Impaired Evidence Accumulation As a Transdiagnostic Vulnerability Factor in Psychopathology

Overview

Journal Front Psychiatry

Specialty Psychiatry

Date 2021 Mar 8

PMID 33679485

Citations 17

Authors

Chandra Sripada

Alexander Weigard

Affiliations

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Abstract

There is substantial interest in identifying biobehavioral dimensions of individual variation that cut across heterogenous disorder categories, and computational models can play a major role in advancing this goal. In this report, we focused on efficiency of evidence accumulation (EEA), a computationally characterized variable derived from sequential sampling models of choice tasks. We created an EEA factor from three behavioral tasks in the UCLA Phenomics dataset ( = 272), which includes healthy participants ( = 130) as well-participants with schizophrenia ( = 50), bipolar disorder ( = 49), and attention-deficit/hyperactivity disorder ( = 43). We found that the EEA factor was significantly reduced in all three disorders, and that it correlated with an overall severity score for psychopathology as well as self-report measures of impulsivity. Although EEA was significantly correlated with general intelligence, it remained associated with psychopathology and symptom scales even after controlling for intelligence scores. Taken together, these findings suggest EEA is a promising computationally-characterized dimension of neurocognitive variation, with diminished EEA conferring transdiagnostic vulnerability to psychopathology.

Citing Articles

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References

Gomez P, Ratcliff R, Perea M . A model of the go/no-go task. J Exp Psychol Gen. 2007; 136(3):389-413. PMC: 2701630. DOI: 10.1037/0096-3445.136.3.389. View

Brosnan M, Sabaroedin K, Silk T, Genc S, Newman D, Loughnane G . Evidence accumulation during perceptual decisions in humans varies as a function of dorsal frontoparietal organization. Nat Hum Behav. 2020; 4(8):844-855. DOI: 10.1038/s41562-020-0863-4. View

Huang-Pollock C, Karalunas S, Tam H, Moore A . Evaluating vigilance deficits in ADHD: a meta-analysis of CPT performance. J Abnorm Psychol. 2012; 121(2):360-71. PMC: 3664643. DOI: 10.1037/a0027205. View

Adams R, Huys Q, Roiser J . Computational Psychiatry: towards a mathematically informed understanding of mental illness. J Neurol Neurosurg Psychiatry. 2015; 87(1):53-63. PMC: 4717449. DOI: 10.1136/jnnp-2015-310737. View

Smith P, Ratcliff R . Psychology and neurobiology of simple decisions. Trends Neurosci. 2004; 27(3):161-8. DOI: 10.1016/j.tins.2004.01.006. View

Turner B, Van Maanen L, Forstmann B . Informing cognitive abstractions through neuroimaging: the neural drift diffusion model. Psychol Rev. 2015; 122(2):312-336. DOI: 10.1037/a0038894. View

Karalunas S, Huang-Pollock C, Nigg J . Decomposing attention-deficit/hyperactivity disorder (ADHD)-related effects in response speed and variability. Neuropsychology. 2012; 26(6):684-94. PMC: 3516369. DOI: 10.1037/a0029936. View

van Ravenzwaaij D, Donkin C, Vandekerckhove J . The EZ diffusion model provides a powerful test of simple empirical effects. Psychon Bull Rev. 2016; 24(2):547-556. PMC: 5389995. DOI: 10.3758/s13423-016-1081-y. View

Weigard A, Huang-Pollock C . A diffusion modeling approach to understanding contextual cueing effects in children with ADHD. J Child Psychol Psychiatry. 2014; 55(12):1336-44. PMC: 4218883. DOI: 10.1111/jcpp.12250. View

10.

Ziegler S, Pedersen M, Mowinckel A, Biele G . Modelling ADHD: A review of ADHD theories through their predictions for computational models of decision-making and reinforcement learning. Neurosci Biobehav Rev. 2016; 71:633-656. DOI: 10.1016/j.neubiorev.2016.09.002. View

11.

Dutilh G, Annis J, Brown S, Cassey P, Evans N, Grasman R . The Quality of Response Time Data Inference: A Blinded, Collaborative Assessment of the Validity of Cognitive Models. Psychon Bull Rev. 2018; 26(4):1051-1069. PMC: 6449220. DOI: 10.3758/s13423-017-1417-2. View

12.

Miller J, Ulrich R . Mental chronometry and individual differences: modeling reliabilities and correlations of reaction time means and effect sizes. Psychon Bull Rev. 2013; 20(5):819-58. DOI: 10.3758/s13423-013-0404-5. View

13.

Lerche V, Voss A . Retest reliability of the parameters of the Ratcliff diffusion model. Psychol Res. 2016; 81(3):629-652. DOI: 10.1007/s00426-016-0770-5. View

14.

Rouder J, Haaf J . A psychometrics of individual differences in experimental tasks. Psychon Bull Rev. 2019; 26(2):452-467. DOI: 10.3758/s13423-018-1558-y. View

15.

Duckworth A, Kern M . A Meta-Analysis of the Convergent Validity of Self-Control Measures. J Res Pers. 2011; 45(3):259-268. PMC: 3105910. DOI: 10.1016/j.jrp.2011.02.004. View

16.

Montague P, Dolan R, Friston K, Dayan P . Computational psychiatry. Trends Cogn Sci. 2011; 16(1):72-80. PMC: 3556822. DOI: 10.1016/j.tics.2011.11.018. View

17.

Huang-Pollock C, Ratcliff R, McKoon G, Roule A, Warner T, Feldman J . A diffusion model analysis of sustained attention in children with attention deficit hyperactivity disorder. Neuropsychology. 2020; 34(6):641-653. PMC: 7957836. DOI: 10.1037/neu0000636. View

18.

Dickman S . Functional and dysfunctional impulsivity: personality and cognitive correlates. J Pers Soc Psychol. 1990; 58(1):95-102. DOI: 10.1037//0022-3514.58.1.95. View

19.

Toplak M, West R, Stanovich K . Practitioner review: do performance-based measures and ratings of executive function assess the same construct?. J Child Psychol Psychiatry. 2012; 54(2):131-43. DOI: 10.1111/jcpp.12001. View

20.

Goodkind M, Eickhoff S, Oathes D, Jiang Y, Chang A, Jones-Hagata L . Identification of a common neurobiological substrate for mental illness. JAMA Psychiatry. 2015; 72(4):305-15. PMC: 4791058. DOI: 10.1001/jamapsychiatry.2014.2206. View