In some cases, reverse inference Tenofovir datasheet underlies the central conclusion of a paper. For example, Takahashi et al. (2009) examined the neural correlates of the experience of envy and schadenfreude. They found that envy was associated with activation in the anterior cingulate cortex, in which they note, “Cognitive conflicts or social pain are processed” (p. 938), whereas schadenfreude was associated with activation in the ventral striatum, “a central node of reward processing” (p. 938). The abstract concludes as follows: “Our findings document mechanisms of painful emotion, envy, and a rewarding reaction, schadenfreude,” in which the psychological states (i.e.,
pain or reward) are inferred primarily from activation in specific regions (anterior cingulate or ventral striatum). This is just one of many examples of reverse Ku-0059436 chemical structure inference that are evident in the neuroimaging literature, and even the present author is not immune. Reverse inference is also common in public presentations of imaging research. A prime example occurred during the US Presidential Primary elections in 2007, when the New York Times published an op-ed by a group of researchers titled “This is Your Brain on Politics” ( Iacoboni
et al., 2007). This piece reported an unpublished study of potential swing voters who were shown a set of videos of the candidates while being scanned using fMRI. Based on these imaging data, the authors made a number of claims about the voters’ feelings regarding the candidates. For example, “When our subjects viewed photos of Mr. Thompson, we saw activity in the superior temporal sulcus and the inferior frontal cortex, both areas involved in empathy,”
and, “Looking at photos of Mitt Romney led to activity in the amygdala, a brain area linked to anxiety.” More recently, another New York Times op-ed by a marketing writer used unpublished fMRI data to infer that people are “in love” with their iPhones ( Lindstrom, 2011). Clearly, the desire to “read minds” using neuroimaging is strong. In 2006, I published a paper that challenged the common use of reverse inference in the neuroimaging all literature (Poldrack, 2006; for a similar earlier critique, see Aguirre, 2003). Since the publication of those critiques, “reverse inference” has gradually become a bad word in some quarters, though very often a citation to those papers is used as a fig leaf to excuse the use of reverse inference. At the same time, a number of researchers have argued that it is a fundamentally important research tool, especially in areas such as neuroeconomics and social neuroscience, in which the underlying mental processes may be less well understood (e.g., Young and Saxe, 2009). In what follows, I will lay out and update the argument against reverse inference as it is often practiced in the literature.
Related posts:
- 11 Eighteen cases of morphoeic basal cell carcinoma and 19 cases
- Irinotecan less common mutations included 13 cases of various P loop mutations and 5 cases of M351T
- Viral DNA synthesis Reverse transcription and integration of your
- Kenneth M Yamada making use of the following forward and reverse
- In cases like this when there is a tie in efficacy, the highest d