A5084520677- Functional Brain Connectivity Studies
- Mental Health Research Topics
- Neural and Behavioral Psychology Studies
- Advanced MRI Techniques and Applications
- Advanced Neuroimaging Techniques and Applications
- Health, Environment, Cognitive Aging
- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
- Attention Deficit Hyperactivity Disorder
- Dementia and Cognitive Impairment Research
- Heart Rate Variability and Autonomic Control
- Diet and metabolism studies
- Autism Spectrum Disorder Research
- Biomedical and Engineering Education
- Action Observation and Synchronization
- Hemispheric Asymmetry in Neuroscience
- Resilience and Mental Health
- Mitochondrial Function and Pathology
- Adversarial Robustness in Machine Learning
- Neuroscience, Education and Cognitive Function
- Cell Image Analysis Techniques
- Neurotransmitter Receptor Influence on Behavior
- Explainable Artificial Intelligence (XAI)
- Psychological Well-being and Life Satisfaction
- Cannabis and Cannabinoid Research
Brigham and Women's Hospital
2024-2025
Yale University
2018-2023
Université de Montréal
2021
Montreal Neurological Institute and Hospital
2021
McGill University
2021
Abstract Recent work has begun to relate individual differences in brain functional organization human behaviors and cognition, but the best state reveal such relationships remains an open question. In two large, independent data sets, we here show that cognitive tasks amplify trait-relevant patterns of connectivity, predictive models built from task fMRI outperform resting-state data. Further, certain consistently yield better predictions fluid intelligence than others, generates...
The goal of human brain mapping has long been to delineate the functional subunits in and elucidate role each these regions. Recent work focused on whole-brain parcellation Magnetic Resonance Imaging (fMRI) data identify create a atlas. Functional connectivity approaches understand at network level require such an atlas assess connections between parcels extract properties. While no single emerged as dominant date, there remains underlying assumption that exists. Using fMRI from highly...
The ability to sustain attention differs across people and changes within a single person over time. Although recent work has demonstrated that patterns of functional brain connectivity predict individual differences in sustained attention, whether these same capture fluctuations individuals remains unclear. Here, five independent studies, we demonstrate the connectome-based predictive model (CPM), validated function, generalizes attentional state from data collected minutes, days, weeks,...
Abstract Individual differences in brain functional organization track a range of traits, symptoms and behaviours 1–12 . So far, work modelling linear brain–phenotype relationships has assumed that single such relationship generalizes across all individuals, but models do not equally well participants 13,14 A better understanding whom fail why is crucial to revealing robust, useful unbiased relationships. To this end, here we related activity phenotype using predictive models—trained tested...
Abstract Autism is a heterogeneous condition, and functional magnetic resonance imaging-based studies have advanced understanding of neurobiological correlates autistic features. Nevertheless, little work has focused on the optimal brain states to reveal brain-phenotype relationships. In addition, there need better understand relevance attentional abilities in mediating Using connectome-based predictive modelling, we interrogate three datasets determine scanning conditions that can boost...
Resting-state and task-based functional connectivity matrices, or connectomes, are powerful predictors of individual differences in phenotypic measures. However, most the current state-of-the-art algorithms only build predictive models based on a single connectome for each individual. This approach neglects complementary information contained connectomes from different sources reduces prediction performance. In order to combine task into model principled way, we propose novel framework,...
Individual differences in working memory relate to performance general cognitive ability. The neural bases of such individual differences, however, remain poorly understood. Here, using a data-driven technique known as connectome-based predictive modeling, we built models predict from whole-brain functional connectivity patterns. Using n-back or rest data the Human Connectome Project, significantly predicted novel individuals' 2-back accuracy. Model predictions also correlated with measures...
Functional connectivity (FC) calculated from task fMRI data better reveals brain-phenotype relationships than rest-based FC, but how tasks have this effect is unknown. In over 700 individuals performing seven tasks, we use psychophysiological interaction (PPI) and predictive modeling analyses to demonstrate that task-induced changes in FC successfully predict phenotype, these are not simply driven by activation. Activation, however, useful for prediction only if the in-scanner related...
Abstract Memory deficits are observed in a range of psychiatric disorders, but it is unclear whether memory arise from shared brain correlate across disorders or various dysfunctions unique to each disorder. Connectome-based predictive modeling computational method that captures individual differences functional connectomes associated with behavioral phenotypes such as memory. We used publicly available task-based MRI data patients schizophrenia (n = 33), bipolar disorder 34), attention...
Handedness influences differences in lateralization of language areas as well dominance motor and somatosensory cortices. However, whole-brain functional connectivity (i.e., connectomes) due to handedness have been relatively understudied beyond pre-specified networks interest. Here, we compared connectomes left- right-handed individuals at the whole brain level. We explored previously established regions interest, showed between primarily motor, somatosensory, using connectivity. then...
Neuroimaging-based predictive models continue to improve in performance, yet a widely overlooked aspect of these is "trustworthiness," or robustness data manipulations. High trustworthiness imperative for researchers have confidence their findings and interpretations. In this work, we used functional connectomes explore how minor manipulations influence machine learning predictions. These included method falsely enhance prediction performance adversarial noise attacks designed degrade...
Opioid use disorder (OUD) impacts millions of people worldwide. Prior studies investigating its underpinning neural mechanisms have not often considered how brain signals evolve over time, so it remains unclear whether dynamics are altered in OUD and subsequent behavioral implications. To characterize dynamic alterations their association with cognitive control individuals OUD. This case-control study collected functional magnetic resonance imaging (fMRI) data from healthy (HC) participants....
The prevalence of risky behavior such as substance use increases during adolescence; however, the neurobiological precursors to adolescent remain unclear. Predictive modeling may complement previous work observing associations with known risk factors or outcomes by developing generalizable models that predict early susceptibility. aims current study were identify and characterize behavioral brain vulnerability future use. Principal components analysis (PCA) used together connectome-based...
Interest in understanding the organization of brain has led to application graph theory methods across a wide array functional connectivity studies. The fundamental basis is node. Recent work shown that nodes reconfigure with state. To date, all studies have used fixed nodes. Here, using fixed-, group-, state-specific, and individualized- parcellations for defining nodes, we demonstrate changes within significantly influence findings at network level. In some cases, state- or group-dependent...
Abstract Exposure to socioeconomic disadvantages (SED) can have negative impacts on mental health, yet SED are a multifaceted construct and the precise processes by which confer deleterious effects less clear. Using large diverse sample of preadolescents (ages 9–10 years at baseline, n = 4038, 49% female) from Adolescent Brain Cognitive Development Study, we examined associations among both household (i.e., income–needs material hardship) neighborhood area deprivation unsafety) levels,...
Performing functional magnetic resonance imaging (fMRI) scans of children can be a difficult task, as participants tend to move while being scanned. Head motion represents significant confound in fMRI connectivity analyses. One approach limit has been use shorter MRI protocols, though this reduces the reliability results. Hence, there is need implement methods achieve high-quality, low-motion data not sacrificing quantity. Here we show that by using mock scan protocol prior scan, conjunction...
Abstract The goal of human brain mapping has long been to delineate the functional subunits in and elucidate role each these regions. Recent work focused on whole-brain parcellation Magnetic Resonance Imaging (fMRI) data identify create a atlas. Functional connectivity approaches understand at network level require such an atlas assess connections between parcels extract properties. While no single emerged as dominant date, there remains underlying assumption that exists. Using fMRI from...
Abstract The endocannabinoid system is an important regulator of emotional responses such as fear, and a number studies have implicated signaling in anxiety. fatty acid amide hydrolase (FAAH) C385A polymorphism, which associated with enhanced the brain, has been identified across species potential protective factor from In particular, adults variant FAAH 385A allele greater fronto‐amygdala connectivity lower anxiety symptoms. Whether broader network‐level differences exist, when during...