A5055994170- Functional Brain Connectivity Studies
- Mental Health Research Topics
- Advanced MRI Techniques and Applications
- Advanced Neuroimaging Techniques and Applications
- Complex Systems and Time Series Analysis
- Neural dynamics and brain function
- Time Series Analysis and Forecasting
- Market Dynamics and Volatility
- Complex Network Analysis Techniques
- Metabolomics and Mass Spectrometry Studies
- Financial Risk and Volatility Modeling
- Child and Adolescent Psychosocial and Emotional Development
- Monetary Policy and Economic Impact
- Neurobiology of Language and Bilingualism
- Resilience and Mental Health
- Anomaly Detection Techniques and Applications
- Posttraumatic Stress Disorder Research
- Artificial Immune Systems Applications
- Electric Power System Optimization
- Digital Mental Health Interventions
- Sport and Mega-Event Impacts
- Data Visualization and Analytics
- Sports Analytics and Performance
- Tensor decomposition and applications
- Reading and Literacy Development
University of Alberta
2016-2025
Women and Children’s Health Research Institute
2017-2025
Alberta Health
2016-2022
All Africa Leprosy Tuberculosis and Rehabilitation Training Centre
2020
Columbia University
2012
Abstract Functional magnetic resonance imaging (fMRI) time series data presents a unique opportunity to understand the behavior of temporal brain connectivity, and models that uncover complex dynamic workings this organ are keen interest in neuroscience. We motivated develop accurate change point detection network estimation techniques for high-dimensional whole-brain fMRI data. To end, we introduce factorized binary search (FaBiSearch), novel method structure multivariate order large-scale...
Recently in functional magnetic resonance imaging (fMRI) studies there has been an increased interest understanding the dynamic manner which brain regions communicate with one another, as subjects perform a set of experimental tasks or their psychological state changes. Dynamic Connectivity Regression (DCR) is data-driven technique used for detecting temporal change points connectivity between where number and location are unknown priori. After finding points, DCR estimates graph...
In order to examine the impact of disasters on adolescent mental health, this study compared population health survey data from two communities in Alberta, Canada: Fort McMurray, which experienced a major natural disaster, and Red Deer, did not.Data 3070 grade 7-12 students Canada (collected 2017, 18 months after 2016 wildfire) was with 2796 2014). The same measurement scales were used for both surveys. Both these cities have populations approximately 100,000, are located Canada. For reason,...
ChatGPT is an artificial-intelligence chatbot developed by OpenAI. It can be used in a variety of applications including content creation, personalized recommendations, copy and for language translation. In Business, it data analysis, provide even process orders. Its benefits have been discussed widely popular media with several articles focusing on the changes will bring to workforce way we live work broadly. this article, discuss limitations Business education research particular focus...
Here we report on findings from a 15-month follow-up of school-based program called Empowering Multimodal Pathway Towards Healthy Youth (EMPATHY). This was primarily intended to reduce suicidal thinking in pre-teens, adolescents, and youth students aged 11-18 Middle Schools (Grades 6-8) High 9-12). It also aimed depression anxiety. The EMPATHY multimodal consisted repeated data collection, identification high-risk group, rapid intervention for this group including offering supervised on-line...
Summary The estimation of time varying networks for functional magnetic resonance imaging data sets is increasing importance and interest. We formulate the problem in a high dimensional series framework introduce data-driven method, namely network change points detection, which detects structure multivariate series, with each component represented by node network. Network detection applied to various simulated resting state set. This new methodology also allows us identify common states...
Background: The May 2016 wildfire in Fort McMurray, Alberta, Canada forced evacuation of the population 88,000 individuals and destroyed 10% homes. Youth are particularly impacted by disaster. Methods: Eighteen months after wildfire, McMurray Public Catholic Schools surveyed 3,252 4,407 students Grades 7-12 to determine possible long-term psychological impacts. survey included validated measurement scales for post-traumatic stress disorder (PTSD), depression, anxiety, use drugs, alcohol,...
We describe initial pilot findings from a novel school-based approach to reduce youth depression and suicidality, the Empowering Multimodal Pathway Towards Healthy Youth (EMPATHY) program. Here we present cohort of 3,244 aged 11–18 (Grades 6-12). They were screened for depression, anxiety, use drugs, alcohol, or tobacco (DAT), quality-of-life, self-esteem. Additionally, all students in Grades 7 8 (mean ages 12.3 13.3 respectively) also received an 8-session cognitive-behavioural therapy...
Sparse graphical models are frequently used to explore both static and dynamic functional brain networks from neuroimaging data. However, the practical performance of has not been studied in detail for networks. In this work, we have two objectives. First, compare several sparse model estimation procedures selection criteria under various experimental settings, such as different dimensions, sample sizes, types data, sparsity levels true structures. We discuss superiority deficiency each...
Previous diffusion tensor imaging (DTI) studies confirmed the vulnerability of corpus callosum (CC) fibers to aging. However, most employed lower order regressions study relationship between age and white matter microstructure. The present investigated whether higher polynomial regression modelling can better describe CC DTI metrics compared models in 140 healthy participants (ages 18–85). was found be non-uniformly affected by aging, with accelerated earlier degradation occurring anterior...
In Fort McMurray, Alberta, Canada, the wildfire of May 2016 forced population 88,000 to rapidly evacuate in a traumatic and chaotic manner. Ten percentage homes city were destroyed, many more structures damaged. Since youth are particularly vulnerable negative effects natural disasters, we examined possible long-term psychological impacts. To assess this, partnered with McMurray Public Catholic Schools, who surveyed Grade 7–12 students (aged 11–19) November 2017, 2018, 2019—i.e., at 1.5,...
The hot-hand theory posits that an athlete who has performed well in the recent past performs better present. We use multilevel logistic regression to test this for National Hockey League playoff goaltenders, controlling a variety of shot-related and game-related characteristics. Our data consists <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mn>48</mml:mn> <mml:mo>,</mml:mo> <mml:mn>431</mml:mn> </mml:math> shots 93 goaltenders 2008–2016...
The most widely used inputs in classification models of brain disorders such as early mild cognitive impairment (eMCI) or Alzheimer's disease are estimates static-based functional connectivity (SFC) and sliding window dynamic (swDFC). Although these methods convenient for estimation computational purposes, it keeps the tractable, they present a simplified version highly integrated phenomenon. Change point (cpDFC) methods, which far less commonly used, offer an alternative to swDFC...
The neural circuitry associated with language processing is complex and dynamic. Graphical models are useful for studying networks as this method provides information about unique connectivity between regions within the context of entire network interest. Here, authors explored during covert reading to determine role feedforward feedback loops in speech production.Brain activity skilled adult readers was assessed real word pseudoword tasks functional MRI (fMRI).The provide evidence coherence...
The construct of imageability refers to the extent which a word evokes tangible sensation. Previous research (Westbury, Shaoul, Hollis, Smithson, Briesemeister, Hofmann, & Jacobs, 2013) suggests that behavioral effects attributed word's can be largely or wholly explained by two objective constructs, contextual density and estimated affect. Here, we extend these previous findings in ways. First, show closely matched stimuli on three measures density, affect, human-judged three-way interaction...
The intraclass correlation coefficient (ICC) is a classical index of measurement reliability. With the advent new and complex types data for which ICC not defined, there need ways to assess To meet this need, we propose distance-based (dbICC), defined in terms arbitrary distances among observations. We introduce bias correction improve coverage bootstrap confidence intervals dbICC, demonstrate its efficacy via simulation. illustrate proposed method by analyzing test-retest reliability brain...
Eight children (3 females; 8-16 years) with motor speech disorders secondary to cerebral palsy underwent 4 weeks of an intensive neuroplasticity-principled voice treatment protocol, LSVT LOUD V R , followed by a structured 12-week maintenance program.Children were asked overtly produce phonation (ah) at conversational loudness, cued-phonation perceived twice-conversational series single words, and prosodic imitation task while being scanned using fMRI, immediately pre-and post-treatment 12...