Skip to main content

Main menu

  • HOME
  • CONTENT
    • Early Release
    • Featured
    • Current Issue
    • Issue Archive
    • Collections
    • Podcast
  • ALERTS
  • FOR AUTHORS
    • Information for Authors
    • Fees
    • Journal Clubs
    • eLetters
    • Submit
    • Special Collections
  • EDITORIAL BOARD
    • Editorial Board
    • ECR Advisory Board
    • Journal Staff
  • ABOUT
    • Overview
    • Advertise
    • For the Media
    • Rights and Permissions
    • Privacy Policy
    • Feedback
    • Accessibility
  • SUBSCRIBE

User menu

  • Log out
  • Log in
  • My Cart

Search

  • Advanced search
Journal of Neuroscience
  • Log out
  • Log in
  • My Cart
Journal of Neuroscience

Advanced Search

Submit a Manuscript
  • HOME
  • CONTENT
    • Early Release
    • Featured
    • Current Issue
    • Issue Archive
    • Collections
    • Podcast
  • ALERTS
  • FOR AUTHORS
    • Information for Authors
    • Fees
    • Journal Clubs
    • eLetters
    • Submit
    • Special Collections
  • EDITORIAL BOARD
    • Editorial Board
    • ECR Advisory Board
    • Journal Staff
  • ABOUT
    • Overview
    • Advertise
    • For the Media
    • Rights and Permissions
    • Privacy Policy
    • Feedback
    • Accessibility
  • SUBSCRIBE
PreviousNext
Brief Communications

From Animal Model to Human Brain Networking: Dynamic Causal Modeling of Motivational Systems

Tal Gonen, Roee Admon, Ilana Podlipsky and Talma Hendler
Journal of Neuroscience 23 May 2012, 32 (21) 7218-7224; https://doi.org/10.1523/JNEUROSCI.6188-11.2012
Tal Gonen
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Roee Admon
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ilana Podlipsky
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Talma Hendler
  • 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.

    Domino game paradigm. Each round of the game was composed of four intervals: the player chose which chip to play next (first interval: “Choose”; 4 s), moved the cursor to the chosen chip, and placed it face down adjacent to the master chip (second interval: “Ready” and “Go”; 4 s). The player then waited for the opponent's response (third interval: “Anticipation”; jittered randomly to 3.4, 5.4, or 7.4 s), and saw whether the opponent challenged this choice by uncovering the chosen chip or not (fourth interval: “Outcome”; jittered randomly to 3.4, 5.4, or 7.4 s). The player's choices and opponent's responses were interactively determined by the flow of the game round after round, creating a natural and unpredictable progression of a game situation that lasted 4 min or until the player won. Each player played consecutively for 14 min (average number of games ± SEM: 4.23 ± 0.06).

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

    Whole-brain analysis. Each of our three contrasts of interest elicited a differential pattern of distributed brain activations that highly corresponded to the motivational neural systems as proposed by the RST model. During response to punishment, activations were observed in the amygdala (1), hypothalamus (2), and sgACC (3), corresponding to the FFFS (red). During response to reward, activations were observed in the NAcc (4) and dmPFC (5), corresponding to BAS (green). Finally, during periods of goal-conflict, activations were observed in the hippocampus (6) and vmPFC (7), corresponding to BIS (blue). n = 24.

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

    DCM results. A, Model comparison. Each comparison refers to one subgraph, consisting of four models with the same architecture (i.e., effective and modulatory connections), defined by different motivational states as inputs: (1) common effects, (2) conflict, (3) punishment, and (4) reward. B, Winning models. I, Effective connections were found to be significant among amygdala, hypothalamus, and sgACC during punishment interval, all suspected to be part of the FFFS. Punishment state had significant input to the amygdala and hypothalamus and modulatory effects on all connections between regions. II, Effective connections were found to be significant between NAcc and dmPFC under reward state, as proposed for BAS. Reward state had significant input to NAcc and modulatory effects on the NAcc–dmPFC connection. III, Effective connections were significant between the hippocampus and vmPFC during goal-conflict, as proposed for BIS. Goal-conflict state had significant input to the hippocampus and modulatory effects on all connections between regions. Tables display averaged parameter estimates (in Hz). n = 24.

Tables

  • Figures
    • View popup
    Table 1.

    Peak of activations elicited by our three predetermined independent whole-brain contrasts of interest (i.e., motivational states)

    RegionCluster (no. of voxels)Peak voxel (x, y, z)Z value (df = 23)p < (uncorrected)
    Response to punishment outcome
        R hypothalamus226, −6., −123.540.000
        L hypothalamus20−6, −6, −93.490.000
        Midbrain180, −13, −212.360.009
        R insula1241, −19, 243.190.001
        R amygdala625, −3, −273.180.001
        R inferior temporal gyrus1047, 3, −422.860.002
        L fusiform gyrus10−28, −53, −122.830.002
        R anterior cingulate cortex (BA 24)120, 25, 92.740.003
        R temporal pole (STG)744, 9, −212.720.003
        L precuneus106, −63, 302.620.004
        R posterior cingulated cortex713, −6, 302.520.006
        L parahippocampal gyrus11−28, −34, −122.510.006
        L superior temporal gyrus6−47, −16, −62.470.007
        R pons66, −19, −272.460.007
        L cerebellum21−6, −41, −182.440.007
        R cerebellum913, −31, −212.370.009
        L temporal pole (STG, BA 38)12−50, 6, −152.130.017
        R sgACC (BA25)83, 26, −42.060.02
        L anterior cingulated cortex (BA 32)6−9, 47, −31.960.025
    Response to reward outcome
        R inferior frontal gyrus (BA 44)5559, 9, 184.10.000
        R supra marginal gyrus1663, −22, 303.910.000
        L inferior parietal lobule (BA40)6−53, −53, 483.890.000
        L precentral gyrus (BA 6)28−63, −13, 363.870.000
        L putamen6−31, −16, −33.790.000
        L SMA280, 0, 663.690.000
        L NAcc61−16, 16, −33.640.000
        R lingual gyrus89, −78, 03.580.000
        R insula1141, −3, 93.520.000
        L insula8−34, −3, −33.500.000
        R cerebellum1128, −66, −303.490.000
        L thalamus9−16, −19, 93.490.000
        R precuneus79, −59, 543.440.000
        R caudate nucleus916, 19, 63.390.000
        L caudate nucleus6−22, 0, 213.360.000
        R NAcc289, 16, −33.350.000
        R middle occipital gyrus641, −81, 03.270.001
        R precentral gyrus774, −13, 513.230.001
        L precuneus (BA 7)14−19, −56, 393.230.001
        L middle frontal gyrus (BA 8)9−34, 22, 363.230.001
        R dorsomedial PFC (BA 10)822, 56, 153.130.001
    Response to goal-conflict
        L inferior frontal gyrus350−47, 19, 245.090.000
        L hippocampus40−22, −34, −64.790.000
        L occipital inferior and middle gyri (BA 17, 18)707−16, −91, −154.790.000
        L occipital inferior gyrus (BA 17)18013, −97, −34.730.000
        R inferior frontal gyrus12541, 22, 274.340.000
        R ventromedial PFC (BA 11)719, 38, −93.950.000
        L ventromedial PFC (BA 11)4019, 38, −93.930.000
        L SMA (BA 8)36−13, 16, 483.80.000
        R fusiform gyrus538, −63, −153.780.000
        R middle frontal gyrus531, 16, 573.740.000
        R caudate nucleus2913, 16, 123.620.000
        L caudate nucleus64−13, 22, 63.570.000
        L posterior cingulated cortex (BA 23)27−3, −34, 243.530.000
        L precuneus (BA 7)9−9, −72, −513.420.000
        R precuneus (BA 7)919, −66, 243.340.000
        R superior frontal gyrus (BA 10)919, 64, 33.630.001
        L anterior cingulated cortex (BA 33)5−3, 13, 273.150.001
        R hippocampus438, −28, −153.040.001
        R posterior cingulated cortex (BA 23)66, −34, 243.030.001
        R superior parietal lobule728, −63, 572.960.002
        R SMA513, 19, 452.860.002
    • Localization is based on Montreal Neurological Institute (MNI) criteria. Estimated level of activation is described by Z score and P values. Minimal p = 0.05, uncorrected, random effect, minimum cluster size 135 mm3 (i.e., 5 voxels). L, Left; R, right; BA, Brodmann area; SMA, supplementary motor area; STG, stomatogastric ganglion. n = 24.

Back to top

In this issue

The Journal of Neuroscience: 32 (21)
Journal of Neuroscience
Vol. 32, Issue 21
23 May 2012
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover
  • Index by author
  • Advertising (PDF)
  • Ed Board (PDF)
Email

Thank you for sharing this Journal of Neuroscience 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.
From Animal Model to Human Brain Networking: Dynamic Causal Modeling of Motivational Systems
(Your Name) has forwarded a page to you from Journal of Neuroscience
(Your Name) thought you would be interested in this article in Journal of Neuroscience.
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
From Animal Model to Human Brain Networking: Dynamic Causal Modeling of Motivational Systems
Tal Gonen, Roee Admon, Ilana Podlipsky, Talma Hendler
Journal of Neuroscience 23 May 2012, 32 (21) 7218-7224; DOI: 10.1523/JNEUROSCI.6188-11.2012

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Respond to this article
Request Permissions
Share
From Animal Model to Human Brain Networking: Dynamic Causal Modeling of Motivational Systems
Tal Gonen, Roee Admon, Ilana Podlipsky, Talma Hendler
Journal of Neuroscience 23 May 2012, 32 (21) 7218-7224; DOI: 10.1523/JNEUROSCI.6188-11.2012
Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Introduction
    • Materials and Methods
    • Results
    • Discussion
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • eLetters
  • PDF

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

  • Heteromodal Cortical Areas Encode Sensory-Motor Features of Word Meaning
  • Pharmacologically Counteracting a Phenotypic Difference in Cerebellar GABAA Receptor Response to Alcohol Prevents Excessive Alcohol Consumption in a High Alcohol-Consuming Rodent Genotype
  • Neuromuscular NMDA Receptors Modulate Developmental Synapse Elimination
Show more Brief Communications
  • Home
  • Alerts
  • Follow SFN on BlueSky
  • 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
  • Issue Archive
  • Collections

Information

  • For Authors
  • For Advertisers
  • For the Media
  • For Subscribers

About

  • About the Journal
  • Editorial Board
  • Privacy Notice
  • Contact
  • Accessibility
(JNeurosci logo)
(SfN logo)

Copyright © 2025 by the Society for Neuroscience.
JNeurosci Online ISSN: 1529-2401

The ideas and opinions expressed in JNeurosci do not necessarily reflect those of SfN or the JNeurosci Editorial Board. Publication of an advertisement or other product mention in JNeurosci 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 JNeurosci.