Skip to main content

Main menu

  • HOME
  • CONTENT
    • Early Release
    • Featured
    • Current Issue
    • Issue Archive
    • Blog
    • Collections
    • Podcast
  • TOPICS
    • Cognition and Behavior
    • Development
    • Disorders of the Nervous System
    • History, Teaching and Public Awareness
    • Integrative Systems
    • Neuronal Excitability
    • Novel Tools and Methods
    • Sensory and Motor Systems
  • ALERTS
  • FOR AUTHORS
  • ABOUT
    • Overview
    • Editorial Board
    • For the Media
    • Privacy Policy
    • Contact Us
    • Feedback
  • SUBMIT

User menu

Search

  • Advanced search
eNeuro

eNeuro

Advanced Search

 

  • HOME
  • CONTENT
    • Early Release
    • Featured
    • Current Issue
    • Issue Archive
    • Blog
    • Collections
    • Podcast
  • TOPICS
    • Cognition and Behavior
    • Development
    • Disorders of the Nervous System
    • History, Teaching and Public Awareness
    • Integrative Systems
    • Neuronal Excitability
    • Novel Tools and Methods
    • Sensory and Motor Systems
  • ALERTS
  • FOR AUTHORS
  • ABOUT
    • Overview
    • Editorial Board
    • For the Media
    • Privacy Policy
    • Contact Us
    • Feedback
  • SUBMIT
PreviousNext
Research ArticleMethods/New Tools, Cognition and Behavior

The Neural Basis of Approach-Avoidance Conflict: A Model Based Analysis

Samuel Zorowitz, Alexander P. Rockhill, Kristen K. Ellard, Katherine E. Link, Todd Herrington, Diego A. Pizzagalli, Alik S. Widge, Thilo Deckersbach and Darin D. Dougherty
eNeuro 25 July 2019, 6 (4) ENEURO.0115-19.2019; DOI: https://doi.org/10.1523/ENEURO.0115-19.2019
Samuel Zorowitz
1Division of Neurotherapeutics, Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Alexander P. Rockhill
1Division of Neurotherapeutics, Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Alexander P. Rockhill
Kristen K. Ellard
1Division of Neurotherapeutics, Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Katherine E. Link
1Division of Neurotherapeutics, Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Todd Herrington
2Department of Neurology, Massachusetts General Hospital, Boston, MA 02114
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Diego A. Pizzagalli
3Department of Psychiatry, McLean Hospital, Belmont, MA 02478
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Diego A. Pizzagalli
Alik S. Widge
1Division of Neurotherapeutics, Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Thilo Deckersbach
1Division of Neurotherapeutics, Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Darin D. Dougherty
1Division of Neurotherapeutics, Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Info & Metrics
  • eLetters
  • PDF
Loading

Article Figures & Data

Figures

  • Tables
  • Figure 1.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 1.

    Aversion-reward conflict (ARC) task. Participants are presented with a safe choice (blue) and a risky choice (orange). The safe choice pays a guaranteed small reward ($0.01) and no aversive stimulation. The risky choice pays a guaranteed larger reward ($0.05–$0.95), and a probability of stimulation as indicated by the centered white bar. Participants decide whether to accept a higher payout at risk of aversive stimulation. Figure Contributions: Darin Dougherty, Thilo Deckersbach, Alik Widge, and Samuel Zorowitz designed the task. Sam Zorowitz created the figure.

  • Figure 2.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 2.

    A Kruschke-style diagram of the hierarchical model. The ∼ symbol indicates stochastic dependency, whereas the = symbol indicates a deterministic dependency. Ellipses indicate the indices over which the dependency applies. The parameter of most interest is d, the inverse distance-to-decision-boundary, which measures the estimated conflict experienced on a given trial. Figure Contributions: Samuel Zorowitz created the model.

  • Figure 3.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 3.

    A priori cortical regions of interest. Regions (Freesurfer labels) were selected from the Mindboggle atlas (https://mindboggle.info/data.html) based on the diffuse locations of activations previously reported in the approach-avoidance decision-making literature. Figure Contributions: Samuel Zorowitz chose the regions of interest based on prior literature and created the figure.

  • Figure 4.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 4.

    Group-level behavior results. A, The estimated likelihood of choosing the risky option for each risk level and across rewards. The model estimated decreases in risky decision-making at both 50% risk (β1 = –1.922, 95% HDI: [–2.606, –1.139]) and 90% risk (β2 = –4.180, 95% HDI: [–5.273, –3.257]). In contrast, the model estimated increases in risky decision-making in response to increasing reward (β3 = 10.652, 95% HDI: [8.239, 12.887]). B, The estimated linear component of deliberation time as a function of decision conflict, d. The model estimated an increase in deliberation time with decision conflict (α1 = 0.456, 95% HDI: [0.388, 0.528]). Shaded regions denote the 95% HDI. Figure Contributions: Samuel Zorowitz, Katherine Link, and Alexander Rockhill performed the behavioral analysis.

  • Figure 5.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 5.

    Individual differences in behavior. Participants in the ARC task exhibited large individual differences in behavior. A, Participants varied in their approach-avoidance preferences (although the majority was approach biased). B, Participants varied in the extent to which their deliberation increased in response to decision conflict (but all participants showed increased response times during conflict). Each point represents one participant. The horizontal axis denotes the observed behavior (proportion of risky choices, A; response time increases, B), and the vertical axis denotes the model predicted behavior. Proximity to the diagonal indicates goodness of fit. Figure Contributions: Samuel Zorowitz, Katherine Link, and Alexander Rockhill performed the behavioral analysis.

  • Figure 6.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 6.

    PSC during deliberation. The control regressor measures changes in the BOLD signal during deliberation (independent of approach-avoidance conflict). Positive activation was found in cortical and subcortical regions including the lateral and medial PFC, striatum, and hippocampus. All voxels corrected for multiple comparisons through 5000-iteration permutation testing and voxel-wise FWE corrections (α = 0.05). LH, left hemisphere; RH, right hemisphere. Figure Contributions: Samuel Zorowitz and Alexander Rockhill performed the fMRI analysis. Samuel Zorowitz, Alexander Rockhill, and Kristen Kellard collected the data.

  • Figure 7.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 7.

    PSC during conflict. The parametric modulation regressor measures changes in BOLD signal during deliberation as a function of approach-avoidance conflict. Positive activation was detected only in bilateral IFG, and right dlPFC, and pre-SMA. All voxels corrected for multiple comparisons through 5000-iteration permutation testing and voxel-wise FWE corrections (α = 0.05). Figure Contributions: Samuel Zorowitz and Alexander Rockhill performed the fMRI analysis; Samuel Zorowitz, Alexander Rockhill and Kristen Kellard collected the data.

  • Figure 8.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 8.

    PSC during conflict for the fixed epochs analysis. In this case, epochs were made from the first stimulus presentation to the end of the response period instead of ending when the subject responded for each particular trial. A more widespread, less specific, smaller, positive activation was detected in the same structures as Figure 7 with the addition of activation in bilateral striatum, left insula as well as greater activation in bilateral dlPFC. All voxels corrected for multiple comparisons through 5000-iteration permutation testing and voxel-wise FWE corrections (α = 0.05). Figure Contributions: Alexander Rockhill performed the fMRI analysis. Samuel Zorowitz, Alexander Rockhill, and Kristen Kellard collected the data.

Tables

  • Figures
    • View popup
    Table 1.

    Coordinates and statistics of peak BOLD activations

    Deliberation phase (control)
    ROIxyzPSCF
    dACC/dmPFC: LH–1222360.08352.92
    RH715240.09462.05
    MCC: LH–7–22290.15328.72
    RH7–15310.18529.27
    pre-SMA: LH–97510.10419.56
    RH1014470.10373.34
    dlPFC: LH–369240.12223.96
    RH3618250.11312.87
    Anterior insula: LH–312790.2351.91
    RH312780.16413.00
    Lateral OFC: RH1338–240.0795.60
    Pre-motor: LH–37–2430.14291.16
    RH36–3440.14333.73
    Caudate: LH–10730.0728.42
    RH101150.0625.16
    Putamen: LH–20510.0529.04
    RH34–7–70.0422.15
    Hippocampus: LH–14–39–30.0934.95
    RH14–39–10.1034.47
    Deliberation phase (conflict)
    IFG: LH–394570.0556.53
    RH4245–60.0555.10
    dlPFC: RH4227310.0468.02
    pre-SMA: RH927460.0459.55
    • The reported statistics are the PSC and WLSs contrast against baseline (F) statistic. The first set of results reflect the unmodulated deliberation and the second set reflect the contrast between deliberation parametrically modulated by conflict and unmodulated deliberation. All coordinates reported in the MNI space and reflect the peak of activation. All voxel statistics were corrected for multiple comparisons through 5000-iteration permutation testing and voxel-wise FWE corrections (α = 0.05). LH, left hemisphere; RH, right hemisphere; MCC, midcingulate cortex.

Back to top

In this issue

eneuro: 6 (4)
eNeuro
Vol. 6, Issue 4
July/August 2019
  • Table of Contents
  • Index by author
  • Ed Board (PDF)
Email

Thank you for sharing this eNeuro article.

NOTE: We request your email address only to inform the recipient that it was you who recommended this article, and that it is not junk mail. We do not retain these email addresses.

Enter multiple addresses on separate lines or separate them with commas.
The Neural Basis of Approach-Avoidance Conflict: A Model Based Analysis
(Your Name) has forwarded a page to you from eNeuro
(Your Name) thought you would be interested in this article in eNeuro.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Print
View Full Page PDF
Citation Tools
The Neural Basis of Approach-Avoidance Conflict: A Model Based Analysis
Samuel Zorowitz, Alexander P. Rockhill, Kristen K. Ellard, Katherine E. Link, Todd Herrington, Diego A. Pizzagalli, Alik S. Widge, Thilo Deckersbach, Darin D. Dougherty
eNeuro 25 July 2019, 6 (4) ENEURO.0115-19.2019; DOI: 10.1523/ENEURO.0115-19.2019

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Respond to this article
Share
The Neural Basis of Approach-Avoidance Conflict: A Model Based Analysis
Samuel Zorowitz, Alexander P. Rockhill, Kristen K. Ellard, Katherine E. Link, Todd Herrington, Diego A. Pizzagalli, Alik S. Widge, Thilo Deckersbach, Darin D. Dougherty
eNeuro 25 July 2019, 6 (4) ENEURO.0115-19.2019; DOI: 10.1523/ENEURO.0115-19.2019
Reddit logo Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Significance Statement
    • Introduction
    • Materials and Methods
    • Results
    • Discussion
    • Acknowledgments
    • Footnotes
    • References
    • Synthesis
    • Author Response
  • Figures & Data
  • Info & Metrics
  • eLetters
  • PDF

Keywords

  • approach-avoidance
  • cognitive
  • decision making
  • fMRI
  • psychiatry
  • psychology

Responses to this article

Respond to this article

Jump to comment:

No eLetters have been published for this article.

Related Articles

Cited By...

More in this TOC Section

Methods/New Tools

  • Bicistronic expression of a high-performance calcium indicator and opsin for all-optical stimulation and imaging at cellular resolution
  • A Toolbox of Criteria for Distinguishing Cajal–Retzius Cells from Other Neuronal Types in the Postnatal Mouse Hippocampus
  • Superficial Bound of the Depth Limit of Two-Photon Imaging in Mouse Brain
Show more Methods/New Tools

Cognition and Behavior

  • Environment Enrichment Facilitates Long-Term Memory Consolidation Through Behavioral Tagging
  • Effects of cortical FoxP1 knockdowns on learned song preference in female zebra finches
  • The genetic architectures of functional and structural connectivity properties within cerebral resting-state networks
Show more Cognition and Behavior

Subjects

  • Cognition and Behavior

  • Home
  • Alerts
  • Visit Society for Neuroscience on Facebook
  • Follow Society for Neuroscience on Twitter
  • Follow Society for Neuroscience on LinkedIn
  • Visit Society for Neuroscience on Youtube
  • Follow our RSS feeds

Content

  • Early Release
  • Current Issue
  • Latest Articles
  • Issue Archive
  • Blog
  • Browse by Topic

Information

  • For Authors
  • For the Media

About

  • About the Journal
  • Editorial Board
  • Privacy Policy
  • Contact
  • Feedback
(eNeuro logo)
(SfN logo)

Copyright © 2023 by the Society for Neuroscience.
eNeuro eISSN: 2373-2822

The ideas and opinions expressed in eNeuro do not necessarily reflect those of SfN or the eNeuro Editorial Board. Publication of an advertisement or other product mention in eNeuro should not be construed as an endorsement of the manufacturer’s claims. SfN does not assume any responsibility for any injury and/or damage to persons or property arising from or related to any use of any material contained in eNeuro.