Rewarding imperfect motor performance reduces adaptive changes.

Could a pat on the back affect motor adaptation? Recent studies indeed suggest that rewards can boost motor adaptation. However, the rewards used were typically reward gradients that carried quite detailed information about performance. We investigated whether simple binary rewards affected how participants learned to correct for a visual rotation of performance feedback in a 3D pointing task. To do so, we asked participants to align their unseen hand with virtual target cubes in alternating blocks with and without spatial performance feedback. Forty participants were assigned to one of two groups: a 'spatial only' group, in which the feedback consisted of showing the (perturbed) endpoint of the hand, or to a 'spatial & reward' group, in which a reward could be received in addition to the spatial feedback. In addition, six participants were tested in a 'reward only' group. Binary reward was given when the participants' hand landed in a virtual 'hit area' that was adapted to individual performance to reward about half the trials. The results show a typical pattern of adaptation in both the 'spatial only' and the 'spatial & reward' groups, whereas the 'reward only' group was unable to adapt. The rewards did not affect the overall pattern of adaptation in the 'spatial & reward' group. However, on a trial-by-trial basis, the rewards reduced adaptive changes to spatial errors.

Alignment to natural and imposed mismatches between the senses.

Does the nervous system continuously realign the senses so that objects are seen and felt in the same place? Conflicting answers to this question have been given. Research imposing a sensory mismatch has provided evidence that the nervous system realigns the senses to reduce the mismatch. Other studies have shown that when subjects point with the unseen hand to visual targets, their end points show visual-proprioceptive biases that do not disappear after episodes of visual feedback. These biases are indicative of intersensory mismatches that the nervous system does not align for. Here, we directly compare how the nervous system deals with natural and imposed mismatches. Subjects moved a hand-held cube to virtual cubes appearing at pseudorandom locations in three-dimensional space. We alternated blocks in which subjects moved without visual feedback of the hand with feedback blocks in which we rendered a cube representing the hand-held cube. In feedback blocks, we rotated the visual feedback by 5° relative to the subject's head, creating an imposed mismatch between vision and proprioception on top of any natural mismatches. Realignment occurred quickly but was incomplete. We found more realignment to imposed mismatches than to natural mismatches. We propose that this difference is related to the way in which the visual information changed when subjects entered the experiment: the imposed mismatches were different from the mismatch in daily life, so alignment started from scratch, whereas the natural mismatches were not imposed by the experimenter, so subjects are likely to have entered the experiment partly aligned.

Surface boundaries do not constrain a depth aftereffect.

We investigated whether a depth aftereffect is better explained in a surface-based organization of depth representation (Nakayama & Shimojo, 1992), where depth is represented in conjunction with surface features, rather than a coordinate-based organization, where depth is represented in conjunction with spatial position. Observers adapted to a stereogram depicting a surface with reference plane and were tested with a surface with either the same contour or position as the adaptation surface. The aftereffect did not depend on test surface position or contour. Thus, a depth aftereffect can be caused by a mechanism that does not depend on grouping by surface contour or position.

[Reasons for non-response of elderly Turkish, Moroccan and Dutch general practice patients on a postal depression screening]. / Redenen voor non-respons van oudere Turkse, Marokkaanse en Nederlandse huisartspatiënten op een schriftelijke Nederlandstalige depressievragenlijst.

BACKGROUND: Depression screening can improve identification and subsequent treatment of depression in general practice. Response of Turkish and Moroccan elderly is unknown. OBJECTIVES: (1) To assess the response of elderly Turkish and Moroccan general practice patients on a postal depression screening. (2) To trace reasons for non-response. METHOD: At 14 different primary care centres, elderly (55+) were screened with GDS-15. Turkish and Moroccan elderly were telephonically and house-to-house approached for tracing the reasons for non-response. RESULTS: Response rate Dutch elderly (n=6060; 62%), Turks (n= 39; 31%) and Moroccans (n=117; 34%). Most important reason for non-response among Turkish elderly was "temporary other place of staying" (Turkey). Among Moroccans it was "illiteracy". CONCLUSION: Response is very low by elderly migrants compared to Dutch elderly. The reasons for non-response implicate that other means to approach migrants' sub-populations should be sought.

Assessment of body composition by bioelectrical impedance in a population aged greater than 60 y.

Body composition was measured in a group of 35 healthy men and 37 healthy women aged 60-83 y. Body mass index (BMI) in men was 25.0 +/- 2.2 kg/m2 (means +/- SD) and in women, 25.9 +/- 3.2 kg/m2. BMI was low in relation to body fat percentage as determined by skinfold-thickness measurements or densitometry in comparison with the relation found in younger adults. Mean body fat percentage of the male subjects (aged 70.4 +/- 5.2 y) as determined by densitometry was 31.0 +/- 4.5%, whereas in women (aged 68.0 +/- 5.2 y) it was 43.9 +/- 4.3%. Body impedance correlated with fat-free mass (FFM). The best prediction formulas for the FFM from body impedance and anthropometric variables were 1) FFM (kg) = (0.671 x 10(4) x H2/R) + 3.1S + 3.9 where H is body height (m), R is resistance (omega), and S is gender (females, 0; males, 1) (r = 0.94; SEE = 3.1 kg) and 2) FFM (kg) = (0.360 x 10(4) x H2/R) + 0.359BW + 4.5S - 20T + 7.0 where BW is body weight (kg) and T is thigh circumference (m) (r = 0.96; SEE = 2.5 kg). The prediction equations from the literature, generally determined in younger populations, overestimated FFM in elderly subjects by approximately 6 kg and are not applicable to elderly subjects.