Article
Neurosciences
Jiali Huang, Jae-Yoon Jung, Chang S. Nam
Summary: This study used Dynamic Causal Modeling to investigate the causal relationship among brain regions in different stages of AD. The results showed reduced connectivity and weaker connection strengths in AD patients, which were partially predictive of cognitive scores.
FRONTIERS IN HUMAN NEUROSCIENCE
(2022)
Article
Psychiatry
Ivy F. Tso, Mike Angstadt, Saige Rutherford, Scott Peltier, Vaibhav A. Diwadkar, Stephan F. Taylor
Summary: Abnormal effective connectivity in brain networks associated with eye gaze processing is found in schizophrenia patients, affecting social cognition and functioning. Altered self-connections, inter-regional connections, and explicit gaze discrimination are associated with these abnormalities.
SCHIZOPHRENIA RESEARCH
(2021)
Article
Neurosciences
Tahereh S. Zarghami, Peter Zeidman, Adeel Razi, Fariba Bahrami, Gholam-Ali Hossein-Zadeh
Summary: Schizophrenia is a severe mental disorder characterized by dysconnection across the brain. This study investigated effective connectivity within large-scale networks in patients with schizophrenia, revealing dysconnection in several networks. The study also found significant correlations between specific effective connections and cognitive abilities of patients. Future research can explore the potential of whole-brain effective connectivity as a biomarker for diagnosis and cognitive assessment in brain disorders.
HUMAN BRAIN MAPPING
(2023)
Article
Engineering, Biomedical
Z. Wu, X. Chen, M. Gao, M. Hong, Z. He, H. Hong, J. Shen
Summary: This study investigated the effective connectivity networks among individual brain parcels using resting-state functional MRI images. The results showed that the effective networks exhibit small world attributes and contain highly interactive regions. This helps to understand how different subregions within large-scale neural networks are coupled together in performing cognitive functions.
Article
Neurosciences
Sayan Nag, Kamil Uludag
Summary: Functional MRI (fMRI) is used to indirectly measure neuronal activity. In this study, a novel approach combining physiologically informed DCM with recurrent units is proposed and validated for determining dynamic effective connectivity between brain areas during complex cognitive tasks. The simulation results demonstrate the accurate prediction and distinction of fMRI BOLD responses and effective connectivity time-courses, highlighting the effectiveness of the proposed approach.
FRONTIERS IN HUMAN NEUROSCIENCE
(2023)
Article
Mathematical & Computational Biology
Supat Saetia, Natsue Yoshimura, Yasuharu Koike
Summary: Studying brain function has been challenging in the past, relying on limited methods like post-mortem studies or clinical data analysis. Modern technology such as fMRI now allows for non-invasive observation of brain activity. The brain connectivity model, along with the Tigramite causal discovery framework, provide insights into how different brain regions interact and influence each other, improving the interpretability of the connectivity model and helping understand complex brain functions.
FRONTIERS IN NEUROINFORMATICS
(2021)
Article
Neurosciences
Bertrand Beffara, Fadila Hadj-Bouziane, Suliann Ben Hamed, C. Nico Boehler, Leonardo Chelazzi, Elisa Santandrea, Emiliano Macaluso
Summary: This study measured occipital activity in different spatial regions during the processing of visual displays and found that goal-directed attention and salience jointly modulate activity distribution in the occipital cortex, with involvement of multiple functional paths and interactions.
Article
Neuroimaging
Luqing Wei, Guo-Rong Wu, Minghua Bi, Chris Baeken
Summary: Effective connectivity analysis revealed altered resting state connections between memory and reward systems in cocaine-dependent individuals, which were associated with empathy ability.
BRAIN IMAGING AND BEHAVIOR
(2021)
Review
Neurosciences
Andrew D. Snyder, Liangsuo Ma, Joel L. Steinberg, Kyle Woisard, Frederick G. Moeller
Summary: Dynamic causal modeling (DCM) is a method used for analyzing the directionality of brain connectivity, but there may be a historical trend of underreporting self-connectivity findings in neuropsychiatric fMRI DCM literature. These self-connectivity findings play an important role in regulating neural activity.
FRONTIERS IN NEUROSCIENCE
(2021)
Article
Neurosciences
Ally Dworetsky, Benjamin A. Seitzman, Babatunde Adeyemo, Maital Neta, Rebecca S. Coalson, Steven E. Petersen, Caterina Gratton
Summary: Recent studies have focused on individual differences in the functional network organization of the human brain and have utilized this information to probabilistically map common functional systems for improved group analyses. While these functional systems exhibit core regions, they vary in their higher-variability components and demonstrate good replication across datasets.
Article
Behavioral Sciences
Peyman Ghobadi-Azbari, Rasoul Mahdavifar Khayati, Arshiya Sangchooli, Hamed Ekhtiari
Summary: Neural reactivity to food cues plays an important role in overeating and excess weight gain. The study identifies activations and neural interactions in the reward network, providing insights into the dynamic circuit mechanisms relevant to obesity.
FRONTIERS IN BEHAVIORAL NEUROSCIENCE
(2022)
Article
Engineering, Biomedical
Cooper J. Mellema, Albert A. Montillo
Summary: This study aims to propose new measures of human brain connectivity to address gaps in the existing measures and facilitate the study of brain function, cognitive capacity, and early markers of human disease. Two new measures of functional and effective connectivity are proposed, using machine learning techniques to capture linear and nonlinear aspects of brain associations. The proposed measures demonstrate higher reproducibility and predictive power compared to traditional measures.
JOURNAL OF NEURAL ENGINEERING
(2023)
Article
Neurosciences
Matteo Grasso, Larissa Albantakis, Jonathan P. Lang, Giulio Tononi
Summary: The Perspective argues that causal reductionism cannot provide a complete and coherent account of causation, and proposes an operational approach to analyzing causal structures.
NATURE NEUROSCIENCE
(2021)
Article
Neurosciences
Murray Bruce Reed, Manfred Klobl, Godber Mathis Godbersen, Patricia Anna Handschuh, Vera Ritter, Benjamin Spurny-Dworak, Jakob Unterholzner, Christoph Kraus, Gregor Gryglewski, Dietmar Winkler, Rene Seiger, Thomas Vanicek, Andreas Hahn, Rupert Lanzenberger
Summary: This study examined the impact of SSRI antidepressants on neuroplasticity in healthy volunteers. The results indicate that SSRI intake can alter effective connections between certain brain regions, without significantly affecting intrinsic or resting-state connections.
Article
Neurosciences
Stefan Frassle, Samuel J. Harrison, Jakob Heinzle, Brett A. Clementz, Carol A. Tamminga, John A. Sweeney, Elliot S. Gershon, Matcheri S. Keshavan, Godfrey D. Pearlson, Albert Powers, Klaas E. Stephan
Summary: Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used for studying brain connectivity. Researchers have developed a method called rDCM that extends to rs-fMRI, offering directional estimates and scalability to whole-brain networks. Through simulations and empirical tests, rDCM has shown to be computationally efficient and produce biologically plausible results consistent with established models of effective connectivity.
HUMAN BRAIN MAPPING
(2021)
Article
Neuroimaging
Dana Mastrovito, Catherine Hanson, Stephen Jose Hanson
NEUROIMAGE-CLINICAL
(2018)
Article
Neurosciences
Anna Manelis, Lynne M. Reder, Stephen Jose Hanson
Article
Neurosciences
Anna Manelis, Catherine Hanson, Stephen Jose Hanson
HUMAN BRAIN MAPPING
(2011)
Article
Neurosciences
Olga Boukrina, Stephen Jose Hanson, Catherine Hanson
HUMAN BRAIN MAPPING
(2014)
Article
Neurosciences
Stephen Jose Hanson, Arielle Schmidt
Article
Neurosciences
Colleen Mills-Finnerty, Catherine Hanson, Stephen Jose Hanson
Article
Neurosciences
Andrew T. Reid, Drew B. Headley, Ravi D. Mill, Ruben Sanchez-Romero, Lucina Q. Uddin, Daniele Marinazzo, Daniel J. Lurie, Pedro A. Valdes-Sosa, Stephen Jose Hanson, Bharat B. Biswal, Vince Calhoun, Russell A. Poldrack, Michael W. Cole
NATURE NEUROSCIENCE
(2019)
Article
Computer Science, Artificial Intelligence
Noah Frazier-Logue, Stephen Jose Hanson
NEURAL COMPUTATION
(2020)
Article
Neurosciences
Colleen Mills-Finnerty, Catherine Hanson, Mohannad Khadr, Stephen Jose Hanson
BRAIN CONNECTIVITY
(2020)
Article
Psychology, Multidisciplinary
Catherine Hanson, Leyla Roskan Caglar, Stephen Jose Hanson
FRONTIERS IN PSYCHOLOGY
(2018)
Proceedings Paper
Computer Science, Artificial Intelligence
Andrei Barbu, Daniel P. Barrett, Wei Chen, Narayanaswamy Siddharth, Caiming Xiong, Jason J. Corso, Christiane D. Fellbaum, Catherine Hanson, Stephen Jose Hanson, Sebastien Helie, Evguenia Malaia, Barak A. Pearlmutter, Jeffrey Mark Siskind, Thomas Michael Talavage, Ronnie B. Wilbur
COMPUTER VISION - ECCV 2014, PT V
(2014)
Proceedings Paper
Computer Science, Artificial Intelligence
Chenliang Xu, Richard F. Doell, Stephen Jose Hanson, Catherine Hanson, Jason J. Corso
2013 IEEE SEVENTH INTERNATIONAL CONFERENCE ON SEMANTIC COMPUTING (ICSC 2013)
(2013)
Article
Computer Science, Artificial Intelligence
Chenliang Xu, Richard F. Doell, Stephen Jose Hanson, Catherine Hanson, Jason J. Corso
INTERNATIONAL JOURNAL OF SEMANTIC COMPUTING
(2013)
Article
Neurosciences
Catherine Hanson, Stephen Jose Hanson, Joseph Ramsey, Clark Glymour
BRAIN CONNECTIVITY
(2013)
Article
Biology
Amanda Maria Dios, Katherine Alexander, Stephen Jose Hanson, Mei Fang Cheng
RESEARCH AND REPORTS IN BIOLOGY
(2013)
Article
Neurosciences
Jose Sanchez-Bornot, Roberto C. Sotero, J. A. Scott Kelso, Ozguer Simsek, Damien Coyle
Summary: This study proposes a multi-penalized state-space model for analyzing unobserved dynamics, using a data-driven regularization method. Novel algorithms are developed to solve the model, and a cross-validation method is introduced to evaluate regularization parameters. The effectiveness of this method is validated through simulations and real data analysis, enabling a more accurate exploration of cognitive brain functions.