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A molecularly integrated amygdalo-fronto-striatal network coordinates flexible learning and memory

Nature Neuroscience volume 25, pages 1213–1224 (2022)Cite this article

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Abstract

Behavioral flexibility—that is, the ability to deviate from established behavioral sequences—is critical for navigating dynamic environments and requires the durable encoding and retrieval of new memories to guide future choice. The orbitofrontal cortex (OFC) supports outcome-guided behaviors. However, the coordinated neural circuitry and cellular mechanisms by which OFC connections sustain flexible learning and memory remain elusive. Here we demonstrate in mice that basolateral amygdala (BLA)→OFC projections bidirectionally control memory formation when familiar behaviors are unexpectedly not rewarded, whereas OFC→dorsomedial striatum (DMS) projections facilitate memory retrieval. OFC neuronal ensembles store a memory trace for newly learned information, which appears to be facilitated by circuit-specific dendritic spine plasticity and neurotrophin signaling within defined BLA–OFC–DMS connections and obstructed by cocaine. Thus, we describe the directional transmission of information within an integrated amygdalo-fronto-striatal circuit across time, whereby novel memories are encoded by BLA→OFC inputs, represented within OFC ensembles and retrieved via OFC→DMS outputs during future choice.

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Fig. 1: BLA→OFC projections are necessary for encoding, but not retrieving, new action memories for sustained response flexibility.
Fig. 2: Selective inactivation of BLA→OFC axon terminals is sufficient to disrupt flexible memory encoding.
Fig. 3: Stimulating BLA→OFC projections reinstates flexible action memory encoding after cocaine.
Fig. 4: OFC→DMS, but not OFC→BLA, projections are necessary for the encoding and retrieval of new action memories for sustained response flexibility.
Fig. 5: Encoding-activated neuronal ensembles in the OFC form a memory trace for later response flexibility.
Fig. 6: New action learning triggers dendritic spine plasticity within a di-synaptic BLA→OFC→DMS circuit.
Fig. 7: Circuit-specific neurotrophin tone in the OFC is required for new learning for sustained response flexibility.

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Data availability

Individual data points are represented throughout. More detailed datasets are available from the corresponding author upon reasonable request.

References

  1. Everitt, B. J. & Robbins, T. W. Drug addiction: updating actions to habits to compulsions ten years on. Annu. Rev. Psychol. 67, 23–50 (2016).

    Article  PubMed  Google Scholar 

  2. Izquierdo, A. Functional heterogeneity within rat orbitofrontal cortex in reward learning and decision making. J. Neurosci. 37, 10529–10540 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Stalnaker, T. A., Cooch, N. K. & Schoenbaum, G. What the orbitofrontal cortex does not do. Nat. Neurosci. 18, 620–627 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Gardner, M. P. H., Conroy, J. C., Sanchez, D. C., Zhou, J. & Schoenbaum, G. Real-time value integration during economic choice is regulated by orbitofrontal cortex. Curr. Biol. 29, 4315–4322 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Parkes, S. L. et al. Insular and ventrolateral orbitofrontal cortices differentially contribute to goal-directed behavior in rodents. Cereb. Cortex 28, 2313–2325 (2018).

    Article  PubMed  Google Scholar 

  6. Banerjee, A. et al. Value-guided remapping of sensory cortex by lateral orbitofrontal cortex. Nature 585, 245–250 (2020).

    Article  CAS  PubMed  Google Scholar 

  7. Schuck, N. W., Cai, M. B., Wilson, R. C. & Niv, Y. Human orbitofrontal cortex represents a cognitive map of state space. Neuron 91, 1402–1412 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Wilson, R. C., Takahashi, Y. K., Schoenbaum, G. & Niv, Y. Orbitofrontal cortex as a cognitive map of task space. Neuron 81, 267–279 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Niv, Y. Learning task-state representations. Nat. Neurosci. 22, 1544–1553 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Behrens, T. E. J. et al. What is a cognitive map? Organizing knowledge for flexible behavior. Neuron 100, 490–509 (2018).

    Article  CAS  PubMed  Google Scholar 

  11. Hirokawa, J., Vaughan, A., Masset, P., Ott, T. & Kepecs, A. Frontal cortex neuron types categorically encode single decision variables. Nature 576, 446–451 (2019).

    Article  CAS  PubMed  Google Scholar 

  12. Zhou, J. et al. Rat orbitofrontal ensemble activity contains multiplexed but dissociable representations of value and task structure in an odor sequence task. Curr. Biol. 29, 897–907 (2019).

    Article  CAS  PubMed  Google Scholar 

  13. Groman, S. M. et al. Orbitofrontal circuits control multiple reinforcement-learning processes. Neuron 103, 734–746 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Namboodiri, V. M. K. et al. Single-cell activity tracking reveals that orbitofrontal neurons acquire and maintain a long-term memory to guide behavioral adaptation. Nat. Neurosci. 22, 1110–1121 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Malvaez, M., Shieh, C., Murphy, M. D., Greenfield, V. Y. & Wassum, K. M. Distinct cortical–amygdala projections drive reward value encoding and retrieval. Nat. Neurosci. 22, 762–769 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Barreiros, I. V., Panayi, M. C. & Walton, M. E. Organization of afferents along the anterior–posterior and medial–lateral axes of the rat orbitofrontal cortex. Neuroscience 460, 53–68 (2021).

    Article  CAS  PubMed  Google Scholar 

  17. Schoenbaum, G., Setlow, B., Saddoris, M. P. & Gallagher, M. Encoding predicted outcome and acquired value in orbitofrontal cortex during cue sampling depends upon input from basolateral amygdala. Neuron 39, 855–867 (2003).

    Article  CAS  PubMed  Google Scholar 

  18. Rudebeck, P. H., Mitz, A. R., Chacko, R. V. & Murray, E. A. Effects of amygdala lesions on reward–value coding in orbital and medial prefrontal cortex. Neuron 80, 1519–1531 (2013).

    Article  CAS  PubMed  Google Scholar 

  19. de Wit, S., Ostlund, S. B., Balleine, B. W. & Dickinson, A. Resolution of conflict between goal-directed actions: outcome encoding and neural control processes. J. Exp. Psychol. Anim. Behav. Process 35, 382–393 (2009).

    Article  PubMed  Google Scholar 

  20. Dickinson, A., Nicholas, D. J. & Adams, A. D. The effect of the instrumental training contingency on susceptibility to reinforcer devaluation. Q. J. Exp. Psychol. B 35, 35–51 (1983).

    Article  Google Scholar 

  21. Lucantonio, F., Stalnaker, T. A., Shaham, Y., Niv, Y. & Schoenbaum, G. The impact of orbitofrontal dysfunction on cocaine addiction. Nat. Neurosci. 15, 358–366 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Ersche, K. D. et al. Carrots and sticks fail to change behavior in cocaine addiction. Science 352, 1468–1471 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. DePoy, L. M., Zimmermann, K. S., Marvar, P. J. & Gourley, S. L. Induction and blockade of adolescent cocaine-induced habits. Biol. Psychiatry 81, 595–605 (2017).

    Article  CAS  PubMed  Google Scholar 

  24. Northoff, G. & Tumati, S. ‘Average is good, extremes are bad’—non-linear inverted U-shaped relationship between neural mechanisms and functionality of mental features. Neurosci. Biobehav. Rev. 104, 11–25 (2019).

    Article  PubMed  Google Scholar 

  25. 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).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Gremel, C. M. & Costa, R. M. Orbitofrontal and striatal circuits dynamically encode the shift between goal-directed and habitual actions. Nat. Commun. 4, 2264 (2013).

    Article  PubMed  CAS  Google Scholar 

  27. Zimmermann, K. S., Yamin, J. A., Rainnie, D. G., Ressler, K. J. & Gourley, S. L. Connections of the mouse orbitofrontal cortex and regulation of goal-directed action selection by brain-derived neurotrophic factor. Biol. Psychiatry 81, 366–377 (2017).

    Article  CAS  PubMed  Google Scholar 

  28. Saddoris, M. P., Gallagher, M. & Schoenbaum, G. Rapid associative encoding in basolateral amygdala depends on connections with orbitofrontal cortex. Neuron 46, 321–331 (2005).

    Article  CAS  PubMed  Google Scholar 

  29. Lucantonio, F. et al. Neural estimates of imagined outcomes in basolateral amygdala depend on orbitofrontal cortex. J. Neurosci. 35, 16521–16530 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Berry, K. P. & Nedivi, E. Spine dynamics: are they all the same? Neuron 96, 43–55 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. DeNardo, L. A., Berns, D. S., DeLoach, K. & Luo, L. Connectivity of mouse somatosensory and prefrontal cortex examined with trans-synaptic tracing. Nat. Neurosci. 18, 1687–1697 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Yang, G., Pan, F. & Gan, W. B. Stably maintained dendritic spines are associated with lifelong memories. Nature 462, 920–924 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Matsuzaki, M., Honkura, N., Ellis-Davies, G. C. & Kasai, H. Structural basis of long-term potentiation in single dendritic spines. Nature 429, 761–766 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Chao, M. V. Neurotrophins and their receptors: a convergence point for many signalling pathways. Nat. Rev. Neurosci. 4, 299–309 (2003).

    Article  CAS  PubMed  Google Scholar 

  35. Gallagher, M., McMahan, R. W. & Schoenbaum, G. Orbitofrontal cortex and representation of incentive value in associative learning. J. Neurosci. 19, 6610–6614 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Pickens, C. L. et al. Different roles for orbitofrontal cortex and basolateral amygdala in a reinforcer devaluation task. J. Neurosci. 23, 11078–11084 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Noonan, M. P., Chau, B. K. H., Rushworth, M. F. S. & Fellows, L. K. Contrasting effects of medial and lateral orbitofrontal cortex lesions on credit assignment and decision-making in humans. J. Neurosci. 37, 7023–7035 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Jocham, G. et al. Reward-guided learning with and without causal attribution. Neuron 90, 177–190 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Panayi, M. C. & Killcross, S. Functional heterogeneity within the rodent lateral orbitofrontal cortex dissociates outcome devaluation and reversal learning deficits. eLife 7, e37357 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Ostlund, S. B. & Balleine, B. W. Orbitofrontal cortex mediates outcome encoding in Pavlovian but not instrumental conditioning. J. Neurosci. 27, 4819–4825 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Ramirez-Lugo, L., Penas-Rincon, A., Angeles-Duran, S. & Sotres-Bayon, F. Choice behavior guided by learned, but not innate, taste aversion recruits the orbitofrontal cortex. J. Neurosci. 36, 10574–10583 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Farovik, A. et al. Orbitofrontal cortex encodes memories within value-based schemas and represents contexts that guide memory retrieval. J. Neurosci. 35, 8333–8344 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. DeNardo, L. A. et al. Temporal evolution of cortical ensembles promoting remote memory retrieval. Nat. Neurosci. 22, 460–469 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Josselyn, S. A. & Tonegawa, S. Memory engrams: recalling the past and imagining the future. Science 367, eaaw4325 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Wikenheiser, A. M., Marrero-Garcia, Y. & Schoenbaum, G. Suppression of ventral hippocampal output impairs integrated orbitofrontal encoding of task structure. Neuron 95, 1197–1207 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Zhou, J. et al. Complementary task structure representations in hippocampus and orbitofrontal cortex during an odor sequence task. Curr. Biol. 29, 3402–3409 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. McGaugh, J. L. The amygdala modulates the consolidation of memories of emotionally arousing experiences. Annu. Rev. Neurosci. 27, 1–28 (2004).

    Article  CAS  PubMed  Google Scholar 

  48. Leong, Y. C., Radulescu, A., Daniel, R., DeWoskin, V. & Niv, Y. Dynamic interaction between reinforcement learning and attention in multidimensional environments. Neuron 93, 451–463 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Niv, Y. et al. Reinforcement learning in multidimensional environments relies on attention mechanisms. J. Neurosci. 35, 8145–8157 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. DePoy, L. M. & Gourley, S. L. Synaptic cytoskeletal plasticity in the prefrontal cortex following psychostimulant exposure. Traffic 16, 919–940 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Wright, W. J. et al. Silent synapses dictate cocaine memory destabilization and reconsolidation. Nat. Neurosci. 23, 32–46 (2020).

    Article  CAS  PubMed  Google Scholar 

  52. Kanta, V., Pare, D. & Headley, D. B. Closed-loop control of gamma oscillations in the amygdala demonstrates their role in spatial memory consolidation. Nat. Commun. 10, 3970 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  53. Huff, M. L., Miller, R. L., Deisseroth, K., Moorman, D. E. & LaLumiere, R. T. Posttraining optogenetic manipulations of basolateral amygdala activity modulate consolidation of inhibitory avoidance memory in rats. Proc. Natl Acad. Sci. USA 110, 3597–3602 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Jones, J. L. et al. Orbitofrontal cortex supports behavior and learning using inferred but not cached values. Science 338, 953–956 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Vertechi, P. et al. Inference-based decisions in a hidden state foraging task: differential contributions of prefrontal cortical areas. Neuron 106, 166–176 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Stalnaker, T. A. et al. Orbitofrontal neurons infer the value and identity of predicted outcomes. Nat. Commun. 5, 3926 (2014).

    Article  CAS  PubMed  Google Scholar 

  57. Takahashi, Y. K. et al. Expectancy-related changes in firing of dopamine neurons depend on orbitofrontal cortex. Nat. Neurosci. 14, 1590–1597 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Hayashi-Takagi, A. et al. Labelling and optical erasure of synaptic memory traces in the motor cortex. Nature 525, 333–338 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Wu, Y. I. et al. A genetically encoded photoactivatable Rac controls the motility of living cells. Nature 461, 104–108 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Feng, G. et al. Imaging neuronal subsets in transgenic mice expressing multiple spectral variants of GFP. Neuron 28, 41–51 (2000).

    Article  CAS  PubMed  Google Scholar 

  61. Rios, M. et al. Conditional deletion of brain-derived neurotrophic factor in the postnatal brain leads to obesity and hyperactivity. Mol. Endocrinol. 15, 1748–1757 (2001).

    Article  CAS  PubMed  Google Scholar 

  62. Dickinson, A. & Balleine, B. Motivational control of goal-directed action. Anim. Learn. Behav. 22, 1–18 (1994).

    Article  Google Scholar 

  63. Vaghi, M. M. et al. Action-outcome knowledge dissociates from behavior in obsessive-compulsive disorder following contingency degradation. Biol. Psychiatry Cogn. Neurosci. Neuroimaging 4, 200–209 (2019).

    PubMed  PubMed Central  Google Scholar 

  64. Rossi, M. A. & Yin, H. H. Methods for studying habitual behavior in mice. Curr. Protoc. Neurosci. 60, 8.29.1–8.29.9 (2012).

    Article  Google Scholar 

  65. Krashes, M. J. et al. Rapid, reversible activation of AgRP neurons drives feeding behavior in mice. J. Clin. Invest. 121, 1424–1428 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Gomez, J. L. et al. Chemogenetics revealed: DREADD occupancy and activation via converted clozapine. Science 357, 503–507 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Huang, L. et al. Organizational principles of amygdalar input-output neuronal circuits. Mol. Psychiatry 26, 7118–7129 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  68. Wang, J. et al. Divergent projection patterns revealed by reconstruction of individual neurons in orbitofrontal cortex. Neurosci. Bull. 37, 461–477 (2021).

    Article  PubMed  Google Scholar 

  69. Shinonaga, Y., Takada, M. & Mizuno, N. Topographic organization of collateral projections from the basolateral amygdaloid nucleus to both the prefrontal cortex and nucleus accumbens in the rat. Neuroscience 58, 389–397 (1994).

    Article  CAS  PubMed  Google Scholar 

  70. Paxinos, G. & Franklin, K. B. J. The Mouse Brain in Stereotaxic Coordinates 2nd edn (Academic Press, 2001).

  71. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).

    Article  CAS  PubMed  Google Scholar 

  72. Zingg, B. et al. AAV-mediated anterograde transsynaptic tagging: mapping corticocollicular input-defined neural pathways for defense behaviors. Neuron 93, 33–47 (2017).

    Article  CAS  PubMed  Google Scholar 

  73. Radley, J. J., Anderson, R. M., Hamilton, B. A., Alcock, J. A. & Romig-Martin, S. A. Chronic stress-induced alterations of dendritic spine subtypes predict functional decrements in an hypothalamo-pituitary-adrenal-inhibitory prefrontal circuit. J. Neurosci. 33, 14379–14391 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank R. A. Davies for technical assistance and laboratory members for feedback on the manuscript. This work was supported by National Institutes of Health grants F30MH117873 (D.C.L.), R01MH117103 (S.L.G.) and R01DA044297 (S.L.G.). The Emory Viral Vector Core is supported by National Institute of Neurological Disorders and Stroke Core Facilities grant P30NS055077. The Emory National Primate Research Center is supported by Office of Research Infrastructure Programs grant P51OD011132. Research reported in this publication was also supported, in part, by the Emory University Integrated Cellular Imaging Core and Children’s Healthcare of Atlanta.

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Authors and Affiliations

  1. Medical Scientist Training Program, Emory University School of Medicine, Atlanta, GA, USA

    Dan C. Li

  2. Department of Pediatrics, Children’s Healthcare of Atlanta, Emory University School of Medicine, Atlanta, GA, USA

    Dan C. Li, Niharika M. Dighe, Britton R. Barbee, Elizabeth G. Pitts, Janet Figueroa, Traci Leong & Shannon L. Gourley

  3. Emory National Primate Research Center, Emory University, Atlanta, GA, USA

    Dan C. Li, Niharika M. Dighe, Britton R. Barbee, Elizabeth G. Pitts, Brik Kochoian, Sarah A. Blumenthal & Shannon L. Gourley

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Contributions

Conceptualization: D.C.L. and S.L.G. Methodology: D.C.L. and S.L.G. Investigation (surgical preparation, behavioral testing and microscopy experiments): D.C.L., N.M.D., B.R.B., E.G.P., B.K. and S.A.B. Formal analysis (including statistical analyses): D.C.L., J.F. and T.L. Writing: D.C.L. and S.L.G. Supervision: S.L.G.

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Correspondence to Shannon L. Gourley.

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Extended data

Extended Data Fig. 1 Mice do not display preference for one nose-poke aperture during training.

Response side bias (responses on aperture to be non-reinforced / total responses) during training sessions. (a) BLA→OFC inactivation: memory encoding (session: F14,378 = 1.22, 0.256; session × CNO: F28,378 < 1), (b) delayed memory encoding (session: F10,80 = 3.18, p = 0.002; session × CNO: F10,80 < 1), or (c) memory retrieval (session: F8,128 = 4.86, p < 0.001; session × CNO: F8,128 < 1). (d) BLA→OFC stimulation (session: F14,392 < 1; session × cocaine: F14,392 < 1; session × CNO: F14,392 = 1.30, p = 0.205; session × cocaine × CNO: F14,392 < 1). (e) OFC→DMS inactivation (session: F8,144 = 1.05, p = 0.404; session× CNO: F8,144 = 1.21, p = 0.295). (f) OFC→BLA inactivation (session: F8,112 = 1.04, p = 0.205; session × CNO: F8,112 < 1). (g) OFC memory trace inactivation: novel (session: F6,96 = 1.03, p = 0.414; session × 4OHT: F6,96 = 1.73, p = 0.122) or (h) familiar reinforcement conditions (session: F6,108 < 1; session × 4OHT: F6,108 < 1). (i) BDNF-dependent circuit function: BLA-OFC (session: F6,204 = 1.10 p = 0.365; session × lateralization: F12,204 < 1) or (j) OFC-DMS disconnections (session: F6,138 = 1.44, p = 0.204; session × lateralization: F12,138 < 1). Data presented as individual points (semi-transparent) and group means (solid). Correspondence to main figures noted.

Extended Data Fig. 2 Nose-poking and lever-pressing actions are instrumental in nature.

(a,e) Behavioral procedure used to assess sensitivity to instrumental omission for nose-poking or lever-pressing. (b, c) Nose-poke responses across training (F6,42 = 10.1, p < 0.001) and during omission session (F5,35 = 16.9, p < 0.001). (d) Raster plot of nose-poking responses for each animal throughout the omission session. (f, g) Lever-pressing across training (F3,21 = 29.1, p < 0.001) and during omission session (F5,35 = 35.0, p < 0.001). (h) Raster plot of lever-pressing responses for each animal throughout the omission session. Data presented as individual points (semi-transparent) and group means (solid). Repeating measures ANOVA was applied, 2-sided, with no adjustment for multiple comparisons required.

Extended Data Fig. 3 Inactivation of posterolateral OFC does not disrupt flexible memory encoding.

(a) Left. Chemogenetic receptor expression in the anterior ventrolateral OFC from experiments described in Figs.1–3 of main text. Right. Extent of inhibitory chemogenetic receptor expression in the posterolateral OFC. Anterior-posterior (A-P) distance from bregma noted. (b) Timing of CNO administration for posterolateral OFC inactivation during memory encoding. (c) Responses across training (session: F6,84 = 73.9, p < 0.001; session × virus: F6,84 < 1). (d, e) Responses during first (reinforcement: F1,14 = 8.49, p = 0.011; reinforcement × virus: F1,14 = 1.59, p = 0.228) and second choice tests (reinforcement: F1,14 = 26.9, p < 0.001; reinforcement × virus: F1,14 < 1). Choice tests were performed on sequential days. Data presented as individual points or mean ± S.E.M. *p < 0.05 (main effect). n = 8 GFP, 8 hM4Di mice. Correspondence to main figures noted. Analyses were performed by ANOVA (2-sided) with repeating measures when appropriate; no adjustments for multiple comparisons required.

Extended Data Fig. 4 Responding during non-reinforced sessions did not differ between groups prior to choice tests.

All non-reinforced sessions were performed drug- and manipulation-free. (a) BLA→OFC inactivation (memory encoding): test 1 (time: F4,108 = 16.5, p < 0.001; time × CNO: F8,108 < 1), test 2 (time: F4,108 = 17.9, p < 0.001; time × CNO: F8,108 < 1), or test 3 (time: F4,108 = 16.2, p < 0.001; time × CNO: F8,108 < 1). (b) BLA→OFC inactivation (delayed memory encoding): test 1 (time: F4,56 = 29.9, p < 0.001; time × CNO: F4,56 < 1) or test 2 (time: F4,56 = 35.2, p < 0.001; time × CNO: F4,56 = 1.63, p = 0.179). (c) BLA→OFC inactivation (memory retrieval): test 1 (time: F4,64 = 12.2, p < 0.001; time × CNO: F4,64 < 1) or test 2 (time: F4,64 = 7.17, p < 0.001; time × CNO: F4,64 < 1). (d) BLA→OFC stimulation: test 1 (time: F4,112 = 16.3, p < 0.001; time × cocaine: F4,112 < 1; time × CNO: F4,112 = 1.18, p = 0.324; time × cocaine × CNO: F4,112 < 1), test 2 (time: F4,112 = 47.0, p < 0.001; time × cocaine: F4,112 = 2.61, p = 0.056; time × CNO: F4,112 = 2.19, p = 0.075; time × cocaine × CNO: F4,112 < 1), or test 3 (time: F4,112 = 55.2, p < 0.001; time × cocaine: F4,112 = 1.27, p = 0.284; time × CNO: F4,112 < 1; time × cocaine × CNO: F4,112 = 1.74, p = 0.147). (e) OFC→DMS inactivation: test 1 (time: F4,72 = 8.30, p < 0.001; time × CNO: F4, 72 < 1) or test 2 (time: F4,72 = 40.5, p < 0.001; time × CNO: F4,72 < 1). (f) OFC→BLA inactivation: test 1 (time: F4,56 = 20.8, p < 0.001; time × CNO: F4,56 < 1) or test 2 (time: F4,56 = 27.1, p < 0.001; time × CNO: F4,56 = 1.62, p = 0.183). (g-h) OFC memory trace inactivation: novel (time: F4,84 = 26.1, p < 0.001; time × 4OHT: F4,84 < 1) or familiar reinforcement conditions (time: F4,72 = 19.3, p < 0.001; time × 4OHT: F4,72 < 1). (i-j) BDNF-dependent circuit function: BLA-OFC (time: F4,136 = 61.6, p < 0.001; time × lateralization: F8,136 < 1) or OFC-DMS disconnections (time: F4,92 = 31.7, p < 0.001; time × lateralization: F8,92 < 1). Data presented as mean ± S.E.M. Correspondence to main figures noted.

Extended Data Fig. 5 Extended interval training prompts inflexible choice behavior.

(a) Responses across training (F14,196 = 16.9, p < 0.001). (b) Choice test responses (t14 < 1). Data presented as individual points or mean ± S.E.M. n = 15 mice. Analyses were performed by ANOVA with repeating measures, and paired t-test (2-sided).

Extended Data Fig. 6 Correlations between choice behavior and relative experience frequency of reinforced vs. non-reinforced nose pokes.

Correlation between individual choice test preference ratios (reinforced / non-reinforced) and the standard contingency measure (ΔP; see Methods) for each 25-minute non-reinforced session. (a) BLA→OFC inactivation: memory encoding (FR1: F1,28 < 1; RI30: F1,28 < 1; RI60: F1,28 = 2.40, p = 0.132), (b) delayed memory encoding (all F1,14 < 1), or (c) memory retrieval (all F1,16 < 1). (d) BLA→OFC stimulation (all F1,30 < 1). (e) OFC→DMS inactivation (all F1,18 < 1). (f) OFC→BLA inactivation (all F1,14 < 1). (g) Correlation coefficients (Pearson’s r) between session ΔP and choice test preference ratios for all experiments in panels a-f (in order). Data presented as individual points or group means. 95% confidence interval (grey shading). Correspondence to main figures noted.

Extended Data Fig. 7 Chemogenetic inactivation of OFC→DMS projections disrupts memory retrieval independent of repeated testing.

(a) Combinatorial viral targeting of OFC→DMS projections. (b) Timing of CNO administration for OFC→DMS projection inactivation during memory retrieval. (c) Responses across training (session: F6,48 = 33.3, p < 0.001; session × CNO: F6,48 < 1). (d) Choice test responses (reinforcement: F1,14 = 15.2, p = 0.002; reinforcement × CNO: F1,14 = 6.74, p = 0.021). Data resented as mean ± S.E.M. *p < 0.05 (post-hoc). n = 8 veh, 8 CNO mice. Experiments were replicated at least once, with concordant results.

Extended Data Fig. 8 Size of chemogenetically inactivated OFC neuronal ensembles does not predict choice behavior.

(a, b) Correlation between number of chemogenetically inactivated OFC neurons and choice test preference ratios (reinforced / non-reinforced) for OFC ensembles labelled following exposure to novel (F1,10 < 1) or familiar reinforcement conditions (F1,8 < 1). Data presented as individual points. 95% confidence interval (shading). Centre lines indicate regression.

Extended Data Fig. 9 Additional dendritic spine parameters among BLA→OFC→DMS relay neurons.

(a) Location of all sampled dendrites from trained (T; filled circles) and yoked (∅; open circles) mice by anterior-posterior (A-P) distance from bregma. (b, c) Dendritic spine density across A-P extent of the ventrolateral OFC for yoked (F1,70 < 1) and trained mice (F1,70 < 1). Centre lines indicate regression. (d–f) Left panels. Dendrite diameter (cocaine: F1,20 < 1; training: F1,20 < 1; cocaine × training: F1,20 < 1), dendritic spine length (cocaine: F1,20 = 3.80, p = 0.053; training: F1,20 = 1.47, p = 0.227; cocaine × training: F1,20 < 1) and dendritic spine diameter (cocaine: F1,20 < 1; training: F1,20 < 1; cocaine × training: F1,20 < 1). Right panels. Percent change (trained mouse vs. yoked cage mate) in dendrite diameter (t10 < 1), dendritic spine length (t10 < 1), and dendritic spine diameter (t10 < 1). Data presented as individual points (solid = per animal; transparent=per dendrite). #p = 0.053 (main effect). n = 6 sal ø, 6 coc ø, 6 sal T, 6 coc T mice.

Extended Data Fig. 10 Correlations between BLA→OFC→DMS circuit-defined dendritic spine plasticity and choice behavior.

Correlation between individual choice test preference ratios (reinforced / non-reinforced) and dendritic spine parameters from Fig.6. (a–d) Dendritic spine density for all spines (F1,10 = 5.12, p = 0.047), and by mushroom- (F1,10 = 5.71, p = 0.038), thin- (F1,10 = 1.14, p = 0.311), and stubby-type spines (F1,10 < 1). (e–h) Percent change (trained mouse vs. yoked [∅] cage mate) in dendritic spine density for all spines (F1,10 = 1.43, p = 0.259), and by mushroom- (F1,10 < 1), thin- (F1,10 = 8.79, p = 0.014), and stubby-type spines (F1,10 = 1.10, p = 0.319). (i-j) Mushroom-to-thin spine-type ratio (F1,10 = 4.88, p = 0.052). Percent change (F1,10 = 4.03, p = 0.073). (k, l) Head volume of mushroom-type spines (F1,10 < 1). Percent change (F1,10 = 8.82, p = 0.014). Data presented as individual points. 95% confidence interval (grey shading). *p < 0.05. †p = 0.052. #p = 0.073. Panels g and l reproduced in Fig.6. Centre lines indicate regression.

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Li, D.C., Dighe, N.M., Barbee, B.R. et al. A molecularly integrated amygdalo-fronto-striatal network coordinates flexible learning and memory. Nat Neurosci 25, 1213–1224 (2022). https://doi.org/10.1038/s41593-022-01148-9

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