Quantitative and qualitative analyses of clock drawings in Alzheimer's and Huntington's disease.

Although visuoconstructive impairment has been reported in both Alzheimer's (DAT) and Huntington's (HD) disease, there is little knowledge concerning how this cognitive deficit differs quantitatively and qualitatively in these two progressive dementias. To address this issue, the present study compared performances on the Clock Drawing Test (CDT: command and copy) of 25 DAT patients, 25 equally demented HD patients, and 25 elderly normal controls (NC). In the command condition, both patients groups were significantly impaired compared to the NC group. Although there was no significant difference between DAT and HD patients' total quantitative scores, a qualitative error analysis revealed a number of dissociations between the two patient groups. Graphic difficulties, very common in HD patients, were virtually absent in DAT patients; in contrast, conceptual errors were almost exclusively seen in DAT patients and were related to the severity of their dementia. Perseveration and "stimulus-bound" responses were also more frequent in DAT patients, and both groups made visuospatial errors. In the copy condition, the DAT, but not the HD, patients evidenced a marked improvement in performance. These results indicate that while both DAT and HD patients have significant visuoconstructive difficulties even in the early stages of their disorders, the specific cognitive processes underlying their quantitative impairments are quite different. It is possible that the DAT patients' conceptual errors are yet another indicator of the deterioration of their semantic knowledge.     

On the Relation Between Time Perception and the Timing of Motor Action: Evidence for a Temporal Oscillator Controlling the Timing of Movement

Studies of time estimation have provided evidence that human time perception is determined by an internal clock containing a temporal oscillator and have also provided estimates of the frequency of this oscillator (Treisman, Faulkner, Naish, & Brogan, 1992; Treisman & Brogan, 1992). These estimates were based on the observation that when the intervals to be estimated are accompanied by auditory clicks that recur at certain critical rates, perturbations in time estimation occur. To test the hypothesis that the mechanisms that underlie the perception of time and those that control the timing of motor performance are similar, analogous experiments were performed on motor timing, with the object of seeing whether evidence for a clock would be obtained and if so whether its properties resemble those of the time perception clock. The prediction was made that perturbations in motor timing would be seen at the same or similar critical auditory click rates. The experiments examined choice reaction time and typing. The results support the hypothesis that a temporal oscillator paces motor performance and that this oscillator is similar to the oscillator underlying time perception. They also provide an estimate of the characteristic frequency of the oscillator.     

Environmental factors in suicide in long-term care facilities.

One major purpose of this study was to identify environmental factors related to suicide in long-term care facilities. Questionnaires were mailed to a random sample of administrators at 1,080 facilities. Information was collected on facility characteristics, overt suicide, and intentional life-threatening behavior. Chi-square analyses revealed 4 environmental characteristics related to suicidal behavior and deaths from suicide: staff turnover, size, auspices, and per diem cost. More suicides occurred in larger facilities and facilities with higher staff turnover. Religious or "other" facilities experienced more suicidal deaths than public or private facilities; facilities charging less experienced more deaths.     

Factors related to sleep quality in healthy elderly women.

Elderly women in subjectively good health--free of acute illness and major sleep pathologies--who were self-identified as good (n = 22) and poor (n = 16) sleepers were compared on measures of physical health, psychological symptoms, psychosocial status, and life-style. Poor sleepers reported longer sleep latencies, less total sleep time, more nonrestorative sleep, and more daytime fatigue than did good sleepers. Sleep recordings confirmed subjective reports, with shorter total sleep times and trends for lower sleep efficiency, longer sleep latencies, and more wake-after-sleep onset among women with subjective poor sleep. Poor sleepers also were more frequent users of sedative-hypnotic medications in the past. Current medication use, alcohol and caffeine use, daytime napping, and exercise were equivalent in both groups. Psychosocial status failed to discriminate groups. Poor sleepers reported significantly more psychological symptoms than did good sleepers. The levels of both psychological symptoms and sleep disturbance were mild.     

Low-dimensional chaos maps learning in a model neuropil (olfactory bulb).

Quantification of a chaotic system can be made by calculating the correlation dimension (D2) of the data that the system generates (Packard et al., 1980). The D2 algorithm, however, requires stationarity of the generator, a feature that biological data rarely reflect (Mayer-Kress et al., 1988). So we developed the "point correlation dimension" (PD2), an algorithm that accurately tracks D2 in linked data of different dimensions (Carpeggiani et al., 1991). We now present a mathematical argument that, for stationary data, individual PD2s converge to D2 and we demonstrate that the algorithm rejects contributions made by bursts of noise. Data were obtained from the surface of the olfactory bulb of the conscious rabbit (64 electrodes, 640 Hz each, 1.3 sec epochs) before and after presentation of a novel or habituated odor. D2 could be calculated in only 1 of 10 novel-odor trials, whereas PD2 could be calculated in all. Both algorithms indicated that a novel odor evokes a spatially uniform dimensional increase. The PD2 uniquely exhibited the dimensional decreases that occur during inspiration and the gradients of mean dimension present during the nonstimulated control state. These control gradients remained unchanged without odor experience, but showed spatially specific PD2 increases following odor habituation. It is interpreted that, 1) the PD2 is sensitive, accurate, and appropriate for dimensional assessment of biological data, 2) that during analysis of unfamiliar information a single global process is transiently evoked in the neuropil, and 3) after experience multiple spatially specific processes tonically map the sites of learning.     

Brief report: An extension of the sequential alternating treatment design using reversals with subjects not available concurrently

This brief report proposes an extension of the traditional Alternating Treatments Design that would be acceptable to use in hospital and residential settings where subjects are often not concurrently available. Concerns about the inability of traditional designs to work in these special situations and the emergence of a “scientist–practitioner split” are discussed. An example of how the Extended Alternating Treatments Design might be used is provided.     

Application of chaos theory to biology and medicine

The application of “chaos theory” to the physical and chemical sciences has resolved some long-standing problems, such as how to calculate a turbulent event in fluid dynamics or how to quantify the pathway of a molecule during Brownian motion. Biology and medicine also have unresolved problems, such as how to predict the occurrence of lethal arrhythmias or epileptic seizures. The quantification of a chaotic system, such as the nervous system, can occur by calculating the correlation dimension (D2) of a sample of the data that the system generates. For biological systems, the point correlation dimension (PD2) has an advantage in that it does not presume stationarity of the data, as the D2 algorithm must, and thus can track the transient non-stationarities that occur when the systems changes state. Such non-stationarities arise during normal functioning (e.g., during an event-related potential) or in pathology (e.g., in epilepsy or cardiac arrhythmogenesis). When stochastic analyses, such as the standard deviation or power spectrum, are performed on the same data they often have a reduced sensitivity and specifity compared to the dimensional measures. For example, a reduced standard deviation of heartbeat intervals can predict increased mortality in a group of cardiac subjects, each of which has a reduced standard deviation, but it cannot specify which individuals will or will not manifest lethal arrhythmogenesis; in contrast, the PD2 of the very same data can specify which patients will manifest sudden death. The explanation for the greater sensitivity and specificity of the dimensional measures is that they aredeterministic, and thus are moreaccurate in quantifying the time-series. This accuracy appears to be significant in detecting pathology in biological systems, and thus the use of deterministic measures may lead to breakthroughs in the diagnosis and treatment of some medical disorders.     

Low-dimensional chaos maps learning in a model neuropil (olfactory bulb)

Quantification of a chaotic system can be made by calculating the correlation dimension (D2) of the data that the system generates (Packard et al., 1980). The D2 algorithm, however, requires stationarity of the generator, a feature that biological data rarely reflect (Mayer-Kress et al., 1988). So we developed the “point correlation dimension” (PD2), an algorithm that accurately tracks D2 in linked data of different dimensions (Carpeggiani et al., 1991). We now present a mathematical argument that, for stationary data, individual PD2s converge to D2 and we demonstrate that the algorithm rejects contributions made by bursts of noise. Data were obtained from the surface of the olfactory bulb of the conscious rabbit (64 electrodes, 640 Hz each, 1.3 sec epochs) before and after presentation of a novel or habituated odor. D2 could be calculated in only 1 of 10 novel-odor trials, whereas PD2 could be calculated in all. Both algorithms indicated that a novel odor evokes a spatially uniform dimensional increase. The PD2 uniquely exhibited the dimensional decreases that occur during inspiration and the gradients of mean dimension present during the nonstimulated control state. These control gradients remained unchanged without odor experience, but showed spatially specific PD2 increases following odor habituation. It is interpreted that, 1) the PD2 issensitive, accurate, and appropriate for dimensional assessment of biological data, 2) that during analysis of unfamiliar information a singleglobal process is transiently evoked in the neuropil, and 3) after experience multiplespatially specific processes tonically map the sites of learning. Grant Support: National Institutes of Health, HL 31164 and NS27745