A situated approach to cognitive interaction modelling

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Transmitting and decoding facial expressions.

Considering the human face as a transmitter of expression signals, if it has evolved to optimize transmission, the basic facial expressions should have minimal overlap in their information. Considering the brain as a decoder of expression signals, if it has evolved to optimize categorization of expressions, it should be efficient with the information available from the transmitter for the task. Here, we characterize the information underlying the recognition of the six basic facial expression signals and evaluate how efficiently each expression is decoded by the underlying brain structures

Observed, executed, and imagined action representations can be decoded from ventral and dorsal areas

Previous functional magnetic resonance imaging (fMRI) research on action observation has emphasized the role of putative mirror neuron areas such as Broca's area, ventral premotor cortex, and the inferior parietal lobule. However, recent evidence suggests action observation involves many distributed cortical regions, including dorsal premotor and superior parietal cortex. How these different regions relate to traditional mirror neuron areas, and whether traditional mirror neuron areas play a special role in action representation, is unclear. Here we use multi-voxel pattern analysis (MVPA) to show that action representations, including observation, imagery, and execution of reaching movements: (1) are distributed across both dorsal (superior) and ventral (inferior) premotor and parietal areas; (2) can be decoded from areas that are jointly activated by observation, execution, and imagery of reaching movements, even in cases of equal-amplitude blood oxygen level-dependent (BOLD) responses; and (3) can be equally accurately classified from either posterior parietal or frontal (premotor and inferior frontal) regions. These results challenge the presumed dominance of traditional mirror neuron areas such as Broca's area in action observation and action representation more generally. Unlike traditional univariate fMRI analyses, MVPA was able to discriminate between imagined and observed movements from previously indistinguishable BOLD activations in commonly activated regions, suggesting finer-grained distributed patterns of activation