Matrix reconstruction with reliable neighbors for predicting potential MiRNA-disease associations.

Numerous experimental studies have indicated that alteration and dysregulation in mircroRNAs (miRNAs) are associated with serious diseases. Identifying disease-related miRNAs is therefore an essential and challenging task in bioinformatics research. Computational methods are an efficient and economical alternative to conventional biomedical studies and can reveal underlying miRNA-disease associations for subsequent experimental confirmation with reasonable confidence. Despite the success of existing computational approaches, most of them only rely on the known miRNA-disease associations to predict associations without adding other data to increase the prediction accuracy, and they are affected by issues of data sparsity. In this paper, we present MRRN, a model that combines matrix reconstruction with node reliability to predict probable miRNA-disease associations. In MRRN, the most reliable neighbors of miRNA and disease are used to update the original miRNA-disease association matrix, which significantly reduces data sparsity. Unknown miRNA-disease associations are reconstructed by aggregating the most reliable first-order neighbors to increase prediction accuracy by representing the local and global structure of the heterogeneous network. Five-fold cross-validation of MRRN produced an area under the curve (AUC) of 0.9355 and area under the precision-recall curve (AUPR) of 0.2646, values that were greater than those produced by comparable models. Two different types of case studies using three diseases were conducted to demonstrate the accuracy of MRRN, and all top 30 predicted miRNAs were verified.

LncRTPred: Predicting RNA-RNA mode of interaction mediated by lncRNA.

Long non-coding RNAs (lncRNAs) play a significant role in various biological processes. Hence, it is utmost important to elucidate their functions in order to understand the molecular mechanism of a complex biological system. This versatile RNA molecule has diverse modes of interaction, one of which constitutes lncRNA-mRNA interaction. Hence, identifying its target mRNA is essential to understand the function of an lncRNA explicitly. Existing lncRNA target prediction tools mainly adopt thermodynamics approach. Large execution time and inability to perform real-time prediction limit their usage. Further, lack of negative training dataset has been a hindrance in the path of developing machine learning (ML) based lncRNA target prediction tools. In this work, we have developed a ML-based lncRNA-mRNA target prediction model- 'LncRTPred'. Here we have addressed the existing problems by generating reliable negative dataset and creating robust ML models. We have identified the non-interacting lncRNA and mRNAs from the unlabelled dataset using BLAT. It is further filtered to get a reliable set of outliers. LncRTPred provides a cumulative_model_score as the final output against each query. In terms of prediction accuracy, LncRTPred outperforms other popular target prediction protocols like LncTar. Further, we have tested its performance against experimentally validated disease-specific lncRNA-mRNA interactions. Overall, performance of LncRTPred is heavily dependent on the size of the training dataset, which is highly reflected by the difference in its performance for human and mouse species. Its performance for human species shows better as compared to that for mouse when applied on an unknown data due to smaller size of the training dataset in case of mouse compared to that of human. Availability of increased number of lncRNA-mRNA interaction data for mouse will improve the performance of LncRTPred in future. Both webserver and standalone versions of LncRTPred are available. Web server link: http://bicresources.jcbose.ac.in/zhumur/lncrtpred/index.html. Github Link: https://github.com/zglabDIB/LncRTPred.

Meaningful cognitive change for the Minimal Assessment of Cognitive Function in Multiple Sclerosis.

BACKGROUND: There is limited information on interpretation of cognitive changes over time in multiple sclerosis (MS). OBJECTIVE: This study aimed to provide normative data for the assessment of statistically meaningful change in all tests of the Minimal Assessment of Cognitive Function in MS (MACFIMS). METHODS: We applied the reliable change methodology to a healthy Italian cohort, assessed with two alternate versions of the MACFIMS 1 year apart. We calculated confidence intervals of retest score variance using the reliable change index (RCI). Moreover, multivariable linear regression models adjusted for age, sex, education, and baseline score were built to calculate the regression-based change index (RB-CI). RESULTS: Overall, 200 healthy individuals were enrolled. Thresholds for interpreting change in each test were calculated. In the multivariable models, baseline score was associated with retest score in all tests (B from 0.439 to 0.760; p < 0.001). RB-CI can be calculated with data of the multivariable models. CONCLUSION: We provide normative data for reliable cognitive change evaluation for all the tests of the MACFIMS, which includes the Symbol Digit Modalities Test and Brief International Cognitive Assessment in MS, two widely used tools for screening and monitoring cognition in MS. Our findings can significantly improve the interpretation of cognitive changes in MS.

Relationship of Hoarding and Depression Symptoms in Older Adults.

Hoarding disorder (HD) is a debilitating neuropsychiatric condition that affects 2%-6% of the population and increases in incidence with age. Major depressive disorder (MDD) co-occurs with HD in approximately 50% of cases and leads to increased functional impairment and disability. However, only one study to date has examined the rate and trajectory of hoarding symptoms in older individuals with a lifetime history of MDD, including those with current active depression (late-life depression; LLD). We therefore sought to characterize this potentially distinct phenotype. We determined the incidence of HD in two separate cohorts of participants with LLD (n = 73) or lifetime history of MDD (n = 580) and examined the reliability and stability of hoarding symptoms using the Saving Inventory-Revised (SI-R) and Hoarding Rating Scale-Self Report (HRS), as well as the co-variance of hoarding and depression scores over time. HD was present in 12% to 33% of participants with MDD, with higher rates found in those with active depressive symptoms. Hoarding severity was stable across timepoints in both samples (all correlations >0.75), and fewer than 30% of participants in each sample experienced significant changes in severity between any two timepoints. Change in depression symptoms over time did not co-vary with change in hoarding symptoms. These findings indicate that hoarding is a more common comorbidity in LLD than previously suggested, and should be considered in screening and management of LLD. Future studies should further characterize the interaction of these conditions and their impact on outcomes, particularly functional impairment in this vulnerable population.

Progress in elementary school reading linked to growth of cortical responses to familiar letter combinations within visual word forms.

Learning to read depends on the ability to extract precise details of letter combinations, which convey critical information that distinguishes tens of thousands of visual word forms. To support fluent reading skill, one crucial neural developmental process is one's brain sensitivity to statistical constraints inherent in combining letters into visual word forms. To test this idea in early readers, we tracked the impact of two years of schooling on within-subject longitudinal changes in cortical responses to three different properties of words: coarse tuning for print, and fine tuning to either familiar letter combinations within visual word forms or whole word representations. We then examined how each related to growth in reading skill. Three stimulus contrasts-words versus pseudofonts, words versus pseudowords, pseudowords versus nonwords-were presented while high-density EEG Steady-State Visual Evoked Potentials (SSVEPs, n = 31) were recorded. Internalization of abstract visual word form structures over two years of reading experience resulted in a near doubling of SSVEP amplitude, with increasing left lateralization. Longitudinal changes (decreases) in brain responses to such word form structural information were linked to the growth in reading skills, especially in rapid automatic naming of letters. No such changes were observed for whole word representation processing and coarse tuning for print. Collectively, these findings indicate that sensitivity to visual word form structure develops rapidly through exposure to print and is linked to growth in reading skill. RESEARCH HIGHLIGHTS: Longitudinal changes in cognitive responses to coarse print tuning, visual word from structure, and whole word representation were examined in early readers. Visual word form structure processing demonstrated striking patterns of growth with nearly doubled in EEG amplitude and increased left lateralization. Longitudinal changes (decreases) in brain responses to visual word form structural information were linked to the growth in rapid automatic naming for letters. No longitudinal changes were observed for whole word representation processing and coarse tuning for print.

A longitudinal study of within-person trajectories in quality of life in patients receiving early palliative care.

PURPOSE: To reveal the within-person trajectories in quality of life (QOL) in patients receiving early palliative care. Previous studies have mostly focused aggregated trajectories, based on all research participants combined, whereas this study focused on within-person trajectories in QOL and on whether the variability in QOL trajectories across patients is substantial enough to raise doubts about aggregated trajectories. METHODS: Twenty-five older persons in early palliative care completed the McGill Quality of Life Questionnaire multiple times. Reliable change analyses provided estimates of the occurrence of statistically significant within-person change. RESULTS: There was reliable, within-person variation in QOL scores across time, more so for physical than for psychological aspects of well-being. Changes in QOL scores occurred for most patients but the trajectories were not linear and there was no common trend in the nonlinear patterns. CONCLUSIONS: Reliable change across time can be identified in persons receiving early palliative care. However, the trajectories are notably variable and patient-specific. The high degrees of within-person variability across time suggests the importance of repeated QOL assessments and of dynamic tailoring of clinical treatments.

This study describes the quality of life (QOL) trajectories of 25 persons in early palliative care for life-limiting chronic conditions. Previous studies have mostly focused on aggregated trajectories for all research participants combined. In contrast, this study focused on within-person trajectories in QOL and on whether the variability in QOL trajectories across patients is substantial enough to question the meaningfulness of aggregated trajectories. There was both between-patient and within-person variation in QOL scores across time and no common trend. For some patients, the change was for improving scores across time. For other patients the change was for worsening scores across time. And for still other patients, the changes were reliable but not linear. The trajectories are thus quite variable and patient-specific. The variability in QOL trajectories is substantial enough to raise concerns about aggregated trajectories. The high degrees of within-person variability across time suggests the importance of repeated QOL assessments and of dynamic tailoring of clinical treatments.

Predicting CBT modality, treatment participation, and reliable improvements for individuals with anxiety and depression in a specialized mental health centre: a retrospective population-based cohort study.

BACKGROUND: Cognitive Behaviour Therapy (CBT) is one of the most successful therapeutic approaches for treating anxiety and depression. Clinical trials show that for some clients, internet-based CBT (eCBT) is as effective as other CBT delivery modes. However, the fidelity of these effects may be weakened in real-world settings where clients and providers have the freedom to choose a CBT delivery mode and switch treatments at any time. The purpose of this study is to measure the CBT attendance rate and identify client-level characteristics associated with delivery mode selection and having reliable and clinically significant improvement (RCSI) of treatment in each delivery mode in a real-world CBT outpatient program. METHODS: This is a retrospective cohort analysis of electronic medical records collected between May 1, 2019, and March 31, 2022, at Ontario Shores Centre for Mental Health Sciences. Regression models were used to investigate the impact of individual client characteristics on participation and achieving RCSI of different CBT delivery modes. RESULTS: Our data show a high attendance rate for two and more CBT sessions across all modalities (98% of electronic, 94% of group, 100% of individual, and 99% of mixed CBT). Individuals were more likely to enter mixed and group CBT modality if they were younger, reported being employed, and reported higher depression severity at the baseline. Among the four modalities of CBT delivery, group CBT clients were least likely to have RCSI. Of those who started sessions, clients were significantly more likely to experience RCSI on the Patient Health Questionnaire (PHQ)-9 and the Generalized Anxiety Disorder (GAD)-7 if they were employed, reported more severe symptoms at baseline, and were living in the most deprived neighborhoods. CONCLUSIONS: This study will contribute to the body of knowledge about the implementation and treatment planning of different CBT delivery modes in real-world settings. With the changing clinical environment, it is possible to advocate for the adoption of the eCBT intervention to improve therapy practices and achieve better treatment success. The findings can help guide future CBT program planning based on client socio-demographic characteristics, allowing the optimal therapy type to be targeted to the right client at the right time.

Longitudinal Feasibility of the Montreal Cognitive Assessment (MoCA) in Non-Demented ALS Patients.

INTRODUCTION: The present study aimed at testing the longitudinal feasibility of the Montreal Cognitive Assessment (MoCA) in an Italian cohort of non-demented amyotrophic lateral sclerosis (ALS) patients. METHODS: N = 39 non-demented ALS patients were followed-up at a 5-to-10-month interval (M = 6.8; SD = 1.4) with the MoCA and the Edinburgh Cognitive and Behavioral ALS Screen (ECAS). Practice effects, test-retest reliability, and predictive validity (against follow-up ECAS scores) were assessed. Reliable change indices (RCIs) were derived via a regression-based approach by accounting for retest interval and baseline confounders (i.e., demographics, disease duration, and severity and progression rate). RESULTS: At retest, 100% and 69.2% of patients completed the ECAS and the MoCA, respectively. Patients who could not complete the MoCA showed a slightly more severe and fast-progressing disease. The MoCA was not subject to practice effects (t[32] = -0.80; p = 0.429) and was reliable at retest (intra-class correlation = 0.82). Moreover, baseline MoCA scores predicted the ECAS at retest. RCIs were successfully derived - with baseline MoCA scores being the only significant predictor of retest performances (ps < 0.001). CONCLUSIONS: As long as motor disabilities do not undermine its applicability, the MoCA appears to be longitudinally feasible at a 5-to-10-month interval in non-demented ALS patients. However, ALS-specific screeners - such as the ECAS - should be preferred whenever possible.

Deltoid Tuberosity Index for Proximal Humerus Fracture: Reliability and A Predictor of Systemic Osteoporosis in an Asian Population.

HYPOTHESIS: Our study investigates the reliability of deltoid tuberosity index (DTI) and DTI as a predictor of systemic osteoporosis. BACKGROUND: The proximal humerus is a common fragility fracture. Current literature suggests that poor local bone density is a significant predictor for surgical fixation failure. The DTI is a simple radiographical tool that is strongly correlates with local humeral BMD aiding surgical planning to consider adjuncts or arthroplasty. However, there is a lack of data in the reliability of assessment of DTI, as well as its correlation to systemic osteoporosis. METHODS: Respective cohort of patients with PHF treated at a trauma center in Singapore from August 2017 to July 2018 were recruited. Four raters at different levels of varying clinical seniority measured DTI using shoulder radiographs. The dual energy X-ray Absorptiometry (DEXA) bone mineral density (BMD) scan of the hip and lumbar spine was used to diagnose osteoporosis. Area under receiver operating characteristics (AUROC) analysis was conducted to study the diagnostic utility of DTI to predict the risk of osteoporosis. RESULTS: Our study had 87 patients consisting 18 males and 69 females, mainly of Chinese ethnicity (84%) and mean age of 69.7 years (SD 9.52, range 39-92yrs). For assessment of DTI, there was good intra-rater reliability amongst four raters (correlation coefficient range 0.805- 0.843) and excellent inter-rater reliability between al raters (intraclass correlation coefficient = 0.898; 95% CI 0.784-0.950, p-value <0.001). Based on BMD, 55.2% (n=48) were osteoporotic using T-score <-2.5. The highest correlation of DTI to BMD was with femoral neck density at 0.580. The DTI cut-off of 1.6 had the highest combined sensitivity and false positive rate, with area under curve (AUC) = 0.682 (95% CI, 0.564-0.799) for the overall population and AUC =0.706 (95% CI, 0.569-0.842) for patients <75 years. DISCUSSION: The DTI is a simple and reliable tool, strengthening its applicability in clinical practice to enhance preoperative planning in the surgical fixation of PHF. DTI with a cut off of 1.6 may be helpful tool prompting clinicians to workup and manage underlying osteoporosis.

Distributed MIMO Measurements for Integrated Communication and Sensing in an Industrial Environment.

Many concepts for future generations of wireless communication systems use coherent processing of signals from many distributed antennas. The aim is to improve communication reliability, capacity, and energy efficiency and provide possibilities for new applications through integrated communication and sensing. The large bandwidths available in the higher bands have inspired much work regarding sensing in the millimeter-wave (mmWave) and sub-THz bands; however, the sub-6 GHz cellular bands will still be the main provider of wide cellular coverage due to the more favorable propagation conditions. In this paper, we present a measurement system and results of sub-6 GHz distributed multiple-input-multiple-output (MIMO) measurements performed in an industrial environment. From the measurements, we evaluated the diversity for both large-scale and small-scale fading and characterized the link reliability. We also analyzed the possibility of multistatic sensing and positioning of users in the environment, with the initial results showing a mean-square error below 20 cm on the estimated position. Further, the results clearly showed that new channel models are needed that are spatially consistent and deal with the nonstationary channel properties among the antennas.

Investigating reliable amyloid accumulation in Centiloids: Results from the AMYPAD Prognostic and Natural History Study.

INTRODUCTION: To support clinical trial designs focused on early interventions, our study determined reliable early amyloid-ß (Aß) accumulation based on Centiloids (CL) in pre-dementia populations. METHODS: A total of 1032 participants from the Amyloid Imaging to Prevent Alzheimer's Disease-Prognostic and Natural History Study (AMYPAD-PNHS) and Insight46 who underwent [18F]flutemetamol, [18F]florbetaben or [18F]florbetapir amyloid-PET were included. A normative strategy was used to define reliable accumulation by estimating the 95th percentile of longitudinal measurements in sub-populations (NPNHS = 101/750, NInsight46 = 35/382) expected to remain stable over time. The baseline CL threshold that optimally predicts future accumulation was investigated using precision-recall analyses. Accumulation rates were examined using linear mixed-effect models. RESULTS: Reliable accumulation in the PNHS was estimated to occur at >3.0 CL/year. Baseline CL of 16 [12,19] best predicted future Aß-accumulators. Rates of amyloid accumulation were tracer-independent, lower for APOE ε4 non-carriers, and for subjects with higher levels of education. DISCUSSION: Our results support a 12-20 CL window for inclusion into early secondary prevention studies. Reliable accumulation definition warrants further investigations.

Training to use smart tablets to access reliable online health information in older adults' post-pandemic: A focused pilot intervention study.

BACKGROUND: Older adults are becoming more accepting and interested in using digital technologies, but difficulties and barriers remain for accessing reliable health-related information. The purpose of this focused pilot intervention study was to: (1) understand older adults' firsthand experiences and challenges while using smart tablets post-COVID-19 pandemic, and (2) gather suggestions for age-appropriate training materials, preference of training materials, and resources to access reliable online health information. METHODS: A focused pilot intervention study that involved training older adults to use smart tablets followed by focus group of a convenience sample of 13 older adults (65-85 years old; 91.6% female) on their experiences of using smart tablets. RESULTS: Thematic analysis revealed three themes: tablets are convenient to access online information and older adults reported technical, security concerns, emotional and cognitive challenges regarding use of smart tablets. Older adults also requested one-on-one support, assistance, and topic specific learning for future training sessions. CONCLUSIONS: Future studies should focus on providing detailed, clear instructions at an acceptable pace for older adults.

Quantifying animals' perception of environmental predictability using anticipatory behavior.

Animals under human care often experience predictable daily husbandry events, which can promote the development of anticipatory behavior. Previous research suggests even short delays in the arrival of a predictable, desired outcome can lead to negative welfare outcomes for animals. As such, providing reliable information to animals regarding the onset of important events may be a simple but useful method to support positive welfare. Here we evaluated the quantitative characteristics of anticipatory behavior of a California sea lion at the San Francisco Zoo in three situations (1) when the animal had accurate information about the occurrence of the event (temporally predictable training sessions), (2) when the information was semi-reliable (unscheduled training session), and (3) when a reliable signal was offered before unscheduled sessions. Results showed that providing a reliable cue resulted in a stronger temporal correlation of anticipation before the beginning of the unscheduled session, similar to the temporally predictable training session. However, providing a reliable cue did not reduce the intensity of the anticipatory behavior. We propose to take into account two aspects of the quantitative characteristics of anticipatory behavior: correlation with time until a desired event (correlation) and intensity, where the correlation indicates the ability of an individual animal to predict the occurrence of an event, and the intensity indicates the degree of sensitivity of the animal to reward. We discuss the implications for animal welfare and husbandry.

Incremental Coding for Real-Time Remote Control over Bandwidth-Limited Channels and Its Applications in Smart Grids.

Remote control over communication networks with bandwidth-constrained channels has attracted considerable recent attention because it holds the promise of enabling a large number of real-time applications, such as autonomous driving, smart grids, and the industrial internet of things (IIoT). However, due to the limited bandwidth, the sub-packets or even bits have to be transmitted successively, thereby experiencing non-negligible latency and inducing serious performance loss in remote control. To overcome this, we introduce an incremental coding method, in which the actuator acts in real time based on a partially received packet instead of waiting until the entire packet is decoded. On this basis, we applied incremental coding to a linear control system to obtain a remote-control scheme. Both its stability conditions and average linear-quadratic-Gaussian-(LQG) cost are presented. Then, we further investigated a multi-user remote-control method, with a particular focus on its applications in the demand response of smart grids over bandwidth-constrained communication networks. The utility loss due to the bandwidth constraint and communication latency are minimized by jointly optimizing the source coding and real-time demand response. The numerical results show that the incremental-coding-aided remote control performed well in both single-user and multi-user scenarios and outperformed the conventional zero-hold control scheme significantly under the LQG metric.

Utilizing a learning health system to capture real-world patient data: Application of the reliable change index to evaluate and improve the outcome of a pain rehabilitation program.

BACKGROUND AND OBJECTIVES: The learning healthcare system (LHS) has been developed to integrate patients' clinical data into clinical decisions and improve treatment outcomes. Having little guidance on this integration process, we aim to explain (a) an applicable analytic tool for clinicians to evaluate the clinical outcomes at a group and an individual level and (b) our quality improvement (QI) project, analyzing the outcomes of a new outpatient pain rehabilitation program ("Back-in-Action": BIA) and applying the analysis results to modify our clinical practice. METHODS: Through our LHS (CHOIR; https://choir.stanford.edu), we administered the Pain Catastrophizing Scale (PCS), Chronic Pain Acceptance Questionnaire (CPAQ), and Patient-Reported Outcomes Measures (PROMIS)® before and after BIA. After searching for appropriate analytic tools, we decided to use the Reliable Change Index (RCI) to determine if an observed change in the direction of better (improvement) or worse (deterioration) would be beyond or within the measurement error (no change). RESULTS: Our RCI calculations revealed that at least a 9-point decrease in the PCS scores and 10-point increase in the CPAQ scores would indicate reliable improvement. RCIs for the PROMIS measures ranged from 5 to 8 T-score points (i.e., 0.5-0.8 SD). When evaluating change scores of the PCS, CPAQ, and PROMIS measures, we found that 94% of patients showed improvement in at least one domain after BIA and 6% showed no reliable improvement. CONCLUSIONS: Our QI project revealed RCI as a useful tool to evaluate treatment outcomes at a group and an individual level, and RCI could be incorporated into the LHS to generate a progress report automatically for clinicians. We further explained how clinicians could use RCI results to modify a clinical practice, to improve the outcomes of a pain program, and to develop individualized care plans. Lastly, we suggested future research areas to improve the LHS application in pain practice.

[The procedural aspects of postmortem defense of non-material goods of patient].

The protection of privacy of patient that is applying for medical care, diagnostics and treatment is one of the main pillars of implementation of medical activities. However, despite sufficient volume of legal regulation of lifetime respect of privacy of examination, observation and facts of medical intervention, in practice occur situations when privacy ceases to be such after death of the patient. The article is based on results of content-analysis of normative legal acts (n = 11), scientific publications (n = 52), cases of judicial practice (n = 8). The problem of non-observance of privacy becomes especially actual after death of person whose name is widely known. Having no possibility to impact on causes and modes of obtaining and propagating such specific information, the deceased, one's illness, stages of treatment, struggle for life, resources spent, clinics and specialists involved become object of close attention of various subjects (mas media, Internet communities) that use obtained information for speculative purposes at the expense of fixation of inhumane public replicas and increase of number of browsing. Despite prohibition provided for by law of dissemination of information constituting privacy of applying for medical care, after death of patient and application of measures of legal liability for fact of such a disclosure, information leak occurs regularly and information that got into common access frequently discredit good name of the deceased or develop other problems that are subjects to legal protection, for family members and legal successors. Yet, circumstances of transfer of information of limited access by medical organization (data leakage) or by intent of medical worker are difficult to be proved. Therefore, in judicial practice there are practically no such cases. At that, after death of famous people, juristic community regularly faces problems of protecting personal rights and non-material values from the side of relatives, legal successors and other interested persons. On the basis of formal logical method and system analysis method of disputable situations, possible perspectives of applying for judicial protection, procedural characteristics of procedure of applying for protection and possible composition of participants are presented.

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.

Sparse Bayesian modeling of hierarchical independent component analysis: Reliable estimation of individual differences in brain networks.

Independent component analysis (ICA) is one of the leading approaches for studying brain functional networks. There is increasing interest in neuroscience studies to investigate individual differences in brain networks and their association with demographic characteristics and clinical outcomes. In this work, we develop a sparse Bayesian group hierarchical ICA model that offers significant improvements over existing ICA techniques for identifying covariate effects on the brain network. Specifically, we model the population-level ICA source signals for brain networks using a Dirichlet process mixture. To reliably capture individual differences on brain networks, we propose sparse estimation of the covariate effects in the hierarchical ICA model via a horseshoe prior. Through extensive simulation studies, we show that our approach performs considerably better in detecting covariate effects in comparison with the leading group ICA methods. We then perform an ICA decomposition of a between-subject meditation study. Our method is able to identify significant effects related to meditative practice in brain regions that are consistent with previous research into the default mode network, whereas other group ICA approaches find few to no effects.

Does Scoring Method Impact Estimation of Significant Individual Changes Assessed by Patient-Reported Outcome Measures? Comparing Classical Test Theory Versus Item Response Theory.

OBJECTIVES: This study aimed to examine the ability of classical test theory (CTT) and item response theory (IRT) scores assessed by Patient-Reported Outcomes Measurement Information System® (PROMIS®) measures to identify significant individual changes in the setting of clinical studies, using both simulated and empirical data. METHODS: We used simulated data to compare the estimation of significant individual changes between CTT and IRT scores across different conditions and a clinical trial data set to verify the simulation results. We calculated reliable change indexes to estimate significant individual changes. RESULTS: For small true change, IRT scores showed a slightly higher rate of classifying change groups than CTT scores and were comparable with CTT scores for a shorter test length. Additionally, IRT scores were found to have a prominent advantage in the classification rates of change groups for medium to high true change over CTT scores. Such an advantage became prominent in a longer test length. The empirical data analysis results using an anchor-based approach further supported the above findings that IRT scores can more accurately classify participants into change groups than CTT scores. CONCLUSIONS: Given that IRT scores perform better, or at least comparably, in most conditions, we recommend using IRT scores to estimate significant individual changes and identify responders to treatment. This study provides evidence-based guidance in detecting individual changes based on CTT and IRT scores under various measurement conditions and leads to recommendations for identifying responders to treatment for participants in clinical trials.

Lexical and sublexical cortical tuning for print revealed by Steady-State Visual Evoked Potentials (SSVEPs) in early readers.

There are multiple levels of processing relevant to reading that vary in their visual, sublexical, and lexical orthographic processing demands. Segregating distinct cortical sources for each of these levels has been challenging in EEG studies of early readers. To address this challenge, we applied recent advances in analyzing high-density EEG using Steady-State Visual Evoked Potentials (SSVEPs) via data-driven Reliable Components Analysis (RCA) in a group of early readers spanning from kindergarten to second grade. Three controlled stimulus contrasts-familiar words versus unfamiliar pseudofonts, familiar words versus pseudowords, and pseudowords versus nonwords-were used to isolate coarse print tuning, lexical processing, and sublexical orthography-related processing, respectively. First, three overlapping yet distinct neural sources-left vOT, dorsal parietal, and primary visual cortex were revealed underlying coarse print tuning. Second, we segregated distinct cortical sources for the other two levels of processing: lexical fine tuning over occipito-temporal/parietal regions; sublexical orthographic fine tuning over left occipital regions. Finally, exploratory group analyses based on children's reading fluency suggested that coarse print tuning emerges early even in children with limited reading knowledge, while sublexical and higher-level lexical processing emerge only in children with sufficient reading knowledge. RESEARCH HIGHLIGHTS: Cognitive processes underlying coarse print tuning, sublexical, and lexical fine tuning were examined in beginning readers. Three overlapping yet distinct neural sources-left ventral occipito-temporal (vOT), left temporo-parietal, and primary visual cortex-were revealed underlying coarse print tuning. Responses to sublexical orthographic fine tuning were found over left occipital regions, while responses to higher-level linguistic fine tuning were found over occipito-temporal/parietal regions. Exploratory group analyses suggested that coarse print tuning emerges in children with limited reading knowledge, while sublexical and higher-level linguistic fine tuning effects emerge in children with sufficient reading knowledge.