Rapid Transfer of Abstract Rules to Novel Contexts in Human Lateral Prefrontal Cortex

Flexible, adaptive behavior is thought to rely on abstract rule representations within lateral prefrontal cortex (LPFC), yet it remains unclear how these representations provide such flexibility. We recently demonstrated that humans can learn complex novel tasks in seconds. Here we hypothesized that this impressive mental flexibility may be possible due to rapid transfer of practiced rule representations within LPFC to novel task contexts. We tested this hypothesis using functional MRI and multivariate pattern analysis, classifying LPFC activity patterns across 64 tasks. Classifiers trained to identify abstract rules based on practiced task activity patterns successfully generalized to novel tasks. This suggests humans can transfer practiced rule representations within LPFC to rapidly learn new tasks, facilitating cognitive performance in novel circumstances

Testing Simulation Theory with Cross-Modal Multivariate Classification of fMRI Data

The discovery of mirror neurons has suggested a potential neural basis for simulation and common coding theories of action perception, theories which propose that we understand other people's actions because perceiving their actions activates some of our neurons in much the same way as when we perform the actions. We propose testing this model directly in humans with functional magnetic resonance imaging (fMRI) by means of cross-modal classification. Cross-modal classification evaluates whether a classifier that has learned to separate stimuli in the sensory domain can also separate the stimuli in the motor domain. Successful classification provides support for simulation theories because it means that the fMRI signal, and presumably brain activity, is similar when perceiving and performing actions. In this paper we demonstrate the feasibility of the technique by showing that classifiers which have learned to discriminate whether a participant heard a hand or a mouth action, based on the activity patterns in the premotor cortex, can also determine, without additional training, whether the participant executed a hand or mouth action. This provides direct evidence that, while perceiving others' actions, (1) the pattern of activity in premotor voxels with sensory properties is a significant source of information regarding the nature of these actions, and (2) that this information shares a common code with motor execution

MVPA Significance Testing When Just Above Chance, and Related Properties of Permutation Tests

data and paper for 2017 Workshop on Pattern Recognition in Neuroimaging (PRNI

Efficient evaluation of the Open QC task fMRI dataset

source and compiled files to accompany "Efficient evaluation of the Open QC task fMRI dataset" doi: 10.3389/fnimg.2023.107027

MVPA Meanderings

Files and code to accompany posts on MVPA Meanderings (mvpa.blogspot.com)

Reward Motivation Enhances Task Coding in Frontoparietal Cortex

Data and analyses associated with Etzel JA, Cole MW, Zacks JM, Kay KN, & Braver TS (2015). Reward Motivation Enhances Task Coding in Frontoparietal Cortex. Cerebral Cortex PMID: 25601237 doi:10.1093/cercor/bhu32

Mechanisms of Age-Related Changes in ER (MARCER)

temporary placeholder for the MARCER projec