Variations on the theme: focus on cerebellum and emotional processing
C Ciapponi, Y Li, DA Osorio Becerra… - Frontiers in Systems …, 2023 - frontiersin.org
The cerebellum operates exploiting a complex modular organization and a unified
computational algorithm adapted to different behavioral contexts. Recent observations …
computational algorithm adapted to different behavioral contexts. Recent observations …
Applications of deep learning for drug discovery systems with bigdata
Y Matsuzaka, R Yashiro - BioMedInformatics, 2022 - mdpi.com
The adoption of “artificial intelligence (AI) in drug discovery”, where AI is used in the process
of pharmaceutical research and development, is progressing. By using the ability to process …
of pharmaceutical research and development, is progressing. By using the ability to process …
A Deep Biclustering Framework for Brain Network Analysis
Brain functional connectivity (FC) analysis has emerged as a compelling quest to
understand human brain dynamics and clarify disorder-related aberrations. Typically FC can …
understand human brain dynamics and clarify disorder-related aberrations. Typically FC can …
A survey of brain functional network extraction methods using fMRI data
Y Du, S Fang, X He, VD Calhoun - Trends in Neurosciences, 2024 - Elsevier
Functional network (FN) analyses play a pivotal role in uncovering insights into brain
function and understanding the pathophysiology of various brain disorders. This paper …
function and understanding the pathophysiology of various brain disorders. This paper …
Convolutional bidirectional GRU for dynamic functional connectivity classification in brain diseases diagnosis
J Ji, C Ye, C Yang - Knowledge-Based Systems, 2024 - Elsevier
Dynamic functional connectivity (DFC) classification is helpful for computer-aided diagnosis
of brain diseases. In recent years, DFC classification based on deep learning has drawed …
of brain diseases. In recent years, DFC classification based on deep learning has drawed …
A Learnable Counter-condition Analysis Framework for Functional Connectivity-based Neurological Disorder Diagnosis
To understand the biological characteristics of neurological disorders with functional
connectivity (FC), recent studies have widely utilized deep learning-based models to identify …
connectivity (FC), recent studies have widely utilized deep learning-based models to identify …
Changes in Community Structure of Brain Dynamic Functional Connectivity States in Mild Cognitive Impairment
H Wang, Z Zhu, H Bi, Z Jiang, Y Cao, S Wang, L Zou - Neuroscience, 2024 - Elsevier
Recent researches have noted many changes of short-term dynamic modalities in mild
cognitive impairment (MCI) patients' brain functional networks. In this study, the dynamic …
cognitive impairment (MCI) patients' brain functional networks. In this study, the dynamic …
A predictor-informed multi-subject bayesian approach for dynamic functional connectivity
Dynamic functional connectivity investigates how the interactions among brain regions vary
over the course of an fMRI experiment. Such transitions between different individual …
over the course of an fMRI experiment. Such transitions between different individual …
Neuroevolve: A dynamic brain graph deep generative model
Graphs are a natural representation of brain activity derived from functional magnetic
imaging (fMRI) data. It is well known that communities of nodes extracted from brain graphs …
imaging (fMRI) data. It is well known that communities of nodes extracted from brain graphs …
DBGDGM: Dynamic Brain Graph Deep Generative Model
Graphs are a natural representation of brain activity derived from functional magnetic
imaging (fMRI) data. It is well known that clusters of anatomical brain regions, known as …
imaging (fMRI) data. It is well known that clusters of anatomical brain regions, known as …