic Dopaminergic Regions to Initiate Motivated Behavior , 2011, The Journal of Neuroscience.

[99]  K. Velanova,et al.  Immaturities in Reward Processing and Its Influence on Inhibitory Control in Adolescence , 2009, Cerebral cortex.

[100]  Nadine Gogolla The insular cortex , 2017, Current Biology.