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The distribution of mass in an object held in the hand, as described by its moment of inertia, is a fundamental and potent but largely unrecognized contributor to the object's "feel." A limited set of experiments has produced Weber fractions for human differential sensitivity to this property in the approximate range of 1/5 to 1/3, which is about ten times the Weber fraction reported for lifted weights.
Thresholds for mass discrimination under zero gravity in flight were found to be higher by a factor of about 1.8 than those for weight discrimination before flight. This suggests that humans are not as sensitive to inertial mass as they are to weight, and that adaptation can only partially compensate for loss of gravity. Weight discrimination thresholds were raised for 2 or 3 days after flight, suggesting an aftereffect of adaptation to weightlessness.
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When humans repetitively lift the same object, the fingertip forces are targeted to the weight of the object. The anticipatory programming of the forces depends on sensorimotor memory representations that provide information on the object weight. In the present study, we investigate the neural substrates of these sensorimotor memory systems by recording the neural activity during predictable or unpredictable changes in the weight of an object in a lifting task. An unpredictable change in weight leads to erroneous programming of the fingertip forces. This triggers corrective mechanisms and an update of the sensorimotor memories. In the present fMRI study, healthy right-handed subjects repetitively lifted an object between right index finger and thumb. In the constant condition, which served as a control, the weight of the object remained constant (either 230 or 830 g). The weight alternated between 230 and 830 g during the regular condition and was irregularly changed between the two weights during the irregular condition. When we contrasted regular minus constant and irregular minus constant, we found activations in the right inferior frontal gyrus pars opercularis (area 44), the left parietal operculum and the right supramarginal gyrus. Furthermore, irregular was associated with stronger activation in the right inferior frontal cortex as compared with regular. Taken together, these results suggest that the updating of sensorimotor memory representations and the corrective reactions that occur when we manipulate different objects correspond to changes in synaptic activity in these fronto-parietal circuits.
The perceptual size-weight illusion (SWI) occurs when two different-sized objects with equal mass are lifted in sequence: the smaller object is consistently reported to feel heavier than the larger object even after repeated lifting attempts. Here we explored the relationship between sensorimotor and perceptual responses to a SWI in which the smaller of the two target objects in fact weighed slightly less (2.7 N) than the larger object (3.2 N). For 20 consecutive lifts, participants consistently reported that the small-light object felt heavier than the large-heavy object; however, concurrently measured lifting dynamics showed exactly the opposite pattern: peak grip force, peak grip force rate, peak load force, and peak load force rate were all significantly greater for the large-heavy object versus the small-light object. The difference in peak load rate between the two objects was greatest for the initial lift but decreased significantly beyond that point, suggesting that the sensorimotor system used sensory feedback to correct for initial over- and underestimations of object mass. Despite these adjustments to lifting dynamics over the early trials, the difference between the judged heaviness of the two objects did not change. The findings clearly demonstrate that the sensorimotor and perceptual systems utilize distinctly different mechanisms for determining object mass.
1. While subjects lifted a variety of commonly handled objects of different shapes, weights, and densities, the isometric vertical lifting force opposing the object's weight was recorded from an analog weight scale, which was instrumented with high-stiffness strain gauge transducers. 2. The force output was scaled differently for the various objects from the first lift, before sensory information related to the object's weight was available. The force output was successfully specified from information in memory related to the weight of common objects, because only small changes in the force-rate profiles occurred across 10 consecutive lifts. This information was retrieved during a process related to visual identification of the target object. 3. The amount of practice necessary to appropriately scale the vertical lifting and grip (pinch) force was also studied when novel objects (equipped with force transducers at the grip surfaces) of different densities were encountered. The mass of a test object that subjects had not seen previously was adjusted to either 300 or 1,000 g by inserting an appropriate mass in the object's base without altering its appearance. This resulted in either a density that was in the range of most common objects (1.2 kg/l) or a density that was unusually high (4.0 kg/l). 4. Low vertical-lifting and grip-force rates were used initially with the high-density object, as if a lighter object had been expected. However, within the first few trials, the duration of the loading phase (period of isometric force increase before lift-off) was reduced by nearly 50% and the employed force-rate profiles were targeted for the weight of the object.(ABSTRACT TRUNCATED AT 250 WORDS)
Three monkeys were trained to lift and hold a test object within a 12- to 25-mm position window for 1 s. The activity of single neurons was recorded during performance of the task in which both the weight and surface texture of the object were systematically varied. Whenever possible, each cell was tested with three weights (15, 65, and 115 g) and three textures (smooth metal, fine 200 grit sandpaper, and rough 60 grit sandpaper). Of 386 cells recorded in 3 monkeys, 45 cells had cutaneous receptive fields on the index or thumb or part of the thenar eminence and were held long enough to be tested in all 9 combinations of texture and weight. Recordings were made for the entire anterior-posterior extent of the thumb and index finger areas in somatosensory cortex including area 7b. However, the statistical analysis required a selection of only those cells for which nine complete recording conditions were available limiting the sample to cells in areas 2, 5, and 7b. Significant differences in the grip force accompanied 98% of the changes in texture and 78% of the changes in weight. Increasing the object weight also increased the force tangential to the skin surface as measured by the load or lifting force. The peak discharge during lifting was judged to be the most sensitive index of cell activity and was analyzed with a two-way analysis of variance (ANOVA). In addition, peak cell discharge was normalized to allow comparisons among different combinations of texture and weight as well as comparisons among different neurons. Overall, the peak firing frequency of 87% of the cells was significantly modulated by changes in object texture, but changes in object weight affected the peak activity of only 58% of the cells. Almost all (17/18, 94%) of the static cells were influenced by the object texture, and 81% of the dynamic cells that were active only briefly at grip and lift onset were modulated by texture. For some cells, surface texture had a significant effect on neuronal discharge that was independent of the object weight. In contrast, weight-related responses were never simple main effects of the weight alone and appeared instead as significant interactions between texture and weight. Four neurons either increased or decreased activity in a graded fashion with surface structure (roughness) regardless of the object weight (P < 0.05). Ten other neurons showed increases or decreases in response to one or two textures, which might represent either a graded response or a tuning preference for a specific texture. The firing frequency of the majority (31/45) of neurons reflected an interaction of both texture and weight. The cells with texture-related but weight-independent activities were thought to encode surface characteristics that are largely independent of the grip and lifting forces used to manipulate the object. Such constancies could be used to construct internal representations or mental models for planning and controlling object manipulation.
The effect of warning time (preview) and task symmetry on the trunk muscular response to sudden loading conditions was investigated. Eleven subjects were asked to catch falling weights with four levels of preview (0, 100, 200, and 400 ms) in saggitally symmetric posture and asymmetric posture. For each of the eight muscles sampled with surface electrodes, the integrated electromyographic (EMG) signal was interpreted in terms of its peak value, mean value, onset rate, and lead/lag time with reference to the weight drop. Results show linear relationships between preview times and peak EMG, preview times and mean EMG, and preview times and lead times. The results show significant change when going from symmetric to asymmetric conditions across most dependent measures. Analysis of peak changes in compression were performed across all conditions but yielded unexpected results.
OBJECTIVE: This study examines potential overlaps between psychiatric comorbidity (Axis I and II) and scores on the subscales of the Eating Disorder Inventory (EDI) in women with eating disorders (EDs). METHOD: In a sample of 248 women (72 with anorexia nervosa, 140 with bulimia nervosa, and 36 with eating disorders not otherwise specified), we determined psychiatric comorbidity using the Structured Clinical Interview for DSM-IV. Behavioural and psychological characteristics of EDs were quantified with the EDI. RESULTS: Psychiatric comorbidity was high in both axes (74% for Axis I and 68% for Axis II). While most EDI subscales pertaining to psychological traits showed significant associations with Axis I and II disorders, the subscales concerning eating and perception of weight and shape were much less associated with psychiatric comorbidity. Affective and anxiety disorders, as well as personality disorders of clusters A and C, showed a similar pattern with links to most psychological subscales. The profile for substance-related disorders was different, showing associations with the Ineffectiveness and Interoceptive Awareness scales. Personality disorders of cluster B were related only to the Bulimia subscale and not to any of the psychological subscales. CONCLUSIONS: The EDI appears to primarily reflect Axis I and II disorders related to affective and anxiety problems. Clinicians and researchers employing the EDI should be aware that it is not sensitive for all forms of comorbidity prevalent in ED patients.
Many colleges in the United States are employing social norms marketing campaigns with the goal of reducing college students' alcohol use by correcting misperceptions about their peers' alcohol use. Although the typical message used in these campaigns describes the quantity and frequency of alcohol use by the average student on campus, many students may find such a vague comparison to others to be socially irrelevant. This study compares the relative weight of perceptions about alcohol use by distant versus proximate peers in the prediction of college students' personal drinking behavior. The results of analyzing data collected from a sample of college students at a large public northeastern university (N=276) show that, as hypothesized, perceived alcohol use by proximate peers (best friends and friends) was a stronger predictor of students' personal alcohol use than perceived alcohol use by more distant peers (such as students in general), controlling for other strong predictors of alcohol use by college students (age, gender, race, off-campus residency, and sensation-seeking tendencies). The implications of these findings for the design of more effective social norms messages are discussed.
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The purpose of this study was to determine whether the addition of chains to a barbell during the performance of the snatch would invoke differences in execution compared with lifting a conventional barbell without chains. Additionally, subjects were asked whether they perceived that the addition of chains had effects on their performance, and, if so, what those effects were. Four male and 3 female competitive weightlifters who regularly used chains as part of their training programs participated in the study. They were compared lifting 80% of 1 repetition maximum (1RM) using conventional barbells with 80% of 1RM, 5% of which was accounted for by chains. The same procedure was used with 85% of 1RM. Variables examined included maximum vertical displacement of the bar, maximum bar velocity, rate of force production of the bar, and vertical ground reaction forces for the first pull, unweighting, and second pull phases of the lift. Results indicated that there were no statistically significant differences between the chain vs. no-chain conditions at either 80% or 85% of 1RM. In contrast, 100% of the subjects stated that they perceived that the addition of chains made them work harder during the snatch. They suggested that the chains forced them to pull harder throughout the lift and that oscillation of the chains required their shoulders, abdominals, and back to work harder to stabilize the bar in the catch phase. Although statistical results indicate that chains have no influence on the snatch technique, chains may have a psychological impact and possibly invoke a physiological training response by increasing strength of muscles required to stabilize the bar during the catch phase if used over time.
A central concept in neuroscience is that the CNS signals the sensory discrepancy between the predicted and actual sensory consequences of action. It has been proposed that the cerebellum and parietal cortex are involved in this process. A discrepancy will trigger preprogrammed corrective responses and update the engaged sensorimotor memories. Here we use functional magnetic resonance imaging with an event-related design to investigate the neuronal correlates of such discrepancies. Healthy adults repeatedly lifted an object between their right index fingers and thumbs, and on some lifting trials, the weight of the object was unpredictably changed between light (230 g) and heavy (830 g). Regardless of whether the weight was heavier or lighter than predicted, activity was found in the right inferior parietal cortex (supramarginal gyrus). This suggests that this region is involved in the comparison of the predicted and actual sensory input and the updating of the sensorimotor memories. When the object was lighter or heavier than predicted, two different types of preprogrammed force corrections occurred. There was a slow force increase when the weight of the object was heavier than predicted. This corrective response was associated with activity in the left primary motor and somatosensory cortices. The fast termination of the excessive force when the object was lighter than predicted activated the right cerebellum. These findings show how the parietal cortex, cerebellum, and motor cortex are involved in the signaling of the discrepancy between predicated and actual sensory feedback and the associated corrective mechanisms.
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