Research note: Peak velocity timing invariance

Summary Subjects used arm movements to move a dot on a visual display into a predefined target area. Measures of the peak velocity values and the timing of the peaks were taken for the initial (preplanned) and the immediately subsequent (corrective) phases of movement. In both phases the value of the maximum velocity depended on task parameters such as amplitude. However, the time of the peak of each phase relative to its onset was invariant. Some implications of these observations for the nature of motor programs are discussed.     

Peak shift in concurrent schedules

Pigeons were exposed to two keys, a main key and a changeover key. Initially non-differential training was given in which pecking the main key was reinforced on a variable-interval 2-min schedule when the key displayed the first stimulus, a black line on a blue background, and was reinforced on an identical but independent variable-interval 2-min schedule when the key displayed a plain blue stimulus. Later, differential training was given in which pecking the main key was reinforced on a variable-interval 2-min schedule when the first stimulus was displayed; and was reinforced on a variable-interval 10-min schedule when a second stimulus, a black line of another orientation on a blue background, was displayed. During non-differential and differential training, each peck on the changeover key changed the stimulus on the main key. Generalization tests were given before and after the differential training. These consisted of presentations on the main key of seven orientations of the black line on the blue background, including the first and second stimuli, with no reinforcements being given. Changeover-key pecks changed the stimuli on the main key. Generalization gradients were obtained using three measures: time spent, responses, and response rate in the presence of each test stimulus. Typically, maximum values on these measures occurred to stimuli away from the first in a direction opposite the second stimulus, and minimum values occurred to stimuli away from the second in a direction opposite the first.     

Effects of varying length of stimulus series and response scale upon response latency,response uncertainty,and transmitted information

A 3 by 3 orthogonal design was employed t o study the interrelations among response latency (RL), response uncertainty (E_R), and transmitted information Nine groups of Ss judged the size of 5, 20, or 40 projected squares in terms of 5, 20, or 40 response categories. Patterns of change in ER and RL over the three stimulus series were differentially effected by increases in the number of available response categories. The increase from 5 to 20 response categories produced, for successively longer stimulus series, a constantly increasing change in E_R; the further increase from 20 to 40 categories produced a contrasting, constantly decreasing change in E_R. The same two changes in number of response categories produced the same pattern of change in RL over the 5- and 20-stimulus series but reversed the pattern for the 40-stimulus series. Correlations between E_R and RL ranged from .28 to .99 and tended to maximize when number of response categories equaled the number of stimuli. I_t was relatively low under all conditions. Within the 5- and 20-stimulus series, increases from 5 to 20 to 40 available responses increased RL in a negatively accelerated fashion but did not increase I_t. Within the 40-stimulus series, the same increases in number of available responses produced an essentially linear increase in both I_t and RL.     

Preference for unsegmented interreinforcement intervals in concurrent chains

Five pigeons were trained under concurrent-chain schedules in which a pair of independent, concurrent variable-interval 60-s schedules were presented in the initial link and either both variable-interval or both fixed-interval schedules were presented in the terminal link. Except for the baseline, one of the terminal-link schedules was always a two-component chained schedule and the other was either a simple or a tandem schedule of equal mean interreinforcement interval. The values of the fixed-interval schedules were either 15 s or 60 s; that of the variable-interval schedules was always 60 s. A 1.5-s changeover delay operated during the initial link in some conditions. The pigeons preferred a simple or a tandem schedule to a chain. For the fixed-interval schedules, this preference was greater when the fixed interval was 60 s than when it was 15 s. For the variable-interval schedules, the preferences were less pronounced and occurred only when the changeover delay was in effect. For a given type of schedule and interreinforcement interval, similar preferences were obtained whether the nonchained schedule was a tandem or simple schedule. The changeover delay generally inflated preference and lowered the changeover rate, especially when the terminal-link schedules were either short (15 s) or aperiodic (variable-interval). The results were consistent with the notion that segmenting the interreinforcement interval of a schedule into a chain lowers the preference for it.     

The nature of the association between diet and serum lipids in the community: a twin study.

Diet is commonly thought to be an environmental influence on serum lipid concentrations. This study evaluated whether total caloric and fat intake predict total cholesterol (TC), low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and triglyceride (TRIG) concentrations for environmental, as compared with genetic, reasons among 137 monozygotic and 67 dizygotic young adult twins. When genetic influences were controlled by correlating differences between monozygotic co-twins, a significant association remained between diet and TC, LDL, and HDL, suggesting that these dietary and serum lipid measures correlate for environmental reasons. Twin structural equation modeling confirmed these results. Overall, these results provide additional support for the hypothesis that diet is an environmental influence on TC, LDL, and HDL.