| dc.creator |
Duncan, John |
|
| dc.creator |
Chylinski, Daphne |
|
| dc.creator |
Mitchell, Daniel |
|
| dc.creator |
Bhandari, Apoorva |
|
| dc.date |
2018-04-05T15:06:15Z |
|
| dc.date |
2018-04-05T15:06:15Z |
|
| dc.date |
2017-05-16 |
|
| dc.date.accessioned |
2019-03-20T08:23:12Z |
|
| dc.date.available |
2019-03-20T08:23:12Z |
|
| dc.identifier |
https://www.repository.cam.ac.uk/handle/1810/274592 |
|
| dc.identifier |
10.17863/CAM.21729 |
|
| dc.identifier.uri |
https://evidence.thinkportal.org/handle/123456789/32259 |
|
| dc.description |
Compositionality, or the ability to build complex cognitive structures from simple parts, is fundamental to the power of the human mind. Here we relate this principle to the psychometric concept of fluid intelligence, traditionally measured with tests of complex reasoning. Following the principle of compositionality, we propose that the critical function in fluid intelligence is splitting a complex whole into simple, separately attended parts. To test this proposal, we modify traditional matrix reasoning problems to minimize requirements on information integration, working memory, and processing speed, creating problems that are trivial once effectively divided into parts. Performance remains poor in participants with low fluid intelligence, but is radically improved by problem layout that aids cognitive segmentation. In line with the principle of compositionality, we suggest that effective cognitive segmentation is important in all organized behavior, explaining the broad role of fluid intelligence in successful cognition. |
|
| dc.description |
This research was supported by Medical Research Council intramural program MC-A060-5PQ10. |
|
| dc.language |
eng |
|
| dc.publisher |
National Academy of Sciences |
|
| dc.publisher |
Proceedings of the National Academy of Sciences |
|
| dc.subject |
cognitive compositionally |
|
| dc.subject |
fluid intelligence |
|
| dc.subject |
focused attention |
|
| dc.subject |
problem solving |
|
| dc.title |
Complexity and compositionality in fluid intelligence. |
|
| dc.type |
Article |
|