Faculty Bibliography

PURPOSE/OBJECTIVE:To estimate the effect size of a serious game for cardiopulmonary resuscitation (CPR) training in comparison with a video-based on-line course in terms of learning outcomes among medical students before simulation-based CPR using a manikin. METHODS:Participants were 45 first-year medical students randomly assigned to CPR self-training using either a video-based Apple Keynote presentation (n = 22) or a serious game developed in a 3D learning environment (n = 23) for up to 20 min. Each participant was evaluated on a written, multiple-choice test (theoretical test) and then on a scenario of cardiac arrest (practical test) before and after exposure to the self-learning methods. The primary endpoint was change in theoretical and practical baseline scores during simulated CPR. This study was conducted in 2017. RESULTS:Both groups improved scores after exposure. The video group had superior performance in both the theoretical test (7.56±0.21 vs 6.51±0.21 for the game group; p = 0.001) and the practical test (9.67±0.21 vs 8.40±0.21 for the game group; p < 0.001). However, students showed a preference for using games, as suggested by the longer time they remained interested in the method (18.57±0.66 min for the game group vs 7.41±0.43 for the video group; p < 0.001). CONCLUSIONS:The self-training modality using a serious game, after a short period of exposure, resulted in inferior students' performance in both theoretical and practical CPR tests compared to the video-based self-training modality. However, students showed a clear preference for using games rather than videos as a form of self-training.

BACKGROUND:There has been a growing amount of evidence indicating that excess visceral fat is associated with alterations in brain structure and function, including brain cortical thinning in adults. OBJECTIVES:This study aims to investigate the relationship between brain cortical thickness with obesity assessments, in adolescents. METHODS:In this study, we measured three different obesity assessments within an adolescent population (aged 15 - 18 years): body mass index (BMI), visceral fat ratio measured with an MRI and hepatorenal gradient measured with an ultrasound. Volunteers also underwent an MRI scan to measure brain structure. RESULTS:Results indicated that there was no relationship of BMI or hepatorenal gradient with brain cortical dimensions. However, there was a significant association between visceral fat ratio and an increase of cortical thickness throughout the brain. CONCLUSIONS:These results suggest that visceral fat, but not BMI, is correlated with cortical thickening in adolescence.

With resting-state functional MRI (rs-fMRI) there are a variety of post-processing methods that can be used to quantify the human brain connectome. However, there is also a choice of which preprocessing steps will be used prior to calculating the functional connectivity of the brain. In this manuscript, we have tested seven different preprocessing schemes and assessed the reliability between and reproducibility within the various strategies by means of graph theoretical measures. Different preprocessing schemes were tested on a publicly available dataset, which includes rs-fMRI data of healthy controls. The brain was parcellated into 190 nodes and four graph theoretical (GT) measures were calculated; global efficiency (GEFF), characteristic path length (CPL), average clustering coefficient (ACC), and average local efficiency (ALE). Our findings indicate that results can significantly differ based on which preprocessing steps are selected. We also found dependence between motion and GT measurements in most preprocessing strategies. We conclude that by using censoring based on outliers within the functional time-series as a processing, results indicate an increase in reliability of GT measurements with a reduction of the dependency of head motion.

Diffusion tensor imaging (DTI) has been used to evaluate white matter (WM) integrity in major depressive disorder (MDD), with several studies reporting differences between depressed patients and controls. However, these findings are variable and taken from relatively small studies often using suboptimal analytic approaches. The presented DTI study examined WM integrity in large samples of medication-free MDD patients (n=134) and healthy controls (n=54) using voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) approaches, and rigorous statistical thresholds. Compared with health control subjects, MDD patients show no significant differences in fractional anisotropy, radial diffusivity, mean diffusivity, and axonal diffusivity with either the VBM or the TBSS approach. Our findings suggest that disrupted WM integrity does not have a major role in the neurobiology of MDD in this relatively large study using optimal imaging acquisition and analysis; however, this does not eliminate the possibility that certain patient subgroups show WM disruption associated with depression.

Alzheimer's disease (AD) is characterized by mental and cognitive problems, particularly with memory, language, visuospatial skills (VS), and executive functions (EF). Advances in the neuroimaging of AD have highlighted dysfunctions in functional connectivity networks (FCNs), especially in the memory related default mode network (DMN). However, little is known about the integrity and clinical significance of FNCs that process other cognitive functions than memory. We evaluated 22 patients with mild AD and 26 healthy controls through a resting state functional MRI scan. We aimed to identify different FCNs: the DMN, language, EF, and VS. Seed-based functional connectivity was calculated by placing a seed in the DMN (posterior cingulate cortex), language (Broca's and Wernicke's areas), EF (right and left dorsolateral prefrontal cortex), and VS networks (right and left associative visual cortex). We also performed regression analyses between individual connectivity maps for the different FCNs and the scores on cognitive tests. We found areas with significant decreases in functional connectivity in patients with mild AD in the DMN and Wernicke's area compared with controls. Increased connectivity in patients was observed in the EF network. Regarding multiple linear regression analyses, a significant correlation was only observed between the connectivity of the DMN and episodic memory (delayed recall) scores. In conclusion, functional connectivity alterations in mild AD are not restricted to the DMN. Other FCNs related to language and EF may be altered. However, we only found significant correlations between cognition and functional connectivity in the DMN and episodic memory performance.

IMPORTANCE/OBJECTIVE:Currently, fewer than 40% of patients treated for major depressive disorder achieve remission with initial treatment. Identification of a biological marker that might improve these odds could have significant health and economic impact. OBJECTIVE:To identify a candidate neuroimaging "treatment-specific biomarker" that predicts differential outcome to either medication or psychotherapy. DESIGN/METHODS:Brain glucose metabolism was measured with positron emission tomography prior to treatment randomization to either escitalopram oxalate or cognitive behavior therapy for 12 weeks. Patients who did not remit on completion of their phase 1 treatment were offered enrollment in phase 2 comprising an additional 12 weeks of treatment with combination escitalopram and cognitive behavior therapy. SETTING/METHODS:Mood and anxiety disorders research program at an academic medical center. PARTICIPANTS/METHODS:Men and women aged 18 to 60 years with currently untreated major depressive disorder. INTERVENTION/METHODS:Randomized assignment to 12 weeks of treatment with either escitalopram oxalate (10-20 mg/d) or 16 sessions of manual-based cognitive behavior therapy. MAIN OUTCOME AND MEASURE/METHODS:Remission, defined as a 17-item Hamilton depression rating scale score of 7 or less at both weeks 10 and 12, as assessed by raters blinded to treatment. RESULTS:Positive and negative predictors of remission were identified with a 2-way analysis of variance treatment (escitalopram or cognitive behavior therapy) × outcome (remission or nonresponse) interaction. Of 65 protocol completers, 38 patients with clear outcomes and usable positron emission tomography scans were included in the primary analysis: 12 remitters to cognitive behavior therapy, 11 remitters to escitalopram, 9 nonresponders to cognitive behavior therapy, and 6 nonresponders to escitalopram. Six limbic and cortical regions were identified, with the right anterior insula showing the most robust discriminant properties across groups (effect size = 1.43). Insula hypometabolism (relative to whole-brain mean) was associated with remission to cognitive behavior therapy and poor response to escitalopram, while insula hypermetabolism was associated with remission to escitalopram and poor response to cognitive behavior therapy. CONCLUSIONS AND RELEVANCE/CONCLUSIONS:If verified with prospective testing, the insula metabolism-based treatment-specific biomarker defined in this study provides the first objective marker, to our knowledge, to guide initial treatment selection for depression. TRIAL REGISTRATION/BACKGROUND:Registered at clinicaltrials.gov (NCT00367341).

Though previous examinations of intrinsic resting-state networks (RSNs) in healthy populations have consistently identified several RSNs that represent connectivity patterns evoked by cognitive and sensory tasks, the effects of different analytic approaches on the reliability and reproducibility of these RSNs have yet to be fully explored. Thus, the primary aim of the current study was to investigate the effect of method (independent component analyses [ICA] vs. seed-based analyses) on RSN reproducibility (independent datasets) for ICA and reliability (independent time points) in both methods using functional magnetic resonance imaging. Good to excellent reproducibility was observed in 9 out of 10 commonly identified RSNs, indicating the robustness of these intrinsic fluctuations at the group level. Reliability analyses showed that results were dependent on three main methodological factors: (1) group versus subject-level analyses (group>subject); (2) whether data from different visits were analyzed separately or jointly with ICA (combined>separate ICA); and (3) whether ICA output was used to directly assess reliability or to inform seed-based analyses (seed-based>ICA). These results suggest that variations in the analytic technique have a significant impact on individual reliability measurements, but do not significantly affect the reproducibility or reliability of RSNs at the group level. Further investigation into the effect of the analytic technique on RSN quantification is warranted to increase the utility of RSN analyses in clinical studies.

Despite intensive study, the role of the dorsal medial frontal cortex (dMFC) in error monitoring and conflict processing remains actively debated. The current experiment manipulated conflict type (stimulus conflict only or stimulus and response selection conflict) and utilized a novel modeling approach to isolate error and conflict variance during a multimodal numeric Stroop task. Specifically, hemodynamic response functions resulting from two statistical models that either included or isolated variance arising from relatively few error trials were directly contrasted. Twenty-four participants completed the task while undergoing event-related functional magnetic resonance imaging on a 1.5-Tesla scanner. Response times monotonically increased based on the presence of pure stimulus or stimulus and response selection conflict. Functional results indicated that dMFC activity was present during trials requiring response selection and inhibition of competing motor responses, but absent during trials involving pure stimulus conflict. A comparison of the different statistical models suggested that relatively few error trials contributed to a disproportionate amount of variance (i.e., activity) throughout the dMFC, but particularly within the rostral anterior cingulate gyrus (rACC). Finally, functional connectivity analyses indicated that an empirically derived seed in the dorsal ACC/pre-SMA exhibited strong connectivity (i.e., positive correlation) with prefrontal and inferior parietal cortex but was anti-correlated with the default-mode network. An empirically derived seed from the rACC exhibited the opposite pattern, suggesting that sub-regions of the dMFC exhibit different connectivity patterns with other large scale networks implicated in internal mentations such as daydreaming (default-mode) versus the execution of top-down attentional control (fronto-parietal).

BACKGROUND:A reliable and meaningful quantitative index of success is paramount in the trial of any new treatment. However, existing methods for defining response and remission for treatments tested for psychiatric disorders are limited in that they often minimize the variance in change over time among individual patients and generally use arbitrarily chosen levels of functioning at specified times during treatment. PURPOSE/OBJECTIVE:To suggest and determine the properties of an alternative measure of treatment success, the Illness Density Index (IDI), that may be more sensitive to fluctuations in symptoms over the course of treatment compared to existing measures. METHODS:We examined data from 64 depressed patients with multiple assessments of the Hamilton Depression Rating Scale (HDRS) over 12 weeks of randomized treatment in order to compare and contrast varying numerical definitions of response and remission, including percent change and linear slope over time. RESULTS:Examination of the indices comparing the within-sample rank of individual patients revealed that these indices agree in cases where patients have little or no response as well as clear and sustained response, while they differ in patients who have a slow (or late) response as well as relapse during the treatment course. LIMITATIONS/CONCLUSIONS:The measure may not be useful for all types of studies, especially short-term treatment trials. CONCLUSIONS:The IDI is highly correlated with both categorical (e.g., remission) and continuous (e.g., percent change) definitions of treatment success. Furthermore, it differentiates certain trajectories of change that current definitions do not. Thus, the proposed index may be a valuable addition to current measures of efficacy, especially when trying to identify biological substrates of illness or predictors of long-term outcome.

Changes in the default mode network (DMN) have been linked to multiple neurological disorders including schizophrenia. The anticorrelated relationship the DMN shares with task-related networks permits the quantification of this network both during task (task-induced deactivations: TID) and during periods of passive mental activity (extended rest). However, the effects of different methodologies (TID vs. extended rest) for quantifying the DMN in the same clinical population are currently not well understood. Moreover, several different analytic techniques, including independent component analyses (ICA) and seed-based correlation analyses, exist for examining functional connectivity during extended resting states. The current study compared both methodologies and analytic techniques in a group of patients with schizophrenia (SP) and matched healthy controls. Results indicated that TID analyses, ICA, and seed-based correlation all consistently identified the midline (anterior and posterior cingulate gyrus) and lateral parietal cortex as core regions of the DMN, as well as more variable involvement of temporal lobe structures. In addition, SP exhibited increased deactivation during task, as well as decreased functional connectivity with frontal regions and increased connectivity with posterior and subcortical areas during periods of extended rest. The increased posterior and reduced anterior connectivity may partially explain some of the cognitive dysfunction and clinical symptoms that are frequently associated with schizophrenia.