Novices and experts show distinct differences in the performance of many tasks. Experts may perform a task quickly and accurately with seemingly little attention or effort, whilst novices will perform the same task more slowly and with great effort. The transition from novice to expert performance occurs only after extended practice and has been conceptualized as a transition from controlled to automatic processing, and has been modeled as a reduction in attention or cognitive resources. Alternatively, based on findings relating to learning in the domain of number arithmetic, it has also been modeled as a transition from an algorithmic, or computationally-based process, to the use of memory retrieval.
However, relatively few studies have investigated the changes in brain activity associated with such a transition. In this study, the Steady-State Probe Topography technique was used to investigate differences in the topography of the Steady-State Visual Evoked Potential (SSVEP) between an unpracticed and a well-practiced analogue of number arithmetic, Alphabet arithmetic.
Subjects showed decreases in response time with practice that followed a power law and were suggestive of automatization. During initial, unpracticed performance of the task, processing of the Alphabet Arithmetic equations was characterised by increased SSVEP amplitude and decreased latency in frontal regions, whilst after extended practice, performance was characterised by reduced SSVEP amplitude and increased latency. It is suggested that the frontal activity during the initial, unpracticed stage of the task implicates a role for working memory, whilst the amplitude decrease and latency increase observed in the well-practiced task may reflect a reduction in excitation, consistent with ideas of an improvement in brain efficiency, and possibly an increase in inhibitory processes.
| Identifer | oai:union.ndltd.org:ADTP/216516 |
| Date | January 1999 |
| Creators | Hocking, Christopher Anthony, Christopher.Hocking@med.monash.edu.au |
| Publisher | Swinburne University of Technology. |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
| Rights | http://www.swin.edu.au/), Copyright Christopher Anthony Hocking |
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