The Discriminating Properties of an Optoelectronic Movement Analysis Method in Patients With Parkinsonism

Several partly overlapping diseases have Parkinsonism as a symptom and tools that may differentiate between these disorders would be helpful. The authors evaluated the discriminating properties of the objective automated posturo-locomotor-manual (PLM) L-DOPA test in regard to health, and the movement disorders Parkinson's disease (PD), multiple system atrophy (MSA), and progressive supranuclear palsy (PSP). A PLM test–retest procedure was performed in healthy controls (n = 37) and results were compared with PLM L-DOPA tests performed by 132 patients with Parkinsonism in intermediate to advanced stages (56 PD, 53 MSA, 23 PSP). The movement time (MT) for the standardized movement and its different components was measured. The discriminating abilities of individual, or combinations of, test variables were determined by forward stepwise multiple logistic regression and evaluated with receiver-operating characteristic (ROC) analysis. Each PLM variable separated healthy persons from patients with Parkinsonism before administration of L-DOPA (area under the curve (AUC) = 0.94–0.99, p <.001 for any separate variable). A combination of (MT_off – MT_on)/MT_off and MT_on had the highest ability to separate patients with PD from patients with atypical Parkinsonism (area under the curve = 0.91, p <.001). The PLM test discriminates between healthy controls and patients with Parkinsonism, and between patients with Parkinson's disease and patients with atypical Parkinsonism.

[Supplementary material is available for this article. Go to the publisher's online edition of Journal of Motor Behavior for the following free supplemental resource: supplementary data.]     

Unraveling the linguistic nature of specific autobiographical memories using a computerized classification algorithm

In the present study, we explored the linguistic nature of specific memories generated with the Autobiographical Memory Test (AMT) by developing a computerized classifier that distinguishes between specific and nonspecific memories. The AMT is regarded as one of the most important assessment tools to study memory dysfunctions (e.g., difficulty recalling the specific details of memories) in psychopathology. In Study 1, we utilized the Japanese corpus data of 12,400 cue-recalled memories tagged with observer-rated specificity. We extracted linguistic features of particular relevance to memory specificity, such as past tense, negation, and adverbial words and phrases pertaining to time and location. On the basis of these features, a support vector machine (SVM) was trained to classify the memories into specific and nonspecific categories, which achieved an area under the curve (AUC) of .92 in a performance test. In Study 2, the trained SVM was tested in terms of its robustness in classifying novel memories (n?= 8,478) that were retrieved in response to cue words that were different from those used in Study 1. The SVM showed an AUC of .89 in classifying the new memories. In Study 3, we extended the binary SVM to a five-class classification of the AMT, which achieved 64%–65% classification accuracy, against the chance level (20%) in the performance tests. Our data suggest that memory specificity can be identified with a relatively small number of words, capturing the universal linguistic features of memory specificity across memories in diverse contents.     

The visuospatial functions in children after cerebellar low‐grade astrocytoma surgery: A contribution to the pediatric neuropsychology of the cerebellum

The aim of this study was to specify whether cerebellar lesions cause visuospatial impairments in children. The study sample consisted of 40 children with low‐grade cerebellar astrocytoma, who underwent surgical treatment and 40 healthy controls matched with regard to age and sex. Visuospatial abilities were tested using the spatial WISC‐R subtests (Block Design and Object Assembly), Rey–Osterrieth Complex Figure, Benton Judgment of Line Orientation Test, PEBL Mental Rotation Task, and Benton Visual Retention Test. To exclude general diffuse intellectual dysfunction, the WISC‐R Verbal Intelligence IQ, Performance IQ, and Full‐Scale IQ scores were analysed. Post‐surgical medical consequences were measured with the International Cooperative Ataxia Rating Scale. Compared to controls, the cerebellar group manifested problems with mental rotation of objects, visuospatial organization, planning, and spatial construction processes which could not be explained by medical complications or general intellectual retardation. The intensity of visuospatial syndrome highly depends on cerebellar lesion side. Patients with left‐sided cerebellar lesions display more severe spatial problems than those with right‐sided cerebellar lesions. In conclusion, focal cerebellar lesions in children affect their visuospatial ability. The impairments profile is characterized by deficits in complex spatial processes such as visuospatial organization and mental rotation, requiring reconstruction of visual stimuli using the imagination, while elementary sensory analysis and perception as well as spatial processes requiring direct manipulation of objects are relatively better preserved. This pattern is analogous to the one previously observed in adult population and appears to be typical for cerebellar pathology in general, regardless of age.     

Visual properties and memorising scenes: Effects of image-space sparseness and uniformity

Previous studies have demonstrated that humans have a remarkable capacity to memorise a large number of scenes. The research on memorability has shown that memory performance can be predicted by the content of an image. We explored how remembering an image is affected by the image properties within the context of the reference set, including the extent to which it is different from its neighbours (image-space sparseness) and if it belongs to the same category as its neighbours (uniformity). We used a reference set of 2,048 scenes (64 categories), evaluated pairwise scene similarity using deep features from a pretrained convolutional neural network (CNN), and calculated the image-space sparseness and uniformity for each image. We ran three memory experiments, varying the memory workload with experiment length and colour/greyscale presentation. We measured the sensitivity and criterion value changes as a function of image-space sparseness and uniformity. Across all three experiments, we found separate effects of 1) sparseness on memory sensitivity, and 2) uniformity on the recognition criterion. People better remembered (and correctly rejected) images that were more separated from others. People tended to make more false alarms and fewer miss errors in images from categorically uniform portions of the image-space. We propose that both image-space properties affect human decisions when recognising images. Additionally, we found that colour presentation did not yield better memory performance over grayscale images.     

Rapid parallel semantic processing of numbers without awareness

In this study, we investigate whether multiple digits can be processed at a semantic level without awareness, either serially or in parallel. In two experiments, we presented participants with two successive sets of four simultaneous Arabic digits. The first set was masked and served as a subliminal prime for the second, visible target set. According to the instructions, participants had to extract from the target set either the mean or the sum of the digits, and to compare it with a reference value. Results showed that participants applied the requested instruction to the entire set of digits that was presented below the threshold of conscious perception, because their magnitudes jointly affected the participant’s decision. Indeed, response decision could be accurately modeled as a sigmoid logistic function that pooled together the evidence provided by the four targets and, with lower weights, the four primes. In less than 800 ms, participants successfully approximated the addition and mean tasks, although they tended to overweight the large numbers, particularly in the sum task. These findings extend previous observations on ensemble coding by showing that set statistics can be extracted from abstract symbolic stimuli rather than low-level perceptual stimuli, and that an ensemble code can be represented without awareness.     

Threats to the Operational Use of Situational Judgment Tests in the College Admission Process

This study examined the coachability of two situational judgment tests, the College Student Questionnaire (CSQ) and the Situational Judgment Inventory (SJI), developed for consideration as selection instruments in the college admission process. Strategies for raising scores on each test were generated, and undergraduates were trained in the use of the strategies using a video‐based training program. Results indicated that the CSQ was susceptible to coaching. In addition, the scoring format of the CSQ was found to be easily exploited, such that trainees could increase their scores by greater than 1 SD simply by avoiding extreme responses on that test. The results as a whole sounded a note of caution for the potential use of the CSQ in the college admission process.     

Scoring the DSM-IV personality disorders using the Five-Factor Model: development and validation of normative scores for North American, French, and Dutch-Flemish samples

Five-Factor Model (FFM) personality disorder (PD) counts have demonstrated significant convergent and discriminant validity with DSM-IV PD symptoms. However, these FFM PD counts are of limited clinical use without normative data because it is difficult to determine what a specific score means with regard to the relative level of elevation. The current study presents data from three large normative samples that can be used as norms for the FFM PD counts in the respective countries: United States (N = 1,000), France (N = 801), and Belgium-Netherlands (N = 549). The present study also examines the performance, with regard to diagnostic efficiency, of statistically-defined cut-offs at 1.5 standard deviations above the mean (T > or = 65) versus previously identified cut-offs using receiver-operator characteristics (ROC) analyses. These cut-offs are tested in three clinical samples-one from each of the aforementioned countries. In general, the T > or = 65 cut-offs performed similarly to those identified using ROC analyses and manifested properties relevant to a screening instrument. These normative data allow FFM data to be used in a flexible and comprehensive manner, which may include scoring this type of personality data in order to screen for DSM-IV PD constructs.     

Personality and personal network type

The association between personality and personal relationships is mostly studied within dyadic relationships. We examined these variables within the context of personal network types. We used Latent Class Analysis to identify groups of students with similar role relationships with three focal figures. We performed Latent Class Logistic Regression to explore the relationships of the latent classes with the Big Five personality factors. Personality was assessed with the Five Factor Personality Inventory. We found three personal network types: a primarily family oriented network, a primarily peer oriented network, and a mixed family/peer oriented network. We found significant associations between personality and personal network type. Extraverted students were more likely to have a primarily peer oriented network relative to a primarily family oriented network. Autonomous students were more likely to have a primarily family oriented network relative to a primarily peer oriented network. Autonomous students were also more likely to have a mixed family/peer oriented network relative to a primarily peer oriented network. Conscientious students were more likely to have a primarily family oriented network relative to a mixed family/peer oriented network.     

A Person-Centered Approach to P-E Fit Questions Using a Multiple-Trait Model

The current study first longitudinally examines the validity of person-environment (P-E) RIASEC congruence, adopting a job analytic method to assess the environment and using P-E difference scores to compute congruence, to predict a range of intrinsic career outcomes—including job satisfaction, skill development, work involvement, and perceived stress—in a sample of 401 college seniors involved in the labor market. Second, the incremental validity of an alternative conceptualization of the P component (i.e., the Five-Factor Model of personality [FFM]) is examined over and beyond RIASEC congruence scores. Congruence across RIASEC types significantly predicted job satisfaction and skill development, but FFM traits significantly and substantially contributed to the prediction of all intrinsic career outcomes. Finally, a person-centered perspective to P-E questions is introduced, demonstrating that cluster analysis of individuals' FFM scores resulted in two clusters (i.e., internalizers/externalizers and resilients) showing very different positions on the labor market and reporting differing initial career outcomes. It is concluded that RIASEC P-E fit congruence studies should be complemented with FFM assessment to increase predictive validity. Applications of an FFM-based, person-centered approach in I/O and P-E fit research and practice are discussed.