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NeuroMark dFNC: Transferable Dynamic-State Templates for Subject-Specific and Frequency-Resolved Chronnectomics
Esfahani MM, Seraji M, Salem S, Jensen KM, Fu Z, Adali T, Wang Y, Calhoun V.. bioRxiv, 2026-10-17
Topic: Brain imaging, connectivity and assessment
Dynamic functional network connectivity (dFNC) commonly identifies recurring connectivity states from resting-state fMRI, but states derived independently in each dataset lack guaranteed correspondence across studies and cannot be directly estimated in new participants. We introduce NeuroMark dFNC, which extends the NeuroMark principle of prior-guided network estimation to dynamic connectivity by using reproducible reference states as priors for estimating corresponding subject-specific states. Reference-state templates were derived from UK Biobank using windowed functional network connectivity and time-frequency moments (TFMs), with split-sample reproducibility evaluated for k-means, independent component analysis (ICA), and principal component analysis (PCA) template-generation approaches. Constrained ICA then used the templates to estimate subject-specific state patterns and continuous loadings in independent FBIRN schizophrenia and ADNI Alzheimer's disease cohorts. ICA loadings were calibrated by their contribution to reconstruction of the original feature matrix. Fractional occupancy and conditional mean dwell time were calculated from the state with the largest absolute calibrated loading at each observation. The predefined templates avoided the need for dataset-specific state discovery and post-hoc state matching. In both clinical cohorts, the analysis identified state-dependent, distributed edgewise differences and differences in selected temporal summaries. Nominal frequency-resolved findings varied across states and moment-frequency bins and were treated as exploratory. NeuroMark dFNC provides a common state space for cross-cohort comparison while retaining subject-specific connectivity patterns and continuous state expression.
Key findings
- Fractional occupancy and conditional mean dwell time were calculated from the state with the largest absolute calibrated loading at each observation.
- The predefined templates avoided the need for dataset-specific state discovery and post-hoc state matching.
- In both clinical cohorts, the analysis identified state-dependent, distributed edgewise differences and differences in selected temporal summaries.
- Nominal frequency-resolved findings varied across states and moment-frequency bins and were treated as exploratory.
- NeuroMark dFNC provides a common state space for cross-cohort comparison while retaining subject-specific connectivity patterns and continuous state expression.
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Study details
- Study designpost-hoc analysis
- Evidence strengthModerate
How this study scored 16/100
Preprint — not yet peer-reviewed. It scored 24 on the same rubric, but non-peer-reviewed sources are capped at 16, so it shows as 16. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 15 of the 62 points we could judge it on, which is 24 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 2 / 10 | Tier 4 — not a peer-reviewed journal (bioRxiv) |
| Journal's citation record | 0 / 4 | Not a journal article, so the journal's record does not count |
| Study design | 0 / 12 | Design recorded as “post-hoc analysis”, which our rubric does not rank (not stated in the record — scored 0) |
| Strength of evidence | 3 / 5 | Rated “moderate” in our summary |
| Peer-review validation | 4 / 10 | Preprint — not yet peer-reviewed. Hosted on a preprint server. |
| How recent | 5 / 5 | 2026 — within 1 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 1 / 2 | Not in PubMed, but has a DOI |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Points | 15 / 62 | Scored on 12 of 20 parts. We have no data for the rest, so they are left out: 15 of the 62 points we could judge it on is 24 out of 100. |
| Total | 24 / 100 | Capped to 16 because this is not a peer-reviewed article. |
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Read the original
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Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record names 8 authors; APA and Vancouver show the first six, BibTeX and the downloads carry all of them. Check the citation against the original before you use it.
APA 7th
Esfahani, M. M., Seraji, M., Salem, S., Jensen, K. M., Fu, Z., Adali, T., et al. (2026). NeuroMark dFNC: Transferable Dynamic-State Templates for Subject-Specific and Frequency-Resolved Chronnectomics. bioRxiv. https://doi.org/10.64898/2026.10.12.758630
Vancouver
Esfahani MM, Seraji M, Salem S, Jensen KM, Fu Z, Adali T, et al. NeuroMark dFNC: Transferable Dynamic-State Templates for Subject-Specific and Frequency-Resolved Chronnectomics. bioRxiv. 2026. doi:10.64898/2026.10.12.758630.
BibTeX
@article{esfahani2026-b8c364bb,
author = {Esfahani, M. M. and Seraji, M. and Salem, S. and Jensen, K. M. and Fu, Z. and Adali, T. and Wang, Y. and Calhoun, V.},
title = {{NeuroMark dFNC: Transferable Dynamic-State Templates for Subject-Specific and Frequency-Resolved Chronnectomics}},
journal = {bioRxiv},
year = {2026},
doi = {10.64898/2026.10.12.758630},
url = {https://doi.org/10.64898/2026.10.12.758630}
}
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