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The brain uses the same neural networks to engage in conscious and unconscious learning

05.11.2002


MRI used in a breakthrough study to explore how we gather information

How do we learn? At the same time, when learning is conscious, does the brain engage in learning based on experience? Many scientists have believed that the two processes are independent of each other. Now, new research findings published in the current edition of the Journal of Neurophysiology, suggest otherwise.
Background


Procedural learning, such as perceptual-motor sequence learning, is thought to be an obligatory consequence of practiced performance and to reflect adaptive plasticity in the neural systems mediating performance. Prior neuroimaging studies, however, have found that sequence learning accompanied with awareness (declarative learning) of the sequence activates entirely different brain regions than learning without awareness of the sequence (procedural learning). However, conflicts between imaging and behavioral studies have not resolved whether true independence exists between the two brain functions.

The Study

A breakthrough imaging study has created conditions that allow for such direct comparison of simultaneous procedural and declarative learning. A team of physiologists used an MRI to discover whether declarative learning does or does not prevent learning in procedural memory systems. They created conditions in which subjects were simultaneously learning different sequences under implicit or explicit instructions.

The authors of "Direct Comparison of Neural Systems Mediating Conscious and Unconscious Skill Learning," are Daniel B. Willingham, from the University of Virginia, Charlottesville, VA; Joanna Salidis, from Stanford University, Stanford, CA; and John D.E. Gabriel, representing both institutions. Their findings appeared in the September 2002 edition of the Journal of Neurophysiology, a journal of the American Physiological Society (APS).

Methodology

Ten males and nine females, all right-handed, participated in the study. Participants ranged in ages from 19 to 30 years old.

The serial response time task (SSRTT) paradigm circle appeared in one of four squares, arranged horizontally in the middle of the computer screen. Subjects pressed the response key (in a row of 4) with the index and middle finger of both hands, each finger mapped to a key. Each stimulus stayed on the screen for 600 ms with a 250-ms interstimulus interval. Sequences (each 12-units long) were randomly chosen for each subject from a corpus of 576 sequences, each of which followed the following constraints: equal frequency of each position, no direct repetitions, and no runs (e.g., 1234) or trills (1212) of more than three positions in a row. Stimuli were presented in blocks of 24 with a 2.2-s inter block interval. Each block started with a 520-ms fixation mark (a cross) between the middle two boxes.

Subjects were explicitly instructed that red circles denoted a repeating sequence of locations and that black circles denoted a random ordering of locations. Prior to scanning, subjects responded to a single repeating sequence that always determined the location of the red circles. This sequence constituted the "explicit-overt" condition because subjects were aware of the repeating sequence appearing in red.

Prior to scanning, subjects also responded to black circles. Unbeknownst to subjects, some black circles actually appeared in a second repeating sequence (the others appeared in random locations). This sequence constituted the "implicit" condition because subjects were unaware that there was a repeating sequence for black circles. Thus, prior to scanning, subjects simultaneously learned one sequence explicitly and another sequence implicitly.

Results
The behavioral results demonstrate that: (1) subjects were conscious of the explicit sequence; (2) unconscious of the implicit sequence; and (3) unconscious of the explicit sequence when it appeared covertly in black.

Subjects were aware of the sequence in the explicit-overt condition. Throughout scanning, they performed it faster than the random or implicit sequences. They also learned it declaratively, indicated by the fact that they selected it among the distracters (random and implicit sequences) in the postscan recognition test as a sequence they had seen before. The subjects also learned the sequence procedurally in the implicit condition. They responded faster to the implicit sequence than to the random sequences, but slower to it than to the explicit sequence.

Nevertheless, even at the end of the experiment, they failed to recognize the implicit sequence above chance. The postscan recognition test was designed to be highly sensitive to any awareness of the sequence: a graded rating scale was used so subjects could show even partial declarative knowledge. Furthermore, subjects made the recognition judgments simultaneously with performing the sequences, showing a concurrent dissociation between their procedural (RTs faster than random) and declarative knowledge (no difference from random sequences). Finally, subjects were not aware of the explicit sequence in the explicit-covert condition.

Conclusions

The behavioral and neuroimaging results from this study demonstrate that procedural learning in this paradigm is an obligatory consequence of performance. In the present paradigm, procedural memory (implicit greater than random condition) activated left prefrontal cortex, left inferior parietal cortex, and right putamen. The same regions were also active in the explicit-covert condition in which the sequence had been declaratively learned. Although the degree of activation differed in some of these structures, the neural network that enhanced performance for the implicit and for the explicit-covert conditions was virtually the same. The explicit covert activation, therefore, documents procedural modulation that occurred under conditions of declarative learning and awareness in the prescan skill learning session.

These findings suggest a more refined interpretation of the parietal cortex’s role in spatial attention in this task. Spatial attention may facilitate orienting to targets in either an externally or internally driven fashion. In the implicit and explicit covert conditions, orienting is externally driven by the appearance of the target. In sum, the role of cognitive load in procedural learning is not yet clear, and may differ across different varieties of procedural knowledge such as motor skill, classification, and classical conditioning.

The present findings indicate that when awareness and performance are well controlled, modulation occurs in the same neural network for procedural learning whether that learning is or is not accompanied by declarative knowledge. Declarative learning, however, activates many additional brain regions. This conclusion suggests an integral role for the procedural system in some skills requiring physical practice regardless of whether learning occurs with or without declarative memory.


###
Source: September 2002 edition of the Journal of Neurophysiology, a journal of the American Physiological Society (APS).

The American Physiological Society (APS) was founded in 1887 to foster basic and applied science, much of it relating to human health. The Bethesda, MD-based Society has more than 10,000 members and publishes 3,800 articles in its 14 peer-reviewed journals every year.

Donna Krupa | EurekAlert!
Further information:
http://www.faseb.org/aps/

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