References

Voxelwise modeling (VM) is a framework to perform functional magnetic resonance imaging (fMRI) data analysis. Over the years, VM has led to many high profile publications [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15].

[1] Kay, K. N., Naselaris, T., Prenger, R. J., & Gallant, J. L. (2008).

Identifying natural images from human brain activity. Nature, 452(7185), 352-355.

[2] Naselaris, T., Prenger, R. J., Kay, K. N., Oliver, M., & Gallant, J. L. (2009).

Bayesian reconstruction of natural images from human brain activity. Neuron, 63(6), 902-915.

[3] Nishimoto, S., Vu, A. T., Naselaris, T., Benjamini, Y., Yu, B., & Gallant, J. L. (2011).

Reconstructing visual experiences from brain activity evoked by natural movies. Current Biology, 21(19), 1641-1646.

[4] Huth, A. G., Nishimoto, S., Vu, A. T., & Gallant, J. L. (2012).

A continuous semantic space describes the representation of thousands of object and action categories across the human brain. Neuron, 76(6), 1210-1224.

[5] Çukur, T., Nishimoto, S., Huth, A. G., & Gallant, J. L. (2013).

Attention during natural vision warps semantic representation across the human brain. Nature neuroscience, 16(6), 763-770.

[6] Çukur, T., Huth, A. G., Nishimoto, S., & Gallant, J. L. (2013).

Functional subdomains within human FFA. Journal of Neuroscience, 33(42), 16748-16766.

[7] Stansbury, D. E., Naselaris, T., & Gallant, J. L. (2013).

Natural scene statistics account for the representation of scene categories in human visual cortex. Neuron, 79(5), 1025-1034

[8] Huth, A. G., De Heer, W. A., Griffiths, T. L., Theunissen, F. E., & Gallant, J. L. (2016).

Natural speech reveals the semantic maps that tile human cerebral cortex. Nature, 532(7600), 453-458.

[9] de Heer, W. A., Huth, A. G., Griffiths, T. L., Gallant, J. L., & Theunissen, F. E. (2017).

The hierarchical cortical organization of human speech processing. Journal of Neuroscience, 37(27), 6539-6557.

[10] Lescroart, M. D., & Gallant, J. L. (2019).

Human scene-selective areas represent 3D configurations of surfaces. Neuron, 101(1), 178-192.

[11] Deniz, F., Nunez-Elizalde, A. O., Huth, A. G., & Gallant, J. L. (2019).

The representation of semantic information across human cerebral cortex during listening versus reading is invariant to stimulus modality. Journal of Neuroscience, 39(39), 7722-7736.

[12] Nunez-Elizalde, A. O., Huth, A. G., & Gallant, J. L. (2019).

Voxelwise encoding models with non-spherical multivariate normal priors. Neuroimage, 197, 482-492.

[13] Popham, S. F., Huth, A. G., Bilenko, N. Y., Deniz, F., Gao, J. S.,

Nunez-Elizalde, A. O., & Gallant, J. L. (2021). Visual and linguistic semantic representations are aligned at the border of human visual cortex. Nature Neuroscience, 24(11), 1628-1636.

[14] LeBel, A., Jain, S., & Huth, A. G. (2021).

Voxelwise encoding models show that cerebellar language representations are highly conceptual. Journal of Neuroscience, 41(50), 10341-10355.

[15] Dupré La Tour, T., Eickenberg, M., Nunez-Elizalde, A.O., & Gallant, J. L. (2022).

Feature-space selection with banded ridge regression. NeuroImage. https://doi.org/10.1016/j.neuroimage.2022.119728

Datasets

[3b] Nishimoto, S., Vu, A. T., Naselaris, T., Benjamini, Y., Yu, B., & Gallant, J. L. (2014).

Gallant Lab Natural Movie 4T fMRI Data. CRCNS.org. http://dx.doi.org/10.6080/K00Z715X

[4b] Huth, A. G., Nishimoto, S., Vu, A. T., Dupré la Tour, T., & Gallant, J. L. (2022).

Gallant Lab Natural Short Clips 3T fMRI Data. GIN. http://dx.doi.org/10.12751/g-node.vy1zjd

Packages

[p1] Dupré La Tour, T., Visconti di Oleggio Castello, M., & Gallant, J. L. (2024).

The Voxelwise Modeling framework: a tutorial introduction to fitting encoding models to fMRI data. https://doi.org/10.31234/osf.io/t975e

[p2] Dupré La Tour, T., Eickenberg, M., Nunez-Elizalde, A.O., & Gallant, J. L. (2022).

Feature-space selection with banded ridge regression. NeuroImage. https://doi.org/10.1016/j.neuroimage.2022.119728

[p3] Gao, J. S., Huth, A. G., Lescroart, M. D., & Gallant, J. L. (2015).

Pycortex: an interactive surface visualizer for fMRI. Frontiers in Neuroinformatics, 23. https://doi.org/10.3389/fninf.2015.00023

[p4] Nunez-Elizalde, A.O., Deniz, F., Dupré la Tour, T., Visconti di Oleggio Castello, M., and Gallant, J.L. (2021).

pymoten: scientific python package for computing motion energy features from video. Zenodo. https://doi.org/10.5281/zenodo.6349625