Recalibration of path integration in hippocampal place cells

Hippocampal place cells are spatially tuned neurons that serve as elements of a ‘cognitive map’ in the mammalian brain 1 . To detect the animal’s location, place cells are thought to rely upon two interacting mechanisms: sensing the position of the animal relative to familiar landmarks 2 , 3 and mea...

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Veröffentlicht in:	Nature (London) Jg. 566; H. 7745; S. 533 - 537
Hauptverfasser:	Jayakumar, Ravikrishnan P., Madhav, Manu S., Savelli, Francesco, Blair, Hugh T., Cowan, Noah J., Knierim, James J.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 01.02.2019 Nature Publishing Group
Schlagworte:	631/378/1595/1554 631/378/1595/3922 631/378/2629/2630 631/601/18 639/166/988 64 Animal models Animal orientation Animal spatial behavior Animals Augmented reality Brain Brain research Cognitive ability Cognitive maps Cognitive models Cues Error correction Feedback, Physiological Grid Cells - cytology Grid Cells - physiology Hippocampus Hippocampus (Brain) Hippocampus - cytology Hippocampus - physiology Humanities and Social Sciences Hypotheses Integration Laboratories Landmarks Letter Male multidisciplinary Neuronal Plasticity - physiology Neurons Place Cells - cytology Place Cells - physiology Position measurement Position sensing Rats Rats, Long-Evans Science Science (multidisciplinary) Spatial Navigation - physiology Spatial Processing - physiology Visual signals
ISSN:	0028-0836, 1476-4687, 1476-4687
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Abstract	Hippocampal place cells are spatially tuned neurons that serve as elements of a ‘cognitive map’ in the mammalian brain 1 . To detect the animal’s location, place cells are thought to rely upon two interacting mechanisms: sensing the position of the animal relative to familiar landmarks 2 , 3 and measuring the distance and direction that the animal has travelled from previously occupied locations 4 – 7 . The latter mechanism—known as path integration—requires a finely tuned gain factor that relates the animal’s self-movement to the updating of position on the internal cognitive map, as well as external landmarks to correct the positional error that accumulates 8 , 9 . Models of hippocampal place cells and entorhinal grid cells based on path integration treat the path-integration gain as a constant 9 – 14 , but behavioural evidence in humans suggests that the gain is modifiable 15 . Here we show, using physiological evidence from rat hippocampal place cells, that the path-integration gain is a highly plastic variable that can be altered by persistent conflict between self-motion cues and feedback from external landmarks. In an augmented-reality system, visual landmarks were moved in proportion to the movement of a rat on a circular track, creating continuous conflict with path integration. Sustained exposure to this cue conflict resulted in predictable and prolonged recalibration of the path-integration gain, as estimated from the place cells after the landmarks were turned off. We propose that this rapid plasticity keeps the positional update in register with the movement of the rat in the external world over behavioural timescales. These results also demonstrate that visual landmarks not only provide a signal to correct cumulative error in the path-integration system 4 , 8 , 16 – 19 , but also rapidly fine-tune the integration computation itself. Evidence from hippocampal place cells shows that path-integration gain, previously thought to be a constant factor in the computation of location, is flexible and can be rapidly fine-tuned.
AbstractList	Hippocampal place cells are spatially tuned neurons that serve as elements of a 'cognitive map' in the mammalian brain.sup.1. To detect the animal's location, place cells are thought to rely upon two interacting mechanisms: sensing the position of the animal relative to familiar landmarks.sup.2,3 and measuring the distance and direction that the animal has travelled from previously occupied locations.sup.4-7. The latter mechanism--known as path integration--requires a finely tuned gain factor that relates the animal's self-movement to the updating of position on the internal cognitive map, as well as external landmarks to correct the positional error that accumulates.sup.8,9. Models of hippocampal place cells and entorhinal grid cells based on path integration treat the path-integration gain as a constant.sup.9-14, but behavioural evidence in humans suggests that the gain is modifiable.sup.15. Here we show, using physiological evidence from rat hippocampal place cells, that the path-integration gain is a highly plastic variable that can be altered by persistent conflict between self-motion cues and feedback from external landmarks. In an augmented-reality system, visual landmarks were moved in proportion to the movement of a rat on a circular track, creating continuous conflict with path integration. Sustained exposure to this cue conflict resulted in predictable and prolonged recalibration of the path-integration gain, as estimated from the place cells after the landmarks were turned off. We propose that this rapid plasticity keeps the positional update in register with the movement of the rat in the external world over behavioural timescales. These results also demonstrate that visual landmarks not only provide a signal to correct cumulative error in the path-integration system.sup.4,8,16-19, but also rapidly fine-tune the integration computation itself. Hippocampal place cells are spatially tuned neurons that serve as elements of a 'cognitive map' in the mammalian brain . To detect the animal's location, place cells are thought to rely upon two interacting mechanisms: sensing the position of the animal relative to familiar landmarks and measuring the distance and direction that the animal has travelled from previously occupied locations . The latter mechanism-known as path integration-requires a finely tuned gain factor that relates the animal's self-movement to the updating of position on the internal cognitive map, as well as external landmarks to correct the positional error that accumulates . Models of hippocampal place cells and entorhinal grid cells based on path integration treat the path-integration gain as a constant , but behavioural evidence in humans suggests that the gain is modifiable . Here we show, using physiological evidence from rat hippocampal place cells, that the path-integration gain is a highly plastic variable that can be altered by persistent conflict between self-motion cues and feedback from external landmarks. In an augmented-reality system, visual landmarks were moved in proportion to the movement of a rat on a circular track, creating continuous conflict with path integration. Sustained exposure to this cue conflict resulted in predictable and prolonged recalibration of the path-integration gain, as estimated from the place cells after the landmarks were turned off. We propose that this rapid plasticity keeps the positional update in register with the movement of the rat in the external world over behavioural timescales. These results also demonstrate that visual landmarks not only provide a signal to correct cumulative error in the path-integration system , but also rapidly fine-tune the integration computation itself. Hippocampal place cells are spatially tuned neurons that serve as elements of a 'cognitive map' in the mammalian brain. To detect the animal's location, place cells are thought to rely upon two interacting mechanisms: sensing the position of the animal relative to familiar landmarks and measuring the distance and direction that the animal has travelled from previously occupied locations. The latter mechanism-known as path integration-requires a finely tuned gain factor that relates the animal's self-movement to the updating of position on the internal cognitive map, as well as external landmarks to correct the positional error that accumulates. Models of hippocampal place cells and entorhinal grid cells based on path integration treat the path-integration gain as a constant, but behavioural evidence in humans suggests that the gain is modifiable. Here we show, using physiological evidence from rat hippocampal place cells, that the path-integration gain is a highly plastic variable that can be altered by persistent conflict between self-motion cues and feedback from external landmarks. In an augmented-reality system, visual landmarks were moved in proportion to the movement of a rat on a circular track, creating continuous conflict with path integration. Sustained exposure to this cue conflict resulted in predictable and prolonged recalibration of the path-integration gain, as estimated from the place cells after the landmarks were turned off. We propose that this rapid plasticity keeps the positional update in register with the movement of the rat in the external world over behavioural timescales. These results also demonstrate that visual landmarks not only provide a signal to correct cumulative error in the path-integration system, but also rapidly fine-tune the integration computation itself. Hippocampal place cells are spatially tuned neurons that serve as elements of a 'cognitive map' in the mammalian brain1. To detect the animal's location, place cells are thought to rely upon two interacting mechanisms: sensing the position of the animal relative to familiar landmarks2,3 and measuring the distance and direction that the animal has travelled from previously occupied locations4-7. The latter mechanism-known as path integration-requires a finely tuned gain factor that relates the animal's self-movement to the updating of position on the internal cognitive map, as well as external landmarks to correct the positional error that accumulates8,9. Models of hippocampal place cells and entorhinal grid cells based on path integration treat the path-integration gain as a constant9-14, but behavioural evidence in humans suggests that the gain is modifiable15. Here we show, using physiological evidence from rat hippocampal place cells, that the path-integration gain is a highly plastic variable that can be altered by persistent conflict between self-motion cues and feedback from external landmarks. In an augmented-reality system, visual landmarks were moved in proportion to the movement of a rat on a circular track, creating continuous conflict with path integration. Sustained exposure to this cue conflict resulted in predictable and prolonged recalibration of the path-integration gain, as estimated from the place cells after the landmarks were turned off. We propose that this rapid plasticity keeps the positional update in register with the movement of the rat in the external world over behavioural timescales. These results also demonstrate that visual landmarks not only provide a signal to correct cumulative error in the path-integration system4,8,16-19, but also rapidly fine-tune the integration computation itself.Hippocampal place cells are spatially tuned neurons that serve as elements of a 'cognitive map' in the mammalian brain1. To detect the animal's location, place cells are thought to rely upon two interacting mechanisms: sensing the position of the animal relative to familiar landmarks2,3 and measuring the distance and direction that the animal has travelled from previously occupied locations4-7. The latter mechanism-known as path integration-requires a finely tuned gain factor that relates the animal's self-movement to the updating of position on the internal cognitive map, as well as external landmarks to correct the positional error that accumulates8,9. Models of hippocampal place cells and entorhinal grid cells based on path integration treat the path-integration gain as a constant9-14, but behavioural evidence in humans suggests that the gain is modifiable15. Here we show, using physiological evidence from rat hippocampal place cells, that the path-integration gain is a highly plastic variable that can be altered by persistent conflict between self-motion cues and feedback from external landmarks. In an augmented-reality system, visual landmarks were moved in proportion to the movement of a rat on a circular track, creating continuous conflict with path integration. Sustained exposure to this cue conflict resulted in predictable and prolonged recalibration of the path-integration gain, as estimated from the place cells after the landmarks were turned off. We propose that this rapid plasticity keeps the positional update in register with the movement of the rat in the external world over behavioural timescales. These results also demonstrate that visual landmarks not only provide a signal to correct cumulative error in the path-integration system4,8,16-19, but also rapidly fine-tune the integration computation itself. Hippocampal place cells are spatially tuned neurons that serve as elements of a “cognitive map” in the mammalian brain1. To detect the animal’s location, place cells are thought to rely upon two interacting mechanisms: sensing the animal’s position relative to familiar landmarks2,3 and measuring the distance and direction that the animal has traveled from previously occupied locations4–7. The latter mechanism, known as path integration, requires a finely tuned gain factor that relates the animal’s self-movement to the updating of position on the internal cognitive map, with external landmarks necessary to correct positional error that accumulates8,9. Path-integration-based models of hippocampal place cells and entorhinal grid cells treat the path integration gain as a constant9–14, but behavioral evidence in humans suggests that the gain is modifiable15. Here we show physiological evidence from hippocampal place cells that the path integration gain is indeed a highly plastic variable that can be altered by persistent conflict between self-motion cues and feedback from external landmarks. In a novel, augmented reality system, visual landmarks were moved in proportion to the animal’s movement on a circular track, creating continuous conflict with path integration. Sustained exposure to this cue conflict resulted in predictable and prolonged recalibration of the path integration gain, as estimated from the place cells after the landmarks were extinguished. We propose that this rapid plasticity keeps the positional update in register with the animal’s movement in the external world over behavioral timescales. These results also demonstrate that visual landmarks not only provide a signal to correct cumulative error in the path integration system4,8,16–19, but also rapidly fine-tune the integration computation itself. Hippocampal place cells are spatially tuned neurons that serve as elements of a ‘cognitive map’ in the mammalian brain 1 . To detect the animal’s location, place cells are thought to rely upon two interacting mechanisms: sensing the position of the animal relative to familiar landmarks 2 , 3 and measuring the distance and direction that the animal has travelled from previously occupied locations 4 – 7 . The latter mechanism—known as path integration—requires a finely tuned gain factor that relates the animal’s self-movement to the updating of position on the internal cognitive map, as well as external landmarks to correct the positional error that accumulates 8 , 9 . Models of hippocampal place cells and entorhinal grid cells based on path integration treat the path-integration gain as a constant 9 – 14 , but behavioural evidence in humans suggests that the gain is modifiable 15 . Here we show, using physiological evidence from rat hippocampal place cells, that the path-integration gain is a highly plastic variable that can be altered by persistent conflict between self-motion cues and feedback from external landmarks. In an augmented-reality system, visual landmarks were moved in proportion to the movement of a rat on a circular track, creating continuous conflict with path integration. Sustained exposure to this cue conflict resulted in predictable and prolonged recalibration of the path-integration gain, as estimated from the place cells after the landmarks were turned off. We propose that this rapid plasticity keeps the positional update in register with the movement of the rat in the external world over behavioural timescales. These results also demonstrate that visual landmarks not only provide a signal to correct cumulative error in the path-integration system 4 , 8 , 16 – 19 , but also rapidly fine-tune the integration computation itself. Evidence from hippocampal place cells shows that path-integration gain, previously thought to be a constant factor in the computation of location, is flexible and can be rapidly fine-tuned. Hippocampal place cells are spatially tuned neurons that serve as elements of a 'cognitive map' in the mammalian brain.sup.1. To detect the animal's location, place cells are thought to rely upon two interacting mechanisms: sensing the position of the animal relative to familiar landmarks.sup.2,3 and measuring the distance and direction that the animal has travelled from previously occupied locations.sup.4-7. The latter mechanism--known as path integration--requires a finely tuned gain factor that relates the animal's self-movement to the updating of position on the internal cognitive map, as well as external landmarks to correct the positional error that accumulates.sup.8,9. Models of hippocampal place cells and entorhinal grid cells based on path integration treat the path-integration gain as a constant.sup.9-14, but behavioural evidence in humans suggests that the gain is modifiable.sup.15. Here we show, using physiological evidence from rat hippocampal place cells, that the path-integration gain is a highly plastic variable that can be altered by persistent conflict between self-motion cues and feedback from external landmarks. In an augmented-reality system, visual landmarks were moved in proportion to the movement of a rat on a circular track, creating continuous conflict with path integration. Sustained exposure to this cue conflict resulted in predictable and prolonged recalibration of the path-integration gain, as estimated from the place cells after the landmarks were turned off. We propose that this rapid plasticity keeps the positional update in register with the movement of the rat in the external world over behavioural timescales. These results also demonstrate that visual landmarks not only provide a signal to correct cumulative error in the path-integration system.sup.4,8,16-19, but also rapidly fine-tune the integration computation itself. Evidence from hippocampal place cells shows that path-integration gain, previously thought to be a constant factor in the computation of location, is flexible and can be rapidly fine-tuned.
Audience	Academic
Author	Knierim, James J. Madhav, Manu S. Blair, Hugh T. Jayakumar, Ravikrishnan P. Savelli, Francesco Cowan, Noah J.
AuthorAffiliation	3 Department of Psychology, UCLA, Los Angeles, CA 4 Solomon H. Snyder Department of Neuroscience, Johns Hopkins University, Baltimore, MD 1 Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 2 Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, MD
AuthorAffiliation_xml	– name: 3 Department of Psychology, UCLA, Los Angeles, CA – name: 4 Solomon H. Snyder Department of Neuroscience, Johns Hopkins University, Baltimore, MD – name: 2 Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, MD – name: 1 Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD
Author_xml	– sequence: 1 givenname: Ravikrishnan P. surname: Jayakumar fullname: Jayakumar, Ravikrishnan P. organization: Department of Mechanical Engineering, Johns Hopkins University – sequence: 2 givenname: Manu S. surname: Madhav fullname: Madhav, Manu S. email: manusmad@gmail.com organization: Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University – sequence: 3 givenname: Francesco surname: Savelli fullname: Savelli, Francesco organization: Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University – sequence: 4 givenname: Hugh T. surname: Blair fullname: Blair, Hugh T. organization: Department of Psychology, UCLA – sequence: 5 givenname: Noah J. surname: Cowan fullname: Cowan, Noah J. organization: Department of Mechanical Engineering, Johns Hopkins University, Laboratory for Computational Sensing and Robotics, Johns Hopkins University – sequence: 6 givenname: James J. surname: Knierim fullname: Knierim, James J. organization: Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Solomon H. Snyder Department of Neuroscience, Johns Hopkins University
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Copyright	The Author(s), under exclusive licence to Springer Nature Limited 2019 COPYRIGHT 2019 Nature Publishing Group Copyright Nature Publishing Group Feb 28, 2019
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Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Author Contributions. J.J.K., N.J.C., and H.T.B. conceived and all authors designed the study. J.J.K. and N.J.C. advised on all aspects of the experiments and analysis. F.S. made key contributions to the analysis and interpretation of the data and provided supervision over data acquisition and analysis. R.P.J. and M.S.M. designed and constructed the apparatus, performed experiments, and analyzed the data. R.P.J., M.S.M., N.J.C., and J.J.K. wrote the paper and F.S. and H.T.B. provided critical feedback. The primary and senior authors contributed equally
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Publisher	Nature Publishing Group UK Nature Publishing Group
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References	MaurerAPVanRhoadsSRSutherlandGRLipaPMcNaughtonBLSelf-motion and the origin of differential spatial scaling along the septo-temporal axis of the hippocampusHippocampus20051584185210.1002/hipo.20114 WittlingerMWehnerRWolfHThe ant odometer: Stepping on stilts and stumpsScience2006312196519672006Sci...312.1965W1:CAS:528:DC%2BD28XmsVahu7Y%3D10.1126/science.1126912 BastianAJLearning to predict the future: the cerebellum adapts feedforward movement controlCurr. Opin. Neurobiol.2006166456491:CAS:528:DC%2BD28Xht1Cls7vN10.1016/j.conb.2006.08.016 BurgessNBarryCO’KeefeJAn oscillatory interference model of grid cell firingHippocampus20071780181210.1002/hipo.20327 TcheangLBulthoffHHBurgessNVisual influence on path integration in darkness indicates a multimodal representation of large-scale spaceProc. Natl Acad. Sci. USA2011108115211572011PNAS..108.1152T1:CAS:528:DC%2BC3MXhtlWqsLo%3D10.1073/pnas.1011843108 Flandrin, P., Francois, A. & Chassande-Mottin, E. in Applications in Time-Frequency Signal Processing (ed. Papandreou-Suppappola, A.) 179–204 (CRC Press, Boca Raton, 2002). KloostermanFLaytonSPChenZWilsonMABayesian decoding using unsorted spikes in the rat hippocampusJ. Neurophysiol.201411121722710.1152/jn.01046.2012 GallistelCRLearning, development, and conceptual change. The organization of learning1990Cambridge, MAMIT Press HardcastleKGanguliSGiocomoLMEnvironmental boundaries as an error correction mechanism for grid cellsNeuron2015868278391:CAS:528:DC%2BC2MXms1ynsLo%3D10.1016/j.neuron.2015.03.039 KnierimJJKudrimotiHSMcNaughtonBLInteractions between idiothetic cues and external landmarks in the control of place cells and head direction cellsJ. Neurophysiol.1998804254461:STN:280:DyaK1czisFWgsQ%3D%3D10.1152/jn.1998.80.1.425 RavassardPMultisensory control of hippocampal spatiotemporal selectivityScience2013340134213462013Sci...340.1342R1:CAS:528:DC%2BC3sXptFKjsL4%3D10.1126/science.1232655 ChenGKingJABurgessNO’KeefeJHow vision and movement combine in the hippocampal place codeProc. Natl Acad. Sci. USA20131103783832013PNAS..110..378C1:CAS:528:DC%2BC3sXnsFeiuw%3D%3D10.1073/pnas.1215834110 Skaggs, W. E., McNaughton, B. L., Gothard, K. M. & Markus, E. J. in Advances in Neural Information Processing Systems5 (eds. Hanson, S. J., Cowan, J. D. & Giles, C. L.) 1030–1037 (NIPS, 1992). KropffECarmichaelJEMoserM-BMoserEISpeed cells in the medial entorhinal cortexNature20155234194242015Natur.523..419K1:CAS:528:DC%2BC2MXhtFyltLrK10.1038/nature14622 CullenKETaubeJSOur sense of direction: Progress, controversies and challengesNat. 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HarveyCDCollmanFDombeckDATankDWIntracellular dynamics of hippocampal place cells during virtual navigationNature20094619419462009Natur.461..941H1:CAS:528:DC%2BD1MXhtlCqs73J10.1038/nature08499 AcharyaLCausal influence of visual cues on hippocampal article causal influence of visual cues on hippocampal directional selectivityCell20161641972071:CAS:528:DC%2BC2MXitVKjt7rF10.1016/j.cell.2015.12.015 WehnerRMenzelRDo insects have cognitive maps?Annu. Rev. Neurosci.1990134034141:STN:280:DyaK3c3isFKiug%3D%3D10.1146/annurev.ne.13.030190.002155 BrownENFrankLMTangDQuirkMC& Wilson, M. a. A statistical paradigm for neural spike train decoding applied to position prediction from ensemble firing patterns of rat hippocampal place cellsJ. Neurosci.199818741174251:CAS:528:DyaK1cXmt1Sjtbk%3D10.1523/JNEUROSCI.18-18-07411.1998 MoserEIMoserM-BMcNaughtonBLSpatial representation in the hippocampal formation: a historyNat. Neurosci.201720144814641:CAS:528:DC%2BC2sXhslansbzO10.1038/nn.4653 HinmanJRBrandonMPClimerJRChapmanGWHasselmoMEMultiple running speed signals in medial entorhinal cortexNeuron2016916666791:CAS:528:DC%2BC28XhtFOlt7zL10.1016/j.neuron.2016.06.027 TennantSAStellate cells in the medial entorhinal cortex are required for spatial learningCell Rep.201822131313241:CAS:528:DC%2BC1cXitVahsL8%3D10.1016/j.celrep.2018.01.005 MittelstaedtMLMittelstaedtHHoming by path integration in a mammalNaturwissenschaften1980675665671980NW.....67..566M10.1007/BF00450672 ZugaroMBArleoABerthozAWienerSIRapid spatial reorientation and head direction cellsJ. Neurosci.200323347834821:CAS:528:DC%2BD3sXjsFSktL0%3D10.1523/JNEUROSCI.23-08-03478.2003 GilMImpaired path integration in mice with disrupted grid cell firingNat. Neurosci.20182181931:CAS:528:DC%2BC1cXltVyiurw%3D10.1038/s41593-017-0039-3 EtienneASJefferyKJPath integration in mammalsHippocampus20041418019210.1002/hipo.10173 FuhsMCTouretzkyDSA spin glass model of path integration in rat medial entorhinal cortexJ. Neurosci.200626426642761:CAS:528:DC%2BD28XktlCltbY%3D10.1523/JNEUROSCI.4353-05.2006 McNaughtonBLBattagliaFPJensenOMoserEIMoserMBPath integration and the neural basis of the ‘cognitive map’Nat. Rev. Neurosci.200676636781:CAS:528:DC%2BD28XntFCgsbs%3D10.1038/nrn1932 BlairHTGuptaKZhangKConversion of a phase- to a rate-coded position signal by a three-stage model of theta cells, grid cells, and place cellsHippocampus2008181239125510.1002/hipo.20509 O’Keefe, J. & Nadel, L. The Hippocampus as a Cognitive Map (Oxford Univ. Press, Oxford, 1978). TerrazasASelf-motion and the hippocampal spatial metricJ. Neurosci.200525808580961:CAS:528:DC%2BD2MXhtVakt77L10.1523/JNEUROSCI.0693-05.2005 MilesFALisbergerSGPlasticity in the vestibulo-ocular reflex: a new hypothesisAnnu. Rev. Neurosci.198142732991:STN:280:DyaL3M7ot1OhtQ%3D%3D10.1146/annurev.ne.04.030181.001421 HölscherCSchneeADahmenHSetiaLMallotHARats are able to navigate in virtual environmentsJ. Exp. Biol.200520856156910.1242/jeb.01371 ZhangKGinzburgIMcNaughtonBLSejnowskiTJInterpreting neuronal population activity by reconstruction: unified framework with application to hippocampal place cellsJ. Neurophysiol.199879101710441:STN:280:DyaK1c7jtVKksA%3D%3D10.1152/jn.1998.79.2.1017 EtienneASMaurerRSéguinotVPath integration in mammals and its interaction with visual landmarksJ. Exp. Biol.19961992012091:STN:280:DyaK287kslGlug%3D%3D8576691 AP Maurer (939_CR29) 2005; 15 J Csicsvari (939_CR34) 1999; 19 MC Fuhs (939_CR10) 2006; 26 EN Brown (939_CR38) 1998; 18 M Wittlinger (939_CR6) 2006; 312 A Samsonovich (939_CR9) 1997; 17 AS Etienne (939_CR19) 1996; 199 KE Cullen (939_CR30) 2017; 20 ML Mittelstaedt (939_CR7) 1980; 67 SA Tennant (939_CR22) 2018; 22 CD Harvey (939_CR24) 2009; 461 AJ Bastian (939_CR26) 2006; 16 939_CR40 AS Etienne (939_CR4) 2004; 14 K Zhang (939_CR36) 1998; 79 939_CR1 M Gil (939_CR21) 2018; 21 P Ravassard (939_CR25) 2013; 340 G Chen (939_CR3) 2013; 110 BL McNaughton (939_CR11) 2006; 7 E Kropff (939_CR31) 2015; 523 K Hardcastle (939_CR18) 2015; 86 R Wehner (939_CR5) 1990; 13 L Acharya (939_CR2) 2016; 164 L Tcheang (939_CR15) 2011; 108 EI Moser (939_CR20) 2017; 20 C Hölscher (939_CR23) 2005; 208 FA Miles (939_CR27) 1981; 4 JR Hinman (939_CR32) 2016; 91 939_CR39 HT Blair (939_CR13) 2008; 18 939_CR35 F Kloosterman (939_CR37) 2014; 111 MB Zugaro (939_CR17) 2003; 23 939_CR33 N Burgess (939_CR14) 2007; 17 CR Gallistel (939_CR8) 1990 JJ Knierim (939_CR16) 1998; 80 ME Hasselmo (939_CR12) 2007; 17 A Terrazas (939_CR28) 2005; 25
References_xml	– reference: WehnerRMenzelRDo insects have cognitive maps?Annu. Rev. Neurosci.1990134034141:STN:280:DyaK3c3isFKiug%3D%3D10.1146/annurev.ne.13.030190.002155 – reference: WittlingerMWehnerRWolfHThe ant odometer: Stepping on stilts and stumpsScience2006312196519672006Sci...312.1965W1:CAS:528:DC%2BD28XmsVahu7Y%3D10.1126/science.1126912 – reference: HarveyCDCollmanFDombeckDATankDWIntracellular dynamics of hippocampal place cells during virtual navigationNature20094619419462009Natur.461..941H1:CAS:528:DC%2BD1MXhtlCqs73J10.1038/nature08499 – reference: TcheangLBulthoffHHBurgessNVisual influence on path integration in darkness indicates a multimodal representation of large-scale spaceProc. Natl Acad. Sci. USA2011108115211572011PNAS..108.1152T1:CAS:528:DC%2BC3MXhtlWqsLo%3D10.1073/pnas.1011843108 – reference: EtienneASMaurerRSéguinotVPath integration in mammals and its interaction with visual landmarksJ. Exp. Biol.19961992012091:STN:280:DyaK287kslGlug%3D%3D8576691 – reference: RavassardPMultisensory control of hippocampal spatiotemporal selectivityScience2013340134213462013Sci...340.1342R1:CAS:528:DC%2BC3sXptFKjsL4%3D10.1126/science.1232655 – reference: MaurerAPVanRhoadsSRSutherlandGRLipaPMcNaughtonBLSelf-motion and the origin of differential spatial scaling along the septo-temporal axis of the hippocampusHippocampus20051584185210.1002/hipo.20114 – reference: KropffECarmichaelJEMoserM-BMoserEISpeed cells in the medial entorhinal cortexNature20155234194242015Natur.523..419K1:CAS:528:DC%2BC2MXhtFyltLrK10.1038/nature14622 – reference: KloostermanFLaytonSPChenZWilsonMABayesian decoding using unsorted spikes in the rat hippocampusJ. Neurophysiol.201411121722710.1152/jn.01046.2012 – reference: SamsonovichAMcNaughtonBPath integration and cognitive mapping in a continuous attractor neural network modelJ. Neurosci.199717590059201:CAS:528:DyaK2sXkvFymsr8%3D10.1523/JNEUROSCI.17-15-05900.1997 – reference: MilesFALisbergerSGPlasticity in the vestibulo-ocular reflex: a new hypothesisAnnu. Rev. Neurosci.198142732991:STN:280:DyaL3M7ot1OhtQ%3D%3D10.1146/annurev.ne.04.030181.001421 – reference: ChenGKingJABurgessNO’KeefeJHow vision and movement combine in the hippocampal place codeProc. Natl Acad. Sci. USA20131103783832013PNAS..110..378C1:CAS:528:DC%2BC3sXnsFeiuw%3D%3D10.1073/pnas.1215834110 – reference: BastianAJLearning to predict the future: the cerebellum adapts feedforward movement controlCurr. Opin. Neurobiol.2006166456491:CAS:528:DC%2BD28Xht1Cls7vN10.1016/j.conb.2006.08.016 – reference: Quigley, M. et al. ROS: an open-source Robot Operating System. In ICRA Workshop on Open Source Software (IEEE, 2009). – reference: EtienneASJefferyKJPath integration in mammalsHippocampus20041418019210.1002/hipo.10173 – reference: HölscherCSchneeADahmenHSetiaLMallotHARats are able to navigate in virtual environmentsJ. Exp. Biol.200520856156910.1242/jeb.01371 – reference: AcharyaLCausal influence of visual cues on hippocampal article causal influence of visual cues on hippocampal directional selectivityCell20161641972071:CAS:528:DC%2BC2MXitVKjt7rF10.1016/j.cell.2015.12.015 – reference: Flandrin, P., Francois, A. & Chassande-Mottin, E. in Applications in Time-Frequency Signal Processing (ed. Papandreou-Suppappola, A.) 179–204 (CRC Press, Boca Raton, 2002). – reference: O’Keefe, J. & Nadel, L. The Hippocampus as a Cognitive Map (Oxford Univ. Press, Oxford, 1978). – reference: BurgessNBarryCO’KeefeJAn oscillatory interference model of grid cell firingHippocampus20071780181210.1002/hipo.20327 – reference: GilMImpaired path integration in mice with disrupted grid cell firingNat. Neurosci.20182181931:CAS:528:DC%2BC1cXltVyiurw%3D10.1038/s41593-017-0039-3 – reference: BlairHTGuptaKZhangKConversion of a phase- to a rate-coded position signal by a three-stage model of theta cells, grid cells, and place cellsHippocampus2008181239125510.1002/hipo.20509 – reference: Campbell, M. G. et al. Principles governing the integration of landmark and self-motion cues in entorhinal cortical codes for navigation. Nat. Neurosci. 21, 1096–1106 (2018). – reference: HasselmoMEGiocomoLMZilliEAGrid cell firing may arise from interference of theta frequency membrane potential oscillations in single neuronsHippocampus2007171252127110.1002/hipo.20374 – reference: ZugaroMBArleoABerthozAWienerSIRapid spatial reorientation and head direction cellsJ. Neurosci.200323347834821:CAS:528:DC%2BD3sXjsFSktL0%3D10.1523/JNEUROSCI.23-08-03478.2003 – reference: HardcastleKGanguliSGiocomoLMEnvironmental boundaries as an error correction mechanism for grid cellsNeuron2015868278391:CAS:528:DC%2BC2MXms1ynsLo%3D10.1016/j.neuron.2015.03.039 – reference: HinmanJRBrandonMPClimerJRChapmanGWHasselmoMEMultiple running speed signals in medial entorhinal cortexNeuron2016916666791:CAS:528:DC%2BC28XhtFOlt7zL10.1016/j.neuron.2016.06.027 – reference: TerrazasASelf-motion and the hippocampal spatial metricJ. Neurosci.200525808580961:CAS:528:DC%2BD2MXhtVakt77L10.1523/JNEUROSCI.0693-05.2005 – reference: ZhangKGinzburgIMcNaughtonBLSejnowskiTJInterpreting neuronal population activity by reconstruction: unified framework with application to hippocampal place cellsJ. Neurophysiol.199879101710441:STN:280:DyaK1c7jtVKksA%3D%3D10.1152/jn.1998.79.2.1017 – reference: FuhsMCTouretzkyDSA spin glass model of path integration in rat medial entorhinal cortexJ. Neurosci.200626426642761:CAS:528:DC%2BD28XktlCltbY%3D10.1523/JNEUROSCI.4353-05.2006 – reference: Skaggs, W. E., McNaughton, B. L., Gothard, K. M. & Markus, E. J. in Advances in Neural Information Processing Systems5 (eds. Hanson, S. J., Cowan, J. D. & Giles, C. L.) 1030–1037 (NIPS, 1992). – reference: BrownENFrankLMTangDQuirkMC& Wilson, M. a. A statistical paradigm for neural spike train decoding applied to position prediction from ensemble firing patterns of rat hippocampal place cellsJ. Neurosci.199818741174251:CAS:528:DyaK1cXmt1Sjtbk%3D10.1523/JNEUROSCI.18-18-07411.1998 – reference: MoserEIMoserM-BMcNaughtonBLSpatial representation in the hippocampal formation: a historyNat. Neurosci.201720144814641:CAS:528:DC%2BC2sXhslansbzO10.1038/nn.4653 – reference: KnierimJJKudrimotiHSMcNaughtonBLInteractions between idiothetic cues and external landmarks in the control of place cells and head direction cellsJ. 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Snippet	Hippocampal place cells are spatially tuned neurons that serve as elements of a ‘cognitive map’ in the mammalian brain 1 . To detect the animal’s location,... Hippocampal place cells are spatially tuned neurons that serve as elements of a 'cognitive map' in the mammalian brain . To detect the animal's location, place... Hippocampal place cells are spatially tuned neurons that serve as elements of a 'cognitive map' in the mammalian brain.sup.1. To detect the animal's location,... Hippocampal place cells are spatially tuned neurons that serve as elements of a 'cognitive map' in the mammalian brain. To detect the animal's location, place... Hippocampal place cells are spatially tuned neurons that serve as elements of a 'cognitive map' in the mammalian brain1. To detect the animal's location, place... Hippocampal place cells are spatially tuned neurons that serve as elements of a “cognitive map” in the mammalian brain1. To detect the animal’s location, place...
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SubjectTerms	631/378/1595/1554 631/378/1595/3922 631/378/2629/2630 631/601/18 639/166/988 64 Animal models Animal orientation Animal spatial behavior Animals Augmented reality Brain Brain research Cognitive ability Cognitive maps Cognitive models Cues Error correction Feedback, Physiological Grid Cells - cytology Grid Cells - physiology Hippocampus Hippocampus (Brain) Hippocampus - cytology Hippocampus - physiology Humanities and Social Sciences Hypotheses Integration Laboratories Landmarks Letter Male multidisciplinary Neuronal Plasticity - physiology Neurons Place Cells - cytology Place Cells - physiology Position measurement Position sensing Rats Rats, Long-Evans Science Science (multidisciplinary) Spatial Navigation - physiology Spatial Processing - physiology Visual signals
Title	Recalibration of path integration in hippocampal place cells
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