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Cognitive Modeling Informs Interpretation of Go/No-Go Task-Related Neural Activations and Their Links to Externalizing Psychopathology

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Abstract

Background

Individuals with attention-deficit/hyperactivity disorder and other externalizing psychopathologies tend to display poor behavioral performance on the go/no-go task, which is thought to reflect deficits in inhibitory control. However, clinical neuroimaging studies using this task have yielded conflicting results, raising basic questions about what the task measures and which aspects of the task relate to clinical outcomes. We used computational modeling to provide a clearer understanding of how neural activations from this task relate to the cognitive mechanisms that underlie performance and to probe the implications of these relationships for clinical research.

Methods

A total of 143 young adults (8–21 years of age) performed the go/no-go task during functional magnetic resonance imaging scanning. We used the diffusion decision model (DDM), a cognitive modeling approach, to quantify distinct neurocognitive processes that underlie go/no-go performance. We then assessed correlations between DDM parameters and brain activation from standard go/no-go contrasts and assessed relationships of DDM parameters and associated neural measures with clinical ratings.

Results

Right-lateralized prefrontal activations on correct inhibition trials, which are generally assumed to isolate neural processes involved in inhibition, were unrelated to DDM parameters (and other performance indices). However, responses to failed inhibitions in brain regions associated with error monitoring were strongly related to more efficient task performance and correlated with externalizing behavior and attention-deficit/hyperactivity disorder symptoms.

Conclusions

Our findings cast doubt on conventional interpretations of go/no-go task-related activations as reflecting the neural basis of inhibitory functioning. We instead found evidence that error-related contrasts provide clinically relevant information about neural systems involved in monitoring and optimizing the efficiency of cognitive performance.

Section snippets

Participants

An initial sample of 147 participants, 18 to 21 years of age, was recruited from the Michigan Longitudinal Study (MLS) to participate in a neuroimaging study. The MLS is an ongoing prospective study that follows a community sample of families with a history of alcohol use disorder and low-risk families from the same neighborhoods (36,37). Participants were excluded from participating in the larger MLS if they displayed signs of fetal alcohol syndrome and were excluded from the neuroimaging

DDM Parameter Estimates

Plots comparing empirical RT and accuracy data to predictions of the DDM suggested that the model generally described behavioral data well (Supplement). Notably, most participants’ z values were above 0.50 (Table 1), indicating that they were biased toward the decision to respond, as would be expected for a task with a greater proportion of go than no-go stimuli.

Table 2 displays Pearson correlation (r) values and credible intervals for relationships between all DDM parameters and traditional

Discussion

We used the DDM, a well-validated computational model (30,31), to test the common assumption that individual differences in go/no-go task-related neural activations index the integrity of neurocognitive mechanisms that underlie individual and clinical differences in inhibitory performance.

FI-related activations in the ACC, IFG, and insula, regions associated with error processing (22,24), were consistently positively related to individuals’ drift rate (v.avg) across whole-brain and ROI-based

Acknowledgments and Disclosures

This project was supported by National Institute on Alcohol Abuse and Alcoholism (NIAAA) Grant Nos. R01 AA07065 (to RZ) and R01 AA025790 (to MH). AW was supported by NIAAA Grant No. T32 AA007477 (to Dr. Frederic Blow, principal investigator).

This article was published as a preprint on bioRxiv: doi: https://doi.org/10.1101/614420.

The authors report no biomedical financial interests or potential conflicts of interest.

References (76)

  • R.J. Huster et al.

    Multimodal imaging of functional networks and event-related potentials in performance monitoring

    Neuroimage

    (2011)
  • R. Ratcliff et al.

    Diffusion decision model: current issues and history

    Trends Cogn Sci

    (2016)
  • Z. Dienes

    How Bayes factors change scientific practice

    J Math Psychol

    (2016)
  • M.E. Martz et al.

    Psychosocial and neural indicators of resilience among youth with a family history of substance use disorder

    Drug Alcohol Depend

    (2018)
  • S. Ziegler et al.

    Modelling ADHD: a review of ADHD theories through their predictions for computational models of decision-making and reinforcement learning

    Neurosci Biobehav Rev

    (2016)
  • C.D. Chambers et al.

    Insights into the neural basis of response inhibition from cognitive and clinical neuroscience

    Neurosci Biobehav Rev

    (2009)
  • M.C. Stevens et al.

    Functional neural networks underlying response inhibition in adolescents and adults

    Behav Brain Res

    (2007)
  • A. Cubillo et al.

    Reduced activation and inter-regional functional connectivity of fronto-striatal networks in adults with childhood attention-deficit hyperactivity disorder (ADHD) and persisting symptoms during tasks of motor inhibition and cognitive switching

    J Psychiatr Res

    (2010)
  • T.W. Janssen et al.

    Neural correlates of response inhibition in children with attention-deficit/hyperactivity disorder: A controlled version of the stop-signal task

    Psychiatry Res

    (2015)
  • M.J. Endres et al.

    Externalizing psychopathology and behavioral disinhibition: Working memory mediates signal discriminability and reinforcement moderates response bias in approach–avoidance learning

    J Abnorm Psychol

    (2011)
  • L. Wright et al.

    Response inhibition and psychopathology: A meta-analysis of go/no-go task performance

    J Abnorm Psychol

    (2014)
  • N. Castellanos-Ryan et al.

    Neural and cognitive correlates of the common and specific variance across externalizing problems in young adolescence

    Am J Psychiatry

    (2014)
  • B. Saunders et al.

    Impulsive errors on a Go-NoGo reaction time task: Disinhibitory traits in relation to a family history of alcoholism

    Alcohol Clin Exp Res

    (2008)
  • B.J. Casey et al.

    A developmental functional MRI study of prefrontal activation during performance of a go-no-go task

    J Cogn Neurosci

    (1997)
  • S. Durston et al.

    A neural basis for the development of inhibitory control

    Dev Sci

    (2002)
  • K.P. Schulz et al.

    Response inhibition in adolescents diagnosed with attention deficit hyperactivity disorder during childhood: An event-related FMRI study

    Am J Psychiatry

    (2004)
  • R.R. Wetherill et al.

    A longitudinal examination of adolescent response inhibition: Neural differences before and after the initiation of heavy drinking

    Psychopharmacology

    (2013)
  • H. Garavan et al.

    Right hemispheric dominance of inhibitory control: an event-related functional MRI study

    Proc Natl Acad Sci U S A

    (1999)
  • D. Zheng et al.

    The key locus of common response inhibition network for no-go and stop signals

    J Cogn Neurosci

    (2008)
  • A. Ahmadi et al.

    Influence of alcohol use on neural response to go/no-go task in college drinkers

    Neuropsychopharmacology

    (2013)
  • E.D. Claus et al.

    Behavioral control in alcohol use disorders: relationships with severity

    J Stud Alcohol Drugs

    (2013)
  • M.C. Stevens et al.

    Brain network dynamics during error commission

    Hum Brain Mapp

    (2009)
  • J. Rasmussen et al.

    ADHD and cannabis use in young adults examined using fMRI of a Go/NoGo task

    Brain Imaging Behav

    (2016)
  • M. Czapla et al.

    Do alcohol-dependent patients show different neural activation during response inhibition than healthy controls in an alcohol-related fMRI go/no-go- task?

    Psychopharmacology

    (2017)
  • W. Dillo et al.

    Neuronal correlates of ADHD in adults with evidence for compensation strategies—a functional MRI study with a Go/No-Go paradigm

    Ger Med Sci

    (2010)
  • W.N. Ding et al.

    Trait impulsivity and impaired prefrontal impulse inhibition function in adolescents with internet gaming addiction revealed by a Go/No-Go fMRI study

    Behav Brain Funct

    (2014)
  • S.F. Tapert et al.

    Functional MRI of inhibitory processing in abstinent adolescent marijuana users

    Psychopharmacology

    (2007)
  • R. Ratcliff

    A theory of memory retrieval

    Psychol Rev

    (1978)
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