13 Result(s)
within
Chapter
Vince D. Calhoun
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Chapter and Conference Paper
A Nearest Neighbor Propagation-Based Partial Label Learning Method for Identifying Biotypes of Psychiatric Disorders
Diagnoses of psychiatric disorders only based on clinical presentation are less reliable. In clinical practice, it is difficult to distinguish bipolar disorder with psychosis (BPP), schizoaffective disorder (S...
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Chapter and Conference Paper
Group Information Guided Smooth Independent Component Analysis Method for Brain Functional Network Analysis
Independent component analysis (ICA) is widely used for extracting brain functional network (FN) from fMRI data, but the low signal-to-noise ratio in fMRI data makes FNs contain a lot of noise. Previous method...
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Chapter and Conference Paper
Extraction of One Time Point Dynamic Group Features via Tucker Decomposition of Multi-subject FMRI Data: Application to Schizophrenia
Group temporal and spatial features of multi-subject fMRI data are essential for studying mental disorders, especially those exhibiting dynamic properties of brain function. Taking advantages of a low-rank Tuc...
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Chapter and Conference Paper
Marginal Spectrum Modulated Hilbert-Huang Transform: Application to Time Courses Extracted by Independent Vector Analysis of Resting-State fMRI Data
Hilbert-Huang transform (HHT) can reveal abnormal activations impacted by mental disorders from regions of interest (ROIs) based functional magnetic resonance imaging (fMRI) data with high temporal and frequen...
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Chapter
Resting-State Functional Network Disturbances in Schizophrenia
Resting-state functional magnetic resonance imaging is a powerful technique to study the severe mental disease – schizophrenia. Particularly, disturbances of functional resting-state brain networks in this ill...
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Chapter and Conference Paper
Whole MILC: Generalizing Learned Dynamics Across Tasks, Datasets, and Populations
Behavioral changes are the earliest signs of a mental disorder, but arguably, the dynamics of brain function gets affected even earlier. Subsequently, spatio-temporal structure of disorder-specific dynamics is...
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Chapter and Conference Paper
Classification of Schizophrenia Patients and Healthy Controls Using ICA of Complex-Valued fMRI Data and Convolutional Neural Networks
Deep learning has contributed greatly to functional magnetic resonance imaging (fMRI) analysis, however, spatial maps derived from fMRI data by independent component analysis (ICA), as promising biomarkers, ha...
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Chapter
Imaging Genetics: Information Fusion and Association Techniques Between Biomedical Images and Genetic Factors
The development of advanced medical imaging technologies and high-throughput genomic measurements has enhanced our understanding of their interplay as well as their relationship with human behavior. In this ch...
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Chapter and Conference Paper
Comparison of Functional Network Connectivity and Granger Causality for Resting State fMRI Data
Functional network connectivity (FNC) and Granger causality have been widely used to identify functional and effective connectivity for resting functional magnetic resonance imaging (fMRI) data. However, the r...
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Chapter and Conference Paper
SchizConnect: Virtual Data Integration in Neuroimaging
In many scientific domains, including neuroimaging studies, there is a need to obtain increasingly larger cohorts to achieve the desired statistical power for discovery. However, the economics of imaging studi...
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Chapter and Conference Paper
Multivariate Fusion of EEG and Functional MRI Data Using ICA: Algorithm Choice and Performance Analysis
It has become common for neurological studies to gather data from multiple modalities, since the modalities examine complementary aspects of neural activity. Functional magnetic resonance imaging (fMRI) and el...
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Chapter and Conference Paper
Terminology Development Towards Harmonizing Multiple Clinical Neuroimaging Research Repositories
Data sharing and mediation across disparate neuroimaging repositories requires extensive effort to ensure that the different domains of data types are referred to by commonly agreed upon terms. Within the Schi...
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Chapter
ICA for Fusion of Brain Imaging Data
Many studies are currently collecting multiple types of imaging data and information from the same participants. Each imaging method reports on a limited domain and is likely to provide some common information...
