Neuroanatomical foundations of delayed reward discounting decision making

Abstract Resolving tradeoffs between smaller immediate rewards and larger delayed rewards is ubiquitous in daily life and steep discounting of future rewards is associated with several psychiatric conditions. This form of decision‐making is referred to as delayed reward discounting (DRD) and the features of brain structure associated with DRD are not well understood. The current study characterized the relationship between gray matter volume (GMV) and DRD in a sample of 1038 healthy adults (54.7% female) using cortical parcellation, subcortical segmentation, and voxelwise cortical surface‐based group analyses. The results indicate that steeper DRD was significantly associated with lower total cortical GMV, but not subcortical GMV. In parcellation analyses, less GMV in 20 discrete cortical regions was associated with steeper DRD. Of these regions, only GMV in the middle temporal gyrus (MTG) and entorhinal cortex (EC) were uniquely associated with DRD. Voxelwise surface‐based analyses corroborated these findings, again revealing significant associations between steeper DRD and less GMV in the MTG and EC. To inform the roles of MTG and EC in DRD, connectivity analysis of resting state data (N = 1003) using seed regions from the structural findings was conducted. This revealed that spontaneous activity in the MTG and EC was correlated with activation in the ventromedial prefrontal cortex, posterior cingulate cortex, and inferior parietal lobule, regions associated with the default mode network, which involves prospection, self‐reflective thinking and mental simulation. Furthermore, meta‐analytic co‐activation analysis using Neurosynth revealed a similar pattern across 11,406 task‐fMRI studies. Collectively, these findings provide robust evidence that morphometric characteristics of the temporal lobe are associated with DRD preferences and suggest it may be because of their role in mental activities in common with default mode activity. HighlightsPreferring smaller immediate rewards to larger delayed rewards is referred to as delayed reward discounting (DRD).This study examined the relationship between gray matter volume (GMV) and DRD in a large sample of adults (N = 1038).Steeper DRD was significantly associated with lower total cortical GMV, but not subcortical GMV.Only GMV in the middle temporal gyrus and entorhinal cortex were uniquely associated with DRD.These findings provide robust evidence that GMV in the temporal lobe is associated with DRD preferences.

[1]  L. Green,et al.  Area under the curve as a measure of discounting. , 2001, Journal of the experimental analysis of behavior.

[2]  G. Madden,et al.  Impulsivity: The Behavioral and Neurological Science of Discounting , 2010 .

[3]  M. Munafo,et al.  Delayed reward discounting and addictive behavior: a meta-analysis , 2011, Psychopharmacology.

[4]  Essa Yacoub,et al.  The WU-Minn Human Connectome Project: An overview , 2013, NeuroImage.

[5]  Lisa H. Lu,et al.  Relationships between brain activation and brain structure in normally developing children. , 2009, Cerebral cortex.

[6]  Daniel D. Holt,et al.  Differential effects of amount on temporal and probability discounting of gains and losses , 2006, Memory & cognition.

[7]  D. Schacter,et al.  The Brain's Default Network , 2008, Annals of the New York Academy of Sciences.

[8]  J. MacKillop,et al.  Steep discounting of delayed monetary and food rewards in obesity: a meta-analysis , 2016, Psychological Medicine.

[9]  A. Dale,et al.  Cortical Surface-Based Analysis II: Inflation, Flattening, and a Surface-Based Coordinate System , 1999, NeuroImage.

[10]  Warren K. Bickel,et al.  Remember the Future II: Meta-analyses and Functional Overlap of Working Memory and Delay Discounting , 2014, Biological Psychiatry.

[11]  E. Youngstrom,et al.  Associations of age with reward delay discounting and response inhibition in adolescents with bipolar disorders. , 2016, Journal of affective disorders.

[12]  Russell A. Poldrack,et al.  Large-scale automated synthesis of human functional neuroimaging data , 2011, Nature Methods.

[13]  D. Hommer,et al.  Delay Discounting Correlates with Proportional Lateral Frontal Cortex Volumes , 2009, Biological Psychiatry.

[14]  E. Martin,et al.  A comparison of delay discounting among substance users with and without suicide attempt history. , 2012, Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors.

[15]  Gary L. Brase,et al.  Taking time to be healthy: Predicting health behaviors with delay discounting and time perspective , 2010 .

[16]  Abraham Z. Snyder,et al.  Human Connectome Project informatics: Quality control, database services, and data visualization , 2013, NeuroImage.

[17]  James MacKillop,et al.  Delayed reward discounting predicts treatment response for heavy drinkers receiving smoking cessation treatment. , 2009, Drug and alcohol dependence.

[18]  Anders M. Dale,et al.  Automated manifold surgery: constructing geometrically accurate and topologically correct models of the human cerebral cortex , 2001, IEEE Transactions on Medical Imaging.

[19]  W. Bickel,et al.  Toward a behavioral economic understanding of drug dependence: delay discounting processes. , 2001, Addiction.

[20]  R. Buckner,et al.  Functional-Anatomic Fractionation of the Brain's Default Network , 2010, Neuron.

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

[22]  A. Dale,et al.  High‐resolution intersubject averaging and a coordinate system for the cortical surface , 1999, Human brain mapping.

[23]  William W. Graves,et al.  Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. , 2009, Cerebral cortex.

[24]  Daniel D. Holt,et al.  Do adjusting-amount and adjusting-delay procedures produce equivalent estimates of subjective value in pigeons? , 2007, Journal of the experimental analysis of behavior.

[25]  D. Hassabis,et al.  Deconstructing episodic memory with construction , 2007, Trends in Cognitive Sciences.

[26]  D. Hassabis,et al.  Patients with hippocampal amnesia cannot imagine new experiences , 2007, Proceedings of the National Academy of Sciences.

[27]  W. Bickel,et al.  Delay discounting rates: a strong prognostic indicator of smoking relapse. , 2014, Addictive behaviors.

[28]  Abraham Z. Snyder,et al.  Function in the human connectome: Task-fMRI and individual differences in behavior , 2013, NeuroImage.

[29]  J. MacKillop,et al.  Attention-Deficit/Hyperactivity Disorder and Monetary Delay Discounting: A Meta-Analysis of Case-Control Studies. , 2016, Biological psychiatry. Cognitive neuroscience and neuroimaging.

[30]  M. Kronbichler,et al.  Impulsivity relates to striatal gray matter volumes in humans: evidence from a delay discounting paradigm , 2015, Front. Hum. Neurosci..

[31]  Scott A. Huettel,et al.  Functional Neuroimaging of Intertemporal Choice Models: A Review , 2010 .

[32]  S. Tapert,et al.  BOLD response to working memory not related to cortical thickness during early adolescence , 2013, Brain Research.

[33]  Qiang Wang,et al.  Dissociated neural substrates underlying impulsive choice and impulsive action , 2016, NeuroImage.

[34]  R. N. Spreng,et al.  The Future of Memory: Remembering, Imagining, and the Brain , 2012, Neuron.

[35]  Matthew D. Lieberman,et al.  Social cognitive neuroscience: a review of core processes. , 2007, Annual review of psychology.

[36]  R. Weller,et al.  Delay discounting and task performance consistency in patients with schizophrenia , 2014, Psychiatry Research.

[37]  Olaf Sporns,et al.  Can structure predict function in the human brain? , 2010, NeuroImage.

[38]  Stephan F. Miedl,et al.  Intertemporal choice behavior is constrained by brain structure in healthy participants and pathological gamblers , 2015, Brain Structure and Function.

[39]  B. Reynolds A review of delay-discounting research with humans: relations to drug use and gambling , 2006, Behavioural pharmacology.

[40]  C. Kahler,et al.  Interactive Relationships Between Sex-Related Alcohol Expectancies and Delay Discounting on Risky Sex. , 2016, Alcoholism, clinical and experimental research.

[41]  Kevin N. Ochsner,et al.  A Meta-analysis of Functional Neuroimaging Studies of Self- and Other Judgments Reveals a Spatial Gradient for Mentalizing in Medial Prefrontal Cortex , 2012, Journal of Cognitive Neuroscience.

[42]  Brian A. Nosek,et al.  Power failure: why small sample size undermines the reliability of neuroscience , 2013, Nature Reviews Neuroscience.

[43]  Phillip Wolff,et al.  Causal reasoning with forces , 2015, Front. Hum. Neurosci..

[44]  Mark Jenkinson,et al.  The minimal preprocessing pipelines for the Human Connectome Project , 2013, NeuroImage.

[45]  M. Bar The proactive brain: using analogies and associations to generate predictions , 2007, Trends in Cognitive Sciences.

[46]  Steen Moeller,et al.  The Human Connectome Project: A data acquisition perspective , 2012, NeuroImage.

[47]  R. N. Spreng,et al.  The default network and self‐generated thought: component processes, dynamic control, and clinical relevance , 2014, Annals of the New York Academy of Sciences.

[48]  W. Bradford,et al.  The Association Between Individual Time Preferences and Health Maintenance Habits , 2010, Medical decision making : an international journal of the Society for Medical Decision Making.

[49]  Ayse Pinar Saygin,et al.  Smoothing and cluster thresholding for cortical surface-based group analysis of fMRI data , 2006, NeuroImage.

[50]  Marisa O. Hollinshead,et al.  The organization of the human cerebral cortex estimated by intrinsic functional connectivity. , 2011, Journal of neurophysiology.

[51]  Nicola J. Ray,et al.  Morphometric Correlation of Impulsivity in Medial Prefrontal Cortex , 2012, Brain Topography.

[52]  Nikos Makris,et al.  Automatically parcellating the human cerebral cortex. , 2004, Cerebral cortex.

[53]  Anders M. Dale,et al.  Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction , 1999, NeuroImage.

[54]  Mert R. Sabuncu,et al.  Measuring and comparing brain cortical surface area and other areal quantities , 2012, NeuroImage.

[55]  Anders M. Dale,et al.  An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest , 2006, NeuroImage.

[56]  Mark W. Woolrich,et al.  Resting-state fMRI in the Human Connectome Project , 2013, NeuroImage.

[57]  J. MacKillop,et al.  Steep delay discounting and addictive behavior: a meta‐analysis of continuous associations , 2017, Addiction.

[58]  Christopher L. Asplund,et al.  Functional Specialization and Flexibility in Human Association Cortex. , 2015, Cerebral cortex.

[59]  Stephan Meier,et al.  Present-Biased Preferences and Credit Card Borrowing , 2009, SSRN Electronic Journal.