Classification of Functional Movement Disorders with Resting-State Functional Magnetic Resonance Imaging.

Introduction: Functional movement disorder (FMD) is a type of functional neurological disorder characterized by abnormal movements that patients do not perceive as self-generated. Prior imaging studies show a complex pattern of altered activity, linking regions of the brain involved in emotional responses, motor control, and agency. This study aimed to better characterize these relationships by building a classifier using a support vector machine to accurately distinguish between 61 FMD patients and 59 healthy controls using features derived from resting-state functional magnetic resonance imaging. Materials and Methods: First, we selected 66 seed regions based on prior related studies, then we calculated the full correlation matrix between them before performing recursive feature elimination to winnow the feature set to the most predictive features and building the classifier. Results: We identified 29 features of interest that were highly predictive of the FMD condition, classifying patients and controls with 80% accuracy. Several key features included regions in the right sensorimotor cortex, left dorsolateral prefrontal cortex, left cerebellum, and left posterior insula. Conclusions: The features selected by the model highlight the importance of the interconnected relationship between areas associated with emotion, reward, and sensorimotor integration, potentially mediating communication between regions associated with motor function, attention, and executive function. Exploratory machine learning was able to identify this distinctive abnormal pattern, suggesting that alterations in functional linkages between these regions may be a consistent feature of the condition in many FMD patients. Clinical-Trials.gov ID: NCT00500994 Impact statement Our research presents novel results that further elucidate the pathophysiology of functional movement disorder (FMD) with a machine learning model that classifies FMD and healthy controls correctly 80% of the time. Herein, we demonstrate how known differences in resting-state functional magnetic resonance imaging connectivity in FMD patients can be leveraged to better understand the complex pattern of neural changes in these patients. Knowing that there are measurable predictable differences in brain activity in patients with FMD may help both clinicians and patients conceptualize and better understand the illness at the point of diagnosis and during treatment. Our methods demonstrate how an effective combination of machine learning and qualitative approaches to analyzing functional brain connectivity can enhance our understanding of abnormal patterns of brain activity in FMD patients.

Longitudinal changes in network homogeneity in presymptomatic C9orf72 mutation carriers.

The risk for carriers of repeat expansion mutations in C9orf72 to develop amyotrophic lateral sclerosis and frontotemporal dementia increases with age. Functional magnetic resonance imaging studies have shown reduced connectivity in symptomatic carriers, but it is not known whether connectivity declines throughout life as an acceleration of the normal aging pattern. In this study, we examined intra-network homogeneity (NeHo) in 5 functional networks in 15 presymptomatic C9+ carriers over an 18-month period and compared to repeated scans in 34 healthy controls and 27 symptomatic C9+ carriers. The longitudinal trajectory of NeHo in the somatomotor, dorsal attention, and default mode networks in presymptomatic carriers differed from aging controls and symptomatic carriers. In somatomotor networks, NeHo increased over time in regions adjacent to regions where symptomatic carriers had reduced NeHo. In the default network, the posterior cingulate exhibited age-dependent increases in NeHo. These findings are evidence against the proposal that the decline in functional connectivity seen in symptomatic carriers represents a lifelong acceleration of the healthy aging process.

Augmenting visual analysis in single-case research with hierarchical linear modeling.

The purpose of this article is to demonstrate how hierarchical linear modeling (HLM) can be used to enhance visual analysis of single-case research (SCR) designs. First, the authors demonstrated the use of growth modeling via HLM to augment visual analysis of a sophisticated single-case study. Data were used from a delayed multiple baseline design, across groups of participants, with an embedded changing criterion design in a single-case literacy project for students with moderate intellectual disabilities (MoID). Visual analysis revealed a functional relation between instruction and sight-word acquisition for all students. Growth HLM quantified relations at the group level and revealed additional information that included statistically significant variability among students at initial-baseline probe and also among growth trajectories within treatment subphases. Growth HLM showed that receptive vocabulary was a significant predictor of initial knowledge of sight words, and print knowledge significantly predicted growth rates in both treatment subphases. Next, to show the benefits of combining these methodologies to examine a different behavioral topography within a more commonly used SCR design, the authors used repeated-measures HLM and visual analysis to examine simulated data within an ABAB design. Visual analysis revealed a functional relation between a hypothetical intervention (e.g., token reinforcement) and a hypothetical dependent variable (e.g., performance of a target response). HLM supported the existence of a functional relation through tests of statistical significance and detected significant variance among participants' response to the intervention that would be impossible to identify visually. This study highlights the relevance of these procedures to the identification of evidence-based interventions.

Effects of error correction during assessment probes on the acquisition of sight words for students with moderate intellectual disabilities.

Simultaneous prompting is an errorless learning strategy designed to reduce the number of errors students make; however, research has shown a disparity in the number of errors students make during instructional versus probe trials. This study directly examined the effects of error correction versus no error correction during probe trials on the effectiveness and efficiency of simultaneous prompting on the acquisition of sight words by three middle school students with moderate intellectual disabilities. A single-case adapted alternating treatments (Sindelar, Rosenberg, & Wilson, 1985) embedded in a multiple baseline across word sets design was employed to examine the effects of error correction during probe trials in order to reduce error rates. A functional relation was established for two of the three students for the use of error correction during probe sessions to reduce error rates. Error correction during assessment probes required fewer sessions to criterion, resulted in fewer probe errors, resulted in a higher percentage of correct responding on the next subsequent trial, and required less total probe time. For two of the three students, probes with error correction resulted in a more rapid acquisition rate requiring fewer sessions to criterion.

Teaching the reading of connected text through sight-word instruction to students with moderate intellectual disabilities.

Sight-word instruction is the most common method of reading instruction for students with Moderate Intellectual Disabilities reported in the research literature. The purpose of this study was to go beyond instruction of single word units to instruction of multiple-word phrases. This study demonstrated the instruction of reading and comprehending individual words and connected text through the use of simultaneous prompting. Instruction progressed through a series of phases which systematically introduced various parts of speech and combinations of parts of speech. Following acquisition, students demonstrated generalization across connected text found in community environments and leisure-reading materials.

Using simultaneous prompting to teach sounds and blending skills to students with moderate intellectual disabilities.

The purpose of this study was to examine the effects of simultaneous prompting on acquisition of letter-sound correspondences and blending skills of previously taught words for three elementary students with moderate intellectual disabilities, and to measure generalization of those skills to untaught words. The three students were first taught to read five nouns using sight-word instruction. After acquisition of the five words the students were taught letter-sound correspondences and to blend the sounds in order to apply word-analysis skills. All the students demonstrated application of letter-sound correspondences and blending skills to read the five sight words and the untaught, generalization words. This study took place across two partial academic school years and therefore provides regression and recoupment data for the students.