Inferring mental states from neuroimaging data: From reverse inference to large-scale decoding
By Russell A. Poldrack. Neuron, 2011
743 citations recorded by the source corpus.
A common goal of neuroimaging research is to use imaging data to identify the mental processes that are engaged when a subject performs a mental task. The use of reasoning from activation to mental functions, known as “reverse inference”, has been previously criticized on the basis that it does not take into account how selectively the area is activated by the mental process in question. In this Perspective, I outline the critique of informal reverse inference, and describe a number of new developments that provide the ability to more formally test the predictive power of neuroimaging data.
Subfields: Cognitive Neuroscience
View Paper: https://www.semanticscholar.org/paper/e11b399db7c2b274c55c2a7615bdb192f6e82ffb
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In Cognitive Neuroscience
Citations in the corpus
- Neural changes underlying successful second language word learning: An fMRI study (2015, background): “Recent interests in large-scale brain networks point to a new framework for understanding distinct vs. overlapping neural systems, and to identify the dynamic interactions among neural systems for both normal and impaired brain functions (Bressler & Menon, 2010; Poldrack, 2011; Sporn, 2010).”
- Conceptual and Methodological Issues in Research on Mindfulness and Meditation (2015, background): “Many commentators (e.g., Poldrack, 2011) have cautioned about the hazards of using imaging measures to make inferences about psychological function and in the case of mindfulness, which is not consensually defined to begin with, those cautions are particularly significant.”
- From brain maps to cognitive ontologies: informatics and the search for mental structure (2015, neutral): “D ow nl oa de d fro m w w w .a nn ua lre vi ew s.o rg A cc es s p ro vi de d by U ni ve rs ity o f P en ns yl va ni a on 0 9/ 28 /1 6.”
- Comparing spatial null models for brain maps (2021, positive): “…to terms that overlapped with those defined in the Cognitive Atlas, an ontological database for defining and relating cognitive processes ( https://www.cognitiveatlas.org/concepts ; Poldrack 2011; Poldrack et al. 2011; Poldrack and Yarkoni 2016 ; refer to Table S1 for a full list of terms).”
- Neural network of cognitive emotion regulation — An ALE meta-analysis and MACM analysis (2013, methodology): “…meta-analysis, but can also be used to validate new paradigms or analyze co-occurring networks via MACM (Laird et al., 2009a) and, in this context for formal reverse inference on associated functions via functional decoding (Cieslik et al., 2012; Poldrack, 2011; Rottschy et al., 2012).”
- Neural Coding of Cognitive Control: The Representational Similarity Analysis Approach. (2020, background): “The key region of interest was the anterior midcingulate cortex (aMCC), a region that has appeared functionally ubiquitous [89] and challenging to characterize [90].”
- On testing for spatial correspondence between maps of human brain structure and function (2018, neutral): “We note that this discussion is in no way meant to imply that these cortical regions are not also involved in other functions (Poldrack, 2011).”
- Considerations for conducting developmental neuroimaging research on mental health topics (2025, unknown): “Neuroimaging results can suffer from “ reverse inference ” - the presumption that the engagement of a particular brain region equates to the presence of a given cognitive construct [92].”