Investigating accuracy of trade-off and its neural correlates, how well can we trade apples for oranges?

As humans, we perform trade-off of incommensurable concepts on daily basis. For example, many of purchase decisions, especially those involving complex products with multiple incommensurable attributes, require us to trade qualities of two or more attributes against each other like in: ?trading apples for oranges?. But, how does human brain maps these concepts of different currencies on each other has not been directly investigated even though literature from consumer research, various psychophysical tasks and decision-making models suggest that our ability to trade-off might be limited and prone to biases. Two experiments combining the Surplus-identification task with the random dot-motion-task, using colour and motion direction discrimination as its two attributes, investigate this question. Experiment 1 investigates origins of potential cognitive bottleneck by focusing on both the precision and biases of trade-off while Experiment 2 investigates neural correlates of trade-off with aim of isolating decision variable representing accumulation of evidence, as suggested by sequential sampling models, during trade-off. It was discovered that large decrease in precision results from mapping incommensurate attributes on each other and not from need to assess quality of two attributes simultaneously. This mapping process is also prone to number of biases. The isolated decision variable differed from those reported in previous studies using perceptual decision tasks and was not modulated by trial difficulty. This suggests that mapping incommensurate attributes is more complex process to that of simple perceptual decisions possibly requiring additional cognitive processes. The highly approximate nature of trade-off involving incommensurate concepts draws parallel with research on cognitive capacity and it also raises a doubt about validity of decision making models assuming calculation of internal ?value? associated with each option