---
OA_place: publisher
OA_type: hybrid
PlanS_conform: '1'
_id: '21378'
abstract:
- lang: eng
text: From insects to mammals, essential brain functions, such as forming long-term
memories (LTMs), increase metabolic activity in stimulated neurons to meet the
energetic demand associated with brain activation. However, while impairing neuronal
metabolism limits brain performance, whether expanding the metabolic capacity
of neurons boosts brain function remains poorly understood. Here, we show that
LTM formation of flies and mice can be enhanced by increasing mitochondrial metabolism
in central memory circuits. By knocking down the mitochondrial Ca2+ exporter Letm1,
we favour Ca2+ retention in the mitochondrial matrix of neurons due to reduction
of mitochondrial H+/Ca2+ exchange. The resulting increase in mitochondrial Ca2+
over-activates mitochondrial metabolism in neurons of central memory circuits,
leading to improved LTM storage in training paradigms in which wild-type counterparts
of both species fail to remember. Our findings unveil an evolutionarily conserved
mechanism that controls mitochondrial metabolism in neurons and indicate its involvement
in shaping higher brain functions, such as LTM.
acknowledgement: We thank all members of the laboratory of J.d.J.-S. for insightful
discussions and comments. We thank S. Perez for technical assistance. This work
was made possible by the Paris Brain Institute Diane Barriere Chair in Synaptic
Bioenergetics awarded to J.d.J.-S., who is also supported by an ERC Starting Grant
(SynaptoEnergy, European Research Council; ERC-StG-852873), 2019 ATIP-Avenir Grant
(CNRS, Inserm), a Big Brain Theory Grant (ICM Foundation) and a Kavli Exploratory
Award (Kavli Foundation). This work was also supported by an ERC Advanced Grant
(EnergyMeMo; ERC-AdG-741550) to T.P. and grants from the Agence Nationale de la
Recherche to P.Y.P. (ANR-20-CE92-0047-01), T.P. (ANR-23-CE16-0029-01), A.P. and
J.d.J.-S. (ANR-22-CE16-0020) and J.d.J.-S. (ANR-24-CE16-0221). T.P., P.Y.P. and
J.d.J.-S. are permanent CNRS researchers. A.P. is a permanent ESPCI associate professor.
T.C. was funded by the French Ministry of Research and the Fondation pour la Recherche
Médicale. V.R. was funded by the Max Planck Society, the Chan Zuckerberg Initiative
DAF, an advised fund of the Silicon Valley Community Foundation grant number 2024-349543
and the NIH Director’s New Innovator Award (DP2 MH140148). A.B.-G. and C.R.-D. received
funding from an ERC Starting Grant (HighMemory; ERC-StG-948217), the Ministry of
Economy and Competitiveness (PID2021-122795OB-I00) and the Departament d’Economia
i Coneixement de la Generalitat de Catalunya (SGR 00022). T.P.V. was funded by the
Wellcome Trust and a Royal Society Sir Henry Dale Research Fellowship (WT100000)
and a Wellcome Trust Senior Research Fellowship (214316/Z/18/Z). K.G. was supported
by the DIM C-BRAINS, funded by the Conseil Régional d’Ile-de-France. The contributions
of H.F. and E.R.S. were supported by the Howard Hughes Medical Institute. The PHENO-ICMice
animal Core at ICM is supported by two ‘Investissements d’avenir’ (ANR-10- IAIHU-06
and ANR-11-INBS-0011-NeurATRIS) and the Fondation pour la Recherche Médicale.
article_processing_charge: Yes (in subscription journal)
article_type: original
author:
- first_name: Anjali
full_name: Amrapali Vishwanath, Anjali
last_name: Amrapali Vishwanath
- first_name: Typhaine
full_name: Comyn, Typhaine
last_name: Comyn
- first_name: Rodrigo G.
full_name: Mira, Rodrigo G.
last_name: Mira
- first_name: Claire
full_name: Brossier, Claire
last_name: Brossier
- first_name: Carlos
full_name: Pascual-Caro, Carlos
last_name: Pascual-Caro
- first_name: Maya
full_name: Faour, Maya
last_name: Faour
- first_name: Kahina
full_name: Boumendil, Kahina
last_name: Boumendil
- first_name: Chaitanya
full_name: Chintaluri, Chaitanya
id: BA06AFEE-A4BA-11EA-AE5C-14673DDC885E
last_name: Chintaluri
orcid: 0000-0003-4252-1608
- first_name: Carla
full_name: Ramon-Duaso, Carla
last_name: Ramon-Duaso
- first_name: Ruolin
full_name: Fan, Ruolin
last_name: Fan
- first_name: Kishalay
full_name: Ghosh, Kishalay
last_name: Ghosh
- first_name: Helen
full_name: Farrants, Helen
last_name: Farrants
- first_name: Jean-Paul
full_name: Berwick, Jean-Paul
last_name: Berwick
- first_name: Riya
full_name: Sivakumar, Riya
last_name: Sivakumar
- first_name: Mario
full_name: Lopez-Manzaneda, Mario
last_name: Lopez-Manzaneda
- first_name: Eric R.
full_name: Schreiter, Eric R.
last_name: Schreiter
- first_name: Thomas
full_name: Preat, Thomas
last_name: Preat
- first_name: Tim P
full_name: Vogels, Tim P
id: CB6FF8D2-008F-11EA-8E08-2637E6697425
last_name: Vogels
orcid: 0000-0003-3295-6181
- first_name: Vidhya
full_name: Rangaraju, Vidhya
last_name: Rangaraju
- first_name: Arnau
full_name: Busquets-Garcia, Arnau
last_name: Busquets-Garcia
- first_name: Pierre-Yves
full_name: Plaçais, Pierre-Yves
last_name: Plaçais
- first_name: Alice
full_name: Pavlowsky, Alice
last_name: Pavlowsky
- first_name: Jaime
full_name: de Juan-Sanz, Jaime
last_name: de Juan-Sanz
citation:
ama: Amrapali Vishwanath A, Comyn T, Mira RG, et al. Mitochondrial Ca2+ efflux controls
neuronal metabolism and long-term memory across species. Nature Metabolism.
2026;8(2):467-488. doi:10.1038/s42255-026-01451-w
apa: Amrapali Vishwanath, A., Comyn, T., Mira, R. G., Brossier, C., Pascual-Caro,
C., Faour, M., … de Juan-Sanz, J. (2026). Mitochondrial Ca2+ efflux controls neuronal
metabolism and long-term memory across species. Nature Metabolism. Springer
Nature. https://doi.org/10.1038/s42255-026-01451-w
chicago: Amrapali Vishwanath, Anjali, Typhaine Comyn, Rodrigo G. Mira, Claire Brossier,
Carlos Pascual-Caro, Maya Faour, Kahina Boumendil, et al. “Mitochondrial Ca2+
Efflux Controls Neuronal Metabolism and Long-Term Memory across Species.” Nature
Metabolism. Springer Nature, 2026. https://doi.org/10.1038/s42255-026-01451-w.
ieee: A. Amrapali Vishwanath et al., “Mitochondrial Ca2+ efflux controls
neuronal metabolism and long-term memory across species,” Nature Metabolism,
vol. 8, no. 2. Springer Nature, pp. 467–488, 2026.
ista: Amrapali Vishwanath A, Comyn T, Mira RG, Brossier C, Pascual-Caro C, Faour
M, Boumendil K, Chintaluri C, Ramon-Duaso C, Fan R, Ghosh K, Farrants H, Berwick
J-P, Sivakumar R, Lopez-Manzaneda M, Schreiter ER, Preat T, Vogels TP, Rangaraju
V, Busquets-Garcia A, Plaçais P-Y, Pavlowsky A, de Juan-Sanz J. 2026. Mitochondrial
Ca2+ efflux controls neuronal metabolism and long-term memory across species.
Nature Metabolism. 8(2), 467–488.
mla: Amrapali Vishwanath, Anjali, et al. “Mitochondrial Ca2+ Efflux Controls Neuronal
Metabolism and Long-Term Memory across Species.” Nature Metabolism, vol.
8, no. 2, Springer Nature, 2026, pp. 467–88, doi:10.1038/s42255-026-01451-w.
short: A. Amrapali Vishwanath, T. Comyn, R.G. Mira, C. Brossier, C. Pascual-Caro,
M. Faour, K. Boumendil, C. Chintaluri, C. Ramon-Duaso, R. Fan, K. Ghosh, H. Farrants,
J.-P. Berwick, R. Sivakumar, M. Lopez-Manzaneda, E.R. Schreiter, T. Preat, T.P.
Vogels, V. Rangaraju, A. Busquets-Garcia, P.-Y. Plaçais, A. Pavlowsky, J. de Juan-Sanz,
Nature Metabolism 8 (2026) 467–488.
das_tickbox: '1'
date_created: 2026-03-02T10:04:49Z
date_published: 2026-02-11T00:00:00Z
date_updated: 2026-07-13T12:30:14Z
day: '11'
ddc:
- '570'
department:
- _id: TiVo
doi: 10.1038/s42255-026-01451-w
external_id:
pmid:
- '41673453'
file:
- access_level: open_access
checksum: 365932a599d05bc9ce8a57204e7a1465
content_type: application/pdf
creator: dernst
date_created: 2026-03-02T15:21:27Z
date_updated: 2026-03-02T15:21:27Z
file_id: '21392'
file_name: 2026_NatureMetab_AmrapaliVishwanath.pdf
file_size: 5326608
relation: main_file
success: 1
file_date_updated: 2026-03-02T15:21:27Z
has_accepted_license: '1'
intvolume: ' 8'
issue: '2'
language:
- iso: eng
month: '02'
oa: 1
oa_version: Published Version
page: 467-488
pmid: 1
project:
- _id: c084a126-5a5b-11eb-8a69-d75314a70a87
grant_number: 214316/Z/18/Z
name: What’s in a memory? Spatiotemporal dynamics in strongly coupled recurrent
neuronal networks.
publication: Nature Metabolism
publication_identifier:
eissn:
- 2522-5812
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Mitochondrial Ca2+ efflux controls neuronal metabolism and long-term memory
across species
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 8
year: '2026'
...
---
OA_place: publisher
OA_type: hybrid
PlanS_conform: '1'
_id: '22295'
abstract:
- lang: eng
text: 'Despite the functional diversity of over 100 causal genes1,2,3, phenotypic
convergence across models may reveal common neurobiological processes in autism
spectrum disorder (ASD). Here we profiled 251 samples from 11 monogenic mouse
models of ASD using single-nucleus multi-omic sequencing across three developmental
stages, both sexes and two brain regions. Despite genetic heterogeneity, ASD-linked
mutations converged on perturbations of the radial glial cell lineage. These alterations
reflect a transient developmental delay rather than lasting lineage misspecification
and resolve by postnatal stages. Molecularly, the largest transcriptional differences
emerged in neurons at early postnatal stages. These changes included downregulation
of synaptic and ion channel-related genes, consistent with homeostatic adaptation
or delayed maturation. Network analysis showed molecular convergence across models
within each developmental stage, suggesting that diverse mutations linked to ASD
impinge on common, stage-specific processes. Convergence becomes less pronounced
by postnatal day 14, highlighting the dynamic nature of ASD-associated changes.
Cross-genotype heterogeneity is superimposed on stage-specific effects. Electrophysiology
corroborated this pattern: mutants generally showed altered neuronal excitability
and synaptic properties with model-specific nuances. Our study also highlighted
sex-specific gene expression alterations, with female mice often displaying larger
effect sizes than male mice. Together, our findings provide a comprehensive view
of developmental cellular and molecular dynamics across models of ASD.'
acknowledged_ssus:
- _id: Bio
- _id: LifeSc
acknowledgement: We thank F. Freeman, V. Voronin and M. Ladron de Guevara for technical
assistance; A. Stichelberger and S. Liegenfeld for the management of our animal
colony; M. Schunn, C. Gold and the Preclinical Facility team for technical assistance;
C. Jansen and the Scientific Computing Facility for bioinformatics support and technical
assistance; the Biomedical Sequencing Facility at CeMM for assistance with next-generation
sequencing; and J. Lin and T. Krausgruber in the laboratory of C. Bock for support
with flow cytometry; J. Kirchner for illustrating the multi-omics approach depicted
in Fig. 1; and all members of the laboratory of G.N. for their support and discussions.
This study was supported by the Scientific Service Units of ISTA through resources
provided by the Imaging & Optics Facility and the Laboratory Support Facility. Bulk
RNA-seq was performed by the Next Generation Sequencing Facility at Vienna BioCenter
Core Facilities, member of the Vienna BioCenter. This work was supported by a European
Research Council Consolidator Grant (PR1028ERC02), by SFARI (PR1028SIM02) and by
the Austrian Science Fund (PE1028W1232 and PR1028FG1803) to G.N. Open access funding
provided by Institute of Science and Technology (IST Austria).
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Lena A
full_name: Schwarz, Lena A
id: 29A8453C-F248-11E8-B48F-1D18A9856A87
last_name: Schwarz
- first_name: Christoph
full_name: Dotter, Christoph
id: 4C66542E-F248-11E8-B48F-1D18A9856A87
last_name: Dotter
orcid: 0000-0002-9033-9096
- first_name: Sergey
full_name: Isaev, Sergey
last_name: Isaev
- first_name: Michela
full_name: Lisi, Michela
id: 39383c1b-d3eb-11ef-8d6c-c8cdf4e10c8c
last_name: Lisi
- first_name: Daniel
full_name: Malzl, Daniel
last_name: Malzl
- first_name: Christoph
full_name: Büschl, Christoph
id: 2a8c054c-0913-11ee-9159-f8ef515809ed
last_name: Büschl
- first_name: Sabrina
full_name: Ladstätter, Sabrina
last_name: Ladstätter
- first_name: Bárbara
full_name: Oliveira, Bárbara
id: 3B03AA1A-F248-11E8-B48F-1D18A9856A87
last_name: Oliveira
- first_name: Matteo
full_name: Barel, Matteo
id: 8959927b-2236-11ed-bd6e-ea83d94ade0e
last_name: Barel
- first_name: Bernadette
full_name: Basilico, Bernadette
id: 36035796-5ACA-11E9-A75E-7AF2E5697425
last_name: Basilico
orcid: 0000-0003-1843-3173
- first_name: Chaitanya
full_name: Chintaluri, Chaitanya
id: BA06AFEE-A4BA-11EA-AE5C-14673DDC885E
last_name: Chintaluri
orcid: 0000-0003-4252-1608
- first_name: Sarah
full_name: Gorkiewicz, Sarah
id: f141a35d-15a9-11ec-9fb2-fef6becc7b6f
last_name: Gorkiewicz
- first_name: Mohammad
full_name: Goudarzi, Mohammad
id: 3384113A-F248-11E8-B48F-1D18A9856A87
last_name: Goudarzi
- first_name: Tereza
full_name: Belinova, Tereza
id: 0bf89b6a-d28b-11eb-8bd6-f43768e4d368
last_name: Belinova
- first_name: Stephan
full_name: Reichl, Stephan
last_name: Reichl
- first_name: Gintarė
full_name: Sendžikaitė, Gintarė
id: dd6d52f2-c50d-11eb-9548-bcf0ff82b344
last_name: Sendžikaitė
- first_name: Satish
full_name: Arcot Jayaram, Satish
id: b0bbee33-09f7-11eb-909c-8b358058d28a
last_name: Arcot Jayaram
orcid: 0000-0002-2479-2669
- first_name: Peter
full_name: Koppensteiner, Peter
id: 3B8B25A8-F248-11E8-B48F-1D18A9856A87
last_name: Koppensteiner
orcid: 0000-0002-3509-1948
- first_name: Christoph M
full_name: Sommer, Christoph M
id: 4DF26D8C-F248-11E8-B48F-1D18A9856A87
last_name: Sommer
orcid: 0000-0003-1216-9105
- first_name: Tim P
full_name: Vogels, Tim P
id: CB6FF8D2-008F-11EA-8E08-2637E6697425
last_name: Vogels
orcid: 0000-0003-3295-6181
- first_name: Jörg
full_name: Menche, Jörg
last_name: Menche
- first_name: Igor
full_name: Adameyko, Igor
last_name: Adameyko
- first_name: Peter Vasili
full_name: Kharchenko, Peter Vasili
id: 0095641e-7eb7-11f1-8665-aec51a2ab5e0
last_name: Kharchenko
- first_name: Christoph
full_name: Bock, Christoph
last_name: Bock
- first_name: Gaia
full_name: Novarino, Gaia
id: 3E57A680-F248-11E8-B48F-1D18A9856A87
last_name: Novarino
orcid: 0000-0002-7673-7178
citation:
ama: Schwarz LA, Dotter C, Isaev S, et al. Cortical development dynamics across
autism spectrum disorder mouse models. Nature. 2026. doi:10.1038/s41586-026-10679-1
apa: Schwarz, L. A., Dotter, C., Isaev, S., Lisi, M., Malzl, D., Büschl, C., … Novarino,
G. (2026). Cortical development dynamics across autism spectrum disorder mouse
models. Nature. Springer Nature. https://doi.org/10.1038/s41586-026-10679-1
chicago: Schwarz, Lena A, Christoph Dotter, Sergey Isaev, Michela Lisi, Daniel Malzl,
Christoph Büschl, Sabrina Ladstätter, et al. “Cortical Development Dynamics across
Autism Spectrum Disorder Mouse Models.” Nature. Springer Nature, 2026.
https://doi.org/10.1038/s41586-026-10679-1.
ieee: L. A. Schwarz et al., “Cortical development dynamics across autism
spectrum disorder mouse models,” Nature. Springer Nature, 2026.
ista: Schwarz LA, Dotter C, Isaev S, Lisi M, Malzl D, Büschl C, Ladstätter S, Oliveira
B, Barel M, Basilico B, Chintaluri C, Gorkiewicz S, Goudarzi M, Belinova T, Reichl
S, Sendžikaitė G, Arcot Jayaram S, Koppensteiner P, Sommer CM, Vogels TP, Menche
J, Adameyko I, Kharchenko PV, Bock C, Novarino G. 2026. Cortical development dynamics
across autism spectrum disorder mouse models. Nature.
mla: Schwarz, Lena A., et al. “Cortical Development Dynamics across Autism Spectrum
Disorder Mouse Models.” Nature, Springer Nature, 2026, doi:10.1038/s41586-026-10679-1.
short: L.A. Schwarz, C. Dotter, S. Isaev, M. Lisi, D. Malzl, C. Büschl, S. Ladstätter,
B. Oliveira, M. Barel, B. Basilico, C. Chintaluri, S. Gorkiewicz, M. Goudarzi,
T. Belinova, S. Reichl, G. Sendžikaitė, S. Arcot Jayaram, P. Koppensteiner, C.M.
Sommer, T.P. Vogels, J. Menche, I. Adameyko, P.V. Kharchenko, C. Bock, G. Novarino,
Nature (2026).
corr_author: '1'
dataavailabilitystatement: Single-nucleus multiomics data are available from the Gene
Expression Omnibus (GSE328363). The mm10 reference genome was used for the alignment
(refdata-cellranger-arc-mm10-2020-A-2.0.0, obtained from https://cf.10xgenomics.com/supp/cell-arc/refdata-cellranger-arc-mm10-2020-A-2.0.0.tar.gz).
Single-cell data can be accessed and visualized through a CELLxGENE database (https://adameykolab.hifo.meduniwien.ac.at/cellxgene_public/filecrawl/.2026_Nature_Schwarz).
Source data are provided with this paper. Scripts and analyses that support the
main findings of this study are accessible in a GitHub repository (https://git.ista.ac.at/research-sofware/mouseome).
date_created: 2026-07-13T09:47:21Z
date_published: 2026-06-17T00:00:00Z
date_updated: 2026-07-13T12:58:19Z
day: '17'
ddc:
- '570'
department:
- _id: AnKi
- _id: GaNo
- _id: TiVo
- _id: ScienComp
- _id: GradSch
- _id: Bio
- _id: PreCl
doi: 10.1038/s41586-026-10679-1
external_id:
pmid:
- '42310454'
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1038/s41586-026-10679-1
month: '06'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: 34ba8964-11ca-11ed-8bc3-e15864e7e9a6
grant_number: '101044865'
name: Toward an understanding of the brain interstitial system and the extracellular
proteome in health and autism spectrum disorders
- _id: 9B91375C-BA93-11EA-9121-9846C619BF3A
grant_number: '707964'
name: Critical windows and reversibility of ASD associated with mutations in chromatin
remodelers
- _id: 2548AE96-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: W1232
name: Molecular Drug Targets
- _id: ebb38b5d-77a9-11ec-83b8-a42e08120a88
grant_number: FG1803 49015
name: Neurobiology of anxiety in autism spectrum disorders
publication: Nature
publication_identifier:
eissn:
- 1476-4687
issn:
- 0028-0836
publication_status: epub_ahead
publisher: Springer Nature
quality_controlled: '1'
researchdata_availability: yes
scopus_import: '1'
status: public
supplementarymaterial: yes
title: Cortical development dynamics across autism spectrum disorder mouse models
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2026'
...
---
DOAJ_listed: '1'
OA_place: publisher
OA_type: gold
_id: '15169'
abstract:
- lang: eng
text: Interpretation of extracellular recordings can be challenging due to the long
range of electric field. This challenge can be mitigated by estimating the current
source density (CSD). Here we introduce kCSD-python, an open Python package implementing
Kernel Current Source Density (kCSD) method and related tools to facilitate CSD
analysis of experimental data and the interpretation of results. We show how to
counter the limitations imposed by noise and assumptions in the method itself.
kCSD-python allows CSD estimation for an arbitrary distribution of electrodes
in 1D, 2D, and 3D, assuming distributions of sources in tissue, a slice, or in
a single cell, and includes a range of diagnostic aids. We demonstrate its features
in a Jupyter Notebook tutorial which illustrates a typical analytical workflow
and main functionalities useful in validating analysis results.
acknowledgement: 'The Python implementation of kCSD was started by Grzegorz Parka
during Google Summer of Code project through the International Neuroinformatics
Coordinating Facility. Jan Mąka implemented the first Python version of skCSD class.
This work was supported by the Polish National Science Centre (2013/08/W/NZ4/00691
to DKW; 2015/17/B/ST7/04123 to DKW). '
article_number: e1011941
article_processing_charge: Yes
article_type: original
author:
- first_name: Chaitanya
full_name: Chintaluri, Chaitanya
id: BA06AFEE-A4BA-11EA-AE5C-14673DDC885E
last_name: Chintaluri
orcid: 0000-0003-4252-1608
- first_name: Marta
full_name: Bejtka, Marta
last_name: Bejtka
- first_name: Wladyslaw
full_name: Sredniawa, Wladyslaw
last_name: Sredniawa
- first_name: Michal
full_name: Czerwinski, Michal
last_name: Czerwinski
- first_name: Jakub M.
full_name: Dzik, Jakub M.
last_name: Dzik
- first_name: Joanna
full_name: Jedrzejewska-Szmek, Joanna
last_name: Jedrzejewska-Szmek
- first_name: Daniel K.
full_name: Wojciki, Daniel K.
last_name: Wojciki
citation:
ama: Chintaluri C, Bejtka M, Sredniawa W, et al. kCSD-python, reliable current source
density estimation with quality control. PLoS Computational Biology. 2024;20(3).
doi:10.1371/journal.pcbi.1011941
apa: Chintaluri, C., Bejtka, M., Sredniawa, W., Czerwinski, M., Dzik, J. M., Jedrzejewska-Szmek,
J., & Wojciki, D. K. (2024). kCSD-python, reliable current source density
estimation with quality control. PLoS Computational Biology. Public Library
of Science. https://doi.org/10.1371/journal.pcbi.1011941
chicago: Chintaluri, Chaitanya, Marta Bejtka, Wladyslaw Sredniawa, Michal Czerwinski,
Jakub M. Dzik, Joanna Jedrzejewska-Szmek, and Daniel K. Wojciki. “KCSD-Python,
Reliable Current Source Density Estimation with Quality Control.” PLoS Computational
Biology. Public Library of Science, 2024. https://doi.org/10.1371/journal.pcbi.1011941.
ieee: C. Chintaluri et al., “kCSD-python, reliable current source density
estimation with quality control,” PLoS Computational Biology, vol. 20,
no. 3. Public Library of Science, 2024.
ista: Chintaluri C, Bejtka M, Sredniawa W, Czerwinski M, Dzik JM, Jedrzejewska-Szmek
J, Wojciki DK. 2024. kCSD-python, reliable current source density estimation with
quality control. PLoS Computational Biology. 20(3), e1011941.
mla: Chintaluri, Chaitanya, et al. “KCSD-Python, Reliable Current Source Density
Estimation with Quality Control.” PLoS Computational Biology, vol. 20,
no. 3, e1011941, Public Library of Science, 2024, doi:10.1371/journal.pcbi.1011941.
short: C. Chintaluri, M. Bejtka, W. Sredniawa, M. Czerwinski, J.M. Dzik, J. Jedrzejewska-Szmek,
D.K. Wojciki, PLoS Computational Biology 20 (2024).
corr_author: '1'
das_tickbox: '1'
date_created: 2024-03-24T23:00:59Z
date_published: 2024-03-14T00:00:00Z
date_updated: 2026-07-13T12:30:33Z
day: '14'
ddc:
- '000'
- '570'
department:
- _id: TiVo
doi: 10.1371/journal.pcbi.1011941
external_id:
isi:
- '001190689800001'
pmid:
- '38484020'
file:
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checksum: c09718d0d09614642d877d0716ce32e8
content_type: application/pdf
creator: dernst
date_created: 2025-06-25T05:47:36Z
date_updated: 2025-06-25T05:47:36Z
file_id: '19897'
file_name: 2024_PLoSCompBio_Chintaluri.pdf
file_size: 2540277
relation: main_file
success: 1
file_date_updated: 2025-06-25T05:47:36Z
has_accepted_license: '1'
intvolume: ' 20'
isi: 1
issue: '3'
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
pmid: 1
publication: PLoS Computational Biology
publication_identifier:
eissn:
- 1553-7358
issn:
- 1553-734X
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/Neuroinflab/kCSD-python
scopus_import: '1'
status: public
title: kCSD-python, reliable current source density estimation with quality control
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 20
year: '2024'
...
---
OA_place: publisher
OA_type: hybrid
_id: '14666'
abstract:
- lang: eng
text: So-called spontaneous activity is a central hallmark of most nervous systems.
Such non-causal firing is contrary to the tenet of spikes as a means of communication,
and its purpose remains unclear. We propose that self-initiated firing can serve
as a release valve to protect neurons from the toxic conditions arising in mitochondria
from lower-than-baseline energy consumption. To demonstrate the viability of our
hypothesis, we built a set of models that incorporate recent experimental results
indicating homeostatic control of metabolic products—Adenosine triphosphate (ATP),
adenosine diphosphate (ADP), and reactive oxygen species (ROS)—by changes in firing.
We explore the relationship of metabolic cost of spiking with its effect on the
temporal patterning of spikes and reproduce experimentally observed changes in
intrinsic firing in the fruitfly dorsal fan-shaped body neuron in a model with
ROS-modulated potassium channels. We also show that metabolic spiking homeostasis
can produce indefinitely sustained avalanche dynamics in cortical circuits. Our
theory can account for key features of neuronal activity observed in many studies
ranging from ion channel function all the way to resting state dynamics. We finish
with a set of experimental predictions that would confirm an integrated, crucial
role for metabolically regulated spiking and firmly link metabolic homeostasis
and neuronal function.
acknowledgement: We thank Prof. C. Nazaret and Prof. J.-P. Mazat for sharing the code
of their mitochondrial model. We also thank G. Miesenböck, E. Marder, L. Abbott,
A. Kempf, P. Hasenhuetl, W. Podlaski, F. Zenke, E. Agnes, P. Bozelos, J. Watson,
B. Confavreux, and G. Christodoulou, and the rest of the Vogels Lab for their feedback.
This work was funded by Wellcome Trust and Royal Society Sir Henry Dale Research
Fellowship (WT100000), a Wellcome Trust Senior Research Fellowship (214316/Z/18/Z),
and a UK Research and Innovation, Biotechnology and Biological Sciences Research
Council grant (UKRI-BBSRC BB/N019512/1).
article_number: e2306525120
article_processing_charge: Yes (in subscription journal)
article_type: original
author:
- first_name: Chaitanya
full_name: Chintaluri, Chaitanya
id: BA06AFEE-A4BA-11EA-AE5C-14673DDC885E
last_name: Chintaluri
orcid: 0000-0003-4252-1608
- first_name: Tim P
full_name: Vogels, Tim P
id: CB6FF8D2-008F-11EA-8E08-2637E6697425
last_name: Vogels
orcid: 0000-0003-3295-6181
citation:
ama: Chintaluri C, Vogels TP. Metabolically regulated spiking could serve neuronal
energy homeostasis and protect from reactive oxygen species. Proceedings of
the National Academy of Sciences of the United States of America. 2023;120(48).
doi:10.1073/pnas.2306525120
apa: Chintaluri, C., & Vogels, T. P. (2023). Metabolically regulated spiking
could serve neuronal energy homeostasis and protect from reactive oxygen species.
Proceedings of the National Academy of Sciences of the United States of America.
National Academy of Sciences. https://doi.org/10.1073/pnas.2306525120
chicago: Chintaluri, Chaitanya, and Tim P Vogels. “Metabolically Regulated Spiking
Could Serve Neuronal Energy Homeostasis and Protect from Reactive Oxygen Species.”
Proceedings of the National Academy of Sciences of the United States of America.
National Academy of Sciences, 2023. https://doi.org/10.1073/pnas.2306525120.
ieee: C. Chintaluri and T. P. Vogels, “Metabolically regulated spiking could serve
neuronal energy homeostasis and protect from reactive oxygen species,” Proceedings
of the National Academy of Sciences of the United States of America, vol.
120, no. 48. National Academy of Sciences, 2023.
ista: Chintaluri C, Vogels TP. 2023. Metabolically regulated spiking could serve
neuronal energy homeostasis and protect from reactive oxygen species. Proceedings
of the National Academy of Sciences of the United States of America. 120(48),
e2306525120.
mla: Chintaluri, Chaitanya, and Tim P. Vogels. “Metabolically Regulated Spiking
Could Serve Neuronal Energy Homeostasis and Protect from Reactive Oxygen Species.”
Proceedings of the National Academy of Sciences of the United States of America,
vol. 120, no. 48, e2306525120, National Academy of Sciences, 2023, doi:10.1073/pnas.2306525120.
short: C. Chintaluri, T.P. Vogels, Proceedings of the National Academy of Sciences
of the United States of America 120 (2023).
corr_author: '1'
das_tickbox: '1'
date_created: 2023-12-10T23:01:00Z
date_published: 2023-11-21T00:00:00Z
date_updated: 2026-07-13T12:30:49Z
day: '21'
ddc:
- '570'
department:
- _id: TiVo
doi: 10.1073/pnas.2306525120
external_id:
isi:
- '001157389000005'
pmid:
- '37988463'
file:
- access_level: open_access
checksum: bf4ec38602a70dae4338077a5a4d497f
content_type: application/pdf
creator: dernst
date_created: 2023-12-11T12:45:12Z
date_updated: 2023-12-11T12:45:12Z
file_id: '14678'
file_name: 2023_PNAS_Chintaluri.pdf
file_size: 16891602
relation: main_file
success: 1
file_date_updated: 2023-12-11T12:45:12Z
has_accepted_license: '1'
intvolume: ' 120'
isi: 1
issue: '48'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: c084a126-5a5b-11eb-8a69-d75314a70a87
grant_number: 214316/Z/18/Z
name: What’s in a memory? Spatiotemporal dynamics in strongly coupled recurrent
neuronal networks.
publication: Proceedings of the National Academy of Sciences of the United States
of America
publication_identifier:
eissn:
- 1091-6490
issn:
- 0027-8424
publication_status: published
publisher: National Academy of Sciences
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/ccluri/metabolic_spiking
scopus_import: '1'
status: public
title: Metabolically regulated spiking could serve neuronal energy homeostasis and
protect from reactive oxygen species
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 120
year: '2023'
...
---
_id: '17132'
abstract:
- lang: eng
text: Extracellular recording is an accessible technique used in animals
and humans to study the brain physiology and pathology. As the number of recording
channels and their density grows it is natural to ask how much improvement the
additional channels bring in and how we can optimally use the new capabilities
for monitoring the brain. Here we show that for any given distribution of electrodes
we can establish exactly what information about current sources in the brain can
be recovered and what information is strictly unobservable. We demonstrate this
in the general setting of previously proposed kernel Current Source Density method
and illustrate it with simplified examples as well as using evoked potentials
from the barrel cortex obtained with a Neuropixels probe and with compatible model
data. We show that with conceptual separation of the estimation space from experimental
setup one can recover sources not accessible to standard methods.
article_number: e1008615
article_processing_charge: No
article_type: original
author:
- first_name: Chaitanya
full_name: Chintaluri, Chaitanya
id: BA06AFEE-A4BA-11EA-AE5C-14673DDC885E
last_name: Chintaluri
orcid: 0000-0003-4252-1608
- first_name: Marta
full_name: Bejtka, Marta
last_name: Bejtka
- first_name: Władysław
full_name: Średniawa, Władysław
last_name: Średniawa
- first_name: Michał
full_name: Czerwiński, Michał
last_name: Czerwiński
- first_name: Jakub M.
full_name: Dzik, Jakub M.
last_name: Dzik
- first_name: Joanna
full_name: Jędrzejewska-Szmek, Joanna
last_name: Jędrzejewska-Szmek
- first_name: Kacper
full_name: Kondrakiewicz, Kacper
last_name: Kondrakiewicz
- first_name: Ewa
full_name: Kublik, Ewa
last_name: Kublik
- first_name: Daniel K.
full_name: Wójcik, Daniel K.
last_name: Wójcik
citation:
ama: Chintaluri C, Bejtka M, Średniawa W, et al. What we can and what we cannot
see with extracellular multielectrodes. PLOS Computational Biology. 2021;17(5).
doi:10.1371/journal.pcbi.1008615
apa: Chintaluri, C., Bejtka, M., Średniawa, W., Czerwiński, M., Dzik, J. M., Jędrzejewska-Szmek,
J., … Wójcik, D. K. (2021). What we can and what we cannot see with extracellular
multielectrodes. PLOS Computational Biology. Public Library of Science.
https://doi.org/10.1371/journal.pcbi.1008615
chicago: Chintaluri, Chaitanya, Marta Bejtka, Władysław Średniawa, Michał Czerwiński,
Jakub M. Dzik, Joanna Jędrzejewska-Szmek, Kacper Kondrakiewicz, Ewa Kublik, and
Daniel K. Wójcik. “What We Can and What We Cannot See with Extracellular Multielectrodes.”
PLOS Computational Biology. Public Library of Science, 2021. https://doi.org/10.1371/journal.pcbi.1008615.
ieee: C. Chintaluri et al., “What we can and what we cannot see with extracellular
multielectrodes,” PLOS Computational Biology, vol. 17, no. 5. Public Library
of Science, 2021.
ista: Chintaluri C, Bejtka M, Średniawa W, Czerwiński M, Dzik JM, Jędrzejewska-Szmek
J, Kondrakiewicz K, Kublik E, Wójcik DK. 2021. What we can and what we cannot
see with extracellular multielectrodes. PLOS Computational Biology. 17(5), e1008615.
mla: Chintaluri, Chaitanya, et al. “What We Can and What We Cannot See with Extracellular
Multielectrodes.” PLOS Computational Biology, vol. 17, no. 5, e1008615,
Public Library of Science, 2021, doi:10.1371/journal.pcbi.1008615.
short: C. Chintaluri, M. Bejtka, W. Średniawa, M. Czerwiński, J.M. Dzik, J. Jędrzejewska-Szmek,
K. Kondrakiewicz, E. Kublik, D.K. Wójcik, PLOS Computational Biology 17 (2021).
das_tickbox: '1'
date_created: 2024-06-11T14:43:37Z
date_published: 2021-05-14T00:00:00Z
date_updated: 2026-07-13T12:31:04Z
day: '14'
doi: 10.1371/journal.pcbi.1008615
extern: '1'
has_accepted_license: '1'
intvolume: ' 17'
issue: '5'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1371/journal.pcbi.1008615
month: '05'
oa: 1
oa_version: Published Version
publication: PLOS Computational Biology
publication_identifier:
issn:
- 1553-7358
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
status: public
title: What we can and what we cannot see with extracellular multielectrodes
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 17
year: '2021'
...
---
_id: '8127'
abstract:
- lang: eng
text: Mechanistic modeling in neuroscience aims to explain observed phenomena in
terms of underlying causes. However, determining which model parameters agree
with complex and stochastic neural data presents a significant challenge. We address
this challenge with a machine learning tool which uses deep neural density estimators—trained
using model simulations—to carry out Bayesian inference and retrieve the full
space of parameters compatible with raw data or selected data features. Our method
is scalable in parameters and data features and can rapidly analyze new data after
initial training. We demonstrate the power and flexibility of our approach on
receptive fields, ion channels, and Hodgkin–Huxley models. We also characterize
the space of circuit configurations giving rise to rhythmic activity in the crustacean
stomatogastric ganglion, and use these results to derive hypotheses for underlying
compensation mechanisms. Our approach will help close the gap between data-driven
and theory-driven models of neural dynamics.
acknowledgement: We thank Mahmood S Hoseini and Michael Stryker for sharing their
data for Figure 2, and Philipp Berens, Sean Bittner, Jan Boelts, John Cunningham,
Richard Gao, Scott Linderman, Eve Marder, Iain Murray, George Papamakarios, Astrid
Prinz, Auguste Schulz and Srinivas Turaga for discussions and/or comments on the
manuscript. This work was supported by the German Research Foundation (DFG) through
SFB 1233 ‘Robust Vision’, (276693517), SFB 1089 ‘Synaptic Microcircuits’, SPP 2041
‘Computational Connectomics’ and Germany's Excellence Strategy – EXC-Number 2064/1
– Project number 390727645 and the German Federal Ministry of Education and Research
(BMBF, project ‘ADIMEM’, FKZ 01IS18052 A-D) to JHM, a Sir Henry Dale Fellowship
by the Wellcome Trust and the Royal Society (WT100000; WFP and TPV), a Wellcome
Trust Senior Research Fellowship (214316/Z/18/Z; TPV), a ERC Consolidator Grant
(SYNAPSEEK; WPF and CC), and a UK Research and Innovation, Biotechnology and Biological
Sciences Research Council (CC, UKRI-BBSRC BB/N019512/1). We gratefully acknowledge
the Leibniz Supercomputing Centre for funding this project by providing computing
time on its Linux-Cluster.
article_number: e56261
article_processing_charge: No
article_type: original
author:
- first_name: Pedro J.
full_name: Gonçalves, Pedro J.
last_name: Gonçalves
orcid: 0000-0002-6987-4836
- first_name: Jan-Matthis
full_name: Lueckmann, Jan-Matthis
last_name: Lueckmann
orcid: 0000-0003-4320-4663
- first_name: Michael
full_name: Deistler, Michael
last_name: Deistler
orcid: 0000-0002-3573-0404
- first_name: Marcel
full_name: Nonnenmacher, Marcel
last_name: Nonnenmacher
orcid: 0000-0001-6044-6627
- first_name: Kaan
full_name: Öcal, Kaan
last_name: Öcal
orcid: 0000-0002-8528-6858
- first_name: Giacomo
full_name: Bassetto, Giacomo
last_name: Bassetto
- first_name: Chaitanya
full_name: Chintaluri, Chaitanya
id: BA06AFEE-A4BA-11EA-AE5C-14673DDC885E
last_name: Chintaluri
orcid: 0000-0003-4252-1608
- first_name: William F.
full_name: Podlaski, William F.
last_name: Podlaski
orcid: 0000-0001-6619-7502
- first_name: Sara A.
full_name: Haddad, Sara A.
last_name: Haddad
orcid: 0000-0003-0807-0823
- first_name: Tim P
full_name: Vogels, Tim P
id: CB6FF8D2-008F-11EA-8E08-2637E6697425
last_name: Vogels
orcid: 0000-0003-3295-6181
- first_name: David S.
full_name: Greenberg, David S.
last_name: Greenberg
- first_name: Jakob H.
full_name: Macke, Jakob H.
last_name: Macke
orcid: 0000-0001-5154-8912
citation:
ama: Gonçalves PJ, Lueckmann J-M, Deistler M, et al. Training deep neural density
estimators to identify mechanistic models of neural dynamics. eLife. 2020;9.
doi:10.7554/eLife.56261
apa: Gonçalves, P. J., Lueckmann, J.-M., Deistler, M., Nonnenmacher, M., Öcal, K.,
Bassetto, G., … Macke, J. H. (2020). Training deep neural density estimators to
identify mechanistic models of neural dynamics. ELife. eLife Sciences Publications.
https://doi.org/10.7554/eLife.56261
chicago: Gonçalves, Pedro J., Jan-Matthis Lueckmann, Michael Deistler, Marcel Nonnenmacher,
Kaan Öcal, Giacomo Bassetto, Chaitanya Chintaluri, et al. “Training Deep Neural
Density Estimators to Identify Mechanistic Models of Neural Dynamics.” ELife.
eLife Sciences Publications, 2020. https://doi.org/10.7554/eLife.56261.
ieee: P. J. Gonçalves et al., “Training deep neural density estimators to
identify mechanistic models of neural dynamics,” eLife, vol. 9. eLife Sciences
Publications, 2020.
ista: Gonçalves PJ, Lueckmann J-M, Deistler M, Nonnenmacher M, Öcal K, Bassetto
G, Chintaluri C, Podlaski WF, Haddad SA, Vogels TP, Greenberg DS, Macke JH. 2020.
Training deep neural density estimators to identify mechanistic models of neural
dynamics. eLife. 9, e56261.
mla: Gonçalves, Pedro J., et al. “Training Deep Neural Density Estimators to Identify
Mechanistic Models of Neural Dynamics.” ELife, vol. 9, e56261, eLife Sciences
Publications, 2020, doi:10.7554/eLife.56261.
short: P.J. Gonçalves, J.-M. Lueckmann, M. Deistler, M. Nonnenmacher, K. Öcal, G.
Bassetto, C. Chintaluri, W.F. Podlaski, S.A. Haddad, T.P. Vogels, D.S. Greenberg,
J.H. Macke, ELife 9 (2020).
das_tickbox: '1'
date_created: 2020-07-16T12:26:04Z
date_published: 2020-09-17T00:00:00Z
date_updated: 2026-07-13T12:31:21Z
day: '17'
ddc:
- '570'
department:
- _id: TiVo
doi: 10.7554/eLife.56261
ec_funded: 1
external_id:
isi:
- '000584989400001'
pmid:
- '32940606'
file:
- access_level: open_access
checksum: c4300ddcd93ed03fc9c6cdf1f77890be
content_type: application/pdf
creator: cziletti
date_created: 2020-10-27T11:37:32Z
date_updated: 2020-10-27T11:37:32Z
file_id: '8709'
file_name: 2020_eLife_Gonçalves.pdf
file_size: 17355867
relation: main_file
success: 1
file_date_updated: 2020-10-27T11:37:32Z
has_accepted_license: '1'
intvolume: ' 9'
isi: 1
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: 0aacfa84-070f-11eb-9043-d7eb2c709234
call_identifier: H2020
grant_number: '819603'
name: Learning the shape of synaptic plasticity rules for neuronal architectures
and function through machine learning.
publication: eLife
publication_identifier:
eissn:
- 2050-084X
publication_status: published
publisher: eLife Sciences Publications
quality_controlled: '1'
scopus_import: '1'
status: public
title: Training deep neural density estimators to identify mechanistic models of neural
dynamics
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 9
year: '2020'
...