Voluntary control of information processing is crucial to allocate resources and prioritize the processes that are most important under a given situation; the algorithms underlying such control, however, are often not clear. We investigated possible algorithms of control for the performance of the majority function, in which participants searched for and identified one of two alternative categories (left or right pointing arrows) as composing the majority in each stimulus set. We manipulated the amount (set size of 1, 3, and 5) and content (ratio of left and right pointing arrows within a set) of the inputs to test competing hypotheses regarding mental operations for information processing. Using a novel measure based on computational load, we found that reaction time was best predicted by a grouping search algorithm as compared to alternative algorithms (i.e., exhaustive or self-terminating search). The grouping search algorithm involves sampling and resampling of the inputs before a decision is reached. These findings highlight the importance of investigating the implications of voluntary control via algorithms of mental operations.
Search is a basic activity that is performed routinely in many different tasks. In the context of medical imaging it involves locating lesions in images under conditions of uncertainty regarding the number and locations of lesions that may be present. A model of search is presented that applies to situations, as in the free-response paradigm, where on each image the number of normal regions that could be mistaken for lesions is unknown, and the number of observer generated localizations of suspicious regions (marks) is unpredictable. The search model is based on a two-stage model that has been proposed in the literature according to which at the first stage (the preattentive stage) the observer uses mainly peripheral vision to identify likely lesion candidates, and at the second stage the observer decides (i.e., cognitively evaluates) whether or not to report the candidates. The search model regards the unpredictable numbers of lesion and non-lesion localizations as random variables and models them via appropriate statistical distributions. The model has three parameters quantifying the lesion signal-to-noise ratio, the observer's expertise at rejecting non-lesion locations, and the observer's expertise at finding lesions. A figure-of-merit quantifying the observer's search performance is described. The search model bears a close resemblance to the initial detection and candidate analysis (IDCA) model that has been recently proposed for analyzing computer aided detection (CAD) algorithms. The ability to analytically model and quantify the search process would enable more powerful assessment and optimization of performance in these activities, which could be highly significant.
search model; lesion localization; free-response paradigm; statistical modeling; observer performance; figure of merit
We estimate a Cox proportional hazards model where one of the covariates measures the level of a subject's cognitive functioning by grading the total score obtained by the subject on the items of a questionnaire. A case study is presented where the sample includes partial respondents, who did not answer some questionnaire items. The total score takes hence the form of an interval-censored variable and, as a result, the level of cognitive functioning is missing on some subjects. We handle partial respondents by taking a likelihood-based approach where survival time is jointly modelled with the censored total score and the size of the censoring interval. Estimates are obtained by an E-M-type algorithm that reduces to the iterative maximization of three complete log-likelihood functions derived from two augmented datasets with case weights, alternated with weights updating. This methodology is exploited to assess the Mini Mental State Examination index as a prognostic factor of survival in a sample of Chinese older adults.
Composite index; Cox model; Data augmentation; E-M algorithm; Generalized linear mixed models; Interval censoring; Non-ignorable missing covariate; Partial respondents
Limitations of working memory force a reliance on motor exploration to retrieve forgotten features of the visual array. A category search task was devised to study tradeoffs between exploration and memory in the face of significant cognitive and motor demands. The task required search through arrays of hidden, multi-featured objects to find three belonging to the same category. Location contents were revealed briefly by either a: (1) mouseclick, or (2) saccadic eye movement with or without delays between saccade offset and object appearance. As the complexity of the category rule increased, search favored exploration, with more visits and revisits needed to find the set. As motor costs increased (mouseclick search or oculomotor search with delays) search favored reliance on memory. Application of the model of J. Epelboim and P. Suppes (2001) to the revisits produced an estimate of immediate memory span (M) of about 4–6 objects. Variation in estimates of M across category rules suggested that search was also driven by strategies of transforming the category rule into concrete perceptual hypotheses. The results show that tradeoffs between memory and exploration in a cognitively demanding task are determined by continual and effective monitoring of perceptual load, cognitive demand, decision strategies and motor effort.
visual search; active vision; memory; exploration; eye movements; saccades; arm movement; immediate memory; oculomotor; categorization; cognitive load; decision-making
A major challenge in modern robotics is to liberate robots from controlled industrial settings, and allow them to interact with humans and changing environments in the real-world. The current research attempts to determine if a neurophysiologically motivated model of cortical function in the primate can help to address this challenge. Primates are endowed with cognitive systems that allow them to maximize the feedback from their environment by learning the values of actions in diverse situations and by adjusting their behavioral parameters (i.e., cognitive control) to accommodate unexpected events. In such contexts uncertainty can arise from at least two distinct sources – expected uncertainty resulting from noise during sensory-motor interaction in a known context, and unexpected uncertainty resulting from the changing probabilistic structure of the environment. However, it is not clear how neurophysiological mechanisms of reinforcement learning and cognitive control integrate in the brain to produce efficient behavior. Based on primate neuroanatomy and neurophysiology, we propose a novel computational model for the interaction between lateral prefrontal and anterior cingulate cortex reconciling previous models dedicated to these two functions. We deployed the model in two robots and demonstrate that, based on adaptive regulation of a meta-parameter β that controls the exploration rate, the model can robustly deal with the two kinds of uncertainties in the real-world. In addition the model could reproduce monkey behavioral performance and neurophysiological data in two problem-solving tasks. A last experiment extends this to human–robot interaction with the iCub humanoid, and novel sources of uncertainty corresponding to “cheating” by the human. The combined results provide concrete evidence for the ability of neurophysiologically inspired cognitive systems to control advanced robots in the real-world.
iCub; humanoid robot; reinforcement learning; meta-learning; bio-inspiration; prefrontal cortex
In this paper, we investigate a new paradigm for studying the development of the colour ‘signal’ by having observers discriminate and categorize the same set of controlled and calibrated cardinal coloured stimuli. Notably, in both tasks, each observer was free to decide whether two pairs of colors were the same or belonged to the same category. The use of the same stimulus set for both tasks provides, we argue, an incremental behavioural measure of colour processing from detection through discrimination to categorisation. The measured data spaces are different for the two tasks, and furthermore the categorisation data is unique to each observer. In addition, we develop a model which assumes that the principal difference between the tasks is the degree of similarity between the stimuli which has different constraints for the categorisation task compared to the discrimination task. This approach not only makes sense of the current (and associated) data but links the processes of discrimination and categorisation in a novel way and, by implication, expands upon the previous research linking categorisation to other tasks not limited to colour perception.
Cognitive impairment is common in Parkinson’s disease (PD). There is a critical need for a brief, standard cognitive screening measure for use in PD trials whose primary focus is not on cognition.
The Parkinson Study Group (PSG) Cognitive/Psychiatric Working Group formed a Task Force to make recommendations for a cognitive scale that could screen for dementia and mild cognitive impairment in clinical trials of PD where cognition is not the primary outcome. This Task Force conducted a systematic literature search for cognitive assessments previously used in a PD population. Scales were then evaluated for their appropriateness to screen for cognitive deficits in clinical trials, including brief administration time (<15 minutes), assessment of the major cognitive domains, and potential to detect subtle cognitive impairment in PD.
Five scales of global cognition met the predetermined screening criteria and were considered for review. Based on the Task Force’s evaluation criteria the Montreal Cognitive Assessment (MoCA), appeared to be the most suitable measure.
This Task Force recommends consideration of the MoCA as a minimum cognitive screening measure in clinical trials of PD where cognitive performance is not the primary outcome measure. The MoCA still requires further study of its diagnostic utility in PD populations but appears to be the most appropriate measure among the currently available brief cognitive assessments. Widespread adoption of a single instrument such as the MoCA in clinical trials can improve comparability between research studies on PD.
Understanding the association between computer use and adult cognition has been limited until now by self-selected samples with restricted ranges of age and education. Here we studied effects of computer use in a large national sample (N=2671) of adults aged 32 to 84, assessing cognition with the Brief Test of Adult Cognition by Telephone (Tun & Lachman, 2005), and executive function with the Stop and Go Switch Task (Tun & Lachman, 2008). Frequency of computer activity was associated with cognitive performance after controlling for age, sex, education, and health status: that is, individuals who used the computer frequently scored significantly higher than those who seldom used the computer. Greater computer use was also associated with better executive function on a task-switching test, even after controlling for basic cognitive ability as well as demographic variables. These findings suggest that frequent computer activity is associated with good cognitive function, particularly executive control, across adulthood into old age, especially for those with lower intellectual ability.
Cognition; computer use; cognitive activity; executive function; task-switching
The contribution of cerebrovascular function to cognitive performance is gaining increased attention. Transcranial doppler (TCD) is portable, reliable, inexpensive and extremely well tolerated by young and clinical samples. It enables measurement of blood flow velocity in major cerebral arteries at rest and during cognitive tasks.
We systematically reviewed evidence for associations between cognitive performance and cerebrovascular function in children (0-18 years), as measured using TCD. A total of 2778 articles were retrieved from PsychInfo, Pubmed, and EMBASE searches and 25 relevant articles were identified.
Most studies investigated clinical groups, where decreased blood flow velocities in infants were associated with poor neurological functioning, and increased blood flow velocities in children with Sickle cell disease were typically associated with cognitive impairment and lower intelligence. Studies were also identified assessing autistic behaviour, mental retardation and sleep disordered breathing. In healthy children, the majority of studies reported cognitive processing produced lateralised changes in blood flow velocities however these physiological responses did not appear to correlate with behavioural cognitive performance.
Poor cognitive performance appears to be associated with decreased blood flow velocities in premature infants, and increased velocities in Sickle cell disease children using TCD methods. However knowledge in healthy samples is relatively limited. The technique is well tolerated by children, is portable and inexpensive. It therefore stands to make a valuable contribution to knowledge regarding the underlying functional biology of cognitive performance in childhood.
Cognition; Infants; Children; Adolescents; Transcranial doppler; Cerebrovascular
Objective: Long-term memory functioning in autism spectrum disorders (ASDs) is marked by a characteristic pattern of impairments and strengths. Individuals with ASD show impairment in memory tasks that require the processing of relational and contextual information, but spared performance on tasks requiring more item-based, acontextual processing. Two experiments investigated the cognitive mechanisms underlying this memory profile. Method: A sample of 14 children with a diagnosis of high-functioning ASD (age: M = 12.2 years), and a matched control group of 14 typically developing (TD) children (age: M = 12.1 years), participated in a range of behavioral memory tasks in which we measured both relational and item-based memory abilities. They also completed a battery of executive function measures. Results: The ASD group showed specific deficits in relational memory, but spared or superior performance in item-based memory, across all tasks. Importantly, for ASD children, executive ability was significantly correlated with relational memory but not with item-based memory. No such relationship was present in the control group. This suggests that children with ASD atypically employed effortful, executive strategies to retrieve relational (but not item-specific) information, whereas TD children appeared to use more automatic processes. Conclusions: The relational memory impairment in ASD may result from a specific impairment in automatic associative retrieval processes with an increased reliance on effortful and strategic retrieval processes. Our findings allow specific neural predictions to be made regarding the interactive functioning of the hippocampus, prefrontal cortex, and posterior parietal cortex in ASD as a neural network supporting relational memory processing.
autism spectrum disorder; relational memory; hippocampus; posterior parietal cortex; executive functions
Robots are increasingly expected to perform tasks in complex environments. To this end, engineers provide them with processing architectures that are based on models of human information processing. In contrast to traditional models, where information processing is typically set up in stages (i.e., from perception to cognition to action), it is increasingly acknowledged by psychologists and robot engineers that perception and action are parts of an interactive and integrated process. In this paper, we present HiTEC, a novel computational (cognitive) model that allows for direct interaction between perception and action as well as for cognitive control, demonstrated by task-related attentional influences. Simulation results show that key behavioral studies can be readily replicated. Three processing aspects of HiTEC are stressed for their importance for cognitive robotics: (1) ideomotor learning of action control, (2) the influence of task context and attention on perception, action planning, and learning, and (3) the interaction between perception and action planning. Implications for the design of cognitive robotics are discussed.
Integrated processes; Perception–action interaction; Computational modeling; Cognitive robotics; Common coding; Ideomotor learning
Executive functions and learning share common neural substrates essential for their expression, notably in prefrontal cortex and basal ganglia. Understanding how they interact requires studying how cognitive control facilitates learning, but also how learning provides the (potentially hidden) structure, such as abstract rules or task-sets, needed for cognitive control. We investigate this question from three complementary angles. First, we develop a new computational “C-TS” (context-task-set) model inspired by non-parametric Bayesian methods, specifying how the learner might infer hidden structure and decide whether to re-use that structure in new situations, or to create new structure. Second, we develop a neurobiologically explicit model to assess potential mechanisms of such interactive structured learning in multiple circuits linking frontal cortex and basal ganglia. We systematically explore the link betweens these levels of modeling across multiple task demands. We find that the network provides an approximate implementation of high level C-TS computations, where manipulations of specific neural mechanisms are well captured by variations in distinct C-TS parameters. Third, this synergism across models yields strong predictions about the nature of human optimal and suboptimal choices and response times during learning. In particular, the models suggest that participants spontaneously build task-set structure into a learning problem when not cued to do so, which predicts positive and negative transfer in subsequent generalization tests. We provide evidence for these predictions in two experiments and show that the C-TS model provides a good quantitative fit to human sequences of choices in this task. These findings implicate a strong tendency to interactively engage cognitive control and learning, resulting in structured abstract representations that afford generalization opportunities, and thus potentially long-term rather than short-term optimality.
Human cognition is characterized by flexibility, the ability to select not only which action but which cognitive process to engage to best achieves the current behavioral objective. The ability to tailor information processing in the brain to rules, goals, or context is typically referred to as executive control, and although there is consensus that prefrontal cortex is importantly involved, at present we have an incomplete understanding of how computational flexibility is implemented at the level of prefrontal neurons and networks. To better understand the neural mechanisms of computational flexibility, we simultaneously recorded the electrical activity of groups of single neurons within prefrontal and posterior parietal cortex of monkeys performing a task that required executive control of spatial cognitive processing. In this task, monkeys applied different spatial categorization rules to reassign the same set of visual stimuli to alternative categories on a trial-by-trial basis. We found that single neurons were activated to represent spatially defined categories in a manner that was rule dependent, providing a physiological signature of a cognitive process that was implemented under executive control. We found also that neurons engaged to represent rule-dependent categories were distributed between the parietal and prefrontal cortex – however, not equally. Rule-dependent category signals were stronger, more powerfully modulated by the rule, and earlier to emerge in prefrontal cortex relative to parietal cortex. This suggests that prefrontal cortex may initiate the switch in neural representation at a network level that is important for computational flexibility.
Human cognition is characterized by flexibility, the ability to select not only which action but which cognitive process to engage to best achieve the current behavioral objective. The ability to tailor information processing in the brain to rules, goals, or context is typically referred to as executive control, and although there is consensus that prefrontal cortex is importantly involved, at present we have an incomplete understanding of how computational flexibility is implemented at the level of prefrontal neurons and networks. To better understand the neural mechanisms of computational flexibility, we simultaneously recorded the electrical activity of groups of single neurons within prefrontal and posterior parietal cortex of monkeys performing a task that required executive control of spatial cognitive processing. In this task, monkeys applied different spatial categorization rules to reassign the same set of visual stimuli to alternative categories on a trial-by-trial basis. We found that single neurons were activated to represent spatially defined categories in a manner that was rule dependent, providing a physiological signature of a cognitive process that was implemented under executive control. We found also that neural signals coding rule-dependent categories were distributed between the parietal and prefrontal cortex—however, not equally. Rule-dependent category signals were stronger, more powerfully modulated by the rule, and earlier to emerge in prefrontal cortex relative to parietal cortex. This suggests that prefrontal cortex may initiate the switch in neural representation at a network level that is important for computational flexibility.
Multiple studies have documented an inverse relationship between the number of to-be-attended or remembered items in a display (“set size”) and task performance. The neural source of this decline in cognitive performance is currently under debate. Here, we used a combination of fMRI and a forward encoding model of orientation-selectivity to generate population tuning functions for each of two stimuli while human observers attended either one or both items. We observed: (1) clear population tuning functions for the attended item(s) that peaked at the stimulus orientation and decreased monotonically as the angular distance from this orientation increased, (2) a set-size dependent decline in the relative precision of orientation-specific population responses, such that attending two items yielded a decline in selectivity of the population tuning function for each item, (3) that the magnitude of the loss of precision in population tuning functions predicted individual differences in the behavioral cost of attending an additional item. These findings demonstrate that attending multiple items degrades the precision of perceptual representations for the target items, and provides a straightforward account for the associated impairments in visually-guided behavior.
Attention; Encoding Model; fMRI; Perception; Primary Visual Cortex
One of the central questions in cognitive neuroscience is the precise neural representation, or brain pattern, associated with a semantic category. In this study, we explored the influence of audiovisual stimuli on the brain patterns of concepts or semantic categories through a functional magnetic resonance imaging (fMRI) experiment. We used a pattern search method to extract brain patterns corresponding to two semantic categories: “old people” and “young people.” These brain patterns were elicited by semantically congruent audiovisual, semantically incongruent audiovisual, unimodal visual, and unimodal auditory stimuli belonging to the two semantic categories. We calculated the reproducibility index, which measures the similarity of the patterns within the same category. We also decoded the semantic categories from these brain patterns. The decoding accuracy reflects the discriminability of the brain patterns between two categories. The results showed that both the reproducibility index of brain patterns and the decoding accuracy were significantly higher for semantically congruent audiovisual stimuli than for unimodal visual and unimodal auditory stimuli, while the semantically incongruent stimuli did not elicit brain patterns with significantly higher reproducibility index or decoding accuracy. Thus, the semantically congruent audiovisual stimuli enhanced the within-class reproducibility of brain patterns and the between-class discriminability of brain patterns, and facilitate neural representations of semantic categories or concepts. Furthermore, we analyzed the brain activity in superior temporal sulcus and middle temporal gyrus (STS/MTG). The strength of the fMRI signal and the reproducibility index were enhanced by the semantically congruent audiovisual stimuli. Our results support the use of the reproducibility index as a potential tool to supplement the fMRI signal amplitude for evaluating multimodal integration.
One of the PROMIS (Patient-Reported Outcome Measurement Information System) network's primary goals is the development of a comprehensive item bank for patient-reported outcomes of chronic diseases. For its first set of item banks, PROMIS chose to focus on pain, fatigue, emotional distress, physical function, and social function. An essential step for the development of an item pool is the identification, evaluation, and revision of extant questionnaire items for the core item pool. In this work, we also describe the systematic process wherein items are classified for subsequent statistical processing by the PROMIS investigators. Six phases of item development are documented: identification of extant items, item classification and selection, item review and revision, focus group input on domain coverage, cognitive interviews with individual items, and final revision before field testing. Identification of items refers to the systematic search for existing items in currently available scales. Expert item review and revision was conducted by trained professionals who reviewed the wording of each item and revised as appropriate for conventions adopted by the PROMIS network. Focus groups were used to confirm domain definitions and to identify new areas of item development for future PROMIS item banks. Cognitive interviews were used to examine individual items. Items successfully screened through this process were sent to field testing and will be subjected to innovative scale construction procedures.
patient-reported outcomes; cognitive interviews; qualitative methods; questionnaire development
The goal of this article is to discuss ways to further improve the search for potentially procognitive agents that could be used to enhance cognition and functional outcome in schizophrenia. In particular, we focus on the potential advantages to this process of using a contemporary, cognitive neuroscience-based approach to measuring cognitive function in clinical trials of procognitive agents in schizophrenia. These tools include computer-administered tasks that measure specific cognitive systems (such as attention, working memory, long-term memory, cognitive control) as well as the component cognitive processes that comprise these more overarching systems. The advantages of using these tools include the ability to identify and use homologous animal and human models in the drug discovery and testing process and the ability to incorporate noninvasive functional imaging measures into clinical trial contexts at several different phases of the drug development process. However, despite the clear potential advantages to using such methods, a number of barriers exist to their translation from basic science tools to tools for drug discovery. We discuss the development and implementation of a new project, Cognitive Neuroscience Treatment to Improve Cognition in Schizophrenia, designed to identify and overcome these barriers to the translation of cognitive neuroscience measures and methods into regular use in the drug discovery and development process of cognition-enhancing agents for use in schizophrenia.
pharmacology; cognitive; imaging
Hierarchical functional data are widely seen in complex studies where sub-units are nested within units, which in turn are nested within treatment groups. We propose a general framework of functional mixed effects model for such data: within unit and within sub-unit variations are modeled through two separate sets of principal components; the sub-unit level functions are allowed to be correlated. Penalized splines are used to model both the mean functions and the principal components functions, where roughness penalties are used to regularize the spline fit. An EM algorithm is developed to fit the model, while the specific covariance structure of the model is utilized for computational efficiency to avoid storage and inversion of large matrices. Our dimension reduction with principal components provides an effective solution to the difficult tasks of modeling the covariance kernel of a random function and modeling the correlation between functions. The proposed methodology is illustrated using simulations and an empirical data set from a colon carcinogenesis study. Supplemental materials are available online.
Correlated functions; Functional data; Longitudinal data; Mixed effects models; Penalized splines; Principal components; Reduced rank models
One of the major issues in synaesthesia research is to identify the level of processing involved in the formation of the subjective colours experienced by synaesthetes: are they perceptual phenomena or are they due to memory and association learning? To address this question, we tested whether the colours reported by a group of grapheme-colour synaesthetes (previously studied in an functional magnetic resonance imaging experiment) influenced them in a visual search task. As well as using a condition where synaesthetic colours should have aided visual search, we introduced a condition where the colours experienced by synaesthetes would be expected to make them worse than controls. We found no evidence for differences between synaesthetes and normal controls, either when colours should have helped them or where they should have hindered. We conclude that the colours reported by our population of synaesthetes are not equivalent to perceptual signals, but arise at a cognitive level where they are unable to affect visual search.
synaesthesia; low-level sensory signals; psychophysics; functional magnetic resonance imaging
In cognitive science, lexical decision task is used to investigate visual word recognition and lexical access. The issue of whether or not individuals who are depressed differ in their access to affectively laden words and specifically to words that have negative affect was examined. Based on some aspects of the Resource Allocation Model (Ellis), it was postulated that patients suffering from depression take more time to recognize items from an affective-loaded list. In order to compare their behavior in a lexical decision task, patients suffering from depression and healthy controls were studied. We hoped to find an interaction between the mood state of subjects and the categories (affective or neutral) of words. Two groups of right-handed adults served as subjects in our experiment. The first group consisted of 11 patients suffering from depression (mean age: 40.2; sd: 6.8). All of this group met the DSM-III-R and the Research Diagnostic Criteria for major depressive disorder. Severity of their disease was rated using the 24-item Hamilton Depressive Rating Scale. All patients suffering from depression were without psychotropic medication. The control group was composed of 24 subjects (mean age: 32.7; sd: 7.9). A depressive word-list and a neutral word-list were built and a computer was used for the lexical-decision task. A longer reaction time to detect the non-word stimuli (F1,33 = 11.19, p < 0.01) was observed with the patients by comparison to the normal subjects. In the analysis of the word stimuli, a group by list interaction (F1,33 = 7.18, p < 0.01) was found.(ABSTRACT TRUNCATED AT 250 WORDS)
This study investigated the influences of knowledge, particularly Internet, Web browser, and search engine knowledge, as well as cognitive abilities on older adult information seeking on the Internet. The emphasis on aspects of cognition was informed by a modeling framework of search engine information-seeking behavior. Participants from two older age groups were recruited: twenty people in a younger-old group (ages 60–70) and twenty people in an older-old group (ages 71–85). Ten younger adults (ages 18–39) served as a comparison group. All participants had at least some Internet search experience. The experimental task consisted of six realistic search problems, all involving information related to health and well-being and which varied in degree of complexity. The results indicated that though necessary, Internet-related knowledge was not sufficient in explaining information-seeking performance, and suggested that a combination of both knowledge and key cognitive abilities is important for successful information seeking. In addition, the cognitive abilities that were found to be critical for task performance depended on the search problem’s complexity. Also, significant differences in task performance between the younger and the two older age groups were found on complex, but not on simple problems. Overall, the results from this study have implications for instructing older adults on Internet information seeking and for the design of Web sites.
Theory; Experimentation; Performance; Measurement; Human Factors; older adults; health information seeking; Internet; mental models; Pathfinder networks; search engines
The present paper examines the tie between knowledge and behavior in a noun generalization context. An experiment directly comparing noun generalizations of children at the same point in development in forced choice and yes/no tasks reveals task-specific differences in the way children's knowledge of nominal categories is brought to bear in a moment. To understand the cognitive system that produced these differences, the real-time decision processes in these tasks were instantiated in a dynamic field model. The model captures both qualitative and quantitative differences in performance across tasks and reveals constraints on the nature of children's accumulated knowledge. Additional simulations of developmental change in the yes/no task between 2 and 4 years of age illustrate how changes in children's representations translate into developmental changes in behavior. Together, the empirical data and model demonstrate the dynamic nature of knowledge and are consistent with the perspective that knowledge cannot be separated from the task-specific processes that create behavior in the moment.
Physical function is a key component of patient-reported outcome (PRO) assessment in rheumatology. Modern psychometric methods, such as Item Response Theory (IRT) and Computerized Adaptive Testing, can materially improve measurement precision at the item level. We present the qualitative and quantitative item-evaluation process for developing the Patient Reported Outcomes Measurement Information System (PROMIS) Physical Function item bank.
The process was stepwise: we searched extensively to identify extant Physical Function items and then classified and selectively reduced the item pool. We evaluated retained items for content, clarity, relevance and comprehension, reading level, and translation ease by experts and patient surveys, focus groups, and cognitive interviews. We then assessed items by using classic test theory and IRT, used confirmatory factor analyses to estimate item parameters, and graded response modeling for parameter estimation. We retained the 20 Legacy (original) Health Assessment Questionnaire Disability Index (HAQ-DI) and the 10 SF-36's PF-10 items for comparison. Subjects were from rheumatoid arthritis, osteoarthritis, and healthy aging cohorts (n = 1,100) and a national Internet sample of 21,133 subjects.
We identified 1,860 items. After qualitative and quantitative evaluation, 124 newly developed PROMIS items composed the PROMIS item bank, which included revised Legacy items with good fit that met IRT model assumptions. Results showed that the clearest and best-understood items were simple, in the present tense, and straightforward. Basic tasks (like dressing) were more relevant and important versus complex ones (like dancing). Revised HAQ-DI and PF-10 items with five response options had higher item-information content than did comparable original Legacy items with fewer response options. IRT analyses showed that the Physical Function domain satisfied general criteria for unidimensionality with one-, two-, three-, and four-factor models having comparable model fits. Correlations between factors in the test data sets were > 0.90.
Item improvement must underlie attempts to improve outcome assessment. The clear, personally important and relevant, ability-framed items in the PROMIS Physical Function item bank perform well in PRO assessment. They will benefit from further study and application in a wider variety of rheumatic diseases in diverse clinical groups, including those at the extremes of physical functioning, and in different administration modes.
Contemporary neuropsychological models of ADHD implicate impaired cognitive control as contributing to disorder characteristic behavioral deficiencies and excesses; albeit to varying degrees. While the traditional view of ADHD postulates a core deficiency in cognitive control processes, alternative dual-process models emphasize the dynamic interplay of bottom-up driven factors such as activation, arousal, alerting, motivation, reward and temporal processing with top-down cognitive control. However, neuropsychological models of ADHD are child-based and have yet to undergo extensive empirical scrutiny with respect to their application to individuals with persistent symptoms in adulthood. Furthermore, few studies of adult ADHD samples have investigated two central cognitive control processes: interference control and task-set coordination. The current study employed experimental chronometric Stroop and task switching paradigms to investigate the efficiency of processes involved in interference control and task-set coordination in ADHD adults.
22 adults diagnosed with persistent ADHD (17 males) and 22 matched healthy control subjects performed a manual trial-by-trial Stroop color-word test and a blocked explicitly cued task switching paradigm. Performance differences between neutral and incongruent trials of the Stroop task measured interference control. Task switching paradigm manipulations allowed for measurement of transient task-set updating, sustained task-set maintenance, preparatory mechanisms and interference control. Control analyses tested for the specificity of group × condition interactions.
Abnormal processing of task-irrelevant stimulus features was evident in ADHD group performance on both tasks. ADHD group interference effects on the task switching paradigm were found to be dependent on the time allotted to prepare for an upcoming task. Group differences in sustained task-set maintenance and transient task-set updating were also found to be dependent on experimental manipulation of task preparation processes. With the exception of Stroop task error rates, all analyses revealed generally slower and less accurate ADHD group response patterns.
The current data obtained with experimental paradigms deliver novel evidence of inefficient interference control and task-set coordination in adults with persistent ADHD. However, all group differences observed in these central cognitive control processes were found to be partially dependent on atypical ADHD group task preparation mechanisms and/or response inconsistency. These deficiences may have contributed not only to inefficient cognitive control, but also generally slower and less accurate ADHD group performance. Given the inability to dissociate these impairments with the current data, it remains inconclusive as to whether ineffecient cognitive control in the clinical sample was due to top-down failure or bottom-up engagement thereof. To clarify this issue, future neuropsychological investigations are encouraged to employ tasks with significantly more trials and direct manipulations of bottom-up mechanisms with larger samples.