Home > Publications Database > Modelling the contributions to hyperexcitability in a mouse model of Alzheimer's disease. > print

001     256459
005     20240112171741.0
024 7 _ |a 10.1113/JP283401
|2 doi
024 7 _ |a pmid:36734280
|2 pmid
024 7 _ |a 0022-3751
|2 ISSN
024 7 _ |a 1469-7793
|2 ISSN
024 7 _ |a altmetric:142366350
|2 altmetric
037 _ _ |a DZNE-2023-00321
041 _ _ |a English
082 _ _ |a 610
100 1 _ |a Mittag, Martin
|0 0000-0002-6429-2423
|b 0
245 _ _ |a Modelling the contributions to hyperexcitability in a mouse model of Alzheimer's disease.
260 _ _ |a Hoboken, NJ
|c 2023
|b Wiley-Blackwell
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 1691420240_2440
|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 CC BY
520 _ _ |a Neuronal hyperexcitability is a pathological characteristic of Alzheimer's disease (AD). Three main mechanisms have been proposed to explain it: (i) dendritic degeneration leading to increased input resistance, (ii) ion channel changes leading to enhanced intrinsic excitability, and (iii) synaptic changes leading to excitation-inhibition (E/I) imbalance. However, the relative contribution of these mechanisms is not fully understood. Therefore, we performed biophysically realistic multi-compartmental modelling of neuronal excitability in reconstructed CA1 pyramidal neurons from wild-type and APP/PS1 mice, a well-established animal model of AD. We show that, for synaptic activation, the excitability-promoting effects of dendritic degeneration are cancelled out by decreased excitation due to synaptic loss. We find an interesting balance between excitability regulation and an enhanced degeneration in the basal dendrites of APP/PS1 cells, potentially leading to increased excitation by the apical but decreased excitation by the basal Schaffer collateral pathway. Furthermore, our simulations reveal three pathomechanistic scenarios that can account for the experimentally observed increase in firing and bursting of CA1 pyramidal neurons in APP/PS1 mice: scenario 1: enhanced E/I ratio; scenario 2: alteration of intrinsic ion channels (IAHP down-regulated; INap , INa and ICaT up-regulated) in addition to enhanced E/I ratio; and scenario 3: increased excitatory burst input. Our work supports the hypothesis that pathological network and ion channel changes are major contributors to neuronal hyperexcitability in AD. Overall, our results are in line with the concept of multi-causality according to which multiple different disruptions are separately sufficient but no single particular disruption is necessary for neuronal hyperexcitability. KEY POINTS: This work presents simulations of synaptically driven responses in pyramidal cells (PCs) with Alzheimer's disease (AD)-related dendritic degeneration. Dendritic degeneration alone alters PC responses to layer-specific input but additional pathomechanistic scenarios are required to explain neuronal hyperexcitability in AD as follows. Possible scenario 1: AD-related increased excitatory input together with decreased inhibitory input (E/I imbalance) can lead to hyperexcitability in PCs. Possible scenario 2: changes in E/I balance combined with altered ion channel properties can account for hyperexcitability in AD. Possible scenario 3: burst hyperactivity of the surrounding network can explain hyperexcitability of PCs during AD.
536 _ _ |a 351 - Brain Function (POF4-351)
|0 G:(DE-HGF)POF4-351
|c POF4-351
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, PubMed, , Journals: pub.dzne.de
650 _ 2 |a Mice
|2 MeSH
650 _ 2 |a Animals
|2 MeSH
650 _ 2 |a Alzheimer Disease
|2 MeSH
650 _ 2 |a Hippocampus: physiology
|2 MeSH
650 _ 2 |a Neurons: physiology
|2 MeSH
650 _ 2 |a Pyramidal Cells: physiology
|2 MeSH
650 _ 2 |a Ion Channels: metabolism
|2 MeSH
650 _ 2 |a Disease Models, Animal
|2 MeSH
650 _ 7 |a Ion Channels
|2 NLM Chemicals
650 _ 7 |a degeneracy
|2 Other
650 _ 7 |a dendritic constancy
|2 Other
650 _ 7 |a hippocampus
|2 Other
650 _ 7 |a morphological modelling
|2 Other
650 _ 7 |a multi-causal pathogenesis
|2 Other
700 1 _ |a Mediavilla, Laura
|0 0000-0003-4174-4076
|b 1
700 1 _ |a Remy, Stefan
|0 P:(DE-2719)2810375
|b 2
|u dzne
700 1 _ |a Cuntz, Hermann
|0 0000-0001-5445-0507
|b 3
700 1 _ |a Jedlicka, Peter
|0 0000-0001-6571-5742
|b 4
770 _ _ |a Computational neuroscience
773 _ _ |a 10.1113/JP283401
|g p. JP283401
|0 PERI:(DE-600)1475290-6
|n 15
|p 3403-3437
|t The journal of physiology
|v 601
|y 2023
|x 0022-3751
856 4 _ |u https://pub.dzne.de/record/256459/files/DZNE-2023-00321%20SUP1.csv
856 4 _ |u https://pub.dzne.de/record/256459/files/DZNE-2023-00321%20SUP1.ods
856 4 _ |u https://pub.dzne.de/record/256459/files/DZNE-2023-00321%20SUP1.xls
856 4 _ |u https://pub.dzne.de/record/256459/files/DZNE-2023-00321%20SUP1.xlsx
856 4 _ |u https://pub.dzne.de/record/256459/files/DZNE-2023-00321%20SUP2.pdf
856 4 _ |u https://pub.dzne.de/record/256459/files/DZNE-2023-00321%20SUP2.pdf?subformat=pdfa
|x pdfa
856 4 _ |u https://pub.dzne.de/record/256459/files/DZNE-2023-00321.pdf
|y OpenAccess
856 4 _ |u https://pub.dzne.de/record/256459/files/DZNE-2023-00321.pdf?subformat=pdfa
|x pdfa
|y OpenAccess
909 C O |o oai:pub.dzne.de:256459
|p openaire
|p open_access
|p VDB
|p driver
|p dnbdelivery
910 1 _ |a Deutsches Zentrum für Neurodegenerative Erkrankungen
|0 I:(DE-588)1065079516
|k DZNE
|b 2
|6 P:(DE-2719)2810375
913 1 _ |a DE-HGF
|b Gesundheit
|l Neurodegenerative Diseases
|1 G:(DE-HGF)POF4-350
|0 G:(DE-HGF)POF4-351
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-300
|4 G:(DE-HGF)POF
|v Brain Function
|x 0
914 1 _ |y 2023
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2022-11-08
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1190
|2 StatID
|b Biological Abstracts
|d 2022-11-08
915 _ _ |a DEAL Wiley
|0 StatID:(DE-HGF)3001
|2 StatID
|d 2022-11-08
|w ger
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2022-11-08
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b J PHYSIOL-LONDON : 2022
|d 2023-10-21
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2023-10-21
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2023-10-21
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0320
|2 StatID
|b PubMed Central
|d 2023-10-21
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
|d 2023-10-21
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
|d 2023-10-21
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2023-10-21
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
|d 2023-10-21
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2023-10-21
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1030
|2 StatID
|b Current Contents - Life Sciences
|d 2023-10-21
915 _ _ |a IF >= 5
|0 StatID:(DE-HGF)9905
|2 StatID
|b J PHYSIOL-LONDON : 2022
|d 2023-10-21
920 1 _ |0 I:(DE-2719)1013006
|k AG Remy
|l Neuronal Networks
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-2719)1013006
980 _ _ |a UNRESTRICTED
980 1 _ |a FullTexts

LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21