Bayesian regression-based developmental norms for the Benton Facial Recognition Test in males and females

Continuous Norming Approaches: A Systematic Review and Real Data Example

Norming of psychological tests is decisive for test score interpretation. However, conventional norming based on subgroups results either in biases or require very large samples to gather precise norms. Continuous norming methods, namely inferential, semi-parametric, and (simplified) parametric norming, propose to solve those issues. This article provides a systematic review of continuous norming. The review includes 121 publications with overall 189 studies. The main findings indicate that most studies used simplified parametric norming, not all studies considered essential distributional assumptions, and the evidence comparing different norming methods is inconclusive. In a real data example, using the standardization sample of the Need for Cognition-KIDS scale, we compared the precision of conventional, semi-parametric, and parametric norms. A hierarchy in terms of precision emerged with conventional norms being least precise, followed by semi-parametric norms, and parametric norms being most precise. We discuss these findings by comparing our findings and methods to previous studies.

The neuropsychological evaluation of face identity recognition

Facial identity recognition (FIR) is arguably the ultimate form of recognition for the adult human brain. Even if the term prosopagnosia is reserved for exceptionally rare brain-damaged cases with a category-specific abrupt loss of FIR at adulthood, subjective and objective impairments or difficulties of FIR are common in the neuropsychological population. Here we provide a critical overview of the evaluation of FIR both for clinicians and researchers in neuropsychology. FIR impairments occur following many causes that should be identified objectively by both general and specific, behavioral and neural examinations. We refute the commonly used dissociation between perceptual and memory deficits/tests for FIR, since even a task involving the discrimination of unfamiliar face images presented side-by-side relies on cortical memories of faces in the right-lateralized ventral occipito-temporal cortex. Another frequently encountered confusion is between specific deficits of the FIR function and a more general impairment of semantic memory (of people), the latter being most often encountered following anterior temporal lobe damage. Many computerized tests aimed at evaluating FIR have appeared over the last two decades, as reviewed here. However, despite undeniable strengths, they often suffer from ecological limitations, difficulties of instruction, as well as a lack of consideration for processing speed and qualitative information. Taking into account these issues, a recently developed behavioral test with natural images manipulating face familiarity, stimulus inversion, and correct response times as a key variable appears promising. The measurement of electroencephalographic (EEG) activity in the frequency domain from fast periodic visual stimulation also appears as a particularly promising tool to complete and enhance the neuropsychological assessment of FIR.

Recent Advances in Neuropsychological Test Interpretation for Clinical Practice

Much attention in the field of clinical neuropsychology has focused on adapting to the modern healthcare environment by advancing telehealth and promoting technological innovation in assessment. Perhaps as important (but less discussed) are advances in the development and interpretation of normative neuropsychological test data. These techniques can yield improvement in diagnostic decision-making and treatment planning with little additional cost. Brooks and colleagues (Can Psychol 50: 196-209, 2009) eloquently summarized best practices in normative data creation and interpretation, providing a practical overview of norm development, measurement error, the base rates of low scores, and methods for assessing change. Since the publication of this seminal work, there have been several important advances in research on development and interpretation of normative neuropsychological test data, which may be less familiar to the practicing clinician. Specifically, we provide a review of the literature on regression-based normed scores, item response theory, multivariate base rates, summary/factor scores, cognitive intraindividual variability, and measuring change over time. For each topic, we include (1) an overview of the method, (2) a rapid review of the recent literature, (3) a relevant case example, and (4) a discussion of limitations and controversies. Our goal was to provide a primer for use of normative neuropsychological test data in neuropsychological practice.

A new approach to diagnosing and researching developmental prosopagnosia: Excluded cases are impaired too

Developmental prosopagnosia is characterized by severe, lifelong difficulties when recognizing facial identity. Unfortunately, the most common diagnostic assessment (Cambridge Face Memory Test) misses 50-65% of individuals who believe that they have this condition. This results in such excluded cases' absence from scientific knowledge, effect sizes of impairment potentially overestimated, treatment efficacy underrated, and may elicit in them a negative experience of research. To estimate their symptomology and group-level impairments in face processing, we recruited a large cohort who believes that they have prosopagnosia. Matching prior reports, 56% did not meet criteria on the Cambridge Face Memory Test. However, the severity of their prosopagnosia symptoms and holistic perception deficits were comparable to those who did meet criteria. Excluded cases also exhibited face perception and memory impairments that were roughly one standard deviation below neurotypical norms, indicating the presence of objective problems. As the prosopagnosia index correctly classified virtually every case, we propose it should be the primary method for providing a diagnosis, prior to subtype categorization. We present researchers with a plan on how they can analyze these excluded prosopagnosia cases in their future work without negatively impacting their traditional findings. We anticipate such inclusion will enhance scientific knowledge, more accurately estimate effect sizes of impairments and treatments, and identify commonalities and distinctions between these different forms of prosopagnosia. Owing to their atypicalities in visual perception, we recommend that the prosopagnosia index should be used to screen out potential prosopagnosia cases from broader vision research.

Establishing normative data for the evaluation of cognitive performance in Huntington's disease considering the impact of gender, age, language, and education

BACKGROUND

A declining cognitive performance is a hallmark of Huntington's disease (HD). The neuropsychological battery of the Unified HD Rating Scale (UHDRS'99) is commonly used for assessing cognition. However, there is a need to identify and minimize the impact of confounding factors, such as language, gender, age, and education level on cognitive decline.

OBJECTIVES

Aim is to provide appropriate, normative data to allow clinicians to identify disease-associated cognitive decline in diverse HD populations by compensating for the impact of confounding factors METHODS: Sample data, N = 3267 (60.5% females; mean age of 46.9 years (SD = 14.61, range 18-86) of healthy controls were used to create a normative dataset. For each neuropsychological test, a Bayesian generalized additive model with age, education, gender, and language as predictors was constructed to appropriately stratify the normative dataset.

RESULTS

With advancing age, there was a non-linear decline in cognitive performance. In addition, performance was dependent on educational levels and language in all tests. Gender had a more limited impact. Standardized scores have been calculated to ease the interpretation of an individual's test outcome. A web-based online tool has been created to provide free access to normative data.

CONCLUSION

For defined neuropsychological tests, the impact of gender, age, education, and language as factors confounding disease-associated cognitive decline can be minimized at the level of a single patient examination.

Face-Processing Performance is an Independent Predictor of Social Affect as Measured by the Autism Diagnostic Observation Schedule Across Large-Scale Datasets

Face-processing deficits, while not required for the diagnosis of autism spectrum disorder (ASD), have been associated with impaired social skills-a core feature of ASD; however, the strength and prevalence of this relationship remains unclear. Across 445 participants from the NIMH Data Archive, we examined the relationship between Benton Face Recognition Test (BFRT) performance and Autism Diagnostic Observation Schedule-Social Affect (ADOS-SA) scores. Lower BFRT scores (worse face-processing performance) were associated with higher ADOS-SA scores (higher ASD severity)-a relationship that held after controlling for other factors associated with face processing, i.e., age, sex, and IQ. These findings underscore the utility of face discrimination, not just recognition of facial emotion, as a key covariate for the severity of symptoms that characterize ASD.

Not so fast! Response times in the computerized Benton Face Recognition Test may not reflect face recognition ability

Response times (RTs) are commonly used to assess cognitive abilities, though it is unclear whether face processing RTs predict recognition ability beyond accuracy. In the current study, we examined accuracy and RT on a widely used face matching assessment modified to collect meaningful RT data, the computerized Benton Facial Recognition Test (BFRT-c), and measured whether RTs predicted face recognition ability and developmental prosopagnosia (DP) vs. control group membership. 62 controls and 36 DPs performed the BFRT-c as well as validated measures of face recognition ability: the Cambridge Face Memory Test (CFMT) and a Famous Faces Memory Test (FFMT). In controls, BFRT-c accuracy robustly predicted CFMT (r = .49, p < .001), FFMT (r = .43, p < .001), and a CFMT-FFMT composite (r = .54, p < .001), whereas BFRT-c RT was not significantly associated with these measures (all r's  .21). We also found that BFRT-c accuracy significantly differed between DPs and controls, but RT failed to differentiate the groups.