Random number generation evaluation in patients with systemic lupus erythematosus indicates a heterogeneous nature of central nervous system vulnerability

Exploring randomness in autism

Introduction

The fast, intuitive and autonomous system 1 along with the slow, analytical and more logical system 2 constitute the dual system processing model of decision making. Whether acting independently or influencing each other both systems would, to an extent, rely on randomness in order to reach a decision. The role of randomness, however, would be more pronounced when arbitrary choices need to be made, typically engaging system 1. The present exploratory study aims to capture the expression of a possible innate randomness mechanism, as proposed by the authors, by trying to isolate system 1 and examine arbitrary decision making in autistic participants with high functioning Autism Spectrum Disorders (ASD).

Methods

Autistic participants withhigh functioning ASD and an age and gender matched comparison group performed the random number generation task. The task was modified to limit the contribution of working memory and allow any innate randomness mechanisms expressed through system 1, to emerge.

Results

Utilizing a standard analyses approach, the random number sequences produced by autistic individuals and the comparison group did not differ in their randomness characteristics. No significant differences were identified when the sequences were examined using a moving window approach. When machine learning was used, random sequences' features could discriminate the groups with relatively high accuracy.

Conclusions

Our findings indicate the possibility that individual patterns during random sequence production could be consistent enough between groups to allow for an accurate discrimination between the autistic and the comparison group. In order to draw firm conclusions around innate randomness and further validate our experiment, our findings need to be replicated in a bigger sample.

Counting on random number generation: Uncovering mild executive dysfunction in congenital heart disease

Congenital heart disease (CHD) is associated with various neurocognitive deficits, particularly targeting executive functions (EFs), of which random number generation (RNG) is one indicator. RNG has, however, never been investigated in CHD. We administered the Mental Dice Task (MDT) to 67 young adults with CHD and 55 healthy controls. This 1-minute-task requires the generation of numbers 1 to 6 in a random sequence. RNG performance was correlated with a global EF score. Participants underwent MRI to examine structural-volumetric correlates of RNG. Compared to controls, CHD patients showed increased backward counting, reflecting deficient inhibition of automatized behavior. They also lacked a small-number bias (higher frequency of small relative to large numbers). RNG performance was associated with global EF scores in both groups. In CHD patients, MRI revealed an inverse association of counting bias with most of the volumetric measurements and the amount of small numbers was positively associated with corpus callosum volume, suggesting callosal involvement in the "pseudoneglect in number space". In conclusion, we found an impaired RNG performance in CHD patients, which is associated with brain volumetric measures. RNG, reportedly resistant to learning effects, may be an ideal task for the longitudinal assessment of EFs in patients with CHD.

Analysing humanly generated random number sequences: a pattern-based approach

In a random number generation task, participants are asked to generate a random sequence of numbers, most typically the digits 1 to 9. Such number sequences are not mathematically random, and both extent and type of bias allow one to characterize the brain's “internal random number generator”. We assume that certain patterns and their variations will frequently occur in humanly generated random number sequences. Thus, we introduce a pattern-based analysis of random number sequences. Twenty healthy subjects randomly generated two sequences of 300 numbers each. Sequences were analysed to identify the patterns of numbers predominantly used by the subjects and to calculate the frequency of a specific pattern and its variations within the number sequence. This pattern analysis is based on the Damerau-Levenshtein distance, which counts the number of edit operations that are needed to convert one string into another. We built a model that predicts not only the next item in a humanly generated random number sequence based on the item′s immediate history, but also the deployment of patterns in another sequence generated by the same subject. When a history of seven items was computed, the mean correct prediction rate rose up to 27% (with an individual maximum of 46%, chance performance of 11%). Furthermore, we assumed that when predicting one subject′s sequence, predictions based on statistical information from the same subject should yield a higher success rate than predictions based on statistical information from a different subject. When provided with two sequences from the same subject and one from a different subject, an algorithm identifies the foreign sequence in up to 88% of the cases. In conclusion, the pattern-based analysis using the Levenshtein-Damarau distance is both able to predict humanly generated random number sequences and to identify person-specific information within a humanly generated random number sequence.

Lymphocytotoxic antibodies in systemic lupus erythematosus are associated with disease activity irrespective of the presence of neuropsychiatric manifestations

OBJECTIVES

To evaluate the association of the presence of lymphocytotoxic, anti-beta2-glycoprotein I (anti-beta2-GPI) and anti-ribosomal P (anti-P) antibodies in patients with systemic lupus erythematosus (SLE), presenting or not neuropsychiatric (NP) manifestations, stratified according to the activity of the disease.

METHODS

A total of 138 patients with SLE (59 with active NPSLE, 49 with active non-NPSLE, and 30 with inactive disease) and 57 healthy controls were studied. Disease activity was assessed by the SLE Disease Activity Index (SLEDAI). The presence of lymphocytotoxic antibodies was assessed using a complement-dependent lymphocytotoxicity assay. The presence of anti-beta2-GPI and anti-P antibodies was detected by enzyme-linked immunosorbent assay (ELISA).

RESULTS

Lymphocytotoxic antibodies were detected primarily in patients with active disease, that is in 35 out of 59 (59.3%) NPSLE and 23 out of 49 (46.9%) non-NPSLE patients, whereas only four out of 30 (13.3%) inactive SLE patients and none of the healthy controls exhibited the autoantibody. The frequency of lymphocytotoxic antibodies in active SLE patients, considered as a whole or stratified into NPSLE or non-NPSLE, was significantly increased in relation to inactive SLE patients (p<0.001 for each comparison). No significant difference was observed when comparing active NPSLE with non-NPSLE patients. No associations were observed between the presence of anti-beta2-GPI or anti-P antibodies and the activity of SLE or the presence of lymphocytotoxic antibodies.

CONCLUSIONS

Lymphocytotoxic antibodies occurred more frequently in patients with active SLE than in patients with inactive disease, irrespective of the presence of NP manifestations, a finding that is similar to classical biomarkers of lupus activity (anti-dsDNA and complement). These results indicate that the assessment of the presence of lymphocytotoxic antibodies may be an additional useful tool for the evaluation of SLE activity.

Eye movement and random number in NP lupus evaluation

We evaluated the vulnerability of central nervous system (CNS) in patients with systemic lupus erythematosus (SLE) using exploratory eye movement analysis and random number generation (RNG), and compared the tests in evaluating CNS vulnerability. Nineteen patients received the tests more than a month after SLE onset in nonpsychotic status. Exploratory eye movements were analyzed using an eye-mark recorder that detects corneal reflection of infrared light, and numbers of eye fixations were counted to calculate responsive search score (RSS). Using digits 0 through 9, 100 numbers were vocally generated at a random fashion. "Seriality score" was calculated from the recorded 100 numbers. RSS of SLE patients was similar to that of normal individuals, irrespective of neuropsychiatric lupus history. Seriality score of patients having a history of neuropsychiatric lupus was higher than that of never having it (p < 0.05). No relations were confirmed between RSS and seriality score. The current study suggested heterogeneous nature of SLE in CNS vulnerability when evaluating with seriality score, but not with RSS. There seemed to be a difference between exploratory eye movement analysis and RNG in evaluating CNS vulnerability. Each test seemed to evaluate different aspects of brain function.