fMRI time series in orbitofrontal cortex during face-house state-space task.

This dataset contains the preprocessed fMRI time series within orbitofrontal cortex (OFC), the design matrix and event timing information of the task performed in the work of Schuck et al., Neuron 2016: Schuck, Nicolas W., Ming Bo Cai, Robert C. Wilson, and Yael Niv. "Human orbitofrontal cortex represents a cognitive map of state space." Neuron 91, no. 6 (2016): 1402-1412.
In the task, participants watched overlapping face and house images and judged the age of one category to be young or old (meaning modern or ancient for houses). The specific rule of which category to judge required participants to keep track of which state out of 16 in total they are in. The result support the theory that orbitofrontal cortex encodes task-relevant hidden states of environments.
The data of 24 healthy human participants used in the trial-wise analysis in the paper are included. Except for the first participant who had four successful runs of data, all participants had five runs of data. The fMRI time series were slice-timing corrected and spatially realigned to correct for head motion within and across experiment runs. An evaluation of an algorithm of Bayesian representational similarity analysis (BRSA) against other approaches of representational similarity analysis by Cai, et al. PLOS Computational Biology, 2019[3] was partly based on this dataset. The work suggested that performing RSA based on activity pattern estimated from the same runs suffer from statistical bias in the similarity matrix, and recommended either BRSA or cross-run RSA. Paper referenced:
[3] Cai, Ming Bo, Nicolas W. Schuck, Jonathan W. Pillow, and Yael Niv. "Representational structure or task structure? Bias in neural representational similarity analysis and a Bayesian method for reducing bias." bioRxiv (2018): 347260.