Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

The brain can be decomposed into large-scale functional networks, but the specific spatial topographies of these networks and the names used to describe them vary across studies. Such discordance has hampered interpretation and convergence of research findings across the field. We have developed the Network Correspondence Toolbox (NCT) to permit researchers to examine and report spatial correspondence between their novel neuroimaging results and multiple widely used functional brain atlases. We provide several exemplar demonstrations to illustrate how researchers can use the NCT to report their own findings. The NCT provides a convenient means for computing Dice coefficients with spin test permutations to determine the magnitude and statistical significance of correspondence among user-defined maps and existing atlas labels. The adoption of the NCT will make it easier for network neuroscience researchers to report their findings in a standardized manner, thus aiding reproducibility and facilitating comparisons between studies to produce interdisciplinary insights.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11937327PMC
http://dx.doi.org/10.1038/s41467-025-58176-9DOI Listing

Publication Analysis

Top Keywords

network correspondence
8
correspondence toolbox
8
novel neuroimaging
8
report findings
8
toolbox quantitative
4
quantitative evaluation
4
evaluation novel
4
neuroimaging brain
4
brain decomposed
4
decomposed large-scale
4

Similar Publications

The 2024 Nobel Prizes in Chemistry and Physics mark a watershed moment in the convergence of artificial intelligence (AI) and molecular biology. This article explores how AI, particularly deep learning and neural networks, has revolutionized protein science through breakthroughs in structure prediction and computational design. It highlights the contributions of 2024 Nobel laureates John Hopfield, Geoffrey Hinton, David Baker, Demis Hassabis, and John Jumper, whose foundational work laid the groundwork for AI tools such as AlphaFold.

View Article and Find Full Text PDF

Transcription factors (TFs) are essential proteins that regulate gene expression by specifically binding to transcription factor binding sites (TFBSs) within DNA sequences. Their ability to precisely control the transcription process is crucial for understanding gene regulatory networks, uncovering disease mechanisms, and designing synthetic biology tools. Accurate TFBS prediction, therefore, holds significant importance in advancing these areas of research.

View Article and Find Full Text PDF

Feature binding in biological and artificial vision.

Trends Cogn Sci

September 2025

Department of Cognitive and Psychological Science, Brown University, Thayer Street, Providence, RI 02906, USA; Robert J. and Nancy D. Carney Institute for Brain Sciences, Brown University, Angell Street, Providence, RI 02906, USA.

View Article and Find Full Text PDF