The effects of sleep deprivation on the neural substrates of cognition are poorly understood. Here we used functional magnetic resonance imaging to measure the effects of 35 hours of sleep deprivation on cerebral activation during verbal learning in normal young volunteers. On the basis of a previous hypothesis, we predicted that the prefrontal cortex (PFC) would be less responsive to cognitive demands following sleep deprivation. Contrary to our expectations, however, the PFC was more responsive after one night of sleep deprivation than after normal sleep. Increased subjective sleepiness in sleep-deprived subjects correlated significantly with activation of the PFC. The temporal lobe was activated after normal sleep but not after sleep deprivation; in contrast, the parietal lobes were not activated after normal sleep but were activated after sleep deprivation. Although sleep deprivation significantly impaired free recall compared with the rested state, better free recall in sleep-deprived subjects was associated with greater parietal lobe activation. These findings show that there are dynamic, compensatory changes in cerebral activation during verbal learning after sleep deprivation and implicate the PFC and parietal lobes in this compensation.

Thirteen normal volunteers were studied with fMRI during arithmetic performance after a normal night of sleep and following sleep deprivation (SD). Aims included determining whether the prefrontal cortex (PFC) and the parietal lobe arithmetic areas are vulnerable to the effects of SD. After a normal night of sleep, activation localized to the bilateral PFC, parietal lobes and premotor areas. Following SD, activity in these regions decreased markedly, especially in the PFC. Performance also dropped. Data from the serial subtraction task are consistent with Horne's PFC vulnerability hypothesis but, based on this and other studies, we suggest the localized, functional effects of SD in the brain may vary, in part, with the specific cognitive task.

The original California Verbal Learning Test (CVLT) employed a semantic clustering index that used the words recalled during a given trial as the baseline for calculating expected values of chance clustering (recall-based expectancy). Although commonly used in cognitive psychology, clustering indices that use recall-based calculations of expectancy are implied by the assumption that organizational processes do not occur until after words are retrieved from memory. This assumption contradicts the generally held assumptions among neuropsychologists that (1) organization is an antecedent to recall, and (2) increases in the use of organizational strategies will result in better recall performance. After reviewing a brief history of clustering metrics, we used Monte Carlo simulations, informative examples, and patient data to examine clustering indices that use the word list as a baseline for calculating expectancy and propose these list-based expectancy measures as a refinement of the clustering indices used on the original CVLT. These indices are used on the recently published CVLT-II. (JINS, 2002, 8, 425-435.)