Warning: The NCBI web site requires JavaScript to function. more...
Generate a file for use with external citation management software.
The International WIC Institute bCollege of Computer Science, Beijing University of Technology, Beijing, China.
We investigated the effects of rule learning based on information granularity. Using two homogeneous Boolean arithmetic tasks, we examined parietal cortex activity during the calculation of labile and stabilized learning. The results revealed stability-related behavioral advantages in a comparison of granularity-based effects with labile learning of Boolean problems. The functional MRI results revealed that different regions within the parietal cortex exhibited increased activity while solving Boolean problems in both the conditions. The calculation of labile rule learning based on low-granularity Boolean rules was significantly correlated with activation in bilateral parietal cortex, whereas stable rule learning based on high-granularity Boolean rules was correlated with activation in the left parietal cortex.
Your browsing activity is empty.
Activity recording is turned off.
Turn recording back on