Random number generation deficits in patients with multiple sclerosis: Characteristics and neural correlates

Explaining the flaws in human random generation as local sampling with momentum

In many tasks, human behavior is far noisier than is optimal. Yet when asked to behave randomly, people are typically too predictable. We argue that these apparently contrasting observations have the same origin: the operation of a general-purpose local sampling algorithm for probabilistic inference. This account makes distinctive predictions regarding random sequence generation, not predicted by previous accounts-which suggests that randomness is produced by inhibition of habitual behavior, striving for unpredictability. We verify these predictions in two experiments: people show the same deviations from randomness when randomly generating from non-uniform or recently-learned distributions. In addition, our data show a novel signature behavior, that people's sequences have too few changes of trajectory, which argues against the specific local sampling algorithms that have been proposed in past work with other tasks. Using computational modeling, we show that local sampling where direction is maintained across trials best explains our data, which suggests it may be used in other tasks too. While local sampling has previously explained why people are unpredictable in standard cognitive tasks, here it also explains why human random sequences are not unpredictable enough.

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.

Instruction effects on randomness in sequence generation

Randomness is a fundamental property of human behavior. It occurs both in the form of intrinsic random variability, say when repetitions of a task yield slightly different behavioral outcomes, or in the form of explicit randomness, say when a person tries to avoid being predicted in a game of rock, paper and scissors. Randomness has frequently been studied using random sequence generation tasks (RSG). A key finding has been that humans are poor at deliberately producing random behavior. At the same time, it has been shown that people might be better randomizers if randomness is only an implicit (rather than an explicit) requirement of the task. We therefore hypothesized that randomization performance might vary with the exact instructions with which randomness is elicited. To test this, we acquired data from a large online sample (n = 388), where every participant made 1,000 binary choices based on one of the following instructions: choose either randomly, freely, irregularly, according to an imaginary coin toss or perform a perceptual guessing task. Our results show significant differences in randomness between the conditions as quantified by conditional entropy and estimated Markov order. The randomization scores were highest in the conditions where people were asked to be irregular or mentally simulate a random event (coin toss) thus yielding recommendations for future studies on randomization behavior.

Dual-Task Treadmill Training for the Prevention of Falls in Parkinson's Disease: Rationale and Study Design

Various factors, such as fear of falling, postural instability, and altered executive function, contribute to the high risk of falling in Parkinson's disease (PD). Dual-task training is an established method to reduce this risk. Motor-perceptual task combinations typically require a patient to walk while simultaneously engaging in a perceptual task. Motor-executive dual-tasking (DT) combines locomotion with executive function tasks. One augmented reality treadmill training (AR-TT) study revealed promising results of a perceptual dual-task training with a markedly reduced frequency of falls especially in patients with PD. We here propose to compare the effects of two types of concurrent tasks, perceptual and executive, on high-intensity TT). Patients will be trained with TT alone, in combination with an augmented reality perceptual DT (AR-TT) or with an executive DT (Random Number Generation; RNG-TT). The results are expected to inform research on therapeutic strategies for the training of balance in PD.

Quantitative Limbic System Mapping of Main Cognitive Domains in Multiple Sclerosis

Background and objective

Cognitive impairment (CI) is common in multiple sclerosis (MS), but underlying mechanisms and their imaging correlates are not completely understood. The gray and white matter structures of the limbic system (LS) play crucial roles in different aspects of cognition. To investigate their role in MS related CI, and since a detailed evaluations are lacking in the literature, we used a comprehensive neuroimaging approach to evaluate CI’s correlations with the main components of the LS.

Methods

Ten non-cognitively impaired MS patients and 30 MS patients with diagnosed CI, who underwent a comprehensive neuropsychological evaluation were included in the analysis. Microstructural integrity, volumetry of main limbic gray and white matter structures and cortical thickness were assessed for associations with CI.

Results

Fornix and cingulum/cingulate cortices were found to be the strongest correlates of CI in MS. As expected, LS’ gray and white matter structures were involved in various cognitive functions. Uncinate fasciculi showed significant correlation with verbal and visuospatial learning and memory, phonemic and semantic fluency; hippocampi with visuospatial skills, phonemic and semantic fluency, executive functions, and processing speed; thalami with verbal learning, visuospatial skills, semantic fluency; and amygdala with verbal recognition discrimination.

Conclusion

This comprehensive neuroimaging approach elucidated the role of the main limbic structures in cognitive functions associated with MS-related CI.

Age-related differences in inhibitory control and memory updating in boys with Asperger syndrome

Deficits in specific executive domains are highly prevalent in autism spectrum disorder; however, age-related improvements in executive functions (reflecting prefrontal maturational changes) have been reported even in individuals diagnosed with autism. The current study examined two components of cognitive flexibility (inhibition of prepotent responses and memory monitoring/updating) by using a random-motor-generation task (MPT) in a group of 23 boys with Asperger syndrome (AS) and 23 matched healthy controls. We found poorer inhibition and more repetitive responses in younger AS children solely, but comparable memory monitoring/updating skills across groups. Overall, our findings correspond well with previous studies and reveal that even in AS specific EFs may improve with age and, thus, call for a more differentiated view of executive (dys) function profiles in children diagnosed with AS. Tests such as the random-motor-generation task may help to disentangle more specific processes of executive deficits in autism spectrum disorder as compared to the more classical tests.

Human behavioral complexity peaks at age 25

Random Item Generation tasks (RIG) are commonly used to assess high cognitive abilities such as inhibition or sustained attention. They also draw upon our approximate sense of complexity. A detrimental effect of aging on pseudo-random productions has been demonstrated for some tasks, but little is as yet known about the developmental curve of cognitive complexity over the lifespan. We investigate the complexity trajectory across the lifespan of human responses to five common RIG tasks, using a large sample (n = 3429). Our main finding is that the developmental curve of the estimated algorithmic complexity of responses is similar to what may be expected of a measure of higher cognitive abilities, with a performance peak around 25 and a decline starting around 60, suggesting that RIG tasks yield good estimates of such cognitive abilities. Our study illustrates that very short strings of, i.e., 10 items, are sufficient to have their complexity reliably estimated and to allow the documentation of an age-dependent decline in the approximate sense of complexity.

It has been unclear how this ability evolves over a person’s lifetime and it had not been possible to be assessed with previous classical tools for statistical randomness. To better understand how age impacts behavior, we have assessed more than 3,400 people aged 4 to 91 years old. Each participant performed a series of online tasks that assessed their ability to behave randomly. The five tasks included listing the hypothetical results of a series of 12 coin flips so that they would “look random to somebody else,” guessing which card would appear when selected from a randomly shuffled deck, and listing the hypothetical results of 10 rolls of a die. We analyzed the participants’ choices according to their algorithmic randomness, which is based on the idea that patterns that are more random are harder to encode in a short computer program. After controlling for characteristics such as gender, language, and education. We have found that age was the only factor that affected the ability to behave randomly. This ability peaked at age 25, on average, and declined from then on. We also demonstrate that a relatively short list of choices, say 10 hypothetical coin flips, can be used to reliably gauge randomness of human behavior. A similar approach could be then used to study potential connections between the ability to behave randomly, cognitive decline, neurodegenerative diseases and abilities such as human creativity.

Diffusion Tensor Imaging-Defined Sulcal Enlargement Is Related to Cognitive Impairment in Multiple Sclerosis

BACKGROUND AND PURPOSE

Cerebrospinal fluid (CSF) in the brain can be compartmentalized into two main divisions: ventricular CSF and subarachnoid space (sulcal CSF). Changes in CSF volumetry are seen in many neurological conditions including multiple sclerosis (MS) and found to correlate with clinical outcomes. We aimed to test the relation between the volumetry of sulcal and ventricular CSF and cognitive impairment (CI) based on the minimal assessment of cognitive function in MS (MACFIMS) in patients with MS.

MATERIAL AND METHODS

Forty-six patients with MS underwent the MACFIMS battery and classified as nonimpaired (MSNI) (n = 10) and cognitively impaired (MSCI) (n = 30) and borderline (MSBD) MS patients (n = 6). Volumes of sulcal and ventricular CSF along with global gray and white matter volumes and cortical thickness were obtained by diffusion tensor imaging (DTI) and T1-weighted (T1w)-based segmentation. These measures were statistically analyzed for associations with CI after adjusting for the age, education in years, lesion load, and disease duration.

RESULTS

Sulcal CSF showed the strongest correlation with CI (r = .51, P = .001) in our cohort, whereas ventricular CSF (P = .28, P = .19) along with cortical thickness and gray matter volume failed to show a significant correlation. Group analyses unadjusted for multiple comparisons showed significant difference in volumes of sulcal CSF and ventricular CSF between MSNI and MSCI groups (P < .05).

CONCLUSION

Sulcal CSF correlates with CI in patients with MS, possibly explained by cortical atrophy. DTI/T1w-based sulcal CSF segmentation method might be used as an indirect and simple neuroimaging marker to monitor CI in MS patients.

The relevance of cortical lesions in patients with multiple sclerosis

BACKGROUND

Recent studies suggest that cortical lesions in multiple sclerosis (MS) substantially contribute to clinical disease severity. The present study aimed at investigating clinical, neuroanatomical, and cognitive correlates of these cortical lesions with a novel approach, i.e. by comparing two samples of relapsing-remitting multiple sclerosis (RRMS) patients, one group with and the other without cortical lesions.

METHODS

High-resolution structural MRI was acquired from 42 RRMS patients and 43 controls (HC). The patient group was dichotomized based on the presence versus absence of DIR-hyperintense cortex-involving lesions, resulting in a cortical lesion group (CL, n = 32) and a non-cortical lesion group (nCL, n =10). Cognitive functioning was assessed in all participants with a comprehensive neuropsychological battery, covering mnestic, executive, and attentional functions.

RESULTS

Highest densities of cortical lesions in the CL group were observed in the bilateral parahippocampal gyrus. Relative to HC, patients with cortical lesions - but not those without - showed significant global cortical thinning and mnestic deficits. The two patient groups did not differ from each other regarding demographic and basic disease characteristics such as EDSS scores.

CONCLUSION

The appearance of cortical lesions in MS patients is associated with cortical thinning as well as mnestic deficits, which might be key characteristics of a 'cortically dominant' MS subtype.