Decoding semantic representations in mind and brain.

State-of-the-art brain imaging studies have recently produced a variety of sometimes contradictory conclusions about the neural systems that support human semantic memory. Multivariate techniques deployed in this work adopt implicit or explicit assumptions that limit the types of signal they can detect, and thus the types of hypotheses they can test. We lay out the space of possible cognitive and neural representations and then critically review contemporary methods to determine which analyses can test which hypotheses. The results account for the heterogeneity of recent findings and identify an important empirical and methodological gap that makes it difficult to connect the imaging literature to neurocomputational models of semantic processing. A key goal for cognitive neuroscience is to understand the neurocognitive systems that support semantic memory. Recent multivariate analyses of neuroimaging data have contributed greatly to this effort, but the rapid development of these novel approaches has made it difficult to track the diversity of findings and to understand how and why they sometimes lead to contradictory conclusions. We address this challenge by reviewing cognitive theories of semantic representation and their neural instantiation. We then consider contemporary approaches to neural decoding and assess which types of representation each can possibly detect. The analysis suggests why the results are heterogeneous and identifies crucial links between cognitive theory, data collection, and analysis that can help to better connect neuroimaging to mechanistic theories of semantic cognition. [ABSTRACT FROM AUTHOR]