Brain can switch to ‘automatic pilot’ during learning

New studies suggest that humans might prefer to switch their brains to automatic pilot whenever possible to conserve their cogitating resources. For example, when learning skills such as arithmetic, the brain doesn’t necessarily reach back into its basic calculating skills for each problem, suggested the researchers who made the finding. Rather, the brain builds a repertoire of rote responses to frequently encountered problems that it can use to save time and effort, they said.From Duke University:Evidence suggests that the brain can switch to ‘automatic pilot’ during learning

New studies suggest that humans might prefer to switch their brains to automatic pilot whenever possible to conserve their cogitating resources.

For example, when learning skills such as arithmetic, the brain doesn’t necessarily reach back into its basic calculating skills for each problem, suggested the researchers who made the finding. Rather, the brain builds a repertoire of rote responses to frequently encountered problems that it can use to save time and effort, they said.

Put anatomically, the new experiments suggest the human brain might rapidly circumvent deliberative processing in higher brain regions, called the cortex, as it learns to respond appropriately and automatically to stimuli such as repeated tasks.

Researchers published their findings online Feb. 29, 2004, in the journal Nature. Lead author on the paper was Ian Dobbins, assistant professor of psychological and brain sciences at Duke University. Other authors were David Schnyer and Mieke Verfaellie at the Boston University School of Medicine, and Daniel Schacter of Harvard University.

In their studies, the researchers sought to distinguish between two theories of how the cerebral cortex manages responding to stimuli such as tasks.

Both theories seek to understand the well-known phenomenon that when people are asked to perform a classification or decision on an object, they become more efficient with repetition of the task. When subject’s brains are imaged during such tasks, they show reduced activity — called “neural priming” — as the task is learned and performance improves.

Such imaging is done using functional magnetic resonance imaging (fMRI) — in which harmless magnetic fields and radio signals are used to detect regions of brain activity as subjects are performing tasks.

The most popular theory about neural priming holds that this reduction in cortical activity is due to “tuning” by the cortex of its information about objects involved in the task. This theory holds that the cortex is refining its knowledge about the object being learned about — eliminating attributes of the object not needed in the task.

However, another theory proposed Dobbins and his colleagues is that the cortex is actually just refining learning of a particular response, and not refining its information about the object itself.

“In other words, we become more rapid with repetition of a decision task because we rapidly recover our prior responses, which under most circumstances is an appropriate and efficient strategy,” Dobbins said. “Thus oftentimes the real work in making a decision about an object happens on the first encounter; subsequent trials, however, can be more easily solved using a short-cut method of simply recovering the previous response.”

“What’s fascinating about neural priming is that it occurs even in people with amnesia, who can’t even remember events or objects,” Dobbins said. “They also show this increase in performance with repetition despite being unable to consciously remember the previous encounters,” Dobbins said. “Such findings have been the basis for the belief that we have separate systems for certain types of memory that function independently.”

To test for this alternative theory, the researchers first asked subjects to judge whether objects such as an acorn, a stroller, a bicycle pump or a shuttlecock were “bigger than a shoebox.” By using some items over and over, and introducing new items, they could study how the brain was responding to familiar versus new items and how performance was improving as subjects became skilled at the decision.

After analyzing the cortical activity during this task, they switched the task — asking subjects to now judge whether many of the same objects were “smaller than a shoebox.” Finally, they then restored the original “bigger-than-a-shoebox” question.

Thus, in the experiment, most of the objects in the tasks would remain the same — and the type of information upon which decisions were made would remain the same — but the task involving the objects was subtly modified such that using prior responses either was or was not appropriate.

“So, the idea is that, if the brain’s representation of the size of the object is what is being rapidly recovered with repetition, just changing the direction of the question from a ‘bigger than’ to a ‘smaller than’ question should not make a difference in performance,” said Dobbins. “Since the subject can immediately recover the size of the object, he or she should be able to rapidly perform the comparison.

“However, if performance improves and neural activity declines because we rapidly recover our previous responses, then this sort of change should severely disrupt performance and preclude neural activity reductions because the subjects can’t use their earlier responses when the question direction changes.”

The researchers got the idea for the experiment from their own personal experiences with the tasks.

“We were going through these size comparisons, and we had this subjective feeling that after a few times, we weren’t really thinking about the size of the object. We were just executing a response,” he said. Such learning becomes automatic “such that at some point, you’re just retrieving responses from memory; you’re not actually performing the deliberations that were necessary on the first decision,” Dobbins said. “It’s like you know that two plus two equals four, not because you’re working through the solution; you’re recovering the answer from memory.”

When the researchers performed their “cue-flipping” experiments on volunteers whose brains were being scanned by fMRI, “we saw a characteristic pattern of item-specific learning, in which performance would slow down when we flipped the cue around, but sped back up when we put it back the way it was,” Dobbins said.

Particularly surprising, Dobbins said, “was that when we looked at areas of the cortex known to be involved in registering objects, it looked as though subjects were responding to a new item whenever the cue made the earlier response inappropriate. So, it appears from these data that people doing such tasks aren’t really rapidly recovering information about object properties when the tasks are repeated; but instead they are just giving their previous response.”

Dobbins emphasized that “these findings don’t really eliminate the idea of tuning, but they lead to another way of looking at learning. They suggest that the brain is set up to circumvent the algorithmic or deliberative processes of decision making wherever possible.

“For example, the task of adding numbers by counting them up is very time-intensive and requires a lot of attention. Since the brain has limited resources, it means the brain can’t do other things. So, in bypassing this and similar general algorithms wherever possible, the brain not only executes responses more rapidly, but it uses fewer resources enabling one to attend to other problems in the environment.”

According to Dobbins, the researchers’ finding contributes to a basic understanding of the difference between “executive control” strategies that govern responses involving recovery of information and conscious deliberation — versus those that appear to be governed by rapidly recovering and executing prior responses without the need for reflection.

The new findings could enrich understanding of the learning and memory process, he said. Also, the discovery opens new research pathways to understanding the neural machinery underlying the object-related deliberative strategy of processing information versus the automatic strategy, and how the brain rapidly switches from one to the other.


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