Correlations of cortical activation and behavior during the application of newly learned categories.
Large individual differences are commonly observed during the early stages of category learning in both functional MRI (fMRI) activation maps and behavioral data. The current investigation characterizes this variability by correlating the volume of activation with behavioral performance. Healthy subjects were trained to classify patterns of random dots into categories. Training was carried out using a 4-choice categorization task with feedback. Functional MRI was performed prior to any training and then following each of 3 training sessions. The fMRI sessions involved the presentation of 3 separate paradigms which required the skill imparted by the training to determine whether two patterns of dots belonged to the same category. Contrasts between the 3 paradigms allowed the examination of the effects of training and of familiarity with the task. For fMRI performed with those materials used during training, increases in the volume of activation were observed initially. As behavioral performance continued to improve, reductions in activation were observed across regions involved in visuospatial processing and spatial attention. These reductions in activation were observed only for those materials used in training and only after high levels of performance were achieved. The magnitude of these reductions in activation correlated with each individual's own rate of learning. The present data support the observation that at least two stages of cortical activation underlie the use of newly learned categories. The first, recruitment of nearby tissue, is observed as initial increases in the volumes of activation. These initial stages of recruitment are followed by specialization across the same network which is observed as a reduction in activation with continued improvements in behavioral performance.
Little
Deborah M
DM
Department of Neurology and Rehabilitation and Anatomy and Cell Biology, Center for Stroke Research, University of Illinois at Chicago, Chicago, IL 60612, USA. little@uic.edu
Thulborn
Keith R
KR
D000328:Adult; D000704:Analysis of Variance; D001519:Behavior / Q000502:physiology*; D001921:Brain / Q000098:blood supply / Q000502:physiology*; D001931:Brain Mapping; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D007206:Individuality; D007858:Learning / Q000502:physiology*; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D010100:Oxygen / Q000097:blood; D010364:Pattern Recognition, Visual / Q000502:physiology*; D010775:Photic Stimulation / Q000379:methods; D011930:Reaction Time / Q000502:physiology; D015203:Reproducibility of Results; D013223:Statistics as Topic
D010100:Oxygen