Petabytes of imaging, clinical, biospecimen, genetics and phenotypic biomedical data are acquired annually. Tens-of-thousands of new methods and computational algorithms are developed and reported in the literature and thousands of software tools and data analytic services are introduced each year.Albert bandura social cognitive learning theory this imaging statistics and predictive data analytics session will include presentations of leading experts in biomedical imaging, computational neuroscience, and statistical learning focused on streamlining big biomedical data methodologies as well as techniques for management, aggregation, manipulation, computational modeling, and statistical inference.Albert bandura social cognitive learning theory the session will blend innovative model-based and model-free techniques for representation, analysis and interpretation of large, heterogeneous, multi-source, incomplete and incongruent imaging and phenotypic data elements.Albert bandura social cognitive learning theory

• the digital revolution demands substantial quantitative skills, data-literacy, and analytical competence: health science doctoral programs need to be revised and expanded to build basic-science (STEM) expertise, emphasize team-science, rely on holistic understanding of biomedical systems and health problems, and amplify dexterous abilities to handle, interrogate and interpret complex multisource information.Albert bandura social cognitive learning theory

This talk will present some of the big neuroscience data research and education challenges and opportunities. Specifically, we will identify the core characteristics of complex neuroscience data, discuss strategies for data harmonization and aggregation, and show case-studies using large normal and pathological cohorts.Albert bandura social cognitive learning theory examples of methods that will be demonstrated include datasifter (enabling secure sharing of data), compressive big data analytics (facilitating inference on multi-source heterogeneous datasets), and model-free prediction (forecasting of clinical features or derived computed phenotypes).Albert bandura social cognitive learning theory simulated data as well as clinical data (UK biobank, alzheimer’s disease neuroimaging initiative, and amyotrophic lateral sclerosis case-studies) will be used for testing and validation of the techniques.Albert bandura social cognitive learning theory in support of open-science, result reproducibility, and methodological improvements, all datasets, statistical methods, computational algorithms, and software tools are freely available online.Albert bandura social cognitive learning theory

The challenge of making comparison of brain networks and multimodal brain imaging data between healthy and diseased cohorts lies in the high dimensionality of brain imaging data.Albert bandura social cognitive learning theory to make statistically significant claims while avoiding false positives and false negatives, prohibitively large sample sizes are needed. This is the main disadvantage of the current framework for hypothesis testing.Albert bandura social cognitive learning theory t-tests, mann-whitney and similar hypothesis testing methods using point statistics make model based assumptions of data that cluster around a mean value.Albert bandura social cognitive learning theory significance is ascertained after ascribing sufficiently improbable difference in means or variance between cohorts. Even when statistically significant differences can be ascribed, there is a lack of usable hypothesis that can grant insight into the nature of these differences.Albert bandura social cognitive learning theory we propose a novel approach to comparing high dimensional brain imaging datasets such as brain networks. We suggest that deep learning algorithms could be applied to create generative models of the underlying dataset which is a type of hypothesis on the data from each cohort.Albert bandura social cognitive learning theory using different deep learning architectures, training algorithms, or different instances of trained networks, we can generate multiple hypothesis / generative models of the underlying datasets.Albert bandura social cognitive learning theory A family of hypothesis / generative models of a given cohort dataset specifies a bound on possible hypothesis for the data. Collecting more brain datasets essentially prunes the hypothesis space and shrinks the boundaries of plausible models.Albert bandura social cognitive learning theory we further propose that the family of generative models from different cohorts can be compared via measures of statistical dissimilarity using statistical distance metrics such as the fisher information metric.Albert bandura social cognitive learning theory generative models as hypothesis on datasets permit further interaction which allows researchers to learn the meaning of each hypothesis, thus adding value and insight to analysis.Albert bandura social cognitive learning theory

Big data provide a playground for researchers to address extremely interesting and novel questions important to deriving a better understanding of both optimal and suboptimal brain health.Albert bandura social cognitive learning theory however, the breadth of available information is also associated with considerable risks when not handled properly. Additionally, despite all of the data that is at our fingertips, sometimes covariate data are missing.Albert bandura social cognitive learning theory this talk will discuss approaches to dealing with large numbers of variables involved in big data, and will address different strategies for inference testing (correction for multiple testing) in genetic, epigenetic, and neuroimaging data.Albert bandura social cognitive learning theory further, the talk will cover the different instances of missing covariate data and will describe approaches to deal with these missing data.Albert bandura social cognitive learning theory audience interaction will take place with short quizzes throughout the talk.

In the neuroimaging literature, the default mode network (DMN) refers to a group of areas in the human cerebral cortex that consistently shows decreased activity in attention-demanding tasks and increased activity under resting-state with eyes-closed or with simple visual fixation.Albert bandura social cognitive learning theory the discovery of DMN has boosted research interest in self-referential or intrinsic activity in the brain in both patients and healthy controls.Albert bandura social cognitive learning theory since 1997, related studies have mainly relied on the group-averaged responses or seed-based correlations to identify increased/decreased activity in the DMN areas.Albert bandura social cognitive learning theory in this study, we conducted a resting-state experiment by considering the eyes-closed and eyes-open conditions, and by particularly analyzing the reproducible activity across subjects in the DMN areas (areas 8, 9, 10, 20, 23, 24, 25, 31, 32, 39, 40 and the entorhinal cortex).Albert bandura social cognitive learning theory the reproducible activity was estimated using the standardized intraclass-correlations (iccs); the statistical thresholding of the ICC maps was done by considering the non-stationarity of on-going BOLD signals during the resting-state conditions.Albert bandura social cognitive learning theory the DMN areas were parcellated according the jubrain cytoarchitectonic atlas. Forty-nine right-handed adults (26 females, averaged age: 23.08±3.188 years) participated the resting-state task involving 4 min eyes-closed followed by 4 min eyes-open.Albert bandura social cognitive learning theory the MRI scan was performed using a 3T MAGNETOM skyra scanner and a standard 20-channel head-neck coil. The echo planar imaging (EPI) scans were acquired with parameters TR/TE = 2000 ms/30 ms, flip angle = 84°, 35 slices, slice thickness = 3.4 mm, FOV = 192 mm, and resolution 3x3x3.74 mm to cover the whole brain including the cerebellum.Albert bandura social cognitive learning theory the results suggested that a variety of brain activity could be found in the DMN areas including short-term increased/decreased activity after the eyes-closed/open instructions.Albert bandura social cognitive learning theory we suggest being cautious in using the DMN in cognitive and clinical studies.

Ivo D. Dinov is a professor of health behavior and biological sciences and computational medicine and bioinformatics at the university of michigan.Albert bandura social cognitive learning theory he directs the statistics online computational resource and co-directs the center for complexity and self-management of chronic disease (CSCD) and the multi-institutional probability distributome project.Albert bandura social cognitive learning theory dr. Dinov is an associate director of the michigan institute for data science (MIDAS). He is a member of the american statistical association (ASA), the international association for statistical education (IASE), the american medical informatics association (AMIA), as well as an elected member of the international statistical institute (ISI).Albert bandura social cognitive learning theory

Eric ho tatt wei is a senior lecturer at universiti teknologi petronas, as well as a malaysia node coordinator of the international neuroinformatics coordinating facility (INCF).Albert bandura social cognitive learning theory he received his msc and phd degrees in electrical engineering from stanford university, USA. During his phd, he developed an automated robotic system to manipulate fruit flies for live brain imaging.Albert bandura social cognitive learning theory back in malaysia, he worked on the development of microfluidic devices for monitoring and manipulating blood cells for immunotherapy in low resource settings.Albert bandura social cognitive learning theory his current research interests are in developing novel tools at the intersection of deep learning, brain sciences and networks and he is applying these techniques to characterize the effect of addiction and aging on the brain as well as to enhance the efficacy of brain interventions to improve cognition

albert bandura social cognitive learning theory

Dr. Qiu is dean’s chair associate professor at department of biomedical engineering and clinical imaging research centre at national university of singapore.Albert bandura social cognitive learning theory she is also a principal investigator at singapore institute for clinical sciences of agency for science technology and research (A*STAR). Dr.Albert bandura social cognitive learning theory qiu received her BS in biomedical engineering from tsinghua university in 1999, MS degrees in biomedical engineering and applied mathematics and statistics from university of connecticut in 2002 and from the johns hopkins university in 2005, respectively.Albert bandura social cognitive learning theory she obtained her phd degree at the johns hopkins university in 2006. After one-year postgraduate training, she joined the national university of singapore as assistant professor and launched her own laboratory for medical image data sciences at both the faculty of engineering and the school of medicine.Albert bandura social cognitive learning theory dr. Qiu has been devoted to innovation in computational analyses of complex and informative datasets comprising of disease phenotypes, neuroimage, and genetic data to understand the origins of individual differences in health throughout the lifespan.Albert bandura social cognitive learning theory she received faculty young research award, 2016 young researcher award of NUS. She has recently been appointed as endowed “dean’s chair” associate professor to honor her outstanding research achievements.Albert bandura social cognitive learning theory she serves on the program committee of organization of human brain mapping and editor of the journals neuroimage and frontiers in neuroscience.Albert bandura social cognitive learning theory

Prof. Ahmed is dean of the brock university school of mathematics and statistics. Prior to that, he was head of mathematics at the university of windsor and university of regina.Albert bandura social cognitive learning theory he is a fellow of american statistical association and an elected member of the international statistical institute. Dr. Ahmed is an expert in statistical inference, shrinkage estimation, and asymptotic theory.Albert bandura social cognitive learning theory he serves on the editorial boards of many statistical journals and served as a board of director and chairman of the education committee of the statistical society of canada.Albert bandura social cognitive learning theory dr. Ahmed is a member of an evaluation group, discovery grants and the grant selection committee, natural sciences and engineering research council of canada (NSERC).Albert bandura social cognitive learning theory