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.

Diverse definitions of the early course of schizophrenia-a targeted literature review

Schizophrenia is a debilitating psychiatric disorder and patients experience significant comorbidity, especially cognitive and psychosocial deficits, already at the onset of disease. Previous research suggests that treatment during the earlier stages of disease reduces disease burden, and that a longer time of untreated psychosis has a negative impact on treatment outcomes. A targeted literature review was conducted to gain insight into the definitions currently used to describe patients with a recent diagnosis of schizophrenia in the early course of disease ('early' schizophrenia). A total of 483 relevant English-language publications of clinical guidelines and studies were identified for inclusion after searches of MEDLINE, MEDLINE In-Process, relevant clinical trial databases and Google for records published between January 2005 and October 2015. The extracted data revealed a wide variety of terminology and definitions used to describe patients with 'early' or 'recent-onset' schizophrenia, with no apparent consensus. The most commonly used criteria to define patients with early schizophrenia included experience of their first episode of schizophrenia or disease duration of less than 1, 2 or 5 years. These varied definitions likely result in substantial disparities of patient populations between studies and variable population heterogeneity. Better agreement on the definition of early schizophrenia could aid interpretation and comparison of studies in this patient population and consensus on definitions should allow for better identification and management of schizophrenia patients in the early course of their disease.

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.

Algorithmic complexity for short binary strings applied to psychology: a primer

As human randomness production has come to be more closely studied and used to assess executive functions (especially inhibition), many normative measures for assessing the degree to which a sequence is randomlike have been suggested. However, each of these measures focuses on one feature of randomness, leading researchers to have to use multiple measures. Although algorithmic complexity has been suggested as a means for overcoming this inconvenience, it has never been used, because standard Kolmogorov complexity is inapplicable to short strings (e.g., of length l ≤ 50), due to both computational and theoretical limitations. Here, we describe a novel technique (the coding theorem method) based on the calculation of a universal distribution, which yields an objective and universal measure of algorithmic complexity for short strings that approximates Kolmogorov-Chaitin complexity.

Neurocognitive deficits, craving, and abstinence among alcohol-dependent individuals following detoxification

Alcohol dependence, a chronic relapsing disorder, is characterized by an impaired ability to regulate compulsive urges to consume alcohol. Very few empirical studies have examined the presence of these executive deficits, how they relate to craving, and the enduring nature of these deficits during abstinence. As such, the current study aimed to characterize these cognitive deficits within a sample of 24 alcohol-dependent participants post-detoxification and 23 non-alcohol-dependent participants. Participants were administered the Sustained Attention to Response Task to measure response inhibition and sustained attention and the Random Number Generation Task to examine executive deficits. Correlations between cognitive performance and clinical measures of alcohol dependence were examined. As predicted, the alcohol-dependent group exhibited poorer performance across the domains of response inhibition, executive function, and attentional control. Cognitive performance was related to clinical measures of craving and years of alcohol consumption, whereas the duration of abstinence was not associated with improved cognitive performance. These findings highlight the need for therapeutic strategies to target these enduring neurocognitive deficits in improving the treatment of alcohol dependence.

Executive function in first-episode schizophrenia: a three-year prospective study of the Hayling Sentence Completion Test

In recent decade, deficits in the mechanism of Supervisory Attentional System (SAS) have become increasingly influential in explaining the nature of dysexecutive syndrome experienced by schizophrenic patients. The SAS model is characterized by having a detailed sub-classification of specific executive function components, among which semantic inhibition has been investigated using the Hayling Sentence Completion Test (HSCT). Several studies thus far have indicated that schizophrenic patients show impairment in HSCT performance. However, HSCT data concerning first-episode patients is still scarce. Besides, as previous HSCT studies were all cross-sectional in nature, they were not able to assess changes in HSCT performance over time. In order to address the paucity of knowledge about the longitudinal trajectories and correlates of semantic inhibition deficits in early schizophrenia, this paper reports a three-year prospective study of HSCT performance in medication-naïve, first-episode patients with schizophrenia-spectrum disorders. HSCT performance was assessed in 34 patients at four times over a period of three years, while the 34 healthy controls were assessed once. We found that medication-naïve patients demonstrated impairment in the inhibition condition in HSCT as compared to controls, but not in the initiation condition. Such HSCT impairment gradually improved in the three years following the first psychotic episode; however, HSCT performance did not predict improvement in negative or positive symptoms over the three-year period. The present findings suggest that semantic inhibition impairment is a specific deficit in schizophrenia that may require early intervention efforts, with the goal of facilitating more successful verbal communication and thereby better interpersonal functioning.