Results 11 to 20 of about 383 (157)

Imaging-genomic spatial-modality attentive fusion for studying neuropsychiatric disorders. [PDF]

Hum Brain Mapp
Multimodal learning has emerged as a powerful technique that leverages diverse data sources to enhance learning and decision-making processes. Adapting this approach to analyzing data collected from different biological domains is intuitive, especially ...
Calhoun, Vince, Chen, Jiayu, Fu, Zening, Garg, Yash, Hong, L, Iraji, Armin, Kochunov, Peter, Preda, Adrian, Rahaman, Md, Van Erp, Theo   +9 more
core   +3 more sources

Whole-Brain Functional Network Connectivity Abnormalities in Affective and Non-Affective Early Phase Psychosis

Frontiers in Neuroscience, 2021
Psychosis disorders share overlapping symptoms and are characterized by a wide-spread breakdown in functional brain integration. Although neuroimaging studies have identified numerous connectivity abnormalities in affective and non-affective psychoses ...
Zening Fu, Armin Iraji, Jing Sui
exaly   +3 more sources

The risk of cannabis use disorder is mediated by altered brain connectivity: A chronnectome study [PDF]

Addiction Biology, Volume 29, Issue 5, May 2024.
The brain mechanisms underlying the risk of cannabis use disorder (CUD) are poorly understood. Several studies have reported changes in functional connectivity (FC) in CUD, although none have focused on the study of time-varying patterns of FC.
Calhoun V. D., Fazio G., Hirjak D., Kubera K. M., Olivo D., Reith W., Sambataro F., Schmitgen M. M., Werler F., Witteman M., Wolf N. D., Wolf R. C.   +11 more
core   +2 more sources

Static and Dynamic Cross-Network Functional Connectivity Shows Elevated Entropy in Schizophrenia Patients. [PDF]

Human Brain Mapping, Volume 46, Issue 2, February 1, 2025.
Schizophrenia (SZ) patients exhibit abnormal static and dynamic functional connectivity across various brain domains. We present a novel approach based on static and dynamic inter-network connectivity entropy (ICE), which represents the entropy of a
Bustillo, Juan, Calhoun, Vince, Ford, Judith, Maksymchuk, Natalia, Mathalon, Daniel, Miller, Robyn, Pearlson, Godfrey, Preda, Adrian   +7 more
core   +2 more sources

Building multivariate molecular imaging brain atlases using the NeuroMark PET independent component analysis framework

Aperture Neuro
# Introduction Molecular imaging analyses using positron emission tomography (PET) data often rely on macro-anatomical regions of interest (ROI), which may not align with chemo-architectural boundaries and obscure functional distinctions.
Murat Bilgel
exaly   +2 more sources

Fully automated estimation of fMRI-guided SPECT brain networks and their functional network connectivity in schizophrenia patients versus controls: A NeuroMark ICA approach

Aperture Neuro
Single photon emission computerized tomography (SPECT) has emerged as a useful imaging modality that has been explored in the literature for the last 40 years.
Maria B Misiura
exaly   +2 more sources

Patient Questions Surrounding Posterior Nasal Nerve Ablation for Chronic Rhinitis [PDF]

OTO Open
OBJECTIVE: In-office ablation of the posterior nasal nerve (PNN) has emerged as an effective treatment option for chronic rhinitis patients. This study explored questions patients commonly search online regarding this therapy and the quality of content ...
Ahmed, Omar G, Brissett, Ella S, Dhanda, Aatin K, Fox, Meha G, Gorelik, Daniel, Khan, Najm, Razmi, Samuel E, Rowan, Nicholas R, Sims, Robert Kenneth, Takashima, Masayoshi, Yim, Michael T   +10 more
core   +3 more sources

Neurobiology-based cognitive biotypes using multi-scale intrinsic connectivity networks in psychotic disorders

Schizophrenia
Understanding neurobiology and developing effective interventions for cognitive dysfunction in psychotic disorders remain elusive. Insufficient knowledge about the biological heterogeneity of cognitive dysfunction hinders progress.
Pablo Andrés Camazón, Vd Calhoun, Covadonga M Díaz-Caneja   +2 more
exaly   +2 more sources

Towards Clinical Diagnoses: Classifying Alzheimer's Disease Using Single fMRI, Small Datasets, and Transfer Learning [PDF]

Brain and Behavior, Volume 15, Issue 3, March 2025.
Purpose: Deep learning and functional magnetic resonance imaging (fMRI) are two unique methodologies that can be combined to diagnose Alzheimer's disease (AD). Multiple studies have harnessed these methods to diagnose AD with high accuracy.
, Moustafa, Ahmed A., Warren, Samuel L.
core   +2 more sources

A Dynamic Entropy Approach Reveals Reduced Functional Network Connectivity Trajectory Complexity in Schizophrenia

Entropy
Over the past decade and a half, dynamic functional imaging has revealed low-dimensional brain connectivity measures, identified potential common human spatial connectivity states, tracked the transition patterns of these states, and demonstrated ...
David Blair, Robyn L Miller, Vd Calhoun
exaly   +3 more sources