A review of the empirical evidence shows that unreliability of research findings relating brain images and cognitive processes is widespread in cognitive neuroscience. Cognitive neuroscientists increasingly claim that brain images generated by new brain imaging technologies reflect, correlate, or represent cognitive processes. In this book, William Uttal warns against these claims, arguing that, despite its utility in anatomic and physiological applications, brain imaging research has not provided consistent evidence for correlation with cognition. Uttal bases his argument on an extensive review of the empirical literature, pointing to variability in data not only among subjects within individual experiments but also in the new meta-analytical approach that pools data from different experiments. This inconsistency of results, he argues, has profound implications for the field, suggesting that cognitive neuroscientists have not yet proven their interpretations of the relation between brain activity captured by macroscopic imaging techniques and cognitive processes; what may have appeared to be correlations may have only been illusions of association. He supports the view that the true correlates are located at a much more microscopic level of analysis: the networks of neurons that make up the brain. Uttal carries out comparisons of the empirical data at several levels of data pooling, including the meta-analytical. He argues that although the idea seems straightforward, the task of pooling data from different experiments is extremely complex, leading to uncertain results, and that little is gained by it. Uttal's investigation suggests a need for cognitive neuroscience to reevaluate the entire enterprise of brain imaging-cognition correlational studies.
In this book, William R. Uttal continues his analysis and critique of theories of mind.
This perspective has led to what some have referred to the reliability paradox for several classical cognitive paradigms, including the Stroop task, Flanker task and several other widely used measures (Hedge et al., 2018).
The Year in Cognitive Neuroscience ....
http://www.nap.edu/catalog/12177.html The National Academy of Sciences is a private, nonprofit, self-perpetuating society of distinguished scholars engaged in scientific and engineering research, dedicated to the furtherance of science ...
The hypothesis is subsequently confirmed and consolidated in long-term memory as a subsequently recoverable hypothesis through activations in the ventral striatum when it is deemed reliable. Conversely, the hypothesis is rejected and ...
Recent findings indicate that metacognitive processes are similarly sensitive to this hierarchical structure [38]. ... Reliability. Formal accounts of categorical decisions, such as the DDM, are often illustrated by analogy to court of ...
Philosophical Transactions of the Royal Society of London, Series B, Biological Sciences, 358, 459–473. Frost, D. O. (1990). ... Galaburda, A. M., Sherman, G. F., Rosen, G. D., Aboitiz, F., & Geschwind, N. (1985).
This volume provides a frame of reference in which to consider the effects of cognitive abnormalities on violent behaviour and the impact on legal decision-makers.
The book features the main schemes of the Monte Carlo method and presents various examples of its application, including queueing, quality and reliability estimations, neutron transport, astrophysics, and numerical analysis.
A data-informed PIF hierarchy for modelbased human reliability analysis. Reliability Engineering and System Safety, 108, 154–174. Haynes, J.D., Sakai, K., Rees, G., Gilbert, S., Firth, C. and Passingham, R.E. (2007).