001     157760
005     20230915092354.0
024 7 _ |a 10.1523/JNEUROSCI.0528-20.2021
|2 doi
024 7 _ |a pmid:33648956
|2 pmid
024 7 _ |a pmc:PMC8026345
|2 pmc
024 7 _ |a 0270-6474
|2 ISSN
024 7 _ |a 1529-2401
|2 ISSN
024 7 _ |a altmetric:101081675
|2 altmetric
037 _ _ |a DZNE-2021-01217
041 _ _ |a English
082 _ _ |a 610
100 1 _ |a Diersch, Nadine
|0 P:(DE-2719)2811077
|b 0
|e First author
|u dzne
245 _ _ |a Increased Hippocampal Excitability and Altered Learning Dynamics Mediate Cognitive Mapping Deficits in Human Aging.
260 _ _ |a Washington, DC
|c 2021
|b Soc.
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1632299114_31140
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
500 _ _ |a ISSN 1529-2401 not unique: **2 hits**.
520 _ _ |a Learning the spatial layout of a novel environment is associated with dynamic activity changes in the hippocampus and in medial parietal areas. With advancing age, the ability to learn spatial environments deteriorates substantially but the underlying neural mechanisms are not well understood. Here, we report findings from a behavioral and a fMRI experiment where healthy human older and younger adults of either sex performed a spatial learning task in a photorealistic virtual environment (VE). We modeled individual learning states using a Bayesian state-space model and found that activity in retrosplenial cortex (RSC)/parieto-occipital sulcus (POS) and anterior hippocampus did not change systematically as a function learning in older compared with younger adults across repeated episodes in the environment. Moreover, effective connectivity analyses revealed that the age-related learning deficits were linked to an increase in hippocampal excitability. Together, these results provide novel insights into how human aging affects computations in the brain's navigation system, highlighting the critical role of the hippocampus.SIGNIFICANCE STATEMENT Key structures of the brain's navigation circuit are particularly vulnerable to the deleterious consequences of aging, and declines in spatial navigation are among the earliest indicators for a progression from healthy aging to neurodegenerative diseases. Our study is among the first to provide a mechanistic account about how physiological changes in the aging brain affect the formation of spatial knowledge. We show that neural activity in the aging hippocampus and medial parietal areas is decoupled from individual learning states across repeated episodes in a novel spatial environment. Importantly, we find that increased excitability of the anterior hippocampus might constitute a potential neural mechanism for cognitive mapping deficits in old age.
536 _ _ |a 353 - Clinical and Health Care Research (POF4-353)
|0 G:(DE-HGF)POF4-353
|c POF4-353
|f POF IV
|x 0
542 _ _ |i 2021-10-07
|2 Crossref
|u https://creativecommons.org/licenses/by-nc-sa/4.0/
588 _ _ |a Dataset connected to CrossRef, PubMed, , Journals: pub.dzne.de
650 _ 7 |a aging
|2 Other
650 _ 7 |a fMRI
|2 Other
650 _ 7 |a learning
|2 Other
650 _ 7 |a memory
|2 Other
650 _ 7 |a spatial navigation
|2 Other
650 _ 7 |a virtual reality
|2 Other
650 _ 2 |a Adult
|2 MeSH
650 _ 2 |a Aged
|2 MeSH
650 _ 2 |a Aging: physiology
|2 MeSH
650 _ 2 |a Aging: psychology
|2 MeSH
650 _ 2 |a Brain Mapping: methods
|2 MeSH
650 _ 2 |a Cognition: physiology
|2 MeSH
650 _ 2 |a Female
|2 MeSH
650 _ 2 |a Hippocampus: diagnostic imaging
|2 MeSH
650 _ 2 |a Hippocampus: physiology
|2 MeSH
650 _ 2 |a Humans
|2 MeSH
650 _ 2 |a Magnetic Resonance Imaging: methods
|2 MeSH
650 _ 2 |a Male
|2 MeSH
650 _ 2 |a Middle Aged
|2 MeSH
650 _ 2 |a Parietal Lobe: diagnostic imaging
|2 MeSH
650 _ 2 |a Parietal Lobe: physiology
|2 MeSH
650 _ 2 |a Psychomotor Performance: physiology
|2 MeSH
650 _ 2 |a Spatial Learning: physiology
|2 MeSH
650 _ 2 |a Spatial Navigation: physiology
|2 MeSH
650 _ 2 |a Virtual Reality
|2 MeSH
650 _ 2 |a Young Adult
|2 MeSH
700 1 _ |a Valdes Herrera, Jose Pedro
|0 P:(DE-2719)2811107
|b 1
|u dzne
700 1 _ |a Tempelmann, Claus
|b 2
700 1 _ |a Wolbers, Thomas
|0 P:(DE-2719)2810583
|b 3
|e Last author
|u dzne
773 1 8 |a 10.1523/jneurosci.0528-20.2021
|b Society for Neuroscience
|d 2021-03-01
|n 14
|p 3204-3221
|3 journal-article
|2 Crossref
|t The Journal of Neuroscience
|v 41
|y 2021
|x 0270-6474
773 _ _ |a 10.1523/JNEUROSCI.0528-20.2021
|g Vol. 41, no. 14, p. 3204 - 3221
|0 PERI:(DE-600)1475274-8
|n 14
|p 3204-3221
|t The journal of neuroscience
|v 41
|y 2021
|x 0270-6474
909 C O |o oai:pub.dzne.de:157760
|p VDB
910 1 _ |a Deutsches Zentrum für Neurodegenerative Erkrankungen
|0 I:(DE-588)1065079516
|k DZNE
|b 0
|6 P:(DE-2719)2811077
910 1 _ |a Deutsches Zentrum für Neurodegenerative Erkrankungen
|0 I:(DE-588)1065079516
|k DZNE
|b 1
|6 P:(DE-2719)2811107
910 1 _ |a Deutsches Zentrum für Neurodegenerative Erkrankungen
|0 I:(DE-588)1065079516
|k DZNE
|b 3
|6 P:(DE-2719)2810583
913 1 _ |a DE-HGF
|b Gesundheit
|l Neurodegenerative Diseases
|1 G:(DE-HGF)POF4-350
|0 G:(DE-HGF)POF4-353
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-300
|4 G:(DE-HGF)POF
|v Clinical and Health Care Research
|x 0
914 1 _ |y 2021
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2021-01-30
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1190
|2 StatID
|b Biological Abstracts
|d 2021-01-30
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2021-01-30
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2022-11-13
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2022-11-13
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2022-11-13
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2022-11-13
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
|d 2022-11-13
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1030
|2 StatID
|b Current Contents - Life Sciences
|d 2022-11-13
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b J NEUROSCI : 2021
|d 2022-11-13
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
|d 2022-11-13
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
|d 2022-11-13
915 _ _ |a IF >= 5
|0 StatID:(DE-HGF)9905
|2 StatID
|b J NEUROSCI : 2021
|d 2022-11-13
920 1 _ |0 I:(DE-2719)1310002
|k AG Wolbers
|l Aging & Cognition
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-2719)1310002
980 _ _ |a UNRESTRICTED
999 C 5 |a 10.7554/eLife.09031
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.nicl.2015.02.009
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1038/40859
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.neuroimage.2007.04.042
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.18637/jss.v031.i10
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1002/alz.12088
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1093/brain/awv236
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |1 Brett
|y 2002
|2 Crossref
|o Brett 2002
999 C 5 |a 10.1073/pnas.1605719113
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.neuroimage.2014.11.009
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.18637/jss.v076.i01
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.cub.2014.11.001
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |2 Crossref
|u Commandeur J , Koopman SJ (2007) Introduction to state space time series analysis. Oxford: Oxford University Press.
999 C 5 |a 10.1006/nimg.1998.0395
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.neuroimage.2012.04.061
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.neuroimage.2010.06.010
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1242/jeb.187252
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.neurobiolaging.2018.06.013
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.tics.2008.07.004
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1038/nn.4656
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1371/journal.pone.0184661
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1038/s41592-018-0235-4
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.3758/BRM.41.4.1149
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/S0896-6273(02)00569-X
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1006/nimg.1998.0396
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.neuroimage.2015.11.015
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.neuroimage.2017.02.045
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1201/b10905-7
|9 -- missing cx lookup --
|2 Crossref
|u Gelman A , Shirley K (2011) Inference from simulations and monitoring convergence. In: Handbook of Markov Chain Monte Carlo ( Brooks S , Gelman A , Jones GL , Meng XL , eds), pp 163–174. Boca Raton: Chapman Hall.
999 C 5 |a 10.1016/j.neuron.2015.04.023
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1038/sdata.2016.44
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1038/nrn3256
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |1 Grinband
|y 2017
|2 Crossref
|o Grinband 2017
999 C 5 |a 10.1002/ana.25406
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1038/s41586-019-1077-7
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.bbr.2008.08.040
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1007/s00429-016-1202-4
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |2 Crossref
|u Jones E , Oliphant T , Peterson P (2001) SciPy: open source scientific tools for Python. Available at http://www.scipy.org .
999 C 5 |a 10.1002/hipo.10070
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1002/cne.10883
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.neuropharm.2012.06.023
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1002/hipo.22801
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.neuropsychologia.2015.11.013
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1002/hipo.22181
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.7554/eLife.22978
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.neuron.2017.06.037
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.neuroimage.2011.01.085
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1002/gps.2101
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1073/pnas.1803224115
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.3389/fnhum.2014.00443
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.neurobiolaging.2005.05.011
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1523/JNEUROSCI.1701-17.2018
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1002/hipo.23099
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1111/j.1532-5415.2005.53221.x
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.neuropsychologia.2018.07.035
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/0028-3932(71)90067-4
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1093/cercor/bhz044
|9 -- missing cx lookup --
|1 Patai
|p 2748 -
|2 Crossref
|t Cereb Cortex
|v 29
|y 2019
999 C 5 |a 10.1016/j.cpc.2010.04.018
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.tics.2013.03.005
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.neuron.2018.01.039
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1002/hipo.22474
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.3389/fnagi.2012.00025
|9 -- missing cx lookup --
|1 Rosenbaum
|p 25 -
|2 Crossref
|t Front Ag Neurosci
|v 4
|y 2012
999 C 5 |a 10.1093/acprof:oso/9780195156744.003.0006
|9 -- missing cx lookup --
|2 Crossref
|u Rugg MD , Morcom AM (2005) The relationship between brain activity, cognitive performance and aging: the case of memory. In: Cognitive neuroscience of aging: linking cognitive and cerebral aging ( Cabeza R , Nyberg L , Park DC , eds), pp 132–154. New York: Oxford University Press.
999 C 5 |a 10.3758/s13421-020-01089-3
|9 -- missing cx lookup --
|1 Segen
|p 249 -
|2 Crossref
|t Memory & Cognition
|v 49
|y 2021
999 C 5 |a 10.1038/s41467-019-11802-9
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1152/jn.00946.2006
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |2 Crossref
|u Stan Development Team (2017) PyStan: the Python interface to Stan. 2.16.0.0. edition. Available at http://mc-stan.org .
999 C 5 |a 10.1038/mp.2015.160
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1007/s11222-016-9696-4
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.cortex.2014.12.007
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1126/science.aau4940
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1523/JNEUROSCI.0717-12.2013
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1523/JNEUROSCI.1744-05.2005
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1523/JNEUROSCI.4705-04.2005
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.3389/fnagi.2012.00014
|9 -- missing cx lookup --
|1 Yamamoto
|p 14 -
|2 Crossref
|t Front Ag Neurosci
|v 4
|y 2012
999 C 5 |a 10.1002/hipo.20808
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.neuroimage.2019.06.032
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1016/j.neuroimage.2019.06.031
|9 -- missing cx lookup --
|2 Crossref
999 C 5 |a 10.1038/nrn.2015.24
|9 -- missing cx lookup --
|2 Crossref


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21