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Cited by 30Memory and Neural MechanismsNeurotransmitter Receptor Influence on BehaviorNeural and Behavioral Psychology Studies

A dual-pathway architecture for stress to disrupt agency and promote habit

Open access
Giovanniello, Jacqueline R., Paredes, Natalie, Wiener, Anna, Ramírez-Armenta, Kathia, Oragwam, Chukwuebuka, Uwadia, Hanniel O., Yu, Abigail L., Lim, Kayla +11 more·2025·Nature
DOI 10.1038/s41586-024-08580-wPMC PMC12011321
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Abstract

Chronic stress can change how we learn and, thus, how we make decisions1, 2, 3, 4–5. Here we investigated the neuronal circuit mechanisms that enable this. Using a multifaceted systems neuroscience approach in male and female mice, we reveal a dual-pathway, amygdala–striatal neuronal circuit architecture by which a recent history of chronic stress disrupts the action–outcome learning underlying adaptive agency and promotes the formation of inflexible habits. We found that the projection from the basolateral amygdala to the dorsomedial striatum is activated by rewarding events to support the action–outcome learning needed for flexible, goal-directed decision-making. Chronic stress attenuates this to disrupt action–outcome learning and, therefore, agency. Conversely, the projection from the central amygdala to the dorsomedial striatum mediates habit formation. Following stress, this pathway is progressively recruited to learning to promote the premature formation of inflexible habits. Thus, stress exerts opposing effects on two amygdala–striatal pathways to disrupt agency and promote habit. These data provide neuronal circuit insights into how chronic stress shapes learning and decision-making, and help understanding of how stress can lead to the disrupted decision-making and pathological habits that characterize substance use disorders and mental health conditions. Adaptive decision-making often requires an understanding of our agency in a situation; however, chronic stress can disrupt agency and promote inflexible, habitual behaviour by turning off a brain pathway needed for agency and activating one that promotes habit.

AI snapshot

Written from the paper’s full text.

TL;DR

Using tracing, fiber photometry, and optogenetic/chemogenetic manipulations in male and female mice, the paper identifies opposing amygdala→dorsomedial striatum pathways through which chronic stress disrupts action-outcome learning and promotes habit. Stress attenuates reward-evoked BLA→DMS activity and recruits CeA→DMS activity, flipping the balance from flexible agency to inflexible habit.

Key findings

  • Chronic mild unpredictable stress (14 consecutive days, 2 stressors/day) increased serum corticosterone and lowered body weight; stressed mice were insensitive to outcome-specific devaluation and contingency degradation, whereas controls reduced lever pressing when the outcome was devalued or the contingency degraded, indicating disrupted agency and premature habit. Initial devaluation experiment: Control N = 22 (13 male), Stress N = 25 (12 male).
  • BLA→DMS neurons were robustly activated by earned reward during learning in controls, and this activity was absent in stressed mice; CeA→DMS neurons were not robustly active in controls but were progressively recruited around earned reward after stress, with the CeA→DMS reward response taking approximately 30 s to return to baseline. Photometry Ns: BLA Control N = 9, BLA Stress N = 12; CeA Control N = 11, CeA Stress N = 11.
  • Optogenetic inhibition of BLA→DMS during learning caused subsequent insensitivity to devaluation; optogenetic or chemogenetic activation of BLA→DMS during post-stress learning restored devaluation sensitivity in stressed mice.
  • CeA→DMS inhibition during overtraining prevented natural habit formation; optogenetic or chemogenetic CeA→DMS inhibition during post-stress learning restored devaluation sensitivity in stressed mice. CeA→DMS activation alone was not sufficient to promote habit in non-stressed mice, but was sufficient to promote premature habit after subthreshold once-daily stress.

Methods

  • Subjects were male and female wildtype C57/Bl6J mice aged 9–12 weeks at surgery; Drd1a-Cre and Adora2A-Cre mice were used for rabies tracing. Chronic mild unpredictable stress consisted of 14 consecutive days of 2 stressors/day, pseudorandomly selected from damp bedding, tilted cage, white noise, continuous illumination, physical restraint, and footshock (0.7 mA); controls received equated handling.
  • Behavioral procedures used food-deprived mice trained to lever press for food pellets on FR-1 followed by random-ratio or random-interval schedules, with outcome-specific satiety devaluation and contingency degradation tests. Circuit methods included anterograde/retrograde and rabies tracing, fiber photometry of GCaMP8s in BLA→DMS or CeA→DMS projections, and optogenetic (Arch, ChR2) or chemogenetic (hM3Dq, hM4Di with CNO) manipulations.
  • Analyses used 2-tailed t-tests and 1-, 2-, or 3-way repeated-measures ANOVA, with Bonferroni post hoc tests, Greenhouse-Geisser correction, and alpha P < 0.05. Sex was initially included as a factor and was not significant for acquisition (F(1,43) = 0.43, P = 0.51), devaluation test press rate (F(1,43) = 0.60, P = 0.44), or devaluation index (F(1,43) = 0.04, P = 0.84), so sexes were combined.

Limitations

  • The paper states that for subsequent experiments the N per sex was underpowered to examine sex differences; investigators were not blinded to viral or stress group because they administered infusions and stress; some datasets were slightly non-normally distributed but parametric statistics were used for consistency; and future work is needed on mechanisms, downstream DMS activity, individual differences, and possible collateralization of the pathways.
  • Evident from the text: bulk fiber photometry cannot resolve specific cell types or whether amygdala→DMS projections collateralize, and although terminal optogenetic inhibition confirms involvement of direct amygdala projections to DMS, the paper notes that collaterals may also contribute.
  • The stress procedure was intentionally mild and did not cause major anxiety- or depression-like phenotypes in classic assays, so the findings may not generalize to more severe or longer-lasting stress procedures.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1038/s41586-024-08580-w

Cites

102 of 102 references verified0 citation errors · 0 not checkable

Statistics

180 tests recomputed · 0 with the reported and recomputed p on opposite sides of .05

Claims the paper makes

0 of 81 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    The central amygdala projection to the dorsomedial striatum mediates habit formation.

    “Conversely, the central amygdala projection to the dorsomedial striatum mediates habit formation.”
    • Also stated in: § CeA→DMS mediates habit formation · plain
      “Thus, the CeA→DMS pathway mediates the natural habit formation that occurs with repeated practice of an instrumental routine.”
    Quote in the paperSubstantial claim
  • Findingown data

    Serum corticosterone was higher in stressed mice than controls.

    “serum corticosterone was higher (Figure 1b; see Supplemental Table 1 for full statistical reporting) and body weight was lower (Figure 1c) in stressed mice than controls.”
    Quote in the paperSubstantial claim
  • Findingown data

    The basolateral amygdala projection to the dorsomedial striatum is activated by rewarding events to support the action-outcome learning needed for flexible, goal-directed decision making.

    “We found that the basolateral amygdala projection to the dorsomedial striatum is activated by rewarding events to support the action-outcome learning needed for flexible, goal-directed decision making.”
    • Also stated in: § Stress oppositely affects BLA→DMS and CeA→DMS · boosted
      “BLA→DMS neurons were robustly activated by earned reward during learning (Figure 2f–i).”
    Quote in the paperSubstantial claim
  • Findingown data

    Following stress, the CeA→DMS pathway is progressively recruited to learning to promote the premature formation of inflexible habits.

    “Following stress this pathway is progressively recruited to learning to promote the premature formation of inflexible habits.”
    • Also stated in: § Stress oppositely affects BLA→DMS and CeA→DMS · plain
      “Stress caused the CeA→DMS pathway to be progressively engaged around earned reward with training (Figure 2l–o).”
    Quote in the paperSubstantial claim
  • Findingown data

    Both control and stressed mice consumed similar amounts during the prefeed.

    “Both control and stressed mice consumed similar amounts during the prefeed (Supplemental Table 3), indicating that stress did not alter food consumption.”
    Quote in the paperSubstantial claim
  • May combine two claims. 45
  • Classified as probably not a substantial claim. 35
  • The quote only partly states this claim. 1

  • May combine two claims.

    Findingown data

    Chronic stress attenuates BLA→DMS activity to disrupt action-outcome learning and, therefore, agency.

    “Chronic stress attenuates this to disrupt action-outcome learning and, therefore, agency.”
    • Also stated in: § Stress oppositely affects BLA→DMS and CeA→DMS · plain
      “Chronic stress attenuated the BLA→DMS activity associated with action-outcome learning.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Aversive responses in BLA→DMS and CeA→DMS pathways were not altered by stress.

    “These aversive responses were not altered by stress (Extended Data Figure 6), providing a positive control for our ability to detect signal in all groups.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Optogenetic stimulation of CeA→DMS neurons with each earned reward during instrumental learning in mice without a history of chronic stress neither affected acquisition nor the action-outcome learning needed to support flexible, goal-directed decision making.

    “This neither affected acquisition of the lever-press behavior, nor the action-outcome learning needed to support flexible, goal-directed decision making during the devaluation test (Extended Data Figure 10).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Stress did not affect food pellet discrimination or devaluation efficacy.

    “Stress also did not affect food pellet discrimination or devaluation efficacy (Supplemental Table 4).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Stress disrupts agency and promotes habit regardless of whether behavior is reinforced on the agency-promoting random-ratio schedule or the habit-promoting random-interval schedule.

    “Stress disrupts agency and promotes habit regardless of whether behavior is reinforced on the agency-promoting random-ratio schedule or the habit-promoting random-interval schedule.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Stressed mice were insensitive to outcome devaluation, indicating disrupted agency.

    “Stressed mice were insensitive to devaluation, indicating disrupted agency.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Using two independent tests, a recent history of chronic stress disrupts the action-outcome knowledge needed for agency and instead causes the formation of inflexible habits in male and female mice.

    “Using two independent tests, we provide evidence in male and female mice that a recent history of chronic stress disrupts the action-outcome knowledge needed for agency and instead causes the formation of inflexible habits.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Stressed mice form habits with only a limited amount of random-interval training, whereas habits formed naturally with overtraining.

    “Whereas we showed habits formed naturally with overtraining on a random-interval schedule, stressed mice form habits with only a limited amount of such training.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Stress attenuated BLA→DMS activity throughout learning, while the CeA→DMS pathway was progressively recruited across training in stressed subjects.

    “Whereas, stress attenuated BLA→DMS activity throughout learning, the CeA→DMS pathway was progressively recruited across training in stressed subjects.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingnone given

    Chronic stress did not alter spontaneous activity in either the BLA→DMS or CeA→DMS pathway.

    “That chronic stress occurred before training and did not alter spontaneous activity in either pathway, suggests that it may lay down neuroplastic changes in these pathways that become influential during subsequent learning opportunities.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    CeA projects to the DMS but not to the dorsolateral striatum.

    “We observed mCherry-expressing putative fibers in the DMS but not dorsolateral striatum.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Unpredicted rewards robustly activated CeA→DMS projections in this study, but rewards did not evoke such a response early in instrumental training; rather, reward responses developed with training.

    “Interestingly, unpredicted rewards robustly activated CeA→DMS projections here, but rewards did not evoke such a response early in instrumental training (Figure 2m). Rather rewards responses developed with training.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    CeA also projects to the bed nucleus of the stria terminalis.

    “Expression was also detected in other well-known CeA projection targets such as the bed nucleus of the stria terminalis.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The chronic mild unpredictable stress procedure does not affect general locomotor activity or avoidance of anxiogenic spaces or create an anhedonia phenotype.

    “Our stress procedure does not affect general locomotor activity or avoidance of anxiogenic spaces or create an anhedonia phenotype.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    DMS D1 and A2A neurons receive projections from BLA and CeA.

    “rabies-labeled, DMS D1-projecting cell bodies in the BLA and CeA (right), consistent with prior reports30,34.”
    • Also stated in: § Extended Data · plain
      “rabies-labeled, DMS A2A-projecting cell bodies in the BLA and CeA (right).”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [30] Pan, W. X., Mao, T. & Dudman, J. T. Inputs to the dorsal striatum of the mouse reflect the parallel circuit architecture of the forebrain. Front. Neuroanat. 4, 147 (2010). source

      Not checked in the free run.

    • cites [34] Wall, N. R., De La Parra, M., Callaway, E. M. & Kreitzer, A. C. Differential innervation of direct- and indirect-pathway striatal projection neurons. Neuron 79, 347–360 (2013). source

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    In devaluation probe test, there was a significant main effect of Value on food-port entry rate, but no significant effects of Stress, Virus, or interactions.

    “(k) Food-port entry rate during the devaluation probe test. 3-way ANOVA: Value x Stress x Virus: F(1, 32) = 0.03, P = 0.86; Value: F(1, 32) = 6.44, P = 0.02; Stress: F(1, 32) = 2.02, P = 0.16; Virus: F(1, 32) = 1.09, P = 0.30; Value x Stress: F(1, 3) = 0.99, P = 0.33; Value x Virus: F(1, 32) = 0.02, P = 0.89; Virus x Stress: F(1, 32) = 0.24, P = 0.63.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    In devaluation probe test, there was a significant main effect of Value on press rate, but no significant Virus or Virus×Value effects.

    “(f) Press rate during the devaluation probe test. 2-way ANOVA: Value: F(1, 21) = 20.32, P = 0.0002; Virus: F(1,21) = 0.92, P = 0.35; Virus x Value: F(1, 21) = 1.17, P = 0.29.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    In the devaluation probe test, chemogenetic activation of BLA→DMS (hM3Dq) in stressed mice produced a significant difference between valued and devalued conditions, whereas control mCherry, control hM3Dq, and stress mCherry did not.

    “(f) Food-port entry rate during the devaluation probe test. Planned comparisons 2-sided t-test valued v. devalued, Control mCherry: t(20) = 1.88, P = 0.07, 95% CI - 0.21 – 5.41; Control hM3Dq: t(10) = 1.32, P = 0.20, 95% CI −1.40 – 6.54; Stress mCherry: t(16) = 0.75, P = 0.46, 95% CI −2.04 – 4.44; Stress hM3Dq: t(18) = 3.36, P = 0.002, 95% CI 2.01 – 8.16.”
    Quote in the paperSubstantial claim

  • The quote only partly states this claim.

    Findingown data

    Optogenetic inactivation of CeA→DMS at reward during post-stress learning significantly affected food-port entry rates across training.

    “(c) Food-port entry rates across training. 3-way ANOVA: Training: F(2.63, 84.18) = 3.21, P = 0.03; Stress: F(1, 32) = 0.60, P = 0.44; Virus: F(1, 32) = 4.75, P = 0.04; Training x Stress: F(3, 96) = 1.55, P = 0.21; Training x Virus: F(3, 96) = 2.42, P = 0.07; Stress x Virus: F(1, 32) = 0.04, P = 0.84; Training x Stress x Virus: F(3, 96) = 1.14, P = 0.34.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Optogenetic stimulation of CeA→DMS at reward during learning in control mice did not significantly affect press rates across training, though there was a significant Training effect.

    “(d) Press rates across training. 2-way ANOVA: Training: F(1.85, 38.75) = 62.18, P < 0.0001; Virus: F(1, 21) = 0.23, P = 0.64; Training x Virus: F(3, 63) = 0.05, P = 0.98.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    In devaluation probe tests, optogenetic activation of BLA→DMS during post-stress instrumental learning did not significantly alter the devaluation effect on food-port entry rates, although there was a significant overall Value effect.

    “(d) Food-port entry rate during the devaluation probe tests. 3-way ANOVA: Value: F(1, 33) = 15.65, P = 0.0004; Stress: F(1, 33) = 0.23, P = 0.63; Virus: F(1, 33) = 0.20, P = 0.65; Value x Stress: F(1, 33) = 2.75, P = 0.11; Value x Virus: F(1, 33) = 0.09, P = 0.76; Virus x Stress: F(1, 33) = 0.17, P = 0.68; Value x Stress x Virus: F(1, 33) = 1.73, P = 0.20.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Chemogenetic inhibition of CeA→DMS during post-stress instrumental learning did not significantly affect food-port entry rates across training, but there were significant Stress, Training×Stress, and Training×Stress×Virus effects.

    “(e) Food-port entry rates across training. Training: F(1.85, 75.67) = 2.02, P = 0.14; Stress: F(1, 41) = 4.42, P = 0.04; Virus: F(1, 41) = 0.41, P = 0.53; Training x Stress: F(3, 123) = 3.08, P = 0.03; Training x Virus: F(3, 123) = 0.64, P = 0.59; Stress x Virus: F(1, 41) = 0.20, P = 0.66; Training x Stress x Virus: F(3, 123) = 3.23, P = 0.02.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    In devaluation probe tests with optogenetic inactivation of BLA→DMS at reward, there was a significant Stress×Value interaction on food-port entry rates, but no significant main effects of Stress or Value.

    “(b) Food-port entry rates during devaluation probe tests. 2-way ANOVA: Stress x Value: F(1, 19) = 4.38, P = 0.05; Stress: F(1, 19) = 0.47, P = 0.50; Value: F(1, 19) = 0.39, P = 0.54.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    In devaluation probe tests, there was a significant main effect of Value on food-port entries, but no significant Virus or Virus×Value effects.

    “(h) Food-port entries during the devaluation probe tests. 2-way ANOVA: Value: F(1, 21) = 30.07, P < 0.0001; Virus: F(1, 21) = 0.12, P = 0.73; Virus x Value: F(1, 21) = 3.45, P = 0.08.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    A recent history of chronic stress disrupts the action-outcome learning underlying adaptive agency and promotes the formation of inflexible habits.

    “Using a multifaceted systems neuroscience approach in male and female mice, we reveal a dual pathway, amygdala-striatal neuronal circuit architecture by which a recent history of chronic stress disrupts the action-outcome learning underlying adaptive agency and promotes the formation of inflexible habits.”
    • Also stated in: § DISCUSSION · plain
      “These data reveal a dual pathway neuronal circuit architecture by which a recent history of chronic stress shapes learning to disrupt adaptive agency and promote inflexible habits.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    Stress did not cause general learning, motivational, or locomotor impairments.

    “Thus, stress did not cause general learning, motivational, or locomotor impairments.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    Stress exerts opposing effects on two amygdala-striatal pathways to disrupt agency and promote habit.

    “Thus, stress exerts opposing effects on two amygdala-striatal pathways to disrupt agency and promote habit.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Suppression of DMS activity attenuates agency and promotes inflexible habits.

    “Suppression of DMS activity attenuates such agency and promotes inflexible habits28.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [28] Yin, H. H., Ostlund, S. B., Knowlton, B. J. & Balleine, B. W. The role of the dorsomedial striatum in instrumental conditioning. Eur. J. Neurosci. 22, 513–523 (2005). source

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    BLA and CeA projections to DMS are unlikely to convey simple positive or negative valence, but rather differentially shape the content of learning.

    “our data indicate that BLA and CeA projections to DMS are unlikely to convey simple positive or negative valence, but rather differentially shape the content of learning.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    Neither BLA→DMS nor CeA→DMS bulk activity is valence-specific.

    “indicating that neither BLA→DMS nor CeA→DMS bulk activity is valence-specific.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    Chronic stress disrupts agency and promotes habit formation by flipping the amygdala input to the DMS that supports learning.

    “Thus, chronic stress disrupts agency and promotes habit formation by flipping the amygdala input to the DMS that supports learning.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    The BLA→DMS pathway mediates action-outcome learning to support agency, whereas the CeA→DMS pathway mediates the formation of routine habits.

    “Whereas the BLA→DMS pathway mediates action-outcome learning to support agency, the CeA→DMS pathway mediates the formation of routine habits.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    BLA→DMS projections are normally activated by rewarding events, but stress prevents this learning-related activity and causes the CeA→DMS pathway to be progressively recruited during learning.

    “BLA→DMS projections are normally activated by rewarding events, but stress prevents this learning-related activity and, instead, causes the CeA→DMS pathway to be progressively recruited during learning.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    Chronic stress disrupts action-outcome learning to attenuate agency and causes the premature formation of inflexible habits.

    “Thus, chronic stress disrupts action-outcome learning to attenuate agency and, instead, causes the premature formation of inflexible habits.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    The tight press-reward relationship of the random-ratio schedule encourages action-outcome learning and use of such knowledge to support agency and goal-directed decision making.

    “The tight press-reward relationship of this regime encourages action-outcome learning and, together with the short training duration, the use of such knowledge to support agency and goal-directed decision making38.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [38] Dickinson, A. D., Nicholas, J. & Adams, C. D. The effect of the instrumental training contingency on susceptibility to reinforcer devaluation. Q. J. Exp. Psychol. 35, 35–51 (1983). source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S1 (asserted), S3 (load-bearing), S4 (based).

    Premisecitation

    BLA→DMS ablation does not disrupt action-outcome learning.

    “These data do not accord with evidence that BLA→DMS ablation does not disrupt action-outcome learning50.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [50] Fisher, S. D., Ferguson, L. A., Bertran-Gonzalez, J. & Balleine, B. W. Amygdala–cortical control of striatal plasticity drives the acquisition of goal-directed action. Curr. Biol. 30, 4541–4546.e5 (2020). source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Both amygdala subregions and DMS participate in drug-seeking and active-avoidance behavior.

    “Both amygdala subregions and DMS participate in drug-seeking66,73,74 and active-avoidance behavior75.”
    Quote in the paperSubstantial claim0 of 4 sources checked
    • cites [66] Murray, J. E. et al. Basolateral and central amygdala differentially recruit and maintain dorsolateral striatum-dependent cocaine-seeking habits. Nat. Commun. 6, 10088 (2015). source

      Not checked in the free run.

    • cites [73] Belin-Rauscent, A., Everitt, B. J. & Belin, D. Intrastriatal shifts mediate the transition from drug-seeking actions to habits. Biol. Psychiatry 72, 343–345 (2012). source

      Not checked in the free run.

    • cites [74] Corbit, L. H., Nie, H. & Janak, P. H. Habitual alcohol seeking: time course and the contribution of subregions of the dorsal striatum. Biol. Psychiatry 72, 389–395 (2012). source

      Not checked in the free run.

    • cites [75] Wendler, E. et al. The roles of the nucleus accumbens core, dorsomedial striatum, and dorsolateral striatum in learning: performance and extinction of Pavlovian fear-conditioned responses and instrumental avoidance responses. Neurobiol. Learn. Mem. 109, 27–36 (2014). source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation

    The BLA is generally hyperactive following chronic stress.

    “The stress-induced attenuation of BLA→DMS activity was surprising because the BLA is, generally, hyperactive following chronic stress54–61 (c.f.62).”
    Quote in the paperSubstantial claim0 of 9 sources checked
    • cites [54] Ugolini, A., Sokal, D. M., Arban, R. & Large, C. H. CRF1 receptor activation increases the response of neurons in the basolateral nucleus of the amygdala to afferent stimulation. Front. Behav. Neurosci. 2, 2 (2008). source

      Not checked in the free run.

    • cites [55] Liu, Z. P. et al. Chronic stress impairs GABAergic control of amygdala through suppressing the tonic GABAA receptor currents. Mol. Brain 7, 32 (2014). source

      Not checked in the free run.

    • cites [56] Rosenkranz, J. A., Venheim, E. R. & Padival, M. Chronic stress causes amygdala hyperexcitability in rodents. Biol. Psychiatry 67, 1128–1136 (2010). source

      Not checked in the free run.

    • cites [57] Hetzel, A. & Rosenkranz, J. A. Distinct effects of repeated restraint stress on basolateral amygdala neuronal membrane properties in resilient adolescent and adult rats. Neuropsychopharmacology 39, 2114–2130 (2014). source

      Not checked in the free run.

    • cites [58] Rau, A. R., Chappell, A. M., Butler, T. R., Ariwodola, O. J. & Weiner, J. L. Increased basolateral amygdala pyramidal cell excitability may contribute to the anxiogenic phenotype induced by chronic early-life stress. J. Neurosci. 35, 9730–9740 (2015). source

      Not checked in the free run.

    • cites [59] Sharp, B. M. Basolateral amygdala and stress-induced hyperexcitability affect motivated behaviors and addiction. Transl. Psychiatry 7, e1194 (2017). source

      Not checked in the free run.

    • cites [60] Masneuf, S. et al. Glutamatergic mechanisms associated with stress-induced amygdala excitability and anxiety-related behavior. Neuropharmacology 85, 190–197 (2014). source

      Not checked in the free run.

    • cites [61] Lowery-Gionta, E. G. et al. Chronic stress dysregulates amygdalar output to the prefrontal cortex. Neuropharmacology 139, 68–75 (2018). source

      Not checked in the free run.

    • cites [62] Blume, S. R., Padival, M., Urban, J. H. & Rosenkranz, J. A. Disruptive effects of repeated stress on basolateral amygdala neurons and fear behavior across the estrous cycle in rats. Sci. Rep. 9, 12292 (2019). source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    BLA lesion or BLA/DMS disconnection disrupts goal-directed behavior.

    “BLA→DMS pathway function in action-outcome learning is consistent with evidence that BLA lesion or BLA/DMS disconnection disrupts goal-directed behavior29,48,49.”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [29] Balleine, B. W., Killcross, A. S. & Dickinson, A. The effect of lesions of the basolateral amygdala on instrumental conditioning. J. Neurosci. 23, 666–675 (2003). source

      Not checked in the free run.

    • cites [48] Corbit, L. H., Leung, B. K. & Balleine, B. W. The role of the amygdala-striatal pathway in the acquisition and performance of goal-directed instrumental actions. J. Neurosci. 33, 17682–17690 (2013). source

      Not checked in the free run.

    • cites [49] Ostlund, S. B. & Balleine, B. W. Differential involvement of the basolateral amygdala and mediodorsal thalamus in instrumental action selection. J. Neurosci. 28, 4398–4405 (2008). source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Earned pellet type was counterbalanced across subjects within each group of each experiment.

    “Earned pellet type (grain or chocolate) was counterbalanced across subjects within each group of each experiment.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    Sex was not included as a factor in statistical analyses for subsequent experiments.

    “Sex was therefore not included as a factor in statistical analyses, though individual data points are visually disaggregated by sex.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Thirteen subjects with off-target viral expression or fiber location were excluded from the dataset.

    “13 subjects with off-target viral expression or fiber location and 6 subjects that did not complete instrumental conditioning were excluded from the dataset.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    Investigators were blinded to group when performing histological validation and determining exclusions based on viral spread or mistargeted implant.

    “Investigators were blinded to group when performing histological validation and determining exclusions based on viral spread or mistargeted implant.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    All behaviors were scored using automated software.

    “All behaviors were scored using automated software (Med Associates).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Eighteen subjects with off-target viral expression and/or fiber location were excluded from the dataset.

    “18 subjects (not included in above N) with off-target viral expression and/or fiber location were excluded from the dataset.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Four Drd1a-cre subjects were removed due to starter virus spillover in the BNST.

    “4 Drd1a-cre and 1 Adora2A-cre subjects were removed due to starter virus spillover in the BNST.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Mice were randomly assigned to Virus and Stress groups.

    “Mice were randomly assigned to Virus and Stress groups.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation

    Stress efficacy was assessed by daily body weight measurements.

    “Stress efficacy was assessed by daily body weight measurements83.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [83] La-Vu, M. Q. et al. Sparse genetically defined neurons refine the canonical role of periaqueductal gray columnar organization. eLife 11, e77115 (2022). source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Mice were randomly assigned to Viral group.

    “Mice were randomly assigned to Viral group.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Left/right hemisphere was counterbalanced across subjects within each group.

    “left/right hemisphere counterbalanced across subjects within each group”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductreasoning

    Body weights did not differ between groups at the start or end of training.

    “Owing to food deprivation, body weights did not differ between groups at the start or end of training (see Supplemental Table 2).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Six subjects were excluded because they did not meet instrumental training performance criteria.

    “6 subjects (not included in above N) were excluded because they did not meet instrumental training performance criteria.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    Each experiment included at least 1 replication cohort and cohorts were balanced by Viral group, Stress group, and hemisphere prior to the start of the experiment.

    “Each experiment included at least 1 replication cohort and cohorts were balanced by Viral group, Stress group, and hemisphere (for photometry recordings and tracing) prior to the start of the experiment.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Six subjects that did not complete instrumental conditioning were excluded from the dataset.

    “13 subjects with off-target viral expression or fiber location and 6 subjects that did not complete instrumental conditioning were excluded from the dataset.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    Investigators were not blinded to viral or stress group because they were required to administer infusions and stress exposure.

    “Investigators were not blinded to viral or stress group because they were required to administer infusions and stress exposure.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationown data

    Data from male and female mice were combined for analyses.

    “Therefore, data from male and female mice was combined for analyses.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Mice were randomly assigned to Control versus Stress groups.

    “Mice were randomly assigned to Control v. Stress groups.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    One Adora2A-cre subject was removed due to starter virus spillover in the BNST.

    “4 Drd1a-cre and 1 Adora2A-cre subjects were removed due to starter virus spillover in the BNST.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductnone given

    Subjects with off-target viral expression or fiber location and subjects that did not complete instrumental conditioning were excluded from the dataset.

    “4 subjects with off-target viral expression or fiber location and 2 subjects that did not complete instrumental conditioning were excluded from the dataset.”
    • Also stated in: § Chemogenetic activation of BLA→DMS projections during instrumental learning following stress · plain
      “15 subjects with off-target viral expression and 2 subjects that did not complete instrumental conditioning were excluded from the dataset.”
    • Also stated in: § Optogenetic inactivation of CeA→DMS projections during instrumental learning following stress · plain
      “12 subjects with off-target viral expression or fiber location and 2 subjects that did not complete instrumental conditioning were excluded from the dataset.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    For subsequent experiments, the N per sex was underpowered to examine sex differences.

    “For subsequent experiments, male and female mice were used in approximately equal numbers, but the N per sex was underpowered to examine sex differences.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Study design and conductown data

    In all cases, mice consumed less of the prefed pellet than the non-prefed pellet, indicating successful sensory-specific satiety devaluation.

    “In all cases, mice consumed less of the prefed pellet than non-prefed pellet, indicating successful sensory-specific satiety devaluation (Supplemental Table 4).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Each stress protocol was consistent across subjects within a cohort.

    “Each stress protocol was consistent across subjects within a cohort.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Four subjects were excluded for missing recording data from one session.

    “4 subjects were excluded for missing recording data from one session.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Three subjects that did not complete instrumental conditioning were excluded.

    “3 subjects that did not complete instrumental conditioning were also excluded.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Test order was counterbalanced across subjects within each group for each experiment.

    “with test order counterbalanced across subjects within each group for each experiment.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductcitation

    Group sizes were estimated based on prior work with this behavioral task and to ensure counterbalancing of virus, stress, pellet type, and devaluation test order.

    “Group sizes were estimated based on prior work with this behavioral task41 and to ensure counterbalancing of virus, stress, pellet type, and devaluation test order.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [41] Malvaez, M. et al. Habits are negatively regulated by histone deacetylase 3 in the dorsal striatum. Biol. Psychiatry 84, 383–392 (2018). source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Four subjects were excluded for loss of optic fibers/headcaps.

    “4 subjects were excluded for loss of optic fibers/headcaps.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductcitation

    Parametric statistics were used for consistency across experiments and given evidence that ANOVA is robust to slight non-normality.

    “We opted to use parametric statistics for consistency across experiments and given evidence that ANOVA is robust to slight non-normality97,98.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [97] Giovanniello, J. et al. A dual-pathway architecture for stress to disrupt agency and promote habit. Dryad https://doi.org/10.5061/dryad.2jm63xt00 (2024). source

      Not checked in the free run.

    • cites [98] Monteiro, S. et al. An efficient chronic unpredictable stress protocol to induce stress-related responses in C57BL/6 mice. Front. Psychiatry 6, 6 (2015). source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Study design and conductown data

    Mice were randomly assigned to experimental groups.

    “Mice were randomly assigned to Virus and Stress groups.”
    • Also stated in: § Chemogenetic activation of BLA→DMS projections during instrumental learning following stress · plain
      “Mice were randomly assigned to Viral and Stress groups.”
    • Also stated in: § Optogenetic inactivation of CeA→DMS projections during instrumental overtraining · plain
      “Mice were randomly assigned to Virus group.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Premisenone given

    The density of CeA→DMS projections is low.

    “Given the low density of CeA→DMS projections, we choose to activate DMS-projecting CeA cell bodies.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    Stress-induced engagement of the CeA→DMS pathway may require repeated reward experience, which may reflect engagement of this pathway with repeated reinforcement and/or opportunity to learn the value or salience of the reward.

    “This indicates that stress-induced engagement of the CeA→DMS pathway may require repeated reward experience, which may reflect engagement of this pathway with repeated reinforcement and/or opportunity to learn the value or salience of the reward.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    Some datasets were slightly non-normally distributed; non-parametric analyses were also run and results were highly consistent.

    “Some datasets were slightly non-normally distributed. For these datasets, statistical tests were also run using non-parametric analyses and the results were highly consistent.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Statistical comparisons were corrected for multiple comparisons.

    “**P < 0.01, corrected for multiple comparisons.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    Optogenetic activation of CeA→DMS projections at reward during learning neither affects acquisition of the lever-press behavior, nor the action-outcome learning needed to support flexible goal-directed decision making during the devaluation test.

    “Optogenetic activation of CeA→DMS projections at reward during learning neither affects affect acquisition of the lever-press behavior, nor the action-outcome learning needed to support flexible goal-directed decision making during the devaluation test.”
    Quote in the paperSubstantial claim
74 of 74

  • The paper relies on this without support.

    Little is known of the neuronal circuits that support the learning underlying agency and habits and even less of those that enable stress to potentiate habit formation.

    “Yet, despite importance for understanding adaptive and maladaptive behavior, little is known of the neuronal circuits that support the learning underlying agency and habits and even less of those that enable stress to potentiate habit formation.”

  • The paper relies on this without support.

    The chronic mild unpredictable stress procedure models aspects of the repeated and varied nature of stress experienced by humans, including uncontrollable physical aversive events, disrupted sleep, and poor environmental conditions.

    “This models aspects of the repeated and varied nature of stress experienced by humans, including uncontrollable physical aversive events, disrupted sleep, and poor environmental conditions.”

  • The paper relies on this without support.

    Overtraining promotes the formation of habits naturally in control subjects.

    “We overtrained subjects to also promote the formation of habits naturally in control subjects.”
3 of 3

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Disruption of brain regions implicated in goal-directed strategy, including dorsomedial striatum, preserves reinforcement learning yet facilitates habit formation.

    “Consistent with this observation, previous behavioral studies in rodents have consistently shown that disruption of brain regions implicated in goal-directed strategy, including the dorsomedial striatum, preserves reinforcement learning, yet facilitates habit formation5,40.”

    From Dissociable roles of prefrontal plasticity in decision-making strategy and execution of habitual behavior (2026) · cites this paper as [40]

    The Abstract (page unavailable) says suppressing dorsomedial striatal activity promotes inflexible habits. The Results, under “BLA→DMS mediates agency learning” (page unavailable), report that inhibiting BLA→DMS projections left acquisition of rewarded lever pressing intact but caused insensitivity to outcome devaluation. That supports preserved instrumental learning alongside a shift toward habit, but the intact acquisition result concerns inhibition of a projection to the DMS, not disruption of the DMS as a whole or brain regions generally. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

Statistics that don’t add up

Each reported p-value recomputed from its test statistic and degrees of freedom.

  • Inconsistent p-value: F(1, 14) = 0.85, p = .87

    Minor

    The paper reports p = .87 here; recomputing from the test statistic and its degrees of freedom gives p = .372. The check cannot tell whether the statistic or the p-value is the misprint.

    Reported p = .87 · recomputed p = .372

  • Inconsistent p-value: F(12, 228) = 2.47, p = .0009

    Minor

    The paper reports p = .0009 here; recomputing from the test statistic and its degrees of freedom gives p = .005. The check cannot tell whether the statistic or the p-value is the misprint.

    Reported p = .0009 · recomputed p = .005

  • Inconsistent p-value: t(8) = 0.47, p = .64

    Minor

    The paper reports p = .64 here; recomputing from the test statistic and its degrees of freedom gives p = .651 (two-tailed). The check cannot tell whether the statistic or the p-value is the misprint.

    Reported p = .64 · recomputed p = .651

  • Inconsistent p-value: t(10) = 1.32, p = .20

    Minor

    The paper reports p = .2 here; recomputing from the test statistic and its degrees of freedom gives p = .216 (two-tailed). The check cannot tell whether the statistic or the p-value is the misprint.

    Reported p = .2 · recomputed p = .216

  • Inconsistent p-value: F(1, 14) = 3.94, p = .06

    Minor

    The paper reports p = .06 here; recomputing from the test statistic and its degrees of freedom gives p = .067. The check cannot tell whether the statistic or the p-value is the misprint.

    Reported p = .06 · recomputed p = .067

  • Inconsistent p-value: t(22) = 0.01, p = .92

    Minor

    The paper reports p = .92 here; recomputing from the test statistic and its degrees of freedom gives p = .992 (two-tailed). The check cannot tell whether the statistic or the p-value is the misprint.

    Reported p = .92 · recomputed p = .992

  • Inconsistent p-value: F(1, 33) = 0.05, p = .95

    Minor

    The paper reports p = .95 here; recomputing from the test statistic and its degrees of freedom gives p = .824. The check cannot tell whether the statistic or the p-value is the misprint.

    Reported p = .95 · recomputed p = .824

  • Inconsistent p-value: F(1, 25) = 1.37, p = .5

    Minor

    The paper reports p = .5 here; recomputing from the test statistic and its degrees of freedom gives p = .253. The check cannot tell whether the statistic or the p-value is the misprint.

    Reported p = .5 · recomputed p = .253

  • Inconsistent p-value: F(1, 20) = 11.79, p = .02

    Minor

    The paper reports p = .02 here; recomputing from the test statistic and its degrees of freedom gives p = .003. The check cannot tell whether the statistic or the p-value is the misprint.

    Reported p = .02 · recomputed p = .003

  • Inconsistent p-value: F(1, 3) = 0.99, p = .33

    Minor

    The paper reports p = .33 here; recomputing from the test statistic and its degrees of freedom gives p = .393. The check cannot tell whether the statistic or the p-value is the misprint.

    Reported p = .33 · recomputed p = .393

  • Inconsistent p-value: t(11) = 1.94, p = .06

    Minor

    The paper reports p = .06 here; recomputing from the test statistic and its degrees of freedom gives p = .078 (two-tailed). The check cannot tell whether the statistic or the p-value is the misprint.

    Reported p = .06 · recomputed p = .078

  • p-value fits an unstated one-tailed test: t(18) = 3.36, p = .002

    Minor

    The paper reports p = .002 here; recomputing from the test statistic and its degrees of freedom gives p = .003 (two-tailed). The reported value is what a one-tailed test gives, but the paper does not say near this result that a one-tailed test was used.

    Reported p = .002 · recomputed p = .003

12 of 12

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.

  • Doesn’t add upt(22) = 0.01reported p = .92 · recomputed p = .992

    “t(22) = 0.01, p = .92”

  • Doesn’t add upF(12, 228) = 2.47reported p = .0009 · recomputed p = .005

    “F(12, 228) = 2.47, p = .0009”

  • Doesn’t add upF(1, 25) = 1.37reported p = .5 · recomputed p = .253

    “F(1, 25) = 1.37, p = .5”

  • Doesn’t add upF(1, 20) = 11.79reported p = .02 · recomputed p = .003

    “F(1, 20) = 11.79, p = .02”

  • Doesn’t add upF(1, 33) = 0.05reported p = .95 · recomputed p = .824

    “F(1, 33) = 0.05, p = .95”

  • Doesn’t add upt(10) = 1.32reported p = .2 · recomputed p = .216

    “t(10) = 1.32, p = .20”

  • Doesn’t add upt(18) = 3.36reported p = .002 · recomputed p = .003

    “t(18) = 3.36, p = .002”

  • Doesn’t add upF(1, 3) = 0.99reported p = .33 · recomputed p = .393

    “F(1, 3) = 0.99, p = .33”

  • Doesn’t add upF(1, 14) = 3.94reported p = .06 · recomputed p = .067

    “F(1, 14) = 3.94, p = .06”

  • Doesn’t add upF(1, 14) = 0.85reported p = .87 · recomputed p = .372

    “F(1, 14) = 0.85, p = .87”

  • Doesn’t add upt(11) = 1.94reported p = .06 · recomputed p = .078

    “t(11) = 1.94, p = .06”

  • Doesn’t add upt(8) = 0.47reported p = .64 · recomputed p = .651

    “t(8) = 0.47, p = .64”

  • Not confirmedF(2.7, 53.97) = 0.21reported p = .88 · recomputed p = .871

    “F(2.70, 53.97) = 0.21, p = .88”

  • ConsistentF(1, 43) = 0.43reported p = .51 · recomputed p = .515

    “F(1, 43) = 0.43, p = .51”

  • ConsistentF(1, 43) = 0.6reported p = .44 · recomputed p = .443

    “F(1,43) = 0.60, p = .44”

  • ConsistentF(1, 43) = 0.04reported p = .84 · recomputed p = .842

    “F(1,43) = 0.04, p = .84”

  • Consistentt(22) = 0.32reported p = .75 · recomputed p = .752

    “t(22) = 0.32, p = .75”

  • Consistentt(22) = 1.1reported p = .28 · recomputed p = .283

    “t(22) = 1.10, p = .28”

  • Consistentt(22) = 0.63reported p = .54 · recomputed p = .535

    “t(22) = 0.63, p = .54”

  • Consistentt(22) = 0.08reported p = .94 · recomputed p = .937

    “t(22) = 0.08, p = .94”

  • Consistentt(22) = 0.23reported p = .82 · recomputed p = .820

    “t(22) = 0.23, p = .82”

  • Consistentt(22) = 0.97reported p = .34 · recomputed p = .343

    “t(22) = 0.97, p = .34”

  • Consistentt(22) = 1.57reported p = .13 · recomputed p = .131

    “t(22) = 1.57, p = .13”

  • Consistentt(22) = 1.37reported p = .19 · recomputed p = .185

    “t(22) = 1.37, p = .19”

  • ConsistentF(1, 22) = 113.2reported p < .0001 · recomputed p < .001

    “F(1, 22) = 113.20, p < .0001”

  • ConsistentF(1, 22) = 0.14reported p = .71 · recomputed p = .712

    “F(1, 22) = 0.14, p = .71”

  • ConsistentF(1, 22) = 0.02reported p = .89 · recomputed p = .889

    “F(1, 22) = 0.02, p = .89”

  • Consistentt(22) = 0.03reported p = .98 · recomputed p = .976

    “t(22) = 0.03, p = .98”

  • Consistentt(22) = 2.13reported p = .04 · recomputed p = .045

    “t(22) = 2.13, p = .04”

  • Consistentt(22) = 2.12reported p = .46 · recomputed p = .046

    “t(22) = 2.12, p = .46”

    The paper states a correction for multiple tests

  • ConsistentF(2.42, 108.9) = 3.17reported p = .04 · recomputed p = .037

    “F(2.42, 108.90) = 3.17, p = .04”

  • ConsistentF(1, 45) = 0.07reported p = .79 · recomputed p = .793

    “F(1, 45) = 0.07, p = .79”

  • ConsistentF(3, 135) = 0.57reported p = .64 · recomputed p = .636

    “F(3, 135) = 0.57, p = .64”

  • ConsistentF(1, 45) = 6.77reported p = .01 · recomputed p = .013

    “F(1, 45) = 6.77, p = .01”

  • ConsistentF(1, 45) = 0.29reported p = .6 · recomputed p = .593

    “F(1, 45) = 0.29, p = .60”

  • ConsistentF(1, 45) = 2.42reported p = .13 · recomputed p = .127

    “F(1, 45) = 2.42, p = .13”

  • ConsistentF(2.84, 62.1) = 6.44reported p = .001 · recomputed p < .001

    “F(2.84, 62.10) = 6.44, p = .001”

  • ConsistentF(1, 25) = 0.01reported p = .91 · recomputed p = .921

    “F(1, 25) = 0.01, p = .91”

  • ConsistentF(1, 25) = 1.27reported p = .27 · recomputed p = .270

    “F(1, 25) = 1.27, p = .27”

  • ConsistentF(3, 75) = 1.62reported p = .19 · recomputed p = .192

    “F(3, 75) = 1.62, p = .19”

  • ConsistentF(3, 75) = 0.24reported p = .87 · recomputed p = .868

    “F(3, 75) = 0.24, p = .87”

  • ConsistentF(1, 25) = 0.004reported p = .95 · recomputed p = .950

    “F(1, 25) = 0.004, p = .95”

  • ConsistentF(3, 75) = 1.49reported p = .23 · recomputed p = .224

    “F(3, 75) = 1.49, p = .23”

  • ConsistentF(1, 25) = 18.88reported p = .0002 · recomputed p < .001

    “F(1, 25) = 18.88, p = .0002”

  • ConsistentF(1, 25) = 4.29reported p = .05 · recomputed p = .049

    “F(1, 25) = 4.29, p = .05”

  • ConsistentF(1, 25) = 1.41reported p = .25 · recomputed p = .246

    “F(1, 25) = 1.41, p = .25”

  • ConsistentF(19, 475) = 2.03reported p = .0063 · recomputed p = .006

    “F(19, 475) = 2.03, p = .0063”

  • ConsistentF(19, 475) = 2.43reported p = .0007 · recomputed p < .001

    “F(19, 475) = 2.43, p = .0007”

  • ConsistentF(1, 25) = 0.0001reported p = .99 · recomputed p = .992

    “F(1, 25) = 0.0001, p = .99”

  • ConsistentF(9.17, 229.2) = 2.13reported p = .03 · recomputed p = .028

    “F(9.17, 229.20) = 2.13, p = .03”

  • ConsistentF(1, 25) = 1.36reported p = .26 · recomputed p = .255

    “F(1, 25) = 1.36, p = .26”

  • ConsistentF(1, 25) = 68.23reported p < .0001 · recomputed p < .001

    “F(1, 25) = 68.23, p < .0001”

  • ConsistentF(19, 475) = 1.3reported p = .19 · recomputed p = .177

    “F(19, 475) = 1.30, p = .19”

    The paper states a sphericity correction

  • ConsistentF(6.62, 79.39) = 2.47reported p = .03 · recomputed p = .026

    “F(6.62, 79.39) = 2.47, p = .03”

  • ConsistentF(1, 12) = 45.16reported p < .0001 · recomputed p < .001

    “F(1, 12) = 45.16, p < .0001”

  • ConsistentF(1, 13) = 28.22reported p = .0001 · recomputed p < .001

    “F(1, 13) = 28.22, p = .0001”

  • ConsistentF(6.01, 78.16) = 2.19reported p = .05 · recomputed p = .053

    “F(6.01, 78.16) = 2.19, p = .05”

  • ConsistentF(19, 247) = 1.1reported p = .35 · recomputed p = .351

    “F(19, 247) = 1.10, p = .35”

  • ConsistentF(19, 475) = 3.8reported p < .0001 · recomputed p < .001

    “F(19, 475) = 3.80, p < .0001”

  • ConsistentF(19, 475) = 1.2reported p = .26 · recomputed p = .252

    “F(19, 475) = 1.20, p = .26”

  • ConsistentF(1, 25) = 0.006reported p = .94 · recomputed p = .939

    “F(1, 25) = 0.006, p = .94”

  • ConsistentF(6.26, 156.6) = 7.53reported p < .0001 · recomputed p < .001

    “F(6.26, 156.60) = 7.53, p < .0001”

  • ConsistentF(1, 25) = 2.51reported p = .13 · recomputed p = .126

    “F(1, 25) = 2.51, p = .13”

  • ConsistentF(19, 475) = 0.86reported p = .63 · recomputed p = .634

    “F(19, 475) = 0.86, p = .63”

  • ConsistentF(2.47, 46.99) = 0.65reported p = .56 · recomputed p = .558

    “F(2.47, 46.99) = 0.65, p = .56”

  • ConsistentF(1, 19) = 0.05reported p = .82 · recomputed p = .825

    “F(1, 19) = 0.05, p = .82”

  • ConsistentF(3, 57) = 0.24reported p = .87 · recomputed p = .868

    “F(3, 57) = 0.24, p = .87”

  • ConsistentF(2.36, 47.19) = 0.89reported p = .43 · recomputed p = .432

    “F(2.36, 47.19) = 0.89, p = .43”

  • ConsistentF(1, 20) = 2.71reported p = .12 · recomputed p = .115

    “F(1, 20) = 2.71, p = .12”

  • ConsistentF(3, 60) = 0.09reported p = .96 · recomputed p = .965

    “F(3, 60) = 0.09, p = .96”

  • ConsistentF(1, 18) = 10.88reported p = .004 · recomputed p = .004

    “F(1, 18) = 10.88, p = .004”

  • ConsistentF(1, 18) = 1.77reported p = .2 · recomputed p = .200

    “F(1, 18) = 1.77, p = .20”

  • ConsistentF(1, 20) = 8.14reported p = .01 · recomputed p = .010

    “F(1, 20) = 8.14, p = .01”

  • ConsistentF(1, 20) = 4.49reported p = .05 · recomputed p = .047

    “F(1, 20) = 4.49, p = .05”

  • ConsistentF(1, 18) = 8.533reported p = .01 · recomputed p = .009

    “F(1, 18) = 8.533, p = .01”

  • ConsistentF(1, 18) = 0.1433reported p = .71 · recomputed p = .709

    “F(1, 18) = 0.1433, p = .71”

  • ConsistentF(1, 18) = 1.725reported p = .21 · recomputed p = .206

    “F(1, 18) = 1.725, p = .21”

  • Consistentt(18) = 2.26reported p = .04 · recomputed p = .036

    “t(18) = 2.26, p = .04”

  • ConsistentF(1, 20) = 28.24reported p < .0001 · recomputed p < .001

    “F(1, 20) = 28.24, p < .0001”

  • ConsistentF(1, 20) = 0.22reported p = .64 · recomputed p = .644

    “F(1, 20) = 0.22, p = .64”

  • ConsistentF(1, 20) = 3.201reported p = .09 · recomputed p = .089

    “F(1, 20) = 3.201, p = .09”

  • Consistentt(20) = 0.88reported p = .39 · recomputed p = .389

    “t(20) = 0.88, p = .39”

  • ConsistentF(2.41, 45.69) = 0.17reported p = .88 · recomputed p = .880

    “F(2.41, 45.69) = 0.17, p = .88”

  • ConsistentF(1, 19) = 0.08reported p = .78 · recomputed p = .780

    “F(1, 19) = 0.08, p = .78”

  • ConsistentF(3, 57) = 0.85reported p = .47 · recomputed p = .472

    “F(3, 57) = 0.85, p = .47”

  • ConsistentF(2.48, 47.1) = 0.86reported p = .45 · recomputed p = .450

    “F(2.48, 47.10) = 0.86, p = .45”

  • ConsistentF(1, 19) = 0.034reported p = .85 · recomputed p = .856

    “F(1, 19) = 0.034, p = .85”

  • ConsistentF(3, 57) = 1.37reported p = .26 · recomputed p = .261

    “F(3, 57) = 1.37, p = .26”

  • ConsistentF(1, 20) = 3.03reported p = .1 · recomputed p = .097

    “F(1, 20) = 3.03, p = .10”

  • ConsistentF(3, 60) = 0.55reported p = .65 · recomputed p = .650

    “F(3, 60) = 0.55, p = .65”

  • ConsistentF(2.59, 51.83) = 0.32reported p = .78 · recomputed p = .782

    “F(2.59, 51.83) = 0.32, p = .78”

  • ConsistentF(1, 20) = 3.7reported p = .07 · recomputed p = .069

    “F(1, 20) = 3.70, p = .07”

  • ConsistentF(3, 60) = 0.75reported p = .52 · recomputed p = .527

    “F(3, 60) = 0.75, p = .52”

  • ConsistentF(2.03, 38.55) = 3.3reported p = .05 · recomputed p = .047

    “F(2.03, 38.55) = 3.30, p = .05”

  • ConsistentF(1, 19) = 0.14reported p = .71 · recomputed p = .712

    “F(1, 19) = 0.14, p = .71”

  • ConsistentF(3, 57) = 0.43reported p = .73 · recomputed p = .732

    “F(3, 57) = 0.43, p = .73”

  • ConsistentF(1, 19) = 4.38reported p = .05 · recomputed p = .050

    “F(1, 19) = 4.38, p = .05”

  • ConsistentF(1, 19) = 0.47reported p = .5 · recomputed p = .501

    “F(1, 19) = 0.47, p = .50”

  • ConsistentF(1, 19) = 0.39reported p = .54 · recomputed p = .540

    “F(1, 19) = 0.39, p = .54”

  • ConsistentF(2.5, 82.82) = 6.47reported p = .001 · recomputed p = .001

    “F(2.5, 82.82) = 6.47, p = .001”

  • ConsistentF(1, 33) = 3.78reported p = .06 · recomputed p = .060

    “F(1, 33) = 3.78, p = .06”

  • ConsistentF(1, 33) = 0.02reported p = .89 · recomputed p = .888

    “F(1, 33) = 0.02, p = .89”

  • ConsistentF(3, 99) = 0.67reported p = .57 · recomputed p = .572

    “F(3, 99) = 0.67, p = .57”

  • ConsistentF(3, 99) = 0.45reported p = .72 · recomputed p = .718

    “F(3, 99) = 0.45, p = .72”

  • ConsistentF(1, 33) = 2.18reported p = .15 · recomputed p = .149

    “F(1, 33) = 2.18, p = .15”

  • ConsistentF(3, 99) = 0.26reported p = .86 · recomputed p = .854

    “F(3, 99) = 0.26, p = .86”

  • ConsistentF(1, 33) = 15.65reported p = .0004 · recomputed p < .001

    “F(1, 33) = 15.65, p = .0004”

  • ConsistentF(1, 33) = 0.23reported p = .63 · recomputed p = .635

    “F(1, 33) = 0.23, p = .63”

  • ConsistentF(1, 33) = 0.2reported p = .65 · recomputed p = .658

    “F(1, 33) = 0.20, p = .65”

  • ConsistentF(1, 33) = 2.75reported p = .11 · recomputed p = .107

    “F(1, 33) = 2.75, p = .11”

  • ConsistentF(1, 33) = 0.09reported p = .76 · recomputed p = .766

    “F(1, 33) = 0.09, p = .76”

  • ConsistentF(1, 33) = 0.17reported p = .68 · recomputed p = .683

    “F(1, 33) = 0.17, p = .68”

  • ConsistentF(1, 33) = 1.73reported p = .2 · recomputed p = .197

    “F(1, 33) = 1.73, p = .20”

  • ConsistentF(1, 16) = 12.42reported p = .003 · recomputed p = .003

    “F(1, 16) = 12.42, p = .003”

  • ConsistentF(1, 16) = 0.0007reported p = .98 · recomputed p = .979

    “F(1, 16) = 0.0007, p = .98”

  • ConsistentF(1, 16) = 0.4reported p = .53 · recomputed p = .536

    “F(1, 16) = 0.40, p = .53”

  • ConsistentF(1, 17) = 3.46reported p = .08 · recomputed p = .080

    “F(1, 17) = 3.46, p = .08”

  • ConsistentF(1, 17) = 0.45reported p = .51 · recomputed p = .511

    “F(1, 17) = 0.45, p = .51”

  • ConsistentF(1, 17) = 1.71reported p = .21 · recomputed p = .208

    “F(1, 17) = 1.71, p = .21”

  • ConsistentF(2.55, 84.12) = 1.64reported p = .19 · recomputed p = .186

    “F(2.55, 84.12) = 1.64, p = .19”

  • ConsistentF(1, 33) = 0.08reported p = .78 · recomputed p = .779

    “F(1, 33) = 0.08, p = .78”

  • ConsistentF(3, 99) = 0.16reported p = .92 · recomputed p = .923

    “F(3, 99) = 0.16, p = .92”

  • ConsistentF(3, 99) = 0.21reported p = .89 · recomputed p = .889

    “F(3, 99) = 0.21, p = .89”

  • ConsistentF(3, 99) = 3.07reported p = .03 · recomputed p = .031

    “F(3, 99) = 3.07, p = .03”

  • Consistentt(20) = 1.88reported p = .07 · recomputed p = .075

    “t(20) = 1.88, p = .07”

  • Consistentt(16) = 0.75reported p = .46 · recomputed p = .464

    “t(16) = 0.75, p = .46”

  • Consistentt(19) = 0.65reported p = .52 · recomputed p = .523

    “t(19) = 0.65, p = .52”

  • Consistentt(21) = 1.75reported p = .1 · recomputed p = .095

    “t(21) = 1.75, p = .10”

  • Consistentt(16) = 0.52reported p = .61 · recomputed p = .610

    “t(16) = 0.52, p = .61”

  • ConsistentF(2.29, 45.82) = 1.81reported p = .17 · recomputed p = .175

    “F(2.29, 45.82) = 1.81, p = .17”

  • ConsistentF(1, 20) = 0.67reported p = .42 · recomputed p = .423

    “F(1, 20) = 0.67, p = .42”

  • ConsistentF(8, 160) = 0.6reported p = .77 · recomputed p = .777

    “F(8, 160) = 0.60, p = .77”

  • ConsistentF(1, 20) = 4.51reported p = .046 · recomputed p = .046

    “F(1, 20) = 4.51, p = .046”

  • ConsistentF(1, 20) = 1.47reported p = .24 · recomputed p = .239

    “F(1, 20) = 1.47, p = .24”

  • ConsistentF(1, 20) = 0.41reported p = .53 · recomputed p = .529

    “F(1, 20) = 0.41, p = .53”

  • ConsistentF(2.63, 84.18) = 3.21reported p = .03 · recomputed p = .027

    “F(2.63, 84.18) = 3.21, p = .03”

  • ConsistentF(1, 32) = 0.6reported p = .44 · recomputed p = .444

    “F(1, 32) = 0.60, p = .44”

  • ConsistentF(1, 32) = 4.75reported p = .04 · recomputed p = .037

    “F(1, 32) = 4.75, p = .04”

  • ConsistentF(3, 96) = 1.55reported p = .21 · recomputed p = .207

    “F(3, 96) = 1.55, p = .21”

  • ConsistentF(3, 96) = 2.42reported p = .07 · recomputed p = .071

    “F(3, 96) = 2.42, p = .07”

  • ConsistentF(1, 32) = 0.04reported p = .84 · recomputed p = .843

    “F(1, 32) = 0.04, p = .84”

  • ConsistentF(3, 96) = 1.14reported p = .34 · recomputed p = .337

    “F(3, 96) = 1.14, p = .34”

  • ConsistentF(1, 32) = 0.03reported p = .86 · recomputed p = .864

    “F(1, 32) = 0.03, p = .86”

  • ConsistentF(1, 32) = 6.44reported p = .02 · recomputed p = .016

    “F(1, 32) = 6.44, p = .02”

  • ConsistentF(1, 32) = 2.02reported p = .16 · recomputed p = .165

    “F(1, 32) = 2.02, p = .16”

  • ConsistentF(1, 32) = 1.09reported p = .3 · recomputed p = .304

    “F(1, 32) = 1.09, p = .30”

  • ConsistentF(1, 32) = 0.02reported p = .89 · recomputed p = .888

    “F(1, 32) = 0.02, p = .89”

  • ConsistentF(1, 32) = 0.24reported p = .63 · recomputed p = .628

    “F(1, 32) = 0.24, p = .63”

  • ConsistentF(1, 18) = 0.09reported p = .77 · recomputed p = .768

    “F(1, 18) = 0.09, p = .77”

  • ConsistentF(1, 18) = 1.99reported p = .17 · recomputed p = .175

    “F(1, 18) = 1.99, p = .17”

  • ConsistentF(1, 18) = 0.21reported p = .65 · recomputed p = .652

    “F(1, 18) = 0.21, p = .65”

  • ConsistentF(1, 14) = 0.0005reported p = .98 · recomputed p = .982

    “F(1, 14) = 0.0005, p = .98”

  • ConsistentF(1.85, 75.67) = 2.02reported p = .14 · recomputed p = .140

    “F(1.85, 75.67) = 2.02, p = .14”

  • ConsistentF(1, 41) = 4.42reported p = .04 · recomputed p = .042

    “F(1, 41) = 4.42, p = .04”

  • ConsistentF(1, 41) = 0.41reported p = .53 · recomputed p = .526

    “F(1, 41) = 0.41, p = .53”

  • ConsistentF(3, 123) = 3.08reported p = .03 · recomputed p = .030

    “F(3, 123) = 3.08, p = .03”

  • ConsistentF(3, 123) = 0.64reported p = .59 · recomputed p = .591

    “F(3, 123) = 0.64, p = .59”

  • ConsistentF(1, 41) = 0.2reported p = .66 · recomputed p = .657

    “F(1, 41) = 0.20, p = .66”

  • ConsistentF(3, 123) = 3.23reported p = .02 · recomputed p = .025

    “F(3, 123) = 3.23, p = .02”

  • Consistentt(12) = 0.38reported p = .71 · recomputed p = .711

    “t(12) = 0.38, p = .71”

  • Consistentt(10) = 0.05reported p = .96 · recomputed p = .961

    “t(10) = 0.05, p = .96”

  • ConsistentF(1.73, 34.5) = 0.89reported p = .41 · recomputed p = .406

    “F(1.73, 34.50) = 0.89, p = .41”

  • ConsistentF(1, 20) = 0.46reported p = .51 · recomputed p = .505

    “F(1, 20) = 0.46, p = .51”

  • ConsistentF(3, 60) = 0.39reported p = .76 · recomputed p = .761

    “F(3, 60) = 0.39, p = .76”

  • ConsistentF(1, 20) = 1.37reported p = .26 · recomputed p = .256

    “F(1, 20) = 1.37, p = .26”

  • ConsistentF(1, 20) = 0.005reported p = .94 · recomputed p = .944

    “F(1, 20) = 0.005, p = .94”

  • ConsistentF(1, 20) = 1.36reported p = .26 · recomputed p = .257

    “F(1, 20) = 1.36, p = .26”

  • ConsistentF(1.85, 38.75) = 62.18reported p < .0001 · recomputed p < .001

    “F(1.85, 38.75) = 62.18, p < .0001”

  • ConsistentF(1, 21) = 0.23reported p = .64 · recomputed p = .636

    “F(1, 21) = 0.23, p = .64”

  • ConsistentF(3, 63) = 0.05reported p = .98 · recomputed p = .985

    “F(3, 63) = 0.05, p = .98”

  • ConsistentF(2.42, 50.77) = 2reported p = .14 · recomputed p = .137

    “F(2.42, 50.77) = 2.00, p = .14”

  • ConsistentF(1, 21) = 1.85reported p = .19 · recomputed p = .188

    “F(1, 21) = 1.85, p = .19”

  • ConsistentF(3, 63) = 0.22reported p = .88 · recomputed p = .882

    “F(3, 63) = 0.22, p = .88”

  • ConsistentF(1, 21) = 20.32reported p = .0002 · recomputed p < .001

    “F(1, 21) = 20.32, p = .0002”

  • ConsistentF(1, 21) = 0.92reported p = .35 · recomputed p = .348

    “F(1,21) = 0.92, p = .35”

  • ConsistentF(1, 21) = 1.17reported p = .29 · recomputed p = .292

    “F(1, 21) = 1.17, p = .29”

  • Consistentt(21) = 1.37reported p = .19 · recomputed p = .185

    “t(21) = 1.37, p = .19”

  • ConsistentF(1, 21) = 30.07reported p < .0001 · recomputed p < .001

    “F(1, 21) = 30.07, p < .0001”

  • ConsistentF(1, 21) = 0.12reported p = .73 · recomputed p = .732

    “F(1, 21) = 0.12, p = .73”

  • ConsistentF(1, 21) = 3.45reported p = .08 · recomputed p = .077

    “F(1, 21) = 3.45, p = .08”

180 of 180

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • White-noise stressor has conflicting intensity and duration

    Major

    The Results describe white noise as 80 dB for 2-16 hours, whereas the Methods specify 100 dB for 6-16 hours.

  • BLA terminal-inhibition wavelength differs between Results and Methods

    Major

    The Results report 532-nm light for BLA→DMS inhibition, whereas the corresponding Methods specify a 593-nm laser.

  • Footshock duration differs between Results and Methods

    Major

    The Results specify 1-second footshocks for the chronic-stress procedure, but the Methods specify shocks lasting 2-3 seconds.

  • Contingency-degradation control group has conflicting sample sizes

    Minor

    The Methods give the control degraded group as three mice, all male; the Extended Data caption gives seven mice, three male. The reported four-group ANOVA denominator degrees of freedom of 25 also accords with the caption's group sizes, not the Methods' count.

  • CeA chemogenetic group labels omit both stress groups

    Minor

    The Methods label all four groups as controls, including a second pair of mCherry and hM4Di groups. The corresponding Extended Data caption identifies that second pair as stress groups.

  • Continuous-illumination duration differs across descriptions

    Minor

    The Results and Methods describe illumination throughout a 12-hour dark phase; the Extended Data caption instead specifies 8 hours.

  • Reported training-session count conflicts with the minimum protocol

    Minor

    The Results say the initial experiment used four training sessions. The Methods require two qualifying FR-1 sessions before escalation and separately specify one session each at RR-2, RR-5, and RR-10, making at least five sessions.

7 of 7

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. Franklin, K. B. J. & Paxinos, G. The Mouse Brain in Stereotaxic Coordinates 3rd edn (Elsevier, 2008).

Cited by

Sorted by citations

Related

Authors
Giovanniello, J. R., Paredes, N., Wiener, A., Ramírez-Armenta, K., Oragwam, C., Uwadia, H. O., Yu, A. L., Lim, K., Pimenta, J. S., Vilchez, G. E., Nnamdi, G., Wang, A., Sehgal, M., Reis, F. M., Sias, A. C., Silva, A. J., Adhikari, A., Malvaez, M., & Wassum, K. M.
Affiliations
University of California, Los Angeles (US)
ORCID
Venue
Nature
Publisher
Springer Science and Business Media LLC
Published
2025-02-19
Volume
640
Issue
8059
Pages
722-731
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
DOI
10.1038/s41586-024-08580-w
PMC
PMC12011321
OpenAlex
W4407741452
Semantic Scholar
1de2b6aa486585dee0b4de12cbb119227bed3f9c
Cited by
30
References
102
Citations by year
2026: 15 · 2025: 15
FWCI
17.02
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • eScholarship (California Digital Library) (submittedVersion, cc-by)
Funders
  • National Institutes of Health (1r01da058374-01a1)
  • National Institute of Mental Health (R01MH119089, L40 MH137809, R00MH135177, K99MH135177)
  • National Institute on Drug Abuse (F32DA056201, R01 DA058374, R01DA046679, T32DA024635, R01DA035443)
  • National Institute of General Medical Sciences (TL4GM118977)
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development (P50HD103557)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
Keywords
chronic stress, agency, habit formation, basolateral amygdala, central amygdala, dorsomedial striatum, action-outcome learning, goal-directed behavior, decision-making, sex differences, substance use disorders
MeSH terms
Amygdala, Animals, Chronic Disease, Corpus Striatum, Decision Making, Female, Goals, Habits, Learning, Male, Mice, Inbred C57BL, Neural Pathways, Reward, Stress, Psychological, Mice

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-09.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-09.

Statistics and arithmetic are recomputed, not judged.

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