Machine Learning in Healthcare.

Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) technology have brought on substantial strides in predicting and identifying health emergencies, disease populations, and disease state and immune response, amongst a few. Although, skepticism remains regarding the practical application and interpretation of results from ML-based approaches in healthcare settings, the inclusion of these approaches is increasing at a rapid pace. Here we provide a brief overview of machine learning-based approaches and learning algorithms including supervised, unsupervised, and reinforcement learning along with examples. Second, we discuss the application of ML in several healthcare fields, including radiology, genetics, electronic health records, and neuroimaging. We also briefly discuss the risks and challenges of ML application to healthcare such as system privacy and ethical concerns and provide suggestions for future applications.

Test-retest of a phoria adaptation stimulus-induced functional MRI experiment.

This study was designed to identify the neural substrates activated during a phoria adaptation task using functional magnetic resonance imaging (MRI) in young adults with normal binocular vision and to test the repeatability of the fMRI measurements for this protocol. The phoria adaptation task consisted of a block protocol of 90 seconds of near visual crossed fixation followed by 90 seconds of far visual uncrossed fixation, repeated three times; the data were collected during two different experimental sessions. Results showed that the oculomotor vermis, cuneus, and primary visual cortex had the greatest functional activity within the regions of interest studied when stimulated by the phoria adaptation task. The oculomotor vermis functional activity had an intraclass correlation coefficient (ICC) of 0.3, whereas the bilateral cuneus and primary visual cortex had good ICC results of greater than 0.6. These results suggest that the sustained visual fixation task described within this study reliably activates the neural substrates of phoria adaptation. This protocol establishes a methodology that can be used in future longitudinal studies investigating therapeutic interventions that may modify phoria adaptation.

Frequency specific resting state functional abnormalities in psychosis.

Resting state functional magnetic resonance imaging studies of psychosis have focused primarily on the amplitude of low-frequency fluctuations in the blood oxygen level dependent (BOLD) signal ranging from .01 to 0.1 Hz. Few studies, however, have investigated the amplitude of frequency fluctuations within discrete frequency bands and higher than 0.1 Hz in patients with psychosis at different illness stages. We investigated BOLD signal within three frequency ranges including slow-4 (.027-.073 Hz), slow-3 (.074-0.198 Hz) and slow-2 (0.199-0.25 Hz) in 89 patients with either first-episode or chronic psychosis and 119 healthy volunteers. We investigated the amplitude of frequency fluctuations within three frequency bands using 47 regions-of-interest placed within 14 known resting state networks derived using group independent component analysis. There were significant group x frequency interactions for the visual and motor cortex networks, with the largest significant group differences (patients < healthy volunteers) evident in slow-4 and slow-3, respectively. Also, healthy volunteers had an overall higher amplitude of frequency fluctuations compared to patients across the three frequency ranges in the visual cortex, dorsal attention and motor cortex networks with the opposite effect (patients > healthy volunteers) evident within the salience and frontal gyrus networks. Subsequent analyses indicated that these effects were evident in both first-episode and chronic patients. Our study provides new data regarding the importance of BOLD signal fluctuations within different frequency bands in the neurobiology of psychosis.

Localized reductions in resting-state functional connectivity in children with prenatal alcohol exposure.

Fetal alcohol spectrum disorders (FASD) are characterized by impairment in cognitive function that may or may not be accompanied by craniofacial anomalies, microcephaly, and/or growth retardation. Resting-state functional MRI (rs-fMRI), which examines the low-frequency component of the blood oxygen level dependent (BOLD) signal in the absence of an explicit task, provides an efficient and powerful mechanism for studying functional brain networks even in low-functioning and young subjects. Studies using independent component analysis (ICA) have identified a set of resting-state networks (RSNs) that have been linked to distinct domains of cognitive and perceptual function, which are believed to reflect the intrinsic functional architecture of the brain. This study is the first to examine resting-state functional connectivity within these RSNs in FASD. Rs-fMRI scans were performed on 38 children with FASD (19 with either full fetal alcohol syndrome (FAS) or partial FAS (PFAS), 19 nonsyndromal heavily exposed (HE)), and 19 controls, mean age 11.3 ± 0.9 years, from the Cape Town Longitudinal Cohort. Nine resting-state networks were generated by ICA. Voxelwise group comparison between a combined FAS/PFAS group and controls revealed localized dose-dependent functional connectivity reductions in five regions in separate networks: anterior default mode, salience, ventral and dorsal attention, and R executive control. The former three also showed lower connectivity in the HE group. Gray matter connectivity deficits in four of the five networks appear to be related to deficits in white matter tracts that provide intra-RSN connections. Hum Brain Mapp 38:5217-5233, 2017. © 2017 Wiley Periodicals, Inc.

From convergence insufficiency to functional reorganization: A longitudinal randomized controlled trial of treatment-induced connectivity plasticity.

INTRODUCTION: Convergence Insufficiency (CI) is the most prevalent oculomotor dysfunction of binocular vision that negatively impacts quality of life when performing visual near tasks. Decreased resting-state functional connectivity (RSFC) is reported in the CI participants compared to binocularly normal control participants. Studies report that therapeutic interventions such as office-based vergence and accommodative therapy (OBVAT) can improve CI participants' clinical signs, visual symptoms, and task-related functional activity. However, longitudinal studies investigating the RSFC changes after such treatments in participants with CI have not been conducted. This study aimed to investigate the neural basis of OBVAT using RSFC in CI participants compared to the placebo treatment to understand how OBVAT improves visual function and symptoms. METHODS: A total of 51 CI participants between 18 and 35 years of age were included in the study and randomly allocated to receive either 12 one-hour sessions of OBVAT or placebo treatment for 6 to 8 weeks (1 to 2 sessions per week). Resting-state functional magnetic resonance imaging and clinical assessments were evaluated at baseline and outcome for each treatment group. Region of interest (ROI) analysis was conducted in nine ROIs of the oculomotor vergence network, including the following: cerebellar vermis (CV), frontal eye fields (FEF), supplementary eye fields (SEF), parietal eye fields (PEF), and primary visual cortices (V1). Paired t-tests assessed RSFC changes in each group. A linear regression analysis was conducted for significant ROI pairs in the group-level analysis for correlations with clinical measures. RESULTS: Paired t-test results showed increased RSFC in 10 ROI pairs after the OBVAT but not placebo treatment (p < 0.05, false discovery rate corrected). These ROI pairs included the following: Left (L)-SEF-Right (R)-V1, L-SEF-CV, R-SEF-R-PEF, R-SEF-L-V1, R-SEF-R-V1, R-SEF-CV, R-PEF-CV, L-V1-CV, R-V1-CV, and L-V1-R-V1. Significant correlations were observed between the RSFC strength of the R-SEF-R-PEF ROI pair and the following clinical visual function parameters: positive fusional vergence and near point of convergence (p < 0.05). CONCLUSION: OBVAT, but not placebo treatment, increased the RSFC in the ROIs of the oculomotor vergence network, which was correlated with the improvements in the clinical measures of the CI participants.

Mechanism-centric regulatory network identifies NME2 and MYC programs as markers of Enzalutamide resistance in CRPC.

Heterogeneous response to Enzalutamide, a second-generation androgen receptor signaling inhibitor, is a central problem in castration-resistant prostate cancer (CRPC) management. Genome-wide systems investigation of mechanisms that govern Enzalutamide resistance promise to elucidate markers of heterogeneous treatment response and salvage therapies for CRPC patients. Focusing on the de novo role of MYC as a marker of Enzalutamide resistance, here we reconstruct a CRPC-specific mechanism-centric regulatory network, connecting molecular pathways with their upstream transcriptional regulatory programs. Mining this network with signatures of Enzalutamide response identifies NME2 as an upstream regulatory partner of MYC in CRPC and demonstrates that NME2-MYC increased activities can predict patients at risk of resistance to Enzalutamide, independent of co-variates. Furthermore, our experimental investigations demonstrate that targeting MYC and its partner NME2 is beneficial in Enzalutamide-resistant conditions and could provide an effective strategy for patients at risk of Enzalutamide resistance and/or for patients who failed Enzalutamide treatment.

Toward discovery science of human brain function.

Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (<0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual's "functional connectome." Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain-behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org/projects/fcon_1000/.

Machine learning models using non-linear techniques improve the prediction of resting energy expenditure in individuals receiving hemodialysis.

PURPOSE: Approximately 700,000 people in the USA have chronic kidney disease requiring dialysis. Protein-energy wasting (PEW), a condition of advanced catabolism, contributes to three-year survival rates of 50%. PEW occurs at all levels of Body Mass Index (BMI) but is devastating for those people at the extremes. Treatment for PEW depends on an accurate understanding of energy expenditure. Previous research established that current methods of identifying PEW and assessing adequate treatments are imprecise. This includes disease-specific equations for estimated resting energy expenditure (eREE). In this study, we applied machine learning (ML) modelling techniques to a clinical database of dialysis patients. We assessed the precision of the ML algorithms relative to the best-performing traditional equation, the MHDE. METHODS: This was a secondary analysis of the Rutgers Nutrition and Kidney Database. To build the ML models we divided the population into test and validation sets. Eleven ML models were run and optimized, with the best three selected by the lowest root mean squared error (RMSE) from measured REE. Values for eREE were generated for each ML model and for the MHDE. We compared precision using Bland-Altman plots. RESULTS: Individuals were 41.4% female and 82.0% African American. The mean age was 56.4 ± 11.1 years, and the median BMI was 28.8 (IQR = 24.8 - 34.0) kg/m2. The best ML models were SVR, Linear Regression and Elastic net with RMSE of 103.6 kcal, 119.0 kcal and 121.1 kcal respectively. The SVR demonstrated the greatest precision, with 91.2% of values falling within acceptable limits. This compared to 47.1% for the MHDE. The models using non-linear techniques were precise across extremes of BMI. CONCLUSION: ML improves precision in calculating eREE for dialysis patients, including those most vulnerable for PEW. Further development for clinical use is a priority.

Potentially impacting millions of patients worldwide, our continuing goal is to understand energy expenditure (EE) across the spectrum of CKD (stages 1­5) in adults and children being treated with dialysis or transplantation, with the intent of providing tools for the health professional that will improve the delivery of quality care.In past research, we have identified and focused on disease-specific variables which account for 60% of the variance in predicting EE in individuals receiving dialysis, but many questions remain unanswered.Our hypotheses are that (1) there are determinants of EE specific to CKD and, (2) predicting EE for individuals may be greatly advanced using sophisticated models that combine these determinants. In this study, we applied machine learning (ML) with linear and non-linear techniques to our existing dataset. The best models demonstrated improved precision in predicting EE for all individuals in the validation group.

Altered Large-Scale Resting-State Functional Network Connectivity in Convergence Insufficiency Young Adults Compared With Binocularly Normal Controls.

Purpose: To investigate the underlying resting-state functional connectivity (RSFC) of symptomatic convergence insufficiency (CI) compared with binocularly normal controls (BNC) using functional magnetic resonance imaging (fMRI) under The Convergence Insufficiency Neuro­mechanism Adult Population Study (NCT03593031). Methods: A total of 101 participants were eligible for this study. After removing datasets with motion artifacts, 49 CI and 47 BNC resting-state functional magnetic resonance imaging datasets were analyzed. CI was diagnosed with the following signs: (1) receded near point of convergence of 6 cm or greater, (2) decreased positive fusional vergence of less than 15∆ or failing Sheard's criteria of twice the near phoria, (3) near phoria of at least 4∆ more exophoric compared with the distance phoria, and (4) symptoms using the Convergence Insufficiency Symptom Survey (score of ≥21). RSFC was assessed using a group-level independent components analysis and dual regression. A behavioral correlation analysis using linear regression method was performed between clinical measures and RSFC using the significant difference between the CI and BNC. Results: On average, a decreased RSFC was observed within the frontoparietal network, default mode network and visual network in patients with CI, compared with the participants with BNC (P < 0.05, corrected for multiple comparisons). The default mode network RSFC strength was significantly correlated with the PFV, near point of convergence, and difference between the horizontal phoria at near compared with far (P < 0.05). Conclusions: Results support altered RSFC in patients with CI compared with participants with BNC and suggest that these differences in underlying neurophysiology may in part be in connection with the differences in optometric visual function used to diagnose CI.

Neuroimaging and Neurocognitive Outcomes in Older Patients with Multiple Myeloma Treated with Chemotherapy and Autologous Stem Cell Transplantation.

There is a paucity of research on treatment-related neurotoxicity in older adults with multiple myeloma (MM) treated with high-dose chemotherapy (HDC) and autologous SCT (HDC/ASCT), despite the increasing use of this regimen. We examined resting state functional connectivity (RSFC), gray matter (GM) volume, neurocognitive function (NF), and proinflammatory cytokines (PCy) in older patients with MM pre- and post-HDC/ASCT. Eighteen patients underwent MRI, NF tests, and serum PCy measurements prior to HDC/ASCT, and fifteen patients completed a follow up five-months post-HDC/ASCT. There were significant decreases in RSFC post-HDC/ASCT in (1) the central executive network (CEN) involving the left dorsolateral prefrontal cortex and right posterior parietal cortex (p = 0.022) and (2) the CEN involving the right posterior parietal cortex and the salience network involving the right dorsal anterior cingulate cortex (p = 0.029). There were no significant changes in GM or NF, except for improvements in attention (Digit Span Backward, p = 0.03). There were significant increases in several PCy post-HDC/ASCT (p ≤ 0.05). In conclusion, RSFC decreased in frontal, parietal, and cingulate cortices post-HDC/ASCT, NF was relatively stable, and several PCy increased. These findings are congruent with other studies in cancer patients and provide supporting evidence for the vulnerability of frontoparietal regions to chemotherapy's adverse effects.

Neuroimaging and Neurocognitive Outcomes in Older Patients with Multiple Myeloma Treated with Chemotherapy and Autologous Stem Cell Transplantation.

Background Many patients with hematological malignancies treated with stem cell transplantation (SCT) experience cognitive dysfunction. However, few studies have investigated treatment-related neurotoxicity in older adults with multiple myeloma (MM) treated with high dose chemotherapy (HDC) and autologous SCT (HDC/ASCT). In this study, we examined gray matter (GM) volume, resting state functional connectivity (RSFC), neurocognitive function (NF), and proinflammatory cytokines (PCy) in older patients with MM pre- and post-HDC/ASCT. Methods Eighteen MM patients underwent magnetic resonance imaging, neurocognitive tests, and serum PCy measurement prior to HDC/ASCT, and fifteen patients completed follow ups an average of five months post-HDC/ASCT. Results There were significant decreases in RSFC from pre- to post-HDC/ASCT in (1) the central executive network (CEN) involving the left dorsolateral prefrontal cortex and right posterior parietal cortex (p = 0.022), and (2) the CEN involving the right posterior parietal cortex and the salience network involving the right dorsal anterior cingulate cortex (p = 0.029); these comparisons were no longer significant after multiple comparisons correction. There were no significant changes in GM volumes or NF, except for improvement in attention (Digit Span Backward, p = 0.03). There were significant increases in several PCy post-HDC/ASCT (p ≤ 0.05). Conclusions This pilot study showed decreased RSFC involving the left frontal, right posterior parietal and right anterior cingulate cortices in MM patients post-HDC/ASCT, relatively stable NF, and increases in PCy. These findings are congruent with studies in patients with hematological malignancies and other cancers and provide supporting evidence for the vulnerability of frontoparietal regions to chemotherapy adverse effects.

Functional connectivity in the central executive network predicts changes in binge drinking behavior during emerging adulthood: an observational prospective study.

BACKGROUND AND AIMS: Binge drinking contributes to the immense public health burden associated with alcohol use, especially among younger drinkers. Little is known about the underlying neurobiology of changes in this behavior over time. This preliminary study aimed to identify neurobiological markers of binge drinking behavior change during emerging adulthood. DESIGN: Observational prospective investigation of neurobiological predictors of binge drinking behavior. SETTING: Communities surrounding a large, public university in the northeastern United States. PARTICIPANTS: A total of 42 emerging adults (48% female), approximately half meeting criteria for an alcohol use disorder. MEASUREMENTS: Past month binge drinking, the dependent variable, was assessed at two time-points (T1, T2) via self-report. Ten indices of resting-state functional connectivity within the central executive network (CEN), a brain network involved in executive function, were collected at T1 and specified as independent variables in cross-sectional and prospective Poisson models. All models controlled for age, sex, and alcohol use disorder status. FINDINGS: The cross-sectional model yielded five significant associations between CEN connectivity and binge drinking incidence. Connections anchored primarily in the anterior CEN exhibited negative associations with binge drinking incidence (P = 0.001, 0.004, 0.011), and connections stemming from the right posterior parietal cortex exhibited positive associations with binge drinking incidence (P = 0.041, 0.045). In prospective models, stronger frontoparietal connectivity between the right dorsolateral prefrontal cortex and left posterior parietal cortex predicted greater increases in binge drinking incidence over time (P = 0.003). CONCLUSIONS: There is an association between central executive network connectivity and heavy drinking, as well as evidence that functional pathways within the central executive network may contribute to changes in problematic drinking behaviors.

Altered regional homogeneity in patients with ovarian cancer treated with chemotherapy: a resting state fMRI study.

Many patients treated with chemotherapy for non-central nervous system (CNS) cancers experience cognitive dysfunction. However, few studies have investigated treatment-related neurotoxicity in women with ovarian cancer. The goal of this study was to assess regional brain function in patients with ovarian cancer after first-line chemotherapy. Seventeen patients with ovarian cancer and seventeen healthy controls matched for gender, age and education participated in the study. The patients were evaluated 1-4 months after completion of first line taxane/platinum chemotherapy. All participants underwent resting state functional MRI (rsfMRI) and regional homogeneity (ReHo) indices were calculated. The results showed that patients had significantly decreased average ReHo values in the left middle frontal gyrus, medial prefrontal cortex, and right superior parietal lobule, compared to healthy controls. This is the first rsfMRI study showing ReHo alterations in frontal and parietal regions in patients with ovarian cancer treated with first-line chemotherapy. The findings are overall congruent with prior studies in non-CNS cancer populations and provide supporting evidence for the prevailing notion that frontal areas are particularly vulnerable to the adverse effects of chemotherapy.

Frontotemporal thalamic connectivity in schizophrenia and schizotypal personality disorder.

Schizotypal personality disorder (SPD) resembles schizophrenia, but with attenuated brain abnormalities and the absence of psychosis. The thalamus is integral for processing and transmitting information across cortical regions and widely implicated in the neurobiology of schizophrenia. Comparing thalamic connectivity in SPD and schizophrenia could reveal an intermediate schizophrenia-spectrum phenotype to elucidate neurobiological risk and protective factors in psychosis. We used rsfMRI to investigate functional connectivity between the mediodorsal nucleus (MDN) and pulvinar, and their connectivity with frontal and temporal cortical regions, respectively in 43 healthy controls (HCs), and individuals in the schizophrenia-spectrum including 45 psychotropic drug-free individuals with SPD, and 20 individuals with schizophrenia-related disorders [(schizophrenia (n = 10), schizoaffective disorder (n = 8), schizophreniform disorder (n = 1) and psychosis NOS (n = 1)]. Individuals with SPD had greater functional connectivity between the MDN and pulvinar compared to individuals with schizophrenia. Thalamo-frontal (i.e., between the MDN and rostral middle frontal cortex) connectivity was comparable in SPD and HCs; in SPD greater connectivity was associated with less symptom severity. Individuals with schizophrenia had less thalamo-frontal connectivity and thalamo-temporal (i.e., pulvinar to the transverse temporal cortex) connectivity compared with HCs. Thalamo-frontal functional connectivity may be comparable in SPD and HCs, but abnormal in schizophrenia, and that this may be protective against psychosis in SPD.

Convergence Insufficiency Neuro-Mechanism Adult Population Study: Phoria Adaptation Results.

Purpose: The purpose of this study was to compare changes in phoria adaptation between young adult binocularly normal controls (BNCs) and participants with symptomatic convergence insufficiency (CI), who were randomized to either office-based vergence accommodative therapy (OBVAT) or office-based placebo therapy (OBPT). Methods: In the double-masked randomized clinical trial, 50 BNC and 50 CI participants were randomized to the following therapeutic interventions: OBVAT or OBPT with home reinforcement for 12 one-hour office sessions. A 6∆ base-out and 6∆ base-in phoria adaptation experiment at near (40 cm) was conducted using the flashed Maddox rod technique at baseline and at outcome. Measurements included the rate and the magnitude of phoria adaptation. Results: At baseline, BNC and CI participants had significantly different rates and magnitudes of base-in and base-out phoria adaptation (P < 0.001). When comparing the outcome to baseline measurements, significant main effect differences in longitudinal measurements were observed for the magnitude and the rate of phoria adaptation for both base-out and base-in experiments (P < 0.05). For the magnitude and rate of phoria adaptation, post hoc analyses using paired t-tests revealed that the CI group administered the OBVAT intervention exhibited a significant increase in the magnitude and rate of phoria adaptation compared to baseline for both base-in and base-out phoria adaptation (P < 0.01) but not for those administered OBPT. Conclusions: Phoria adaptation is significantly different at baseline between those with normal binocular vision and symptomatic CI participants. OBVAT significantly improves the rate and magnitude of both base-out and base-in phoria adaptation at near compared to OBPT. Results have clinical implications for new therapeutic interventions.

Underlying neurological mechanisms associated with symptomatic convergence insufficiency.

Convergence insufficiency (CI) is the most common binocular vision problem, associated with blurred/double vision, headaches, and sore eyes that are exacerbated when doing prolonged near work, such as reading. The Convergence Insufficiency Neuro-mechanism Adult Population Study (NCT03593031) investigates the mechanistic neural differences between 50 binocularly normal controls (BNC) and 50 symptomatic CI participants by examining the fast and slow fusional disparity vergence systems. The fast fusional system is preprogrammed and is assessed with convergence peak velocity. The slow fusional system optimizes vergence effort and is assessed by measuring the phoria adaptation magnitude and rate. For the fast fusional system, significant differences are observed between the BNC and CI groups for convergence peak velocity, final position amplitude, and functional imaging activity within the secondary visual cortex, right cuneus, and oculomotor vermis. For the slow fusional system, the phoria adaptation magnitude and rate, and the medial cuneus functional activity, are significantly different between the groups. Significant correlations are observed between vergence peak velocity and right cuneus functional activity (p = 0.002) and the rate of phoria adaptation and medial cuneus functional activity (p = 0.02). These results map the brain-behavior of vergence. Future therapeutic interventions may consider implementing procedures that increase cuneus activity for this debilitating disorder.

Vision therapy in adults with convergence insufficiency: clinical and functional magnetic resonance imaging measures.

PURPOSE: This research quantified clinical measurements and functional neural changes associated with vision therapy in subjects with convergence insufficiency (CI). METHODS: Convergence and divergence 4° step responses were compared between 13 control adult subjects with normal binocular vision and four CI adult subjects. All CI subjects participated in 18 h of vision therapy. Clinical parameters quantified throughout the therapy included: nearpoint of convergence, recovery point of convergence, positive fusional vergence at near, near dissociated phoria, and eye movements that were quantified using peak velocity. Neural correlates of the CI subjects were quantified with functional magnetic resonance imaging scans comparing random vs. predictable vergence movements using a block design before and after vision therapy. Images were quantified by measuring the spatial extent of activation and the average correlation within five regions of interests (ROI). The ROIs were the dorsolateral prefrontal cortex, a portion of the frontal lobe, part of the parietal lobe, the cerebellum, and the brain stem. All measurements were repeated 4 months to 1 year post-therapy in three of the CI subjects. RESULTS: Convergence average peak velocities to step stimuli were significantly slower (p = 0.016) in CI subjects compared with controls; however, significant differences in average peak velocities were not observed for divergence step responses (p = 0.30). The investigation of CI subjects participating in vision therapy showed that the nearpoint of convergence, recovery point of convergence, and near dissociated phoria significantly decreased. Furthermore, the positive fusional vergence, average peak velocity from 4° convergence steps, and the amount of functional activity within the frontal areas, cerebellum, and brain stem significantly increased. Several clinical and cortical parameters were significantly correlated. CONCLUSIONS: Convergence peak velocity was significantly slower in CI subjects compared with controls, which may result in asthenopic complaints reported by the CI subjects. Vision therapy was associated with and may have evoked clinical and cortical activity changes.

Current methods and new directions in resting state fMRI.

Resting state functional connectivity magnetic resonance imaging (rsfcMRI) has become a key component of investigations of neurocognitive and psychiatric behaviors. Over the past two decades, several methods and paradigms have been adopted to utilize and interpret data from resting-state fluctuations in the brain. These findings have increased our understanding of changes in many disease states. As the amount of resting state data available for research increases with big datasets and data-sharing projects, it is important to review the established traditional analysis methods and recognize areas where research methodology can be adapted to better accommodate the scale and complexity of rsfcMRI analysis. In this paper, we review established methods of analysis as well as areas that have been receiving increasing attention such as dynamic rsfcMRI, independent vector analysis, multiband rsfcMRI and network of networks.

Test-Retest Reliability of Functional Magnetic Resonance Imaging Activation for a Vergence Eye Movement Task.

Vergence eye movements are the inward and outward rotation of the eyes responsible for binocular coordination. While studies have mapped and investigated the neural substrates of vergence, it is not well understood whether vergence eye movements evoke the blood oxygen level-dependent signal reliably in separate experimental visits. The test-retest reliability of stimulus-induced vergence eye movement tasks during a functional magnetic resonance imaging (fMRI) experiment is important for future randomized clinical trials (RCTs). In this study, we established region of interest (ROI) masks for the vergence neural circuit. Twenty-seven binocularly normal young adults participated in two functional imaging sessions measured on different days on the same 3T Siemens scanner. The fMRI experiments used a block design of sustained visual fixation and rest blocks interleaved between task blocks that stimulated eight or four vergence eye movements. The test-retest reliability of task-activation was assessed using the intraclass correlation coefficient (ICC), and that of spatial extent was assessed using the Dice coefficient. Functional activation during the vergence eye movement task of eight movements compared to rest was repeatable within the primary visual cortex (ICC = 0.8), parietal eye fields (ICC = 0.6), supplementary eye field (ICC = 0.5), frontal eye fields (ICC = 0.5), and oculomotor vermis (ICC = 0.6). The results demonstrate significant test-retest reliability in the ROIs of the vergence neural substrates for functional activation magnitude and spatial extent using the stimulus protocol of a task block stimulating eight vergence eye movements compared to sustained fixation. These ROIs can be used in future longitudinal RCTs to study patient populations with vergence dysfunctions.

The Convergence Insufficiency Neuro-mechanism in Adult Population Study (CINAPS) Randomized Clinical Trial: Design, Methods, and Clinical Data.

Purpose: To describe the design and methodology of the Convergence Insufficiency Neuro-mechanism in Adult Population Study (CINAPS), the first randomized clinical trial (RCT) studying young adults with symptomatic convergence insufficiency (CI) using a combination of traditional clinical tests, objective eye movement recordings, and functional brain activities as outcome measures.Methods: In this double-masked RCT, binocularly normal controls (BNC) (N = 50) and CI patients (N = 50) are randomized into office-based vergence/accommodative therapy (OBVAT) or office-based placebo therapy (OBPT). Outcome measures included clinical signs and symptoms, phoria adaptation, forced fixation disparity curves, binocular rivalry, vergence and saccadic objective eye movements, and task-induced functional brain activities. This study is registered on ClinicalTrials.gov NCT03593031.Results: No significant baseline differences are observed between the BNC (p > .4) or CI (p > .3) participants assigned to OBVAT or OBPT for age, near point of convergence (NPC), positive fusional vergence (PFV), phoria at distance and near, amplitude of accommodation, or the Convergence Insufficiency Symptom Survey (CISS). Significant differences are observed between the CI and BNC cohorts at baseline measurements for NPC, PFV, difference in phoria from far to near, amplitude of accommodation, and CISS (p < .001). For the CI patients, 26% had a comorbidity of accommodation insufficiency, and 16% self-reported ADHD.Conclusion: Features of the study design include the following: standardized diagnostic and office-based therapeutic intervention, placebo treatment arm, masked clinical outcome examinations, objective eye movement recordings, functional imaging, phoria adaptation, fixation disparity curves and binocular rivalry measurements.