The Impact of Reactivation During Sleep on the Consolidation of Abstract Information in Humans

The Emergence of Abstract Structure Knowledge Across Learning and Sleep

In any given cognitive domain, representations of individual elements are not independent but are organized by means of structured relations. Representations of this underlying structure are powerful, allowing generalization and inference in novel environments. In the semantic domain, structure captures associations between different semantic features or concepts (e.g., green, wings, can fly) and is known to influence the development and deterioration of semantic knowledge. The investigators recently found that humans more easily learn novel categories that contain clusters of reliably co-occurring features, revealing an influence of structure on novel category formation. However, a critical unknown is whether learned representations of structure are closely tied to category-specific elements, or whether such representations become abstract to some extent, transformed away from the experienced features. Further, if abstract structural representations do emerge, prior work provides intriguing hints that these representations may require offline consolidation during awake rest or sleep. The investigators have developed a paradigm in which carefully designed graph structures govern the pattern of feature co-occurrences within individual categories. Here the investigators implement a "structure transfer" extension of this paradigm in order to determine whether learning one structured category facilitates learning of a second identically structured category defined by a new set of features. This facilitation would provide evidence that structure representations are abstract to some degree. Aim 1 will use these methods to evaluate whether abstract structural representations emerge immediately during learning. Aim 2 will determine whether these representations persist, or emerge, over a delay, and whether sleep-based consolidation in particular is needed. The role of replay of recent experience during sleep will be evaluated using electroencephalography (EEG) paired with closed-loop targeted memory reactivation (TMR), a technique that enables causal influence over the consolidation of recently learned information in humans. This work will inform and constrain theories of semantic learning as well as theories of structure learning and representation more broadly.

Study Overview

• Status: Recruiting
• Conditions: Memory Consolidation
• Intervention / Treatment: Behavioral: Congruent vs. Incongruent; Behavioral: Immediate vs. Awake vs. Asleep; Behavioral: Targeted memory reactivation (TMR)

• Study Type: Interventional
• Enrollment (Estimated): 250
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Anna C Schapiro, PhD; Phone Number: 6177974555; Email: aschapir@sas.upenn.edu
• Study Contact Backup: Name: Sarah H Solomon, PhD; Phone Number: 9144340164; Email: sarahsol@sas.upenn.edu

Study Locations

• United States
  • Pennsylvania
    • Philadelphia, Pennsylvania, United States, 19104
      • Recruiting
      • University of Pennsylvania
      • Contact: Rishi Krishnamurthy, BA; Phone Number: 425-505-0841; Email: rishikr@sas.upenn.edu

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 35 years (Adult)
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

• Ages between 18 and 35

Exclusion Criteria:

• No medical or neurological illness that would impact experimental performance
• Not a member of a vulnerable population

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Basic Science
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

7

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Immediate Congruent; Participants will learn and be tested on two different semantic categories with the same structure that dictates the co-occurrence of different features.	Behavioral: Congruent vs. Incongruent; The Congruent vs. Incongruent intervention relates to the feature-based structure of the novel categories (Modular or non-Modular) and whether there is (Congruent) or is not (Incongruent) a match between what was previously learned and the final target category.; Behavioral: Immediate vs. Awake vs. Asleep; Immediate, Awake, and Sleep refer to either no break, 2.5 hours awake, or 2 hours asleep plus a 30-minute post-nap break to account for sleep inertia between learning and target category.
Experimental: Immediate Incongruent; Participants will learn and be tested on two different semantic categories with different structures that dictate the co-occurrence of different features.	Behavioral: Congruent vs. Incongruent; The Congruent vs. Incongruent intervention relates to the feature-based structure of the novel categories (Modular or non-Modular) and whether there is (Congruent) or is not (Incongruent) a match between what was previously learned and the final target category.; Behavioral: Immediate vs. Awake vs. Asleep; Immediate, Awake, and Sleep refer to either no break, 2.5 hours awake, or 2 hours asleep plus a 30-minute post-nap break to account for sleep inertia between learning and target category.
Experimental: Awake Incongruent; Participants will learn two different semantic categories, neither of which has a Modular structure. After a 2.5-hour break, they will learn and be tested on a novel semantic category with a Modular structure.	Behavioral: Congruent vs. Incongruent; The Congruent vs. Incongruent intervention relates to the feature-based structure of the novel categories (Modular or non-Modular) and whether there is (Congruent) or is not (Incongruent) a match between what was previously learned and the final target category.; Behavioral: Immediate vs. Awake vs. Asleep; Immediate, Awake, and Sleep refer to either no break, 2.5 hours awake, or 2 hours asleep plus a 30-minute post-nap break to account for sleep inertia between learning and target category.
Experimental: Awake Congruent; Participants will learn two different semantic categories, one of which has a Modular structure. After a 2.5-hour break, they will learn and be tested on a novel semantic category with a Modular structure.	Behavioral: Congruent vs. Incongruent; The Congruent vs. Incongruent intervention relates to the feature-based structure of the novel categories (Modular or non-Modular) and whether there is (Congruent) or is not (Incongruent) a match between what was previously learned and the final target category.; Behavioral: Immediate vs. Awake vs. Asleep; Immediate, Awake, and Sleep refer to either no break, 2.5 hours awake, or 2 hours asleep plus a 30-minute post-nap break to account for sleep inertia between learning and target category.
Experimental: Sleep Incongruent; Participants will learn two different semantic categories, one of which has a Modular structure. After a 2-hour nap opportunity, during which TMR will be used to reactivate the non-Modular category, participants will take a 30-minute break. After the break, they will learn and be tested on a novel semantic category with a Modular structure.	Behavioral: Congruent vs. Incongruent; The Congruent vs. Incongruent intervention relates to the feature-based structure of the novel categories (Modular or non-Modular) and whether there is (Congruent) or is not (Incongruent) a match between what was previously learned and the final target category.; Behavioral: Immediate vs. Awake vs. Asleep; Immediate, Awake, and Sleep refer to either no break, 2.5 hours awake, or 2 hours asleep plus a 30-minute post-nap break to account for sleep inertia between learning and target category.; Behavioral: Targeted memory reactivation (TMR); Targeted memory reactivation (TMR) is the systematic presentation of sounds during sleep that were associated with certain stimuli during learning and will be administered either during slow wave sleep (SWS) or rapid eye movement (REM) sleep.
Experimental: Sleep Congruent (SWS); Participants will learn two different semantic categories, one of which has a Modular structure. After a 2-hour nap opportunity, during which TMR will be used to reactivate the Modular category during slow wave sleep (SWS), participants will take a 30-minute break. After the break, they will learn and be tested on a novel semantic category with a Modular structure.	Behavioral: Congruent vs. Incongruent; The Congruent vs. Incongruent intervention relates to the feature-based structure of the novel categories (Modular or non-Modular) and whether there is (Congruent) or is not (Incongruent) a match between what was previously learned and the final target category.; Behavioral: Immediate vs. Awake vs. Asleep; Immediate, Awake, and Sleep refer to either no break, 2.5 hours awake, or 2 hours asleep plus a 30-minute post-nap break to account for sleep inertia between learning and target category.; Behavioral: Targeted memory reactivation (TMR); Targeted memory reactivation (TMR) is the systematic presentation of sounds during sleep that were associated with certain stimuli during learning and will be administered either during slow wave sleep (SWS) or rapid eye movement (REM) sleep.
Experimental: Sleep Congruent (REM); Participants will learn two different semantic categories, one of which has a Modular structure. After a 2-hour nap opportunity, during which TMR will be used to reactivate the Modular category during rapid eye movement (REM) sleep, participants will take a 30-minute break. After the break, they will learn and be tested on a novel semantic category with a Modular structure.	Behavioral: Congruent vs. Incongruent; The Congruent vs. Incongruent intervention relates to the feature-based structure of the novel categories (Modular or non-Modular) and whether there is (Congruent) or is not (Incongruent) a match between what was previously learned and the final target category.; Behavioral: Immediate vs. Awake vs. Asleep; Immediate, Awake, and Sleep refer to either no break, 2.5 hours awake, or 2 hours asleep plus a 30-minute post-nap break to account for sleep inertia between learning and target category.; Behavioral: Targeted memory reactivation (TMR); Targeted memory reactivation (TMR) is the systematic presentation of sounds during sleep that were associated with certain stimuli during learning and will be administered either during slow wave sleep (SWS) or rapid eye movement (REM) sleep.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Structure knowledge for a new Modular category in Stage 2	Accuracy (0-100%) on the missing feature task in Stage 2	In Aim 1, accuracy is collected in a missing feature task 25 min. into the experiment, taking 25 min. In Aim 2, accuracy is collected in a missing feature task over 25 min in Stage 2

Collaborators and Investigators

• Sponsor: University of Pennsylvania
• Collaborators: National Institute of Mental Health (NIMH)
• Investigators: Principal Investigator: Anna C Schapiro, PhD, University of Pennsylvania

Publications and helpful links

General Publications

• Rasch B, Born J. About sleep's role in memory. Physiol Rev. 2013 Apr;93(2):681-766. doi: 10.1152/physrev.00032.2012.
• Monti JM, Monti D. Sleep disturbance in schizophrenia. Int Rev Psychiatry. 2005 Aug;17(4):247-53. doi: 10.1080/09540260500104516.
• Tsuno N, Besset A, Ritchie K. Sleep and depression. J Clin Psychiatry. 2005 Oct;66(10):1254-69. doi: 10.4088/jcp.v66n1008.
• Gentner, D.. Structure-mapping: A theoretical framework for analogy. Cognitive science. 1983;7(2): 155-170.
• Thibodeau PH, Flusberg SJ, Glick JJ, & Sternberg DA. An emergent approach to analogical inference. Connection Science. 2013; 25(1): 27-53.
• Collins AGE, Frank MJ. Neural signature of hierarchically structured expectations predicts clustering and transfer of rule sets in reinforcement learning. Cognition. 2016 Jul;152:160-169. doi: 10.1016/j.cognition.2016.04.002. Epub 2016 Apr 12.
• Baram AB, Muller TH, Nili H, Garvert MM, Behrens TEJ. Entorhinal and ventromedial prefrontal cortices abstract and generalize the structure of reinforcement learning problems. Neuron. 2021 Feb 17;109(4):713-723.e7. doi: 10.1016/j.neuron.2020.11.024. Epub 2020 Dec 22.
• TOLMAN EC. Cognitive maps in rats and men. Psychol Rev. 1948 Jul;55(4):189-208. doi: 10.1037/h0061626. No abstract available.
• Behrens TEJ, Muller TH, Whittington JCR, Mark S, Baram AB, Stachenfeld KL, Kurth-Nelson Z. What Is a Cognitive Map? Organizing Knowledge for Flexible Behavior. Neuron. 2018 Oct 24;100(2):490-509. doi: 10.1016/j.neuron.2018.10.002.
• Whittington JCR, Muller TH, Mark S, Chen G, Barry C, Burgess N, Behrens TEJ. The Tolman-Eichenbaum Machine: Unifying Space and Relational Memory through Generalization in the Hippocampal Formation. Cell. 2020 Nov 25;183(5):1249-1263.e23. doi: 10.1016/j.cell.2020.10.024. Epub 2020 Nov 11.
• McClelland JL, Rogers TT. The parallel distributed processing approach to semantic cognition. Nat Rev Neurosci. 2003 Apr;4(4):310-22. doi: 10.1038/nrn1076. No abstract available.
• Bahdanau D, Murty S, Noukhovitch M, Nguyen TH, de Vries H, Courville A. Systematic generalization: what is required and can it be learned?. arXiv preprint. 2018.
• Mark S, Moran R, Parr T, Kennerley SW, Behrens TEJ. Transferring structural knowledge across cognitive maps in humans and models. Nat Commun. 2020 Sep 22;11(1):4783. doi: 10.1038/s41467-020-18254-6.
• Durrant SJ, Cairney SA, Lewis PA. Cross-modal transfer of statistical information benefits from sleep. Cortex. 2016 May;78:85-99. doi: 10.1016/j.cortex.2016.02.011. Epub 2016 Feb 27.
• Tamminen J, Lambon Ralph MA, Lewis PA. Targeted memory reactivation of newly learned words during sleep triggers REM-mediated integration of new memories and existing knowledge. Neurobiol Learn Mem. 2017 Jan;137:77-82. doi: 10.1016/j.nlm.2016.11.012. Epub 2016 Nov 15.
• Wang B, Antony JW, Lurie S, Brooks PP, Paller KA, Norman KA. Targeted Memory Reactivation during Sleep Elicits Neural Signals Related to Learning Content. J Neurosci. 2019 Aug 21;39(34):6728-6736. doi: 10.1523/JNEUROSCI.2798-18.2019. Epub 2019 Jun 24.
• Schapiro AC, Turk-Browne NB, Norman KA, Botvinick MM. Statistical learning of temporal community structure in the hippocampus. Hippocampus. 2016 Jan;26(1):3-8. doi: 10.1002/hipo.22523. Epub 2015 Oct 13.
• Mack ML, Love BC, Preston AR. Building concepts one episode at a time: The hippocampus and concept formation. Neurosci Lett. 2018 Jul 27;680:31-38. doi: 10.1016/j.neulet.2017.07.061. Epub 2017 Aug 8.
• Weickert TW, Goldberg TE, Callicott JH, Chen Q, Apud JA, Das S, Zoltick BJ, Egan MF, Meeter M, Myers C, Gluck MA, Weinberger DR, Mattay VS. Neural correlates of probabilistic category learning in patients with schizophrenia. J Neurosci. 2009 Jan 28;29(4):1244-54. doi: 10.1523/JNEUROSCI.4341-08.2009.
• Riemann D, Berger M, Voderholzer U. Sleep and depression--results from psychobiological studies: an overview. Biol Psychol. 2001 Jul-Aug;57(1-3):67-103. doi: 10.1016/s0301-0511(01)00090-4.
• Nutt D, Wilson S, Paterson L. Sleep disorders as core symptoms of depression. Dialogues Clin Neurosci. 2008;10(3):329-36. doi: 10.31887/DCNS.2008.10.3/dnutt.
• Karuza EA, Kahn AE, Bassett DS. Human sensitivity to community structure is robust to topological variation. Complexity. 2019.
• Karuza EA, Kahn AE, Thompson-Schill SL, Bassett DS. Process reveals structure: How a network is traversed mediates expectations about its architecture. Sci Rep. 2017 Oct 6;7(1):12733. doi: 10.1038/s41598-017-12876-5.
• Karuza EA, Thompson-Schill SL, Bassett DS. Local Patterns to Global Architectures: Influences of Network Topology on Human Learning. Trends Cogn Sci. 2016 Aug;20(8):629-640. doi: 10.1016/j.tics.2016.06.003. Epub 2016 Jun 29.
• Lynn CW, Bassett DS. How humans learn and represent networks. Proc Natl Acad Sci U S A. 2020 Nov 24;117(47):29407-29415. doi: 10.1073/pnas.1912328117.
• Schapiro AC, Rogers TT, Cordova NI, Turk-Browne NB, Botvinick MM. Neural representations of events arise from temporal community structure. Nat Neurosci. 2013 Apr;16(4):486-92. doi: 10.1038/nn.3331. Epub 2013 Feb 17.
• Kahn AE, Karuza EA, Vettel JM, Bassett DS. Network constraints on learnability of probabilistic motor sequences. Nat Hum Behav. 2018 Dec;2(12):936-947. doi: 10.1038/s41562-018-0463-8. Epub 2018 Nov 5.
• Kakaei E, Aleshin S, Braun J. Visual object recognition is facilitated by temporal community structure. Learn Mem. 2021 Apr 15;28(5):148-152. doi: 10.1101/lm.053306.120. Print 2021 May.
• Eichenbaum H. Time cells in the hippocampus: a new dimension for mapping memories. Nat Rev Neurosci. 2014 Nov;15(11):732-44. doi: 10.1038/nrn3827. Epub 2014 Oct 1.
• Moser MB, Rowland DC, Moser EI. Place cells, grid cells, and memory. Cold Spring Harb Perspect Biol. 2015 Feb 2;7(2):a021808. doi: 10.1101/cshperspect.a021808.
• Maguire EA, Spiers HJ, Good CD, Hartley T, Frackowiak RS, Burgess N. Navigation expertise and the human hippocampus: a structural brain imaging analysis. Hippocampus. 2003;13(2):250-9. doi: 10.1002/hipo.10087.
• Kumaran D, McClelland JL. Generalization through the recurrent interaction of episodic memories: a model of the hippocampal system. Psychol Rev. 2012 Jul;119(3):573-616. doi: 10.1037/a0028681.
• Cohen N., Eichenbaum H. Memory, amnesia, and the hippocampal system. MIT press. 1993.
• Belal S, Cousins J, El-Deredy W, Parkes L, Schneider J, Tsujimura H, Zoumpoulaki A, Perapoch M, Santamaria L, Lewis P. Identification of memory reactivation during sleep by EEG classification. Neuroimage. 2018 Aug 1;176:203-214. doi: 10.1016/j.neuroimage.2018.04.029. Epub 2018 Apr 17.
• Stickgold R. Sleep-dependent memory consolidation. Nature. 2005 Oct 27;437(7063):1272-8. doi: 10.1038/nature04286.
• Wagner U, Gais S, Haider H, Verleger R, Born J. Sleep inspires insight. Nature. 2004 Jan 22;427(6972):352-5. doi: 10.1038/nature02223.
• Ellenbogen JM, Hu PT, Payne JD, Titone D, Walker MP. Human relational memory requires time and sleep. Proc Natl Acad Sci U S A. 2007 May 1;104(18):7723-8. doi: 10.1073/pnas.0700094104. Epub 2007 Apr 20.
• Schapiro AC, McDevitt EA, Chen L, Norman KA, Mednick SC, Rogers TT. Sleep Benefits Memory for Semantic Category Structure While Preserving Exemplar-Specific Information. Sci Rep. 2017 Nov 1;7(1):14869. doi: 10.1038/s41598-017-12884-5.
• Lewis PA, Knoblich G, Poe G. How Memory Replay in Sleep Boosts Creative Problem-Solving. Trends Cogn Sci. 2018 Jun;22(6):491-503. doi: 10.1016/j.tics.2018.03.009.
• Feld GB, Bernard M, Rawson AB, Spiers HJ. Sleep targets highly connected global and local nodes to aid consolidation of learned graph networks. Sci Rep. 2022 Sep 5;12(1):15086. doi: 10.1038/s41598-022-17747-2.
• McClelland JL, McNaughton BL, O'Reilly RC. Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory. Psychol Rev. 1995 Jul;102(3):419-457. doi: 10.1037/0033-295X.102.3.419.
• Marshall L, Born J. The contribution of sleep to hippocampus-dependent memory consolidation. Trends Cogn Sci. 2007 Oct;11(10):442-50. doi: 10.1016/j.tics.2007.09.001. Epub 2007 Oct 1.
• Davidson TJ, Kloosterman F, Wilson MA. Hippocampal replay of extended experience. Neuron. 2009 Aug 27;63(4):497-507. doi: 10.1016/j.neuron.2009.07.027.
• Schapiro AC, McDevitt EA, Rogers TT, Mednick SC, Norman KA. Human hippocampal replay during rest prioritizes weakly learned information and predicts memory performance. Nat Commun. 2018 Sep 25;9(1):3920. doi: 10.1038/s41467-018-06213-1.
• Cairney SA, Durrant SJ, Hulleman J, Lewis PA. Targeted memory reactivation during slow wave sleep facilitates emotional memory consolidation. Sleep. 2014 Apr 1;37(4):701-7, 707A. doi: 10.5665/sleep.3572.
• Batterink LJ, Paller KA. Sleep-based memory processing facilitates grammatical generalization: Evidence from targeted memory reactivation. Brain Lang. 2017 Apr;167:83-93. doi: 10.1016/j.bandl.2015.09.003. Epub 2015 Oct 9.
• Goldi M, van Poppel EAM, Rasch B, Schreiner T. Increased neuronal signatures of targeted memory reactivation during slow-wave up states. Sci Rep. 2019 Feb 25;9(1):2715. doi: 10.1038/s41598-019-39178-2.
• Ngo HV, Martinetz T, Born J, Molle M. Auditory closed-loop stimulation of the sleep slow oscillation enhances memory. Neuron. 2013 May 8;78(3):545-53. doi: 10.1016/j.neuron.2013.03.006. Epub 2013 Apr 11.
• Ngo HV, Miedema A, Faude I, Martinetz T, Molle M, Born J. Driving sleep slow oscillations by auditory closed-loop stimulation-a self-limiting process. J Neurosci. 2015 Apr 29;35(17):6630-8. doi: 10.1523/JNEUROSCI.3133-14.2015.
• Navarrete M, Schneider J, Ngo HV, Valderrama M, Casson AJ, Lewis PA. Examining the optimal timing for closed-loop auditory stimulation of slow-wave sleep in young and older adults. Sleep. 2020 Jun 15;43(6):zsz315. doi: 10.1093/sleep/zsz315.
• Solomon SH, Medaglia JD, Thompson-Schill SL. Implementing a concept network model. Behav Res Methods. 2019 Aug;51(4):1717-1736. doi: 10.3758/s13428-019-01217-1.
• Collins AM, Loftus EF. A spreading-activation theory of semantic processing. Psychological review. 1975; 82(6): 407.
• De Deyne S, Navarro DJ, Perfors A, Storms G. Structure at every scale: A semantic network account of the similarities between unrelated concepts. J Exp Psychol Gen. 2016 Sep;145(9):1228-54. doi: 10.1037/xge0000192.
• McRae K, de Sa VR, Seidenberg MS. On the nature and scope of featural representations of word meaning. J Exp Psychol Gen. 1997 Jun;126(2):99-130. doi: 10.1037//0096-3445.126.2.99.
• Tyler LK, Moss HE, Durrant-Peatfield MR, Levy JP. Conceptual structure and the structure of concepts: a distributed account of category-specific deficits. Brain Lang. 2000 Nov;75(2):195-231. doi: 10.1006/brln.2000.2353.
• Saffran JR, Johnson EK, Aslin RN, Newport EL. Statistical learning of tone sequences by human infants and adults. Cognition. 1999 Feb 1;70(1):27-52. doi: 10.1016/s0010-0277(98)00075-4.
• Saffran JR. The use of predictive dependencies in language learning. Journal of Memory and Language. 2001; 44(4): 493-515.
• Fiser J, Aslin RN. Statistical learning of new visual feature combinations by infants. Proc Natl Acad Sci U S A. 2002 Nov 26;99(24):15822-6. doi: 10.1073/pnas.232472899. Epub 2002 Nov 12.
• Kirkham NZ, Slemmer JA, Johnson SP. Visual statistical learning in infancy: evidence for a domain general learning mechanism. Cognition. 2002 Mar;83(2):B35-42. doi: 10.1016/s0010-0277(02)00004-5.
• Pearce MT, Ruiz MH, Kapasi S, Wiggins GA, Bhattacharya J. Unsupervised statistical learning underpins computational, behavioural, and neural manifestations of musical expectation. Neuroimage. 2010 Mar;50(1):302-13. doi: 10.1016/j.neuroimage.2009.12.019. Epub 2009 Dec 11.
• Turk-Browne NB, Junge J, Scholl BJ. The automaticity of visual statistical learning. J Exp Psychol Gen. 2005 Nov;134(4):552-64. doi: 10.1037/0096-3445.134.4.552.
• O'Keefe J, Nadel L. The hippocampus as a cognitive map. Oxford university press. 1978.
• Hafting T, Fyhn M, Molden S, Moser MB, Moser EI. Microstructure of a spatial map in the entorhinal cortex. Nature. 2005 Aug 11;436(7052):801-6. doi: 10.1038/nature03721. Epub 2005 Jun 19.
• Javadi AH, Emo B, Howard LR, Zisch FE, Yu Y, Knight R, Pinelo Silva J, Spiers HJ. Hippocampal and prefrontal processing of network topology to simulate the future. Nat Commun. 2017 Mar 21;8:14652. doi: 10.1038/ncomms14652.
• Killian NJ, Buffalo EA. Grid cells map the visual world. Nat Neurosci. 2018 Feb;21(2):161-162. doi: 10.1038/s41593-017-0062-4. No abstract available.
• Stachenfeld KL, Botvinick MM, Gershman SJ. The hippocampus as a predictive map. Nat Neurosci. 2017 Nov;20(11):1643-1653. doi: 10.1038/nn.4650. Epub 2017 Oct 2. Erratum In: Nat Neurosci. 2018 Apr 25;:
• Epstein RA, Patai EZ, Julian JB, Spiers HJ. The cognitive map in humans: spatial navigation and beyond. Nat Neurosci. 2017 Oct 26;20(11):1504-1513. doi: 10.1038/nn.4656.
• Erickson JE, Chin-Parker S, Ross BH. Inference and classification learning of abstract coherent categories. J Exp Psychol Learn Mem Cogn. 2005 Jan;31(1):86-99. doi: 10.1037/0278-7393.31.1.86.
• Park SA, Miller DS, Boorman ED. Inferences on a multidimensional social hierarchy use a grid-like code. Nat Neurosci. 2021 Sep;24(9):1292-1301. doi: 10.1038/s41593-021-00916-3. Epub 2021 Aug 31.
• Tavares RM, Mendelsohn A, Grossman Y, Williams CH, Shapiro M, Trope Y, Schiller D. A Map for Social Navigation in the Human Brain. Neuron. 2015 Jul 1;87(1):231-43. doi: 10.1016/j.neuron.2015.06.011.
• Constantinescu AO, O'Reilly JX, Behrens TEJ. Organizing conceptual knowledge in humans with a gridlike code. Science. 2016 Jun 17;352(6292):1464-1468. doi: 10.1126/science.aaf0941. Epub 2016 Jun 16.
• Hassabis D, Kumaran D, Vann SD, Maguire EA. Patients with hippocampal amnesia cannot imagine new experiences. Proc Natl Acad Sci U S A. 2007 Jan 30;104(5):1726-31. doi: 10.1073/pnas.0610561104. Epub 2007 Jan 17.
• Franklin NT, Frank MJ. Compositional clustering in task structure learning. PLoS Comput Biol. 2018 Apr 19;14(4):e1006116. doi: 10.1371/journal.pcbi.1006116. eCollection 2018 Apr.
• Schuck NW, Cai MB, Wilson RC, Niv Y. Human Orbitofrontal Cortex Represents a Cognitive Map of State Space. Neuron. 2016 Sep 21;91(6):1402-1412. doi: 10.1016/j.neuron.2016.08.019.
• Theves S, Fernandez G, Doeller CF. The Hippocampus Encodes Distances in Multidimensional Feature Space. Curr Biol. 2019 Apr 1;29(7):1226-1231.e3. doi: 10.1016/j.cub.2019.02.035. Epub 2019 Mar 21.
• Hu X, Cheng LY, Chiu MH, Paller KA. Promoting memory consolidation during sleep: A meta-analysis of targeted memory reactivation. Psychol Bull. 2020 Mar;146(3):218-244. doi: 10.1037/bul0000223.
• Yamauchi T, Markman AB. Category learning by inference and classification. Journal of Memory and language. 1998; 39(1): 124-148.
• Anderson AL, Ross BH, Chin-Parker S. A further investigation of category learning by inference. Mem Cognit. 2002 Jan;30(1):119-28. doi: 10.3758/bf03195271.
• Chin-Parker S, Ross BH. The effect of category learning on sensitivity to within-category correlations. Mem Cognit. 2002 Apr;30(3):353-62. doi: 10.3758/bf03194936.
• Chin-Parker S, Ross BH. Diagnosticity and prototypicality in category learning: a comparison of inference learning and classification learning. J Exp Psychol Learn Mem Cogn. 2004 Jan;30(1):216-26. doi: 10.1037/0278-7393.30.1.216.
• Markman AB, Ross BH. Category use and category learning. Psychol Bull. 2003 Jul;129(4):592-613. doi: 10.1037/0033-2909.129.4.592.
• Cousins JN, El-Deredy W, Parkes LM, Hennies N, Lewis PA. Cued Reactivation of Motor Learning during Sleep Leads to Overnight Changes in Functional Brain Activity and Connectivity. PLoS Biol. 2016 May 3;14(5):e1002451. doi: 10.1371/journal.pbio.1002451. eCollection 2016 May.
• Cairney SA, Guttesen AAV, El Marj N, Staresina BP. Memory Consolidation Is Linked to Spindle-Mediated Information Processing during Sleep. Curr Biol. 2018 Mar 19;28(6):948-954.e4. doi: 10.1016/j.cub.2018.01.087. Epub 2018 Mar 8.
• Solomon SH, Schapiro AC. Structure shapes the representation of a novel category. J Exp Psychol Learn Mem Cogn. 2024 Mar;50(3):458-483. doi: 10.1037/xlm0001257. Epub 2023 Jun 15.

Study record dates

Study Major Dates

• Study Start (Actual): March 29, 2023
• Primary Completion (Estimated): June 30, 2024
• Study Completion (Estimated): June 30, 2024

Study Registration Dates

• First Submitted: February 14, 2023
• First Submitted That Met QC Criteria: February 14, 2023
• First Posted (Actual): February 27, 2023

Study Record Updates

• Last Update Posted (Actual): April 19, 2024
• Last Update Submitted That Met QC Criteria: April 17, 2024
• Last Verified: April 1, 2024

More Information

Terms related to this study

• Keywords: memory; sleep; learning
• Other Study ID Numbers: 833228A; 1R21MH128788-01A1 (U.S. NIH Grant/Contract)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: All IPD that underlie results in a publication.
• IPD Sharing Time Frame: IPD will be available at the time of study publication.
• IPD Sharing Access Criteria: IPD will be publicly available without restriction.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No