Optimized Multi-scale fMRI Neuromark Templates derived from very large data (N~100K) was released in March, 2023 and is here supplied with three different model orders:
- A low order Independent Component Network (ICN) template, created from 25 components, yielding 11 non-artifactual networks. The network template is downloaded by clicking following link, Neuromark_fMRI_2.0_modelorder-25.nii, including a label file at Neuromark_fMRI_2.0_modelorder-25.txt.
- A high order Independent Component Network (ICN) template, created from 175 components, yielding 58 non-artifactual networks. The network template is downloaded by clicking following link, Neuromark_fMRI_2.0_modelorder-175.nii, including the label file Neuromark_fMRI_2.0_modelorder-175.txt.
- A multi-scale order Independent Component Network (ICN) template, created from 25, 50, 75, 100, 125, 150, 175, 200 components, yielding 105 non-artifactual and overlapping networks and can be downloaded by clicking following link, Neuromark_fMRI_2.1_modelorder-multi.nii, including the label file Neuromark_fMRI_2.1_modelorder-multi.txt.
- A. Iraji, Z. Fu, A. Faghiri, M. Duda, J. Chen, S. Rachakonda, T. DeRamus, P. Kochunov et. al. “Canonical and Replicable Multi-Scale Intrinsic Connectivity Networks in 100k+ Resting-State fMRI Datasets”, bioRxiv, 2022, DOI: https://doi.org/10.1101/2022.09.03.506487
- Y. Du, Z. Fu, J. Sui, S. Gao, Y. Xing, D. Lin, M. Salman, A. Abrol, M. A. Rahaman, J. Chen, L. E. Hong, P. Kochunov, E. A. Osuch, V. D. Calhoun, for the Alzheimer’s Disease Neuroimaging Initiative, “NeuroMark: An automated and adaptive ICA based pipeline to identify reproducible fMRI markers of brain disorders” Neuroimage Clin, vol. 28, p. 102375, 2020, PMC7509081.
Filtered Sliding Window Correlation. Please see Victor M. Vergara, PhD and Vince D Calhoun, PhD, “Filtered Correlation and Allowed Frequency Spectra in Dynamic Functional Connectivity”, Journal of Neuroscience Methods, July 2020.
Autism Aggregate ICA map and labels used in paper:
Z. Fu, Y. Tu, X. Di, Y. Du, J. Sui, B. B. Biswal, Z. Zhang, N. de Lacy, V. D. Calhoun, “Transient increased thalamic-sensory connectivity and decreased whole-brain dynamism in autism”, Neuroimage 190, 2019, 191-204
Resting State Aggregate ICA maps used in papers:
- B. Rashid, E. Damaraju, G. D. Pearlson and V. D. Calhoun, “Dynamic connectivity states estimated from resting fMRI Identify differences among Schizophrenia, bipolar disorder, and healthy control subjects”, Front Hum Neurosci. 2014; 8: 897.
- B. Rashid, M. Arabshirani, E. Damaraju, M. Cetin, R. Miller, G. D. Pearlson and V. D. Calhoun, “Classification of schizophrenia and bipolar patients using static and dynamic resting-state fMRI brain connectivity”, NeuroImage, Volume 134, 1 July 2016, Pages 645-657.
Data visualization in the neurosciences: overcoming the curse of dimensionality. Click here for more information
- E. A. Allen, E. B. Erhardt, V. D. Calhoun. “Data visualization in the neurosciences: overcoming the curse of dimensionality”, Neuron, 74(4), 603-608, 2012.
Mean ICA components from Stevens, V. D. Calhoun, G. D. Pearlson, and K. A. Kiehl, “Brain network dynamics during error commission,” Hum.Brain Map., vol. 30, pp. 24-37, 2009