Publications

Applied Filters: First Letter Of Last Name: K Reset
2 Publications

K

Kroger, J. K., Nystrom, L. E., Cohen, J. D., & Johnson-Laird, P. N. (2008). Distinct neural substrates for deductive and mathematical processing. Brain Research, 1243, 86–103. https://doi.org/10.1016/j.brainres.2008.07.128
In an effort to clarify how deductive reasoning is accomplished, an fMRI study was performed to observe the neural substrates of logical reasoning and mathematical calculation. Participants viewed a problem statement and three premises, and then either a conclusion or a mathematical formula. They had to indicate whether the conclusion followed from the premises, or to solve the mathematical formula. Language areas of the brain (Broca s and Wernicke s area) responded as the premises and the conclusion were read, but solution of the problems was then carried out by non-language areas. Regions in right prefrontal cortex and inferior parietal lobe were more active for reasoning than for calculation, whereas regions in left prefrontal cortex and superior parietal lobe were more active for calculation than for reasoning. In reasoning, only those problems calling for a search for counterexamples to conclusions recruited right frontal pole. These results have important implications for understanding how higher cognition, including deduction, is implemented in the brain. Different sorts of thinking recruit separate neural substrates, and logical reasoning goes beyond linguistic regions of the brain.
Krueger, P. M., van Vugt, M. K., Simen, P., Nystrom, L. E., Holmes, P. J., & Cohen, J. D. (2017). Evidence accumulation detected in BOLD signal using slow perceptual decision making. Journal of Neuroscience Methods, 281, 21–32. https://doi.org/10.1016/j.jneumeth.2017.01.012
Background We assessed whether evidence accumulation could be observed in the BOLD signal during perceptual decision making. This presents a challenge since the hemodynamic response is slow, while perceptual decisions are typically fast. New method Guided by theoretical predictions of the drift diffusion model, we slowed down decisions by penalizing participants for incorrect responses. Second, we distinguished BOLD activity related to stimulus detection (modeled using a boxcar) from activity related to integration (modeled using a ramp) by minimizing the collinearity of GLM regressors. This was achieved by dissecting a boxcar into its two most orthogonal components: an “up-ramp” and a “down-ramp.” Third, we used a control condition in which stimuli and responses were similar to the experimental condition, but that did not engage evidence accumulation of the stimuli. Results The results revealed an absence of areas in parietal cortex that have been proposed to drive perceptual decision making but have recently come into question; and newly identified regions that are candidates for involvement in evidence accumulation. Comparison with existing methods Previous fMRI studies have either used fast perceptual decision making, which precludes the measurement of evidence accumulation, or slowed down responses by gradually revealing stimuli. The latter approach confounds perceptual detection with evidence accumulation because accumulation is constrained by perceptual input. Conclusions We slowed down the decision making process itself while leaving perceptual information intact. This provided a more sensitive and selective observation of brain regions associated with the evidence accumulation processes underlying perceptual decision making than previous methods.