Reliability in Cognitive Neuroscience: A Meta-Meta-Analysis by William R. Uttal

By William R. Uttal

Cognitive neuroscientists more and more declare that mind pictures generated via new mind imaging applied sciences replicate, correlate, or characterize cognitive strategies. during this publication, William Uttal warns opposed to those claims, arguing that, regardless of its application in anatomic and physiological purposes, mind imaging examine has now not supplied constant facts for correlation with cognition. Uttal bases his argument on an in depth assessment of the empirical literature, pointing to variability in facts not just between matters inside person experiments but additionally within the new meta-analytical method that swimming pools facts from assorted experiments. This inconsistency of effects, he argues, has profound implications for the sphere, suggesting that cognitive neuroscientists haven't but confirmed their interpretations of the relation among mind task captured via macroscopic imaging thoughts and cognitive procedures; what could have seemed to be correlations could have basically been illusions of organization. He helps the view that the real correlates are positioned at a way more microscopic point of study: the networks of neurons that make up the brain.

Uttal contains out comparisons of the empirical info at numerous degrees of knowledge pooling, together with the meta-analytical. He argues that even if the belief turns out user-friendly, the duty of pooling information from varied experiments is very complicated, resulting in doubtful effects, and that little is received through it. Uttal's research indicates a necessity for cognitive neuroscience to reevaluate the complete firm of mind imaging-cognition correlational studies.

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Nevertheless, even for these small numbers and the resulting low power of their experimental protocols, experimenters often felt confident enough to publish their findings and presumably draw strong conclusions from their work. Given the unreliability of the typical brain image, this may have been a reckless strategy. Because of the relatively low power of many cognitive brain imaging experiments, there have been many recent attempts to develop powerful methods to further pool the outcome of a number of experiments.

Their meta-analysis was a fairly simple one typical of those in use at the time; they simply tabulated which side of the brain was active in the encoding and retrieval processes, respectively, in a series of 14 experiments using PET scans. In this and some other early attempts to pool data, a meta-analysis simply meant comparing or tabulating the results from a number of experiments in what was little more than a simple voting procedure. The results of their study were startling in their 16 Chapter 1 simplicity; all encoding activations occurred in the left hemisphere and all retrieval activation in the right hemisphere.

Indeed, the reasons for applying meta-analyses to neuroscientific data are fundamentally no different from those required in any other science displaying considerable variability. Among the first reported applications of a meta-analysis to brain image data was a study by Tulving, Kapur, Craik, Moscovitch, and Houle (1994) on hemispheric representation of encoding and retrieval processes as reflected in PET scans. Their meta-analysis was a fairly simple one typical of those in use at the time; they simply tabulated which side of the brain was active in the encoding and retrieval processes, respectively, in a series of 14 experiments using PET scans.

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