Rapid picture naming in Parkinson's disease using the Mobile Universal Lexicon Evaluation System (MULES)

Rapid Automatized Picture Naming in an Outpatient Concussion Center: Quantitative Eye Movements during the Mobile Universal Lexicon Evaluation System (MULES) Test

Number and picture rapid automatized naming (RAN) tests are useful sideline diagnostic tools. The main outcome measure of these RAN tests is the completion time, which is prolonged with a concussion, yet yields no information about eye movement behavior. We investigated eye movements during a digitized Mobile Universal Lexicon Evaluation System (MULES) test of rapid picture naming. A total of 23 participants with a history of concussion and 50 control participants performed MULES testing with simultaneous eye tracking. The test times were longer in participants with a concussion (32.4 s [95% CI 30.4, 35.8] vs. 26.9 s [95% CI 25.9, 28.0], t=6.1). The participants with a concussion made more saccades per picture than the controls (3.6 [95% CI 3.3, 4.1] vs. 2.7 [95% CI 2.5, 3.0]), and this increase was correlated with longer MULES times (r = 0.46, p = 0.026). The inter-saccadic intervals (ISI) did not differ between the groups, nor did they correlate with the test times. Following a concussion, eye movement behavior differs during number versus picture RAN performance. Prior studies have shown that ISI prolongation is the key finding for a number-based RAN test, whereas this study shows a primary finding of an increased saccade number per picture with a picture-based RAN test. Number-based and picture-based RAN tests may be complimentary in concussion detection, as they may detect different injury effects or compensatory strategies.

Exploration of Rapid Automatized Naming and Standard Visual Tests in Prodromal Alzheimer Disease Detection

BACKGROUND

Visual tests in Alzheimer disease (AD) have been examined over the last several decades to identify a sensitive and noninvasive marker of the disease. Rapid automatized naming (RAN) tasks have shown promise for detecting prodromal AD or mild cognitive impairment (MCI). The purpose of this investigation was to determine the capacity for new rapid image and number naming tests and other measures of visual pathway structure and function to distinguish individuals with MCI due to AD from those with normal aging and cognition. The relation of these tests to vision-specific quality of life scores was also examined in this pilot study.

METHODS

Participants with MCI due to AD and controls from well-characterized NYU research and clinical cohorts performed high and low-contrast letter acuity (LCLA) testing, as well as RAN using the Mobile Universal Lexicon Evaluation System (MULES) and Staggered Uneven Number test, and vision-specific quality of life scales, including the 25-Item National Eye Institute Visual Function Questionnaire (NEI-VFQ-25) and 10-Item Neuro-Ophthalmic Supplement. Individuals also underwent optical coherence tomography scans to assess peripapillary retinal nerve fiber layer and ganglion cell/inner plexiform layer thicknesses. Hippocampal atrophy on brain MRI was also determined from the participants' Alzheimer disease research center or clinical data.

RESULTS

Participants with MCI (n = 14) had worse binocular LCLA at 1.25% contrast compared with controls (P = 0.009) and longer (worse) MULES test times (P = 0.006) with more errors in naming images (P = 0.009) compared with controls (n = 16). These were the only significantly different visual tests between groups. MULES test times (area under the receiver operating characteristic curve [AUC] = 0.79), MULES errors (AUC = 0.78), and binocular 1.25% LCLA (AUC = 0.78) showed good diagnostic accuracy for distinguishing MCI from controls. A combination of the MULES score and 1.25% LCLA demonstrated the greatest capacity to distinguish (AUC = 0.87). These visual measures were better predictors of MCI vs control status than the presence of hippocampal atrophy on brain MRI in this cohort. A greater number of MULES test errors (rs = -0.50, P = 0.005) and worse 1.25% LCLA scores (rs = 0.39, P = 0.03) were associated with lower (worse) NEI-VFQ-25 scores.

CONCLUSIONS

Rapid image naming (MULES) and LCLA are able to distinguish MCI due to AD from normal aging and reflect vision-specific quality of life. Larger studies will determine how these easily administered tests may identify patients at risk for AD and serve as measures in disease-modifying therapy clinical trials.

Deciphering the Retinal Epigenome during Development, Disease and Reprogramming: Advancements, Challenges and Perspectives

Retinal neurogenesis is driven by concerted actions of transcription factors, some of which are expressed in a continuum and across several cell subtypes throughout development. While seemingly redundant, many factors diversify their regulatory outcome on gene expression, by coordinating variations in chromatin landscapes to drive divergent retinal specification programs. Recent studies have furthered the understanding of the epigenetic contribution to the progression of age-related macular degeneration, a leading cause of blindness in the elderly. The knowledge of the epigenomic mechanisms that control the acquisition and stabilization of retinal cell fates and are evoked upon damage, holds the potential for the treatment of retinal degeneration. Herein, this review presents the state-of-the-art approaches to investigate the retinal epigenome during development, disease, and reprogramming. A pipeline is then reviewed to functionally interrogate the epigenetic and transcriptional networks underlying cell fate specification, relying on a truly unbiased screening of open chromatin states. The related work proposes an inferential model to identify gene regulatory networks, features the first footprinting analysis and the first tentative, systematic query of candidate pioneer factors in the retina ever conducted in any model organism, leading to the identification of previously uncharacterized master regulators of retinal cell identity, such as the nuclear factor I, NFI. This pipeline is virtually applicable to the study of genetic programs and candidate pioneer factors in any developmental context. Finally, challenges and limitations intrinsic to the current next-generation sequencing techniques are discussed, as well as recent advances in super-resolution imaging, enabling spatio-temporal resolution of the genome.

The MICK (Mobile integrated cognitive kit) app: Digital rapid automatized naming for visual assessment across the spectrum of neurological disorders

OBJECTIVE

Rapid automatized naming (RAN) tasks have been utilized for decades to evaluate neurological conditions. Time scores for the Mobile Universal Lexicon Evaluation System (MULES, rapid picture naming) and Staggered Uneven Number (SUN, rapid number naming) are prolonged (worse) with concussion, mild cognitive impairment, multiple sclerosis and Parkinson's disease. The purpose of this investigation was to compare paper/pencil versions of MULES and SUN with a new digitized format, the MICK app.

METHODS

Participants (healthy office-based volunteers, professional women's hockey players), completed two trials of the MULES and SUN tests on both platforms (tablet, paper/pencil). The order of presentation of the testing platforms was randomized. Between-platform variability was calculated using the two-way random-effects intraclass correlation coefficient (ICC).

RESULTS

Among 59 participants (median age 32, range 22-83), no significant differences were observed for comparisons of mean best scores for the paper/pencil versus MICK app platforms, counterbalanced for order of administration (P = 0.45 for MULES, P = 0.50 for SUN, linear regression). ICCs for agreement between the MICK and paper/pencil tests were 0.92 (95% CI 0.86, 0.95) for MULES and 0.94 (95% CI 0.89, 0.96) for SUN, representing excellent levels of agreement. Inter-platform differences did not vary systematically across the range of average best time score for either test.

CONCLUSION

The MICK app for digital administration of MULES and SUN demonstrates excellent agreement of time scores with paper/pencil testing. The computerized app allows for greater accessibility and scalability in neurological diseases, inclusive of remote monitoring. Sideline testing for sports-related concussion may also benefit from this technology.

Management of Visual Dysfunction in Patients with Parkinson's Disease

Parkinson’s disease (PD) is a movement disorder with many symptoms responsive to treatment with dopamine agonists, anti-cholinergics and the dopamine precursor, levodopa. The cardinal features of PD include tremor, rigidity, bradykinesia, and postural instability. There also are non-motor features that include sleep disorders, cognitive and affective dysfunction, hyposmia, pain and dysautonomia (constipation, bloating, orthostasis, urinary symptoms, sexual dysfunction, dysphagia). Among these non-motor features are signs and symptoms of visual system impairment that range from subtle examination findings to those causing severe disability. In this review we describe common PD-related abnormalities in the visual system, how they present, and potential treatments.

Sleep-deprived residents and rapid picture naming performance using the Mobile Universal Lexicon Evaluation System (MULES) test

Objective

The Mobile Universal Lexicon Evaluation System (MULES) is a rapid picture naming task that captures extensive brain networks involving neurocognitive, afferent/efferent visual, and language pathways. Many of the factors captured by MULES may be abnormal in sleep-deprived residents. This study investigates the effect of sleep deprivation in post-call residents on MULES performance.

Methods

MULES, consisting of 54 color photographs, was administered to a cohort of neurology residents taking 24-hour in-hospital call (n = 18) and a group of similar-aged controls not taking call (n = 18). Differences in times between baseline and follow-up MULES scores were compared between the two groups.

Results

MULES time change in call residents was significantly worse (slower) from baseline (mean 1.2 s slower) compared to non-call controls (mean 11.2 s faster) (P < 0.001, Wilcoxon rank sum test). The change in MULES time from baseline was significantly correlated to the change in subjective level of sleepiness for call residents and to the amount of sleep obtained in the 24 h prior to follow-up testing for the entire cohort. For call residents, the duration of sleep obtained during call did not significantly correlate with change in MULES scores. There was no significant correlation between MULES change and sleep quality questionnaire score for the entire cohort.

Conclusion

The MULES is a novel test for effects of sleep deprivation on neurocognition and vision pathways. Sleep deprivation significantly worsens MULES performance. Subjective sleepiness may also affect MULES performance. MULES may serve as a useful performance assessment tool for sleep deprivation in residents.

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MULES is a rapid picture naming test that captures extensive brain networks.

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MULES performance is impaired in sleep deprived residents.

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Subjective sleepiness may also affect MULES performance.

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MULES may serve as an assessment tool for sleep deprivation in residents.

Afferent and Efferent Visual Markers of Alzheimer's Disease: A Review and Update in Early Stage Disease

Vision, which requires extensive neural involvement, is often impaired in Alzheimer's disease (AD). Over the last few decades, accumulating evidence has shown that various visual functions and structures are compromised in Alzheimer's dementia and when measured can detect those with dementia from those with normal aging. These visual changes involve both the afferent and efferent parts of the visual system, which correspond to the sensory and eye movement aspects of vision, respectively. There are fewer, but a growing number of studies, that focus on the detection of predementia stages. Visual biomarkers that detect these stages are paramount in the development of successful disease-modifying therapies by identifying appropriate research participants and in identifying those who would receive future therapies. This review provides a summary and update on common afferent and efferent visual markers of AD with a focus on mild cognitive impairment (MCI) and preclinical disease detection. We further propose future directions in this area. Given the ease of performing visual tests, the accessibility of the eye, and advances in ocular technology, visual measures have the potential to be effective, practical, and non-invasive biomarkers of AD.