A5062295478- Functional Brain Connectivity Studies
- Advanced Neuroimaging Techniques and Applications
- Advanced MRI Techniques and Applications
- Mental Health Research Topics
- Health, Environment, Cognitive Aging
- Neural dynamics and brain function
- Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Treatment of Major Depression
- RNA and protein synthesis mechanisms
- Complex Network Analysis Techniques
- Health and Well-being Studies
- Cell Image Analysis Techniques
- RNA modifications and cancer
- Genomics and Phylogenetic Studies
Yale University
2017-2021
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...
There is extensive evidence that functional organization of the human brain varies dynamically as switches between task demands, or cognitive states. This also across subjects, even when engaged in similar tasks. To date, network has been considered static. In this work, we use fMRI data obtained multiple states (task-evoked and rest conditions) to measure state- subject-specific parcellation (the assignment nodes networks). Our approach provides a how node-to-network (NNA) changes subjects....
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...
Clinically approved antidepressants modulate the brain's emotional valence circuits, suggesting that response of these circuits could serve as a biomarker for screening candidate antidepressant drugs. However, it is necessary modulations can be reliably detected. Here, we apply cross-validated predictive model to classify and pharmacologic effect across eleven task-based fMRI datasets (n = 306) exploring administration on face processing. We created subject-level contrast parameter estimates...
Abstract There is extensive evidence that human brain functional organization dynamic, varying within a subject as the switches between tasks demands. This also varies across subjects, even when they are all engaged in similar tasks. Currently, we lack comprehensive model unifies two dimensions of variation (brain state and subject). Using fMRI data obtained multiple task-evoked rest conditions (which operationally define states) develop state-and subject-specific network parcellation (the...
Large datasets that enable researchers to perform investigations with unprecedented rigor are growing increasingly common in neuroimaging. Due the simultaneous increasing popularity of open science, these state-of-the-art more accessible than ever around world. While analysis samples has pushed field forward, they pose a new set challenges might cause difficulties for novice users. Here, we offer practical tips working large from end-user’s perspective. We cover all aspects data...
We propose a novel approach for building classification/identification framework based on the full complement of RNA post-transcriptional modifications (rPTMs) expressed by an organism at basal conditions. The relies advanced mass spectrometry techniques to characterize products exonuclease digestion total extracts. Sample profiles comprising identities and relative abundances all detected rPTM were used train test capabilities different machine learning (ML) algorithms. Each algorithm...
ABSTRACT Background Clinically approved antidepressants modulate the brain’s emotional valence circuits, suggesting that response of these circuits could serve as a biomarker for screening candidate antidepressant drugs. However, it is necessary modulations can be reliably detected. Here, we apply cross-validated predictive model to classify and pharmacologic effect across eleven task-based fMRI datasets (n=306) exploring administration on face processing. Methods We created subject-level...