Abstract
In this study functional magnetic resonance imaging (fMRI) was used to examine cerebral activity patterns in relation to increasing mental load of a working memory task. Aim of the experiment was to distinguish nonspecific task-related processes from specific workload processes analytically. Twelve healthy volunteers engaged in a spatial n-back task with four levels. FMRI data were acquired with the 3D-PRESTO pulse sequence. Analysis entailed a two-step multiple regression algorithm, which was specifically designed to measure and separate load-sensitive and load-insensitive activity simultaneously, while preserving the original high spatial resolution of the fMRI signal. Load-sensitive and load-insensitire activity was found in both dorsolateral-prefrontal and parietal cortex, predominantly bilaterally, and in the anterior cingulate. As expected, the left primary sensorimotor cortex showed predominantly load-insensitive activity. Load-sensitive activity reflects specific working memory functions, such as temporary retention and manipulation of information, while load-insensitive activity reflects supportire functions, such as visual orientation, perception, encoding, and response selection and execution. Good performance was correlated with a large area of load-sensitive activity in anterior cingulate, and with a small area of load-insensitive activity in the right parietal cortex. The findings indicate that non-specific and specific working memory processes co-localize and are represented in multiple frontal and parietal regions. Implication of this analytical strategy for application in research on psychiatric disorders is discussed. (C) 2000 Academic Press.
| Original language | English |
|---|---|
| Pages (from-to) | 688-697 |
| Number of pages | 10 |
| Journal | NeuroImage |
| Volume | 12 |
| Issue number | 6 |
| DOIs | |
| State | Published - 2000 |
| Externally published | Yes |
Keywords
- Anterior cingulate
- Parametric design
- Parietal cortex
- Prefrontal cortex
- Working memory
- fMRI
- n-back task
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