Article
Psychology, Clinical
Cope Feurer, Jagan Jimmy, Fini Chang, Scott A. Langenecker, K. Luan Phan, Olusola Ajilore, Heide Klumpp
Summary: This study explored the relationship between brain activity and rumination and worry in internalizing conditions. The results indicate the involvement of the affective network in rumination and worry, as well as distinct connectivity patterns observed in patients with internalizing conditions. The findings suggest different mechanisms contribute to rumination as a unitary construct and worry as a unique construct.
DEPRESSION AND ANXIETY
(2021)
Article
Psychology, Multidisciplinary
Li Geng, Qiuyang Feng, Xueyang Wang, Yixin Gao, Lei Hao, Jiang Qiu
Summary: The present study examines the impact of social rejection on rumination and investigates the underlying neural mechanisms. The results show a positive correlation between social rejection and rumination. The predictive model for rumination scores suggests that the default mode network, dorsal attention network, frontoparietal control network, and sensorimotor networks play important roles in this process. Mediation analysis reveals that the strength of the prediction network mediates the relationship between social rejection and rumination.
FRONTIERS IN PSYCHOLOGY
(2023)
Article
Psychology, Clinical
Lizhu Luo, Christelle Langley, Laura Moreno-Lopez, Keith Kendrick, David K. Menon, Emmanuel A. Stamatakis, Barbara J. Sahakian
Summary: This study examined the association between depressive symptoms in traumatic brain injury (TBI) patients and altered resting-state functional connectivity (rs-fc) or voxel-based morphology in brain regions involved in emotional regulation and associated with depression. The results showed a positive association between depression scores and rs-fc between limbic regions and cognitive control regions, while there was a negative association between depression scores and rs-fc between limbic and frontal regions involved in emotion regulation. These findings contribute to a better understanding of the mechanisms underlying depression following TBI and can inform treatment decisions.
PSYCHOLOGICAL MEDICINE
(2023)
Article
Clinical Neurology
Dana DeMaster, Beata R. Godlewska, Mingrui Liang, Marina Vannucci, Taya Bockmann, Bo Cao, Sudhakar Selvaraj
Summary: This study aimed to investigate the influence of brain regions on each other in patients with depression and explore the relationship with treatment response. The results showed widespread dysfunction of rsEC in patients with depression, and the connectivity strength was related to baseline depression severity and treatment response. This suggests that functional rsEC may be useful for predicting the effectiveness of antidepressant treatment.
JOURNAL OF AFFECTIVE DISORDERS
(2022)
Article
Clinical Neurology
Masaya Misaki, Aki Tsuchiyagaito, Salvador M. Guinjoan, Michael L. Rohan, Martin P. Paulus
Summary: This study investigated the relationship between resting-state functional connectivity (RSFC) and repetitive negative thinking (RNT) in individuals with major depressive disorder (MDD) and compared RSFC with functional connectivity during an induced negative-thinking state (NTFC). The results showed that both RSFC and NTFC could distinguish between healthy and depressed individuals, but only NTFC could predict trait RNT in depressed individuals. Additionally, connectome-wide association analysis revealed higher functional connectivity between the default mode and executive control regions in depression, which was not observed in RSFC. These findings suggest that RNT in depression involves an active mental process encompassing multiple brain regions across functional networks, which is not represented in the resting state.
JOURNAL OF AFFECTIVE DISORDERS
(2023)
Article
Anatomy & Morphology
Zhenni Gao, Xiaojin Liu, Delong Zhang, Ming Liu, Ning Hao
Summary: Recent studies have shown that creative visual divergent thinking is associated with specific subcortical regions and the fronto-striatal dopaminergic pathways. This study used resting-state functional magnetic resonance imaging data to explore differences in spontaneous fluctuations of the subcortex between individuals with different levels of creativity. The results indicate significant differences in functional connectivity within the subcortex and a positive correlation between subcortical functional connectivity and visual divergent thinking scores.
BRAIN STRUCTURE & FUNCTION
(2021)
Article
Psychology, Clinical
Ryan Ahmed, Brian D. Boyd, Damian Elson, Kimberly Albert, Patrick Begnoche, Hakmook Kang, Bennett A. Landman, Sarah M. Szymkowicz, Patricia Andrews, Jennifer Vega, Warren D. Taylor
Summary: This study found that clinical improvement in late-life depression is associated with functional connectivity in intrinsic brain networks, particularly in the default mode, cognitive control, and limbic networks. Future research should focus on clinical markers of network connectivity informing prognosis.
PSYCHOLOGICAL MEDICINE
(2023)
Article
Immunology
Johnna R. Swartz, Angelica F. Carranza, Laura M. Tully, Annchen R. Knodt, Janina Jiang, Michael R. Irwin, Camelia E. Hostinar
Summary: The study found associations between peripheral inflammation and adolescent brain connectivity, with higher TNF-α levels linked to changes in neural network connections. Associations with IL-6 and CRP were not significant, suggesting that inflammation may have unique effects on brain connectivity during adolescence.
BRAIN BEHAVIOR AND IMMUNITY
(2021)
Article
Clinical Neurology
Jifei Sun, Yue Ma, Chunlei Guo, Zhongming Du, Limei Chen, Zhi Wang, Xiaojiao Li, Ke Xu, Yi Luo, Yang Hong, Xue Yu, Xue Xiao, Jiliang Fang, Jie Lu
Summary: This study found abnormal functional connectivity (FC) in four brain networks (DMN, AN, SN, CCN) in both patients with treatment-resistant depression (TRD) and non-TRD (nTRD). FC alterations in the affective network (AN) and cognitive control network (CCN) were more severe in the TRD group compared to the nTRD group. Additionally, specific brain regions' FC values were positively correlated with clinical symptoms.
PROGRESS IN NEURO-PSYCHOPHARMACOLOGY & BIOLOGICAL PSYCHIATRY
(2023)
Article
Neurosciences
Limin Peng, Zhiguo Luo, Ling-Li Zeng, Chenping Hou, Hui Shen, Zongtan Zhou, Dewen Hu
Summary: This study developed a brain parcellation method based on dynamic functional connectivity and created a new functional brain atlas. The atlas can reveal finer functional boundaries that static methods may overlook, and shows good agreement with cytoarchitectonic areas and task activation maps.
Article
Neurosciences
Chunlian Chen, Bo Li, Shufen Zhang, Zhe Liu, Yu Wang, Minghe Xu, Yuqing Ji, Shuang Wang, Gang Sun, Kai Liu
Summary: In this study, brain structural alterations and relevant functional changes in patients with postpartum depression (PPD) were investigated. The findings revealed increased gray matter volume in the left dorsolateral prefrontal cortex, right precentral gyrus, and orbitofrontal cortex of PPD patients compared to healthy postnatal women. The functional connectivity between these regions also showed enhancement. Additionally, the increased gray matter volume in the left dorsolateral prefrontal cortex and the functional connectivity between the right precentral gyrus and right median cingulate gyrus were positively correlated with the severity of depression symptoms.
FRONTIERS IN NEUROSCIENCE
(2023)
Article
Computer Science, Artificial Intelligence
Mingliang Wang, Jiashuang Huang, Mingxia Liu, Daoqiang Zhang
Summary: This study proposes a temporal dynamics learning (TDL) method for network-based brain disease identification using rs-fMRI time-series data. By integrating network feature extraction and classifier training into a unified framework, it addresses the issues of previous studies paying less attention to the evolution of global network structures over time and treating feature extraction and training as separate tasks.
MEDICAL IMAGE ANALYSIS
(2021)
Article
Psychiatry
Rozemarijn S. van Kleef, Pallavi Kaushik, Marlijn Besten, Jan-Bernard C. Marsman, Claudi L. H. Bockting, Marieke van Vugt, Andre Aleman, Marie-Jose van Tol
Summary: This study investigated the persistence of abnormalities in self-referential cognitions and functioning of associated brain networks in remitted recurrent MDD patients and their predictive value for relapse. The results showed no significant differences between remitted patients and controls in self-associations and resting-state functional connectivity. However, relapse was related to baseline functional connectivity, implicit self-associations, and uncontrollability of ruminative thinking. These findings suggest that variations in self-related processing play a role in the vulnerability to developing recurrent depressive episodes.
JOURNAL OF PSYCHIATRIC RESEARCH
(2023)
Article
Neurosciences
Eleonora Fadel, Heinz Boeker, Matti Gaertner, Andre Richter, Birgit Kleim, Erich Seifritz, Simone Grimm, Laura M. Wade-Bohleber
Summary: Depressive symptoms and ELA have distinct associations with FC, with symptoms related to increased FC within SN and decreased FC between SN and other networks. The study contributes to understanding the differential impacts of depression and ELA.
Article
Neurosciences
Jung-Hoon Kim, Josepheen De Asis-Cruz, Kushal Kapse, Catherine Limperopoulos
Summary: The reliability and robustness of rs-fcMRI depend on minimizing the influence of head motion on brain signals. This study examined the impact of head motion on newborn brain connectivity using a large dataset. The findings revealed that head motion significantly affected connectivity, with specific effects observed in sensory-related and default mode networks. Implementing a motion correction strategy helped reduce the confounding effects of head motion on neonatal rs-fcMRI.
HUMAN BRAIN MAPPING
(2023)
Article
Neurosciences
Tyler B. Grove, Carly A. Lasagna, Ramon Martinez-Cancino, Preetha Pamidighantam, Patricia J. Deldin, Ivy F. Tso
Summary: The study found that individuals with schizophrenia exhibit abnormal theta phase consistency and dysconnection between posterior face processing and anterior areas during gaze processing, potentially underlying deficits in gaze discrimination accuracy.
BIOLOGICAL PSYCHIATRY-COGNITIVE NEUROSCIENCE AND NEUROIMAGING
(2021)
Article
Psychology, Clinical
Yuen-Siang Ang, Gerard E. Bruder, John G. Keilp, Ashleigh Rutherford, Daniel M. Alschuler, Pia Pechtel, Christian A. Webb, Thomas Carmody, Maurizio Fava, Cristina Cusin, Patrick J. McGrath, Myrna Weissman, Ramin Parsey, Maria A. Oquendo, Melvin G. McInnis, Crystal M. Cooper, Patricia Deldin, Madhukar H. Trivedi, Diego A. Pizzagalli
Summary: This study investigated whether neurocognitive variables could predict the response to antidepressant treatment. The results suggest that quick and non-invasive behavioral tests may have substantial clinical value in predicting antidepressant treatment response.
PSYCHOLOGICAL MEDICINE
(2022)
Article
Clinical Neurology
Vasily A. Vakorin, Dragos A. Nita, Eric T. Payne, Kristin L. McBain, Helena Frndova, Cristina Go, Urs Ribary, Nicholas S. Abend, William B. Gallentine, Kendall B. Nash, James S. Hutchison, Christopher S. Parshuram, O. Carter Snead, Ilse E. C. W. van Straaten, Cornelis J. Stam, Sam M. Doesburg, Cecil D. Hahn
Summary: The computational features of the first few minutes of EEG recording can be used to estimate the risk of acute seizures in comatose critically-ill children. Children who developed acute seizures showed higher spectral power in the theta frequency range, and distinct patterns of inter-regional connectivity. Future studies could incorporate these features into a decision support system for optimizing seizure management in comatose children.
CLINICAL NEUROPHYSIOLOGY
(2021)
Review
Mathematical & Computational Biology
Leon Stefanovski, Jil Mona Meier, Roopa Kalsank Pai, Paul Triebkorn, Tristram Lett, Leon Martin, Konstantin Buelau, Martin Hofmann-Apitius, Ana Solodkin, Anthony Randal McIntosh, Petra Ritter
Summary: Despite the rapid advancement in neuroscience, Alzheimer's Disease (AD) remains a significant challenge. There is currently a lack of disease-modifying treatments for AD, and our understanding of the disease mechanism is still incomplete.
FRONTIERS IN NEUROINFORMATICS
(2021)
Article
Neurosciences
Lucas Arbabyazd, Kelly Shen, Zheng Wang, Martin Hofmann-Apitius, Petra Ritter, Anthony R. McIntosh, Demian Battaglia, Viktor Jirsa
Summary: In this study, the issue of missing connectivity features in large neuroimaging datasets is addressed by proposing strategies based on computational whole-brain network modeling. By demonstrating the feasibility of virtual data completion and showing the success of machine learning algorithms trained on virtual connectomes, the study opens the way to generating virtual connectomic datasets with realistic surrogate connectivity matrices.
Article
Neurosciences
Phillip R. Johnston, Claude Alain, Anthony R. McIntosh
Summary: The brain's ability to extract information from multiple sensory channels is crucial to perception and effective engagement with the environment, but the individual differences observed in multisensory processing lack mechanistic explanation. Researchers have found that individuals with more effective multisensory processing exhibit a higher degree of shared information among distributed neural populations while engaged in a multisensory task, representing more effective coordination of information among regions.
JOURNAL OF COGNITIVE NEUROSCIENCE
(2022)
Article
Multidisciplinary Sciences
Kelly Shen, Alison McFadden, Anthony R. McIntosh
Summary: The study found unique time-scale-dependent differences in multiscale entropy (MSE) of brain signals among different neurological disorder patient groups. Furthermore, MSE was able to differentiate individuals with non-brain comorbidities, indicating its sensitivity to brain signal changes caused by metabolic and other non-brain disorders. These findings suggest that brain signal complexity may provide complementary information to spectral power and hold promise for clinical biomarker development.
SCIENTIFIC REPORTS
(2021)
Article
Neurosciences
Tyler Good, Michael Schirner, Kelly Shen, Petra Ritter, Pratik Mukherjee, Brian Levine, Anthony Randal McIntosh
Summary: This study uses large-scale brain network modeling to investigate the effects of microscale and macroscale changes on cognitive impairments in traumatic brain injury (TBI) patients. The results show that TBI patients with acute intracranial lesions have lower cortical regional inhibitory connection strengths, and these strengths are correlated with symptoms and cognitive performance at a six-month follow-up. Importantly, even patients without acute lesions show clinical relevance of regional inhibitory connection strengths.
Article
Psychology, Multidisciplinary
Philippe Verduyn, Nino Gugushvili, Ethan Kross
Summary: Research shows that the impact of social networking sites on well-being depends on how users utilize them, with active engagement benefiting well-being and passive consumption being detrimental. However, the traditional active-passive model may not fully capture this relationship. The extended active-passive model refines the original model by decomposing active and passive use, as well as considering user characteristics, offering a nuanced understanding of the link between SNS use and well-being.
CURRENT DIRECTIONS IN PSYCHOLOGICAL SCIENCE
(2022)
Article
Neurosciences
Alexandria D. Samson, Kelly Shen, Cheryl L. Grady, Anthony R. McIntosh
Summary: This study explored the prevalence of seven established MCI risk categories among older adults with and without MCI. The results showed that neuropsychological risk categories had the largest differences between groups, and age, gender, and education were identified as important risk factors for MCI. Additionally, CSF tau levels were correlated with ApoE4 carrier status, age, and a decrease in daily activities.
EUROPEAN JOURNAL OF NEUROSCIENCE
(2022)
Article
Neurosciences
Erin Gibson, Nancy J. Lobaugh, Steve Joordens, Anthony R. McIntosh
Summary: The ongoing activity of neurons in the brain is highly variable and may play a significant role in cognitive function. This study investigated the variability and strength of EEG activity in younger adults during cognitive skill learning. The results showed that variability in EEG activity was more sensitive to individual differences, while changes in the strength of EEG activity reflected task-driven changes. The variability of EEG activity was also found to be related to stable indicators of subject identity rather than dynamic indicators of subject performance.
Article
Psychology, Clinical
Kristen P. Lindgren, Scott A. Baldwin, Kirsten P. Peterson, Jason J. Ramirez, Bethany A. Teachman, Ethan Kross, Reinout W. Wiers, Clayton Neighbors
Summary: Many college students naturally reduce hazardous drinking after graduation, and their drinking identity may function as a marker rather than a mechanism, changing along with the changes in hazardous drinking behavior.
CLINICAL PSYCHOLOGICAL SCIENCE
(2023)
Article
Medical Informatics
Haoyang Yan, Stephanie K. Kukora, Kenneth Pituch, Patricia J. Deldin, Cynthia Arslanian-Engoren, Brian J. Zikmund-Fisher
Summary: By interviewing parents with tracheostomy decision-making experience, we developed an intervention with peer parent narratives to help parents anticipate and prepare for future challenges. The user-centered design process allowed us to incorporate parental perspectives and tailor the intervention to meet their expectations.
BMC MEDICAL INFORMATICS AND DECISION MAKING
(2022)
Article
Mathematical & Computational Biology
Noah Frazier-Logue, Justin Wang, Zheng Wang, Devin Sodums, Anisha Khosla, Alexandria D. Samson, Anthony R. McIntosh, Kelly Shen
Summary: TheVirtualBrain is an open-source platform for large-scale network modeling that can be personalized to individuals using various neuroimaging modalities. The use of growing neuroimaging data sharing initiatives presents an opportunity to create large and heterogeneous sets of dynamic network models to improve our understanding of individual differences in network dynamics and their impact on brain health. In this paper, the authors introduce TheVirtualBrain-UK Biobank pipeline, a robust and automated brain image processing solution that generates connectome-based modeling inputs compatible with TheVirtualBrain. The pipeline has been tested on various datasets and is able to handle morphological changes associated with aging and dementia.
FRONTIERS IN NEUROINFORMATICS
(2022)
Article
Clinical Neurology
Paul Triebkorn, Leon Stefanovski, Kiret Dhindsa, Margarita-Arimatea Diaz-cortes, Patrik Bey, Konstantin Bulau, Roopa Pai, Andreas Spiegler, Ana Solodkin, Viktor Jirsa, Anthony Randal McIntosh, Petra Ritter
Summary: Computational brain network modeling using The Virtual Brain (TVB) simulation platform, combined with machine learning and multi-modal neuroimaging, can reveal mechanisms and improve diagnostics in Alzheimer's disease (AD). This study enhances whole-brain simulation by linking local amyloid beta (Aβ) positron emission tomography (PET) with altered excitability, and demonstrates improved classification accuracy when combining empirical neuroimaging features and simulated local field potentials (LFPs).
ALZHEIMERS & DEMENTIA-TRANSLATIONAL RESEARCH & CLINICAL INTERVENTIONS
(2022)
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.
