Cited by 246Neural and Behavioral Psychology StudiesPain Mechanisms and TreatmentsNeurotransmitter Receptor Influence on Behavior

The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index; none of the 27 sources its claims cite is checked for support yet.

Representation of aversive prediction errors in the human periaqueductal gray

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Roy, Mathieu, Shohamy, Daphna, Daw, Nathaniel, Jepma, Marieke, Wimmer, G Elliott, Wager, Tor D·2014·Nature Neuroscience

DOI 10.1038/nn.3832PMC PMC4213247

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Abstract

Pain is a primary driver of learning and motivated action. It is also a target of learning, as nociceptive brain responses are shaped by learning processes. We combined an instrumental pain avoidance task with an axiomatic approach to assessing fMRI signals related to prediction errors (PEs), which drive reinforcement-based learning. We found that pain PEs were encoded in the periaqueductal gray (PAG), a structure important for pain control and learning in animal models. Axiomatic tests combined with dynamic causal modeling suggested that ventromedial prefrontal cortex, supported by putamen, provides an expected value–related input to the PAG, which then conveys PE signals to prefrontal regions important for behavioral regulation, including orbitofrontal, anterior mid-cingulate and dorsomedial prefrontal cortices. Thus, pain-related learning involves distinct neural circuitry, with implications for behavior and pain dynamics.

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Crossref · 10.1038/nn.3832

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In the paper
“As expected, in contradistinction to the main study, appetitive PEs to monetary rewards were tracked by activity in the VS. (t(20) = 5.77, p < 0.001), but not the PAG (PAG–appetitive: t(20) = 1.54, p = 0.14; see Supplementary Fig. 2).”
§ Representation of aversive prediction errors in the human periaqueductal gray > RESULTS > Studies 2 and 3: Monetary rewards and varying pain levels
What the sources say
- Not checked yetcites [23] Wimmer, G.E., Daw, N.D. & Shohamy, D. Generalization of value in reinforcement learning by humans. Eur. J. Neurosci. 35, 1092–1104 (2012). source
Load-bearingStrength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes

Show all 36 claims

It may state two separate claims as one. 26
Probably not a substantial claim. 11

In the paper
“The analysis revealed learning rates (α=0.63±0.26), softmax inverse temperatures (β=4.74±2.74), and model fits (negative log likelihood = 65 ± 21) comparable to those found in similar studies of reinforcement learning20.”
§ Representation of aversive prediction errors in the human periaqueductal gray > RESULTS > Behavioral results
What the sources say
- Not checked yetcites [20] Schönberg, T., Daw, N.D., Joel, D. & O'Doherty, J.P. Reinforcement learning signals in the human striatum distinguish learners from nonlearners during reward-based decision making. J. Neurosci. 27, 12860–12867 (2007). source
Load-bearingStrength:plain· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In this model, vmPFC projects most directly to PAG, and avoidance value is most closely related to the putamen, which transmits value information to vmPFC.”
§ Representation of aversive prediction errors in the human periaqueductal gray > Online Methods > fMRI data analyses
Load-bearingStrength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
It may state two separate claims as one.
- The authors state this as an assumption: Primary nociceptive afferents project directly to the PAG.
- The authors state this as an assumption: Expected avoidance value reaches the PAG through at least one of the three expected-value structures (vmPFC, putamen, hippocampus).
- The authors state this as an assumption: Prediction error signals can be sent directly to the OFC and aMCC, and indirectly to the dmPFC via either aMCC or OFC.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The best model overall is shown in Figure 4, and included a) direct connections from both putamen and midbrain to OFC and aMCC, with dmPFC effects mediated by OFC, and b) modulatory effects of noxious input to putamen → OFC, putamen → aMCC, and midbrain → aMCC connections.”
§ Representation of aversive prediction errors in the human periaqueductal gray > Online Methods > fMRI data analyses
Load-bearingStrength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
It may state two separate claims as one.
- The authors state this as an assumption: Primary nociceptive afferents project directly to the PAG.
- The authors state this as an assumption: Expected avoidance value reaches the PAG through at least one of the three expected-value structures (vmPFC, putamen, hippocampus).
- The authors state this as an assumption: Prediction error signals can be sent directly to the OFC and aMCC, and indirectly to the dmPFC via either aMCC or OFC.
In the paper
“Our data and connectivity models identify the PAG as a primary site for aversive PEs, in contrast to previous neuroimaging findings and theories that a single system drives appetitive and aversive PEs29.”
§ Representation of aversive prediction errors in the human periaqueductal gray > DISCUSSION > Towards a neural systems model for aversive PEs
What the sources say
- Not checked yetcites [29] Brooks, A.M. & Berns, G.S. Aversive stimuli and loss in the mesocorticolimbic dopamine system. Trends Cogn. Sci. 17, 281–286 (2013). source
Load-bearingStrength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
It may state two separate claims as one.
In the paper
“The PAG a priori ROI was constructed by aligning three overlapping 6-mm spheres along the central aqueduct ([0 –24 –4; 0 –26 –6; 0 –29 –8]), and closely matched the findings of a recent meta-analysis on pain-processing in the PAG (Linnman, Moulton, Barmettler, Becerra, & Borsook, 2012a).”
§ Representation of aversive prediction errors in the human periaqueductal gray > Online Methods > fMRI data analyses
What the sources say
- Not checked yetcites Linnman, Moulton, Barmettler, Becerra, & Borsook, 2012a
Strength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“PAG neurons respond more strongly to unexpected vs. expected electric shocks18, consistent with our fMRI findings here.”
§ Representation of aversive prediction errors in the human periaqueductal gray > DISCUSSION > Towards a neural systems model for aversive PEs
What the sources say
- Not checked yetcites [18] Johansen, J.P., Tarpley, J.W., LeDoux, J.E. & Blair, H.T. Neural substrates for expectation-modulated fear learning in the amygdala and periaqueductal gray. Nat. Neurosci. 13, 979–986 (2010). source
Load-bearingStrength:plain· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
It may state two separate claims as one.
In the paper
“The aMCC in particular is critical for pain avoidance18 and is heavily connected to motor and premotor centers (aMCC).”
§ Representation of aversive prediction errors in the human periaqueductal gray > DISCUSSION > Towards a neural systems model for aversive PEs
What the sources say
- Not checked yetcites [18] Johansen, J.P., Tarpley, J.W., LeDoux, J.E. & Blair, H.T. Neural substrates for expectation-modulated fear learning in the amygdala and periaqueductal gray. Nat. Neurosci. 13, 979–986 (2010). source
Strength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes
It may state two separate claims as one.
In the paper
“This is consistent with recent findings that the vmPFC may act as a “hub” or “convergence point” for different types of expected value signals, such as experienced-based expected value signals computed in the putamen and model-based value signals computed in the caudate48.”
§ Representation of aversive prediction errors in the human periaqueductal gray > DISCUSSION > Overlap in systems for reward and aversive PEs
What the sources say
- Not checked yetcites [48] Wunderlich, K., Dayan, P. & Dolan, R.J. Mapping value based planning and extensively trained choice in the human brain. Nat. Neurosci. 15, 786–791 (2012). source
Strength:hedged· not yet calibratedCausal:conditional· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Noxious input had direct effects on PAG, in keeping with the known anatomy of the ascending spinomesencephalic nociceptive pathway28, and modulatory effects on ascending putamen-to-OFC, putamen-to-aMCC, and midbrain-to-aMCC connections.”
§ Representation of aversive prediction errors in the human periaqueductal gray > RESULTS > Network dynamics underlying aversive PE signals
What the sources say
- Not checked yetcites [28] Millan, M.J. The induction of pain: an integrative review. Prog. Neurobiol. 57, 1–164 (1999). source
Load-bearingStrength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“The PAG receives monosynaptic inputs from both nociceptive spinal projection neurons28 and top-down projections from the vmPFC30, positioning it as a potential comparator of ‘bottom up’ aversive sensations with expectations.”
§ Representation of aversive prediction errors in the human periaqueductal gray > DISCUSSION > Towards a neural systems model for aversive PEs
What the sources say
- Not checked yetcites [28] Millan, M.J. The induction of pain: an integrative review. Prog. Neurobiol. 57, 1–164 (1999). source
- Not checked yetcites [30] Price, J.L. Definition of the orbital cortex in relation to specific connections with limbic and visceral structures and other cortical regions. Ann. NY Acad. Sci. 1121, 54–71 (2007). source
Load-bearingStrength:hedged· not yet calibratedCausal:correlational· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
It may state two separate claims as one.
In the paper
“The VS ROI was based on Rutledge et al. (2010)9 nucleus accumbens ROI and was comprised of three 5 mm spheres for each hemisphere ([8 13 –3; 12 13 –8; 9 13 –7; –8 13 –3; –12 13 –8; –9 13 –7 ]).”
§ Representation of aversive prediction errors in the human periaqueductal gray > Online Methods > fMRI data analyses
What the sources say
- Not checked yetcites Rutledge et al. (2010) source
Strength:plain· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Though this procedure cannot definitively isolate causal relationships among regions, this model provides a plausible working model considering the direct anatomical projections from vmPFC to PAG30.”
§ Representation of aversive prediction errors in the human periaqueductal gray > Online Methods > fMRI data analyses
What the sources say
- Not checked yetcites [30] Price, J.L. Definition of the orbital cortex in relation to specific connections with limbic and visceral structures and other cortical regions. Ann. NY Acad. Sci. 1121, 54–71 (2007). source
Load-bearingStrength:hedged· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
It may state two separate claims as one.
- The authors state this as an assumption: Primary nociceptive afferents project directly to the PAG.
- The authors state this as an assumption: Expected avoidance value reaches the PAG through at least one of the three expected-value structures (vmPFC, putamen, hippocampus).
- The authors state this as an assumption: Prediction error signals can be sent directly to the OFC and aMCC, and indirectly to the dmPFC via either aMCC or OFC.
None of the sources cited for this claim have been checked yet.
In the paper
“Based on existent animal models of fear conditioning1,18, we posited that these regions receive the PE signals generated in PAG.”
§ Representation of aversive prediction errors in the human periaqueductal gray > Online Methods > fMRI data analyses
What the sources say
- Not checked yetcites [1] McNally, G.P., Johansen, J.P. & Blair, H.T. Placing prediction into the fear circuit. Trends Neurosci. 34, 283–292 (2011). source
- Not checked yetcites [18] Johansen, J.P., Tarpley, J.W., LeDoux, J.E. & Blair, H.T. Neural substrates for expectation-modulated fear learning in the amygdala and periaqueductal gray. Nat. Neurosci. 13, 979–986 (2010). source
Load-bearingStrength:hedged· not yet calibratedCausal:direct· not yet calibrated
Tests✗ Asserted: fails✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
Probably not a substantial claim. The authors may not put it forward as true.

34 of 34

The authors state this as an assumption.
Primary nociceptive afferents project directly to the PAG.
“1) primary nociceptive afferents directly project to PAG28”
The authors state this as an assumption.
Expected avoidance value reaches the PAG through at least one of the three expected-value structures (vmPFC, putamen, hippocampus).
“2) expected avoidance value is conveyed to the PAG through one or more of the three expected value structures (green in Fig. 3).”
The authors state this as an assumption.
Prediction error signals can be sent directly to the OFC and aMCC, and indirectly to the dmPFC via either aMCC or OFC.
“we constrained the space of possible models by assuming that PE signals could be directly conveyed to the OFC and aMCC32, and indirectly to the dmPFC through either aMCC or OFC.”
The authors state this as an assumption.
Higher pain is always more aversive than lower pain (monotonicity in pain intensity).
“namely, that higher pain is always more aversive than lower pain (monotonicity in pain intensity)”
The authors state this as an assumption.
High versus low expectancies are similarly monotonic.
“and that high vs. low expectancies are similarly monotonic.”
The authors state this as an assumption.
More intense noxious stimulus intensities are more aversive (monotonicity of aversiveness with stimulus intensity).
“we adapted study 1 axioms by making the additional assumption that more intense noxious stimulus intensities should be more aversive (i.e., monotonicity of aversiveness with stimulus intensity).”

6 of 6

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Statistics recomputed

Every reported test result, recomputed from its test statistic and degrees of freedom. A result shows as not adding up only once an independent check has confirmed it.

Not confirmedt(22) = -2.05reported p < .05 · recomputed p = .052
“t(22)=-2.05, p < .05”
Not confirmedt(22) = -1.98reported p < .05 · recomputed p = .060
“t(22)=-1.98, p < .05”
Consistentt(22) = 3.67reported p < .05 · recomputed p = .001
“t(22) = 3.67, p < .05”
Consistentt(20) = 5.77reported p < .001 · recomputed p < .001
“t(20) = 5.77, p < .001”
Consistentt(20) = 1.54reported p = .14 · recomputed p = .139
“t(20) = 1.54, p = .14”
ConsistentF(1, 49) = 4.39reported p < .05 · recomputed p = .041
“F(1,49) = 4.39, p < .05”
ConsistentF(1, 49) = 16.03reported p < .001 · recomputed p < .001
“F(1,49) =16.03, p < .001”
Consistentt(22) = -1.82reported p < .05 · recomputed p = .082
“t(22)=-1.82, p < .05”
The paper states a one-tailed test

8 of 8

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Daw, N.D. in Decision Making, Affect and Learning. (eds. Delgado, M.R., Phelps, E.A. & Robbins, T.W.) 3–38 (Oxford Univ. Press, 2011).

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Authors: Roy, M., Shohamy, D., Daw, N., Jepma, M., Wimmer, G. E., & Wager, T. D.
Affiliations: University of Colorado Boulder (US)
New York University (US)
University Medical Center Hamburg-Eppendorf (DE)
Corresponding author: Wager, Tor D
ORCID: Roy, Mathieu
Daw, Nathaniel
Jepma, Marieke
Wimmer, G Elliott
Wager, Tor D
Venue: Nature Neuroscience
Publisher: Springer Science and Business Media LLC
Published: 2014-10-05
Volume: 17
Issue: 11
Pages: 1607-1612
ISSN: 1097-6256 (ISSN-L)
1546-1726
DOI: 10.1038/nn.3832
PMC: PMC4213247
OpenAlex: W1995906064
Semantic Scholar: 3b5deee843f5e9ff6e35df44aee33bc777a01def
Cited by: 246
References: 52
Citations by year: 2026: 13 · 2025: 21 · 2024: 20 · 2023: 19 · 2022: 24 · 2021: 20 · 2020: 24 · 2019: 16 · 2018: 24 · 2017: 27 · 2016: 18 · 2015: 18 · 2014: 2
FWCI: 12.09
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Licence: www.springer.com/tdm (tdm)
Locations: Nature Neuroscience (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Funders: Canadian Institutes of Health Research
National Institute of Mental Health (R01MH076136)
National Institute on Drug Abuse (R01DA027794, R01DA035484)
Topics: Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
Health Sciences › Medicine › Physiology (medical) › Pain Mechanisms and Treatments
Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
Keywords: periaqueductal gray, pain, pain avoidance, reinforcement learning, expected value, ventromedial prefrontal cortex, putamen, midbrain, dynamic causal modeling, axiomatic analysis, nociception, pain management, orbitofrontal cortex, anterior midcingulate cortex, dorsomedial prefrontal cortex
MeSH terms: Adolescent, Adult, Behavior, Brain Mapping, Female, Gyrus Cinguli, Humans, Learning, Magnetic Resonance Imaging, Male, Pain, Periaqueductal Gray, Reinforcement, Psychology, Prefrontal Cortex, Young Adult, Pain Management

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Representation of aversive prediction errors in the human periaqueductal gray

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