Linking the microarchitecture of neurotransmitter systems to large-scale MEG resting state networks

Approved

Classifications

MinEdu publication type
A1 Journal article (peer-reviewed)
Definition
Article
Target group
Scientific
Peer reviewed
Peer-reviewed
Article type
Journal article
Host publication type
Journal

Authors of the publication

Number of authors
3
Authors
Siebenhuhner, Felix; Palva, J. Matias; Palva, Satu
Local authors
Author
Palva, Satu
Unit
Values, Ideologies and Social Contexts of Education, VISE, until 31.12.2024

Publication channel information

Title of journal/series
iScience
ISSN (electronic)
2589-0042
ISSN (linking)
2589-0042
Publisher
Elsevier
Publication forum ID
87254
Publication forum level
1
Internationality
Yes

Detailed publication information

Publication year
2024
Reporting year
2024
Journal/series volume number
27
Journal/series issue number
11
Article number
111111
DOI
10.1016/j.isci.2024.111111
Language of publication
English

Co-publication information

International co-publication
Yes
Co-publication with a company
No

Availability

Classification and additional information

MinEdu field of science classification
515 Psychology
Keywords
human cortex; coupling networks; specific patterns; networks

Funding information

Funding information in the publication
This work was supported by the Academy of Finland with grants 1266745 and 1296304 to J.M.P. and 325404 to S.P. and by the Cultural Foundation of Finland with grants 00220945 and 00242647 to F.S.

Research data information

Research data information in the publication
Ethical restrictions apply to data and original neuroimaging time series cannot be shared on a public server. Original PS and AC data underlying figures, statistics, and main conclusions have been uploaded to Dryad server.Data: We utilized the neurotransmitter receptor and transporter maps by Hansen et al.31 which is freely accessible online (link in key resources table). Original PS and AC data and metadata have been deposited with Dryad. The DOI can be found in the key resources table. Code: We used the freely available Freesurfer and MNE-python software for preprocessing. All analyses were carried out in python, using freely available standard packages as well as custom code which we have shared on Github. Links are provided in the key resources table. Additional information: Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

Source database ID

WoS ID
WOS:001344567900001
Scopus ID
2-s2.0-85207379308
Other database ID
, PMID: 39524335