Resting-state fMRI

Default mode network (DMN)

(Raichle et al. 2001)

Resting state activity

(Fox et al. 2005)

Reminder: the checkerboard experiment

Resting state fluctuations

Typical analysis

• Preprocessing

• Extensive denoising

• Functional “connectivity”

• Other measures

  • Network science characteristics

  • Functional connectivity density

Preprocessing

Like in a typical fMRI experiment, see the corresponding chapter

Denoising using a GLM

Typical signals that get regressed out:

• Motion (relignment parameters)

• nth order derivatives of the realignment parameters

• Physiology regressors (respiration and heart beat)

  • Derivatives of white matter and CSF signals

  • Derivatives of pre-recorded pulse and respiration

Physiology recording

Oxymeter; Image credit: Siemens

Respiration belt; Image credit: Siemens

Raw data

Regressors

See also: https://visualneuroscience.github.io/mri/physiology/

Spine coil respiration sensor

(Wilding, Ischebeck, and Zaretskaya 2024)

Seed-to-voxel connectivity

(Wilding, Ischebeck, and Zaretskaya 2023)

ROI-to-ROI connectivity

Parcellation schemes

(Glasser et al. 2016)

Independent component analysis

Network parcellation

(Yeo et al. 2011)

(Yeo et al. 2011)

Independent component analysis, procedure similar to factor analysis

Functional connectivity density mapping

(Tomasi and Volkow 2010)

lFCD: within a local viscinity of a voxel gFCD: global, i.e. across the whole brain

Graph theory

(Sporns 2010) (accessible through UniKat); see also: (Bassett and Sporns 2017)

Thresholded correlation matrix

ROI pairs that correlate above a certain threshold are considered connected.

The difference between FCD and rich club coefficient is that the FSD is related to the number of connections, and rich club coefficient to a number of connections specifically to other highly connected areas.

Software

References

Bassett, Danielle S, and Olaf Sporns. 2017. “Network Neuroscience.” Nature Neuroscience 20 (3): 353–64. https://doi.org/10.1038/nn.4502.

Fox, Michael D., Abraham Z. Snyder, Justin L. Vincent, Maurizio Corbetta, David C. Van Essen, and Marcus E. Raichle. 2005. “The Human Brain Is Intrinsically Organized into Dynamic, Anticorrelated Functional Networks.” Proceedings of the National Academy of Sciences 102 (27): 9673–78. https://doi.org/10.1073/pnas.0504136102.

Glasser, Matthew F., Timothy S. Coalson, Emma C. Robinson, Carl D. Hacker, John Harwell, Essa Yacoub, Kamil Ugurbil, et al. 2016. “A Multi-Modal Parcellation of Human Cerebral Cortex.” Nature 536 (7615): 171–78. https://doi.org/10.1038/nature18933.

Raichle, Marcus E., Ann Mary MacLeod, Abraham Z. Snyder, William J. Powers, Debra A. Gusnard, and Gordon L. Shulman. 2001. “A Default Mode of Brain Function.” Proceedings of the National Academy of Sciences 98 (2): 676–82. https://doi.org/10.1073/pnas.98.2.676.

Sporns, Olaf. 2010. “Networks of the Brain,” October. https://doi.org/10.7551/mitpress/8476.001.0001.

Tomasi, Dardo, and Nora D. Volkow. 2010. “Functional Connectivity Density Mapping.” Proceedings of the National Academy of Sciences 107 (21): 9885–90. https://doi.org/10.1073/pnas.1001414107.

Wilding, Marilena, Anja Ischebeck, and Natalia Zaretskaya. 2023. “Resting-State Neural Correlates of Visual Gestalt Experience.” Cerebral Cortex, February. https://doi.org/10.1093/cercor/bhad029.

———. 2024. “Respiration Recording for fMRI: Breathing Belt Versus Spine Coil Sensor.” Imaging Neuroscience 2. https://doi.org/10.1162/imag_a_00239.

Yeo, B T Thomas, Fenna M Krienen, Jorge Sepulcre, Mert R Sabuncu, Danial Lashkari, Marisa Hollinshead, Joshua L Roffman, et al. 2011. “The Organization of the Human Cerebral Cortex Estimated by Intrinsic Functional Connectivity.” Journal of Neurophysiology 106 (3): 1125–65. https://doi.org/10.1152/jn.00338.2011.