Cargando…

Joint Coupling of Awake EEG Frequency Activity and MRI Gray Matter Volumes in the Psychosis Dimension: A BSNIP Study

BACKGROUND: Many studies have examined either electroencephalogram (EEG) frequency activity or gray matter volumes (GMV) in various psychoses [including schizophrenia (SZ), schizoaffective (SZA), and psychotic bipolar disorder (PBP)]. Prior work demonstrated similar EEG and gray matter abnormalities...

Descripción completa

Detalles Bibliográficos
Autores principales:	Soh, Pauline, Narayanan, Balaji, Khadka, Sabin, Calhoun, Vince D., Keshavan, Matcheri S., Tamminga, Carol A., Sweeney, John A., Clementz, Brett A., Pearlson, Godfrey D.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2015
Materias:	Psychiatry
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4637406/ https://www.ncbi.nlm.nih.gov/pubmed/26617533 http://dx.doi.org/10.3389/fpsyt.2015.00162

Ejemplares similares

O10.6. ANTERIOR VERSUS POSTERIOR HIPPOCAMPUS WITHIN PSYCHOSIS: A BSNIP STUDY
por: del Re, Elisabetta C, et al.
Publicado: (2020)

Multivariate genetic determinants of EEG oscillations in schizophrenia and psychotic bipolar disorder from the BSNIP study
por: Narayanan, B, et al.
Publicado: (2015)

9.3 PSYCHOSIS BIOTYPES VERSUS CLINICAL SYNDROMES THROUGH THE PRISM OF INTRINSIC NEURAL ACTIVITY
por: Clementz, Brett, et al.
Publicado: (2018)

Large-Scale Fusion of Gray Matter and Resting-State Functional MRI Reveals Common and Distinct Biological Markers across the Psychosis Spectrum in the B-SNIP Cohort
por: Wang, Zheng, et al.
Publicado: (2015)

5.3 EVIDENCE ON A TRANSDIAGNOSTIC PSYCHOSIS SPECTRUM OF SCHIZOPHRENIA, SCHIZOAFFECTIVE AND PSYCHOTIC BIPOLAR DISORDER IN THE BIPOLAR-SCHIZOPHRENIA NETWORK ON INTERMEDIATE PHENOTYPES (B-SNIP)
por: Reininghaus, Ulrich, et al.
Publicado: (2018)

Supervised machine learning classification of psychosis biotypes based on brain structure: findings from the Bipolar-Schizophrenia network for intermediate phenotypes (B-SNIP)
por: Koen, Joshua D., et al.
Publicado: (2023)

O3.4. PSYCHOSIS PHENOTYPES FROM B-SNIP FOR CLINICAL ADVANCES: BIOTYPE CHARACTERISTICS AND TARGETS
por: Clementz, Brett, et al.
Publicado: (2020)

T22. PITUITARY GLAND VOLUME DIFFERENCES IN INDIVIDUALS WITH PSYCHOSIS: RESULTS FROM THE BIPOLAR-SCHIZOPHRENIA NETWORK ON INTERMEDIATE PHENOTYPES (B-SNIP) STUDY
por: Guimond, Synthia, et al.
Publicado: (2018)

Brain gray matter network organization in psychotic disorders
por: Zhang, Wenjing, et al.
Publicado: (2019)

Auditory paired-stimuli responses across the psychosis and bipolar spectrum and their relationship to clinical features
por: Parker, David A., et al.
Publicado: (2020)

O2.6. DELUSIONS ASSOCIATED WITH ABNORMAL FRONTOSTRIATAL EFFECTIVE CONNECTIVITY IN A SPECTRAL DCM ANALYSIS OF RESTING STATE FMRI
por: Okuneye, Victoria, et al.
Publicado: (2020)

Resting state auditory-language cortex connectivity is associated with hallucinations in clinical and biological subtypes of psychotic disorders
por: Okuneye, Victoria T., et al.
Publicado: (2020)

Inflammation subtypes in psychosis and their relationships with genetic risk for psychiatric and cardiometabolic disorders
por: Zhang, Lusi, et al.
Publicado: (2022)

Psychosis Biotypes: Replication and Validation from the B-SNIP Consortium
por: Clementz, Brett A, et al.
Publicado: (2021)

GWAS Significance Thresholds for Deep Phenotyping Studies Can Depend Upon Minor Allele Frequencies and Sample Size
por: Asif, Huma, et al.
Publicado: (2020)

Regression dynamic causal modeling for resting‐state fMRI
por: Frässle, Stefan, et al.
Publicado: (2021)

Multivariate Imaging Genetics Study of MRI Gray Matter Volume and SNPs Reveals Biological Pathways Correlated with Brain Structural Differences in Attention Deficit Hyperactivity Disorder
por: Khadka, Sabin, et al.
Publicado: (2016)

Multivariate Relationships Between Peripheral Inflammatory Marker Subtypes and Cognitive and Brain Structural Measures in Psychosis
por: Lizano, Paulo, et al.
Publicado: (2020)

VEGFA GENE variation influences hallucinations and frontotemporal morphology in psychotic disorders: a B-SNIP study
por: Lizano, Paulo, et al.
Publicado: (2018)

Polygenic risk for schizophrenia and measured domains of cognition in individuals with psychosis and controls
por: Shafee, Rebecca, et al.
Publicado: (2018)

Structural Angle and Power Images Reveal Interrelated Gray and White Matter Abnormalities in Schizophrenia
por: Xu, Lai, et al.
Publicado: (2012)

Exploring the Psychosis Functional Connectome: Aberrant Intrinsic Networks in Schizophrenia and Bipolar Disorder
por: Calhoun, Vince D, et al.
Publicado: (2012)

Evaluation of boundaries between mood and psychosis disorder using dynamic functional network connectivity (dFNC) via deep learning classification
por: Rokham, Hooman, et al.
Publicado: (2023)

Identifying commonality and specificity across psychosis sub-groups via classification based on features from dynamic connectivity analysis
por: Du, Yuhui, et al.
Publicado: (2020)

NRXN1 is associated with enlargement of the temporal horns of the lateral ventricles in psychosis
por: Alliey-Rodriguez, Ney, et al.
Publicado: (2019)

Convergent Approaches for Defining Functional Imaging Endophenotypes in Schizophrenia
por: Pearlson, Godfrey D., et al.
Publicado: (2009)

Functional Brain Networks in Schizophrenia: A Review
por: Calhoun, Vince D., et al.
Publicado: (2009)

Deficient Suppression of Default Mode Regions during Working Memory in Individuals with Early Psychosis and at Clinical High-Risk for Psychosis
por: Fryer, Susanna L., et al.
Publicado: (2013)

An introductory review of parallel independent component analysis (p-ICA) and a guide to applying p-ICA to genetic data and imaging phenotypes to identify disease-associated biological pathways and systems in common complex disorders
por: Pearlson, Godfrey D., et al.
Publicado: (2015)

Whole brain polarity regime dynamics are significantly disrupted in schizophrenia and correlate strongly with network connectivity measures
por: Miller, Robyn L., et al.
Publicado: (2019)

Microstructural Cortical Gray Matter Changes Preceding Accelerated Volume Changes in Individuals at Clinical High Risk for Psychosis
por: Kang, Ik Cho, et al.
Publicado: (2023)

A Data-Driven Investigation of Gray Matter–Function Correlations in Schizophrenia during a Working Memory Task
por: Michael, Andrew M., et al.
Publicado: (2011)

Dynamic connectivity states estimated from resting fMRI Identify differences among Schizophrenia, bipolar disorder, and healthy control subjects
por: Rashid, Barnaly, et al.
Publicado: (2014)

Classification of schizophrenia patients based on resting-state functional network connectivity
por: Arbabshirani, Mohammad R., et al.
Publicado: (2013)

A Hybrid Machine Learning Method for Fusing fMRI and Genetic Data: Combining both Improves Classification of Schizophrenia
por: Yang, Honghui, et al.
Publicado: (2010)

Opposite Modulation of Brain Functional Networks Implicated at Low vs. High Demand of Attention and Working Memory
por: Xu, Jiansong, et al.
Publicado: (2014)

Altered amygdala shape trajectories and emotion recognition in youth at familial high risk of schizophrenia who develop psychosis
por: Guimond, Synthia, et al.
Publicado: (2022)

A Selective Review of Multimodal Fusion Methods in Schizophrenia
por: Sui, Jing, et al.
Publicado: (2012)

Multiframe Evolving Dynamic Functional Connectivity (EVOdFNC): A Method for Constructing and Investigating Functional Brain Motifs
por: Miller, Robyn L., et al.
Publicado: (2022)

Evidence for Anomalous Network Connectivity during Working Memory Encoding in Schizophrenia: An ICA Based Analysis
por: Meda, Shashwath A., et al.
Publicado: (2009)

Cannot write session to /tmp/vufind_sessions/sess_7v3nag8nffecjjm0t5ivihpjf5