Neural Decoding
Neural decoding is a data analysis method in which a pattern classifier is trained to predict which experimental condition was present from patterns of neural activity. Applying these methods to recordings from populations of neurons makes it possible to ask what information is present in a brain region, and how that information changes over time. Much of my work has gone into developing software that makes these analyses straightforward to run, and into applying them to recordings from high level visual and cognitive brain regions.
Software
The Neural Decoding Toolbox
A Matlab package that makes it easy to apply population decoding analyses to neural data. Documentation, tutorials and datasets are available at readout.info, and the source code is on GitHub.
NeuroDecodeR
An R package that implements the same style of decoding analyses in a tidyverse-friendly form. The package documentation includes several tutorials. The package is available on CRAN and the source code is on GitHub.
Tutorials
A tutorial on neural decoding that I have given at the Brains, Minds and Machines summer course at the Marine Biological Laboratory in Woods Hole:
Brains, Minds and Machines Summer Course – Tutorial 4: Neural Decoding (video)
Accompanying materials on MIT OpenCourseWare
Papers
Methods and software
Meyers E (2024). NeuroDecodeR: a package for neural decoding in R. Frontiers in Neuroinformatics, 17:1275903.
Meyers E (2013). The Neural Decoding Toolbox. Frontiers in Neuroinformatics, 7:8.
Meyers E, and Kreiman G (2011). Tutorial on Pattern Classification in Cell Recording. In: Visual population codes. Kreigeskorte, N., and Kreiman, G. (eds.), MIT Press.
Studies using decoding
Meyers E (2018). Dynamic population coding and its relationship to working memory. Journal of Neurophysiology, 120:2260–2268.
Meyers E, Borzello M, Freiwald W, Tsao D (2015). Intelligent Information Loss: The Coding of Facial Identity, Head Pose, and Non-Face Information in the Macaque Face Patch System. Journal of Neuroscience, 35(18):7069–81.
Meyers E, Qi XL, Constantinidis C (2012). Incorporation of new information into prefrontal cortical activity after learning working memory tasks. Proceedings of the National Academy of Sciences, 109:4651–4656.
Zhang Y*, Meyers E*, Bichot N, Serre T, Poggio T, and Desimone R (2011). Object decoding with attention in inferior temporal cortex. Proceedings of the National Academy of Sciences, 108:8850–8855.
Meyers E, Freedman D, Kreiman G, Miller E, Poggio T (2008). Dynamic Population Coding of Category Information in Inferior Temporal and Prefrontal Cortex. Journal of Neurophysiology, 100:1407–1419.
A full list is on the publications page.