We employ multiple analytical approaches, mainly Multivariate Pattern (MVPA) and Representational Similarity Analysis (RSA) of neuroimaging data, to advance our understanding of how the brain represents information across several cognitive contexts.
Arco, J.E., González-García, C., Díaz-Gutiérrez, P., Ramírez, J. & Ruz, M. (2018). Influence of activation pattern estimates and statistical significance tests in fMRI decoding analysis. Journal of Neuroscience Methods, 308, 248–260.
Díaz-Gutiérrez, P., Gilbert, S. J., Arco, J. E., Sobrado, A. & Ruz, M. (2020). Neural representation of current and intended task sets during sequential judgements on human faces. NeuroImage, 204, 116219
González-García, C., Arco, J. E., Palenciano, A. F., Ramírez, J.& Ruz, M. (2017) Encoding, preparation and implementation of novel complex verbal instructions. Neuroimage 1;148:264-273.
López-García, D., Sobrado, A., Peñalver, JMG., Górriz, JM., Ruz, M. (in press) Multivariate pattern analysis techniques for electroencephalography data to study Flanker interference effects. International Journal of Neural Systems. https://doi.org/10.1142/S0129065720500240
Ortiz-Tudela, J., Bergmann, J., Bennett, M., Ehrlich, I., Muckli, L. & Shing, Y. L. (2023) Concurrent contextual and time-distant mnemonic information co-exist as feedback in the human visual cortex. https://doi.org/10.1016/j.neuroimage.2022.119778
Palenciano, A. F., González-García, C., Arco, J. E., Pessoa, L. & Ruz, M. (2019) Representational organization of novel task sets during proactive encoding. Journal of Neuroscience, 719–725