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
Lei Zhang, Guanya Li, Yang Hu, Wenchao Zhang, Jia Wang, Weibin Ji, Fukun Jiang, Yaqi Zhang, Feifei Wu, Karen M. von Deneen, Shijun Duan, Guangbin Cui, Yi Zhang, Yongzhan Nie
Summary: This study found that patients with functional constipation showed altered functional connectivity within and between resting-state networks. These changes in brain connectivity were associated with constipation symptoms and altered emotions.
NEUROLOGICAL SCIENCES
(2022)
Article
Neurosciences
Han Jin, Ri-Bo Chen, Yu-Lin Zhong, Ping-Hong Lai, Xin Huang
Summary: This study revealed that patients with comitant exotropia have abnormal brain networks. These findings provide important insights into the neural mechanisms of eye movements and stereoscopic vision dysfunction in patients with comitant exotropia.
FRONTIERS IN NEUROSCIENCE
(2022)
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
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
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
Luoyao Pang, Huidi Li, Quanying Liu, Yue-Jia Luo, Dean Mobbs, Haiyan Wu
Summary: Motivated dishonesty is a common social behavior that varies among individuals. This study explores the relationship between brain networks and dishonesty using resting-state functional magnetic resonance imaging (rsfMRI), and demonstrates the ability to predict dishonest behavior through a model based on functional connectivity.
Article
Neuroimaging
Uttam Kumar, Amit Arya, Vivek Agarwal
Summary: This study utilized rsfMRI to investigate the functional connectivity in children with ADHD, revealing stronger and more dispersed connectivity within the DMN and other neural networks in comparison to typically developing children.
BRAIN IMAGING AND BEHAVIOR
(2021)
Article
Neurosciences
Yongfa Zhang, Fei Wang, Jie Sui
Summary: Recent research supports a fundamental self hypothesis, suggesting that the self is a baseline function of the brain that regulates cognitive processing and behavior. Understanding this hypothesis can help identify the emergence of self-biased behaviors and predict the influence of brain signals at rest on such behaviors.
Article
Neurosciences
Jeffrey M. Kenzie, Deepthi Rajashekar, Bradley G. Goodyear, Sean P. Dukelow
Summary: Around 50% of stroke patients have deficits in proprioception, but our understanding of the neurological mechanisms behind these deficits is limited. This study used resting-state functional magnetic resonance imaging (fMRI) to investigate changes in functional brain networks associated with proprioception deficits in stroke patients. The results showed reduced connectivity in specific brain regions, including the supplementary motor area and the supramarginal gyrus, in stroke patients compared to healthy controls. Functional connectivity of these regions, as well as the primary somatosensory cortex and the parietal opercular area, was significantly associated with proprioceptive function. The parietal lobe of the lesioned hemisphere was identified as an important node for proprioception after stroke, and evaluating the functional connectivity of this region could help predict recovery. The study also identified potential targets for therapeutic neurostimulation to aid in stroke recovery.
HUMAN BRAIN MAPPING
(2023)
Article
Neurosciences
Shachar Gal, Yael Coldham, Niv Tik, Michal Bernstein-Eliav, Ido Tavor
Summary: The search for an ideal approach to investigate functional connections in the human brain is a challenge for neuroscience. Recent studies have found that using naturalistic stimuli to collect functional connectivity data predicts cognitive and emotional scores more accurately than using resting-state data. Furthermore, activation maps predicted using naturalistic stimuli are better predictors of individual intelligence scores than those predicted using resting-state data.
Article
Neurosciences
Andria J. Farrens, Shahabeddin Vahdat, Fabrizio Sergi
Summary: Dynamic adaptation is the process of adjusting motor actions to changes in task dynamics. Adapted motor plans are consolidated into memories that contribute to better performance on re-exposure. This study used functional magnetic resonance imaging (fMRI) to investigate resting state functional connectivity (rsFC) specific to dynamic adaptation of wrist movements and subsequent memory formation.
JOURNAL OF NEUROSCIENCE
(2023)
Article
Multidisciplinary Sciences
Won Beom Jung, Haiyan Jiang, Soohyun Lee, Seong-Gi Kim
Summary: In order to advance fMRI-based brain science, it is important to analyze fMRI activity at the circuit level. This study combines whole-brain fMRI with neuronal silencing to dissect the responses and circuits of the somatosensory network.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
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, 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
Psychology, Clinical
Wisteria Deng, Jean Addington, Carrie E. Bearden, Kristin S. Cadenhead, Barbara A. Cornblatt, Daniel H. Mathalon, Diana O. Perkins, Larry J. Seidman, Ming T. Tsuang, Scott W. Woods, Elaine F. Walker, Tyrone D. Cannon
Summary: This study found that there are different covariant trajectories of social anxiety and positive symptoms over time in individuals at clinical high-risk for psychosis. One subgroup showed sustained social anxiety despite moderate recovery in positive symptoms, while the other two subgroups showed recovery in both social anxiety and positive symptoms. The subgroup with sustained social anxiety had poorer long-term functional outcomes and higher levels of genetic and environmental risk factors for psychosis.
PSYCHOLOGICAL MEDICINE
(2023)
Article
Computer Science, Interdisciplinary Applications
Harshvardhan Gazula, Kelly Rootes-Murdy, Bharath Holla, Sunitha Basodi, Zuo Zhang, Eric Verner, Ross Kelly, Pratima Murthy, Amit Chakrabarti, Debasish Basu, Subodh Bhagyalakshmi Nanjayya, Rajkumar Lenin Singh, Roshan Lourembam Singh, Kartik Kalyanram, Kamakshi Kartik, Kumaran Kalyanaraman, Krishnaveni Ghattu, Rebecca Kuriyan, Sunita Simon Kurpad, Gareth J. Barker, Rose Dawn Bharath, Sylvane Desrivieres, Meera Purushottam, Dimitri Papadopoulos Orfanos, Eesha Sharma, Matthew Hickman, Mireille Toledano, Nilakshi Vaidya, Tobias Banaschewski, Arun L. W. Bokde, Herta Flor, Antoine Grigis, Hugh Garavan, Penny Gowland, Andreas Heinz, Rudiger Bruhl, Jean-Luc Martinot, Marie-Laure Paillere Martinot, Eric Artiges, Frauke Nees, Tomas Paus, Luise Poustka, Juliane H. Frohner, Lauren Robinson, Michael N. Smolka, Henrik Walter, Jeanne Winterer, Robert Whelan, Jessica A. Turner, Anand D. Sarwate, Sergey M. Plis, Vivek Benegal, Gunter Schumann, Vince D. Calhoun
Summary: With the growth of decentralized/federated analysis approaches in neuroimaging, the opportunities to study brain disorders using data from multiple sites has grown multi-fold. One such initiative is the Neuromark, a fully automated spatially constrained independent component analysis (ICA) that is used to link brain network abnormalities among different datasets, studies, and disorders while leveraging subject-specific networks.
Article
Neurosciences
Noah Lewis, Robyn Miller, Harshvardhan Gazula, Vince Calhoun
Summary: Deep learning is effective for classifying biological sex based on fMRI, but research on the most relevant brain features for this classification is lacking. Model interpretability is important for understanding deep learning models, but little work has been done on the relationship between temporal dimension of fMRI signals and sex classification. In this study, a methodology is provided to address underspecification and instability in feature explanation models, and sex differences in functional brain networks are explored using intrinsic connectivity networks.
Article
Neurosciences
Marlena Duda, Armin Iraji, Judith M. Ford, Kelvin O. Lim, Daniel H. Mathalon, Bryon A. Mueller, Steven G. Potkin, Adrian Preda, Theo G. M. Van Erp, Vince D. Calhoun
Summary: By using spatially constrained independent component analysis (scICA), this study found that rsfMRI scans of just 2-5 minutes can provide good clinical utility without significant loss of individual functional network connectivity (FNC) information from longer scan lengths.
HUMAN BRAIN MAPPING
(2023)
Article
Engineering, Biomedical
Anton Orlichenko, Gang Qu, Gemeng Zhang, Binish Patel, Tony W. W. Wilson, Julia M. M. Stephen, Vince D. D. Calhoun, Yu-Ping Wang
Summary: In this study, we developed an interpretable multivariate classification/regression algorithm called LatSim, which is suitable for small sample size and high feature dimension datasets. Results showed that LatSim achieved higher predictive accuracy compared to other methods, and identified functional brain networks associated with brain age, sex, and intelligence prediction. This research provides new insights for algorithm design and neuroscience research.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
(2023)
Correction
Biochemistry & Molecular Biology
Sean R. McWhinney, Katharina Brosch, Vince D. Calhoun, Benedicto Crespo-Facorro, Nicolas A. Crossley, Udo Dannlowski, Erin Dickie, Lorielle M. F. Dietze, Gary Donohoe, Stefan Du Plessis, Stefan Ehrlich, Robin Emsley, Petra Furstova, David C. Glahn, Alfonso Gonzalez-Valderrama, Dominik Grotegerd, Laurena Holleran, Tilo T. J. Kircher, Pavel Knytl, Marian Kolenic, Rebekka Lencer, Igor Nenadic, Nils Opel, Julia-Katharina Pfarr, Amanda L. Rodrigue, Kelly Rootes-Murdy, Alex J. Ross, Kang Sim, Antonin Skoch, Filip Spaniel, Frederike Stein, Patrik Svancer, Diana Tordesillas-Gutierrez, Juan Undurraga, Javier Vaquez-Bourgon, Aristotle Voineskos, Esther Walton, Thomas W. Weickert, Cynthia Shannon Weickert, Paul M. Thompson, Theo G. M. van Erp, Jessica A. Turner, Tomas Hajek
MOLECULAR PSYCHIATRY
(2023)
Review
Biochemistry & Molecular Biology
Esther Walton, Vilte Baltramonaityte, Vince Calhoun, Bastiaan T. Heijmans, Paul M. Thompson, Charlotte A. M. Cecil
Summary: Epigenetic mechanisms, such as DNA methylation (DNAm), have been studied as potential biomarkers and mechanisms underlying brain-based disorders. However, there is little understanding of the relationship between DNAm and individual differences in the brain, especially during development. This systematic review examines the field of Neuroimaging Epigenetics and finds inconsistent findings regarding DNAm-brain associations and a lack of replication or meta-analysis. The authors propose three recommendations to advance the field, including a focus on development, large prospective studies, and interdisciplinary collaboration.
MOLECULAR PSYCHIATRY
(2023)
Article
Pharmacology & Pharmacy
Bryan Shapiro, Eric Kramer, Dina Khoury, Adrian Preda
Summary: This study investigated the prevalence and severity of common withdrawal symptoms after chronic antidepressant treatment. The symptoms of dizziness, brain zaps, irritability/agitation, and anxiety/nervousness showed the largest increase in severity during withdrawal. Almost all participants reported worsening of at least one of these four symptoms. Incorporating these four core symptoms into a screening test may be useful in ruling out antidepressant withdrawal.
PHARMACOPSYCHIATRY
(2023)
Article
Clinical Neurology
Eun-jin Cheon, Alie G. Male, Bingchen Gao, Bhim M. Adhikari, Jesse T. Edmond, Stephanie M. Hare, Aysenil Belger, Steven G. Potkin, Juan R. Bustillo, Daniel H. Mathalon, Judith M. Ford, Kelvin O. Lim, Bryon A. Mueller, Adrian Preda, Daniel O'Leary, Gregory P. Strauss, Anthony O. Ahmed, Paul M. Thompson, Neda Jahanshad, Peter Kochunov, Vince D. Calhoun, Jessica A. Turner, Theo G. M. van Erpa
Summary: This study examined the association between resting-state amplitude of low frequency fluctuations (ALFF) and negative symptoms in schizophrenia. It found positive associations between total negative symptom scores and ALFF in temporal and frontal brain regions. Additionally, it found that negative symptom domain scores had stronger associations with regional ALFF compared to total scores, suggesting that domain scores may be better indicators of neural signatures.
PSYCHIATRY RESEARCH-NEUROIMAGING
(2023)
Article
Neurosciences
A. Iraji, Z. Fu, A. Faghiri, M. Duda, J. Chen, S. Rachakonda, T. DeRamus, P. Kochunov, B. M. Adhikari, A. Belger, J. M. Ford, D. H. Mathalon, G. D. Pearlson, S. G. Potkin, A. Preda, J. A. Turner, T. G. M. van Erp, J. R. Bustillo, K. Yang, K. Ishizuka, A. Faria, A. Sawa, K. Hutchison, E. A. Osuch, J. Theberge, C. Abbott, B. A. Mueller, D. Zhi, C. Zhuo, S. Liu, Y. Xu, M. Salman, J. Liu, Y. Du, J. Sui, T. Adali, V. D. Calhoun
Summary: This study identifies replicable multi-spatial-scale canonical intrinsic connectivity network (ICN) templates using rsfMRI data from over 100k individuals through multi-model-order independent component analysis (ICA). The feasibility of estimating subject-specific ICNs via spatially constrained ICA is also studied. The results show that subject-level ICN estimations vary as a function of the ICN itself, the data length, and the spatial resolution. Longer scans may not always be desirable and spatial smoothness should be considered in optimizing data length.
HUMAN BRAIN MAPPING
(2023)
Article
Engineering, Biomedical
Lan Yang, Chen Qiao, Huiyu Zhou, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yuping Wang
Summary: This study proposes an explainable multimodal deep dictionary learning method to uncover the commonality and specificity of different modalities in brain developmental differences. The results show that the proposed model can achieve better reconstruction and identify age-related differences in reoccurring patterns.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
(2023)
Article
Neurosciences
Paul A. Taylor, Richard C. Reynolds, Vince Calhoun, Javier Gonzalez-Castillo, Daniel A. Handwerker, Peter A. Bandettini, Amanda F. Mejia, Gang Chen
Summary: Neuroimaging studies often display only a small fraction of the collected data, which hides important information and leads to issues of selection bias and irreproducibility. Instead, it is suggested to highlight as many results as possible through visualization to improve scientific communication and understanding.
Article
Clinical Neurology
Soichiro Nakahara, Alie G. Male, Jessica A. Turner, Vince D. Calhoun, Kelvin O. Lim, Bryon A. Mueller, Juan R. Bustillo, Daniel S. O'Leary, James Voyvodic, Aysenil Belger, Adrian Preda, Daniel H. Mathalon, Judith M. Ford, Guia Guffanti, Fabio Macciardi, Steven G. Potkin, Theo G. M. Van Erp
Summary: Individuals with schizophrenia show abnormal brain activation during auditory oddball tasks, which is associated with cognitive performance and genetic contributions. This study compares individuals with schizophrenia to healthy volunteers and identifies novel relationships between regional brain activity, cognitive performance, and genetic loci. The findings highlight the importance of continued data sharing and collaborative efforts in schizophrenia research.
PSYCHIATRY RESEARCH-NEUROIMAGING
(2023)
Article
Neuroimaging
Mohammad S. E. Sendi, Elaheh Zendehrouh, Charles A. Ellis, Zening Fu, Jiayu Chen, Robyn L. Miller, Elizabeth C. Mormino, David H. Salat, Vince D. Calhoun
Summary: This study investigated the association between static and dynamic functional network connectivity (FNC) and Alzheimer's disease (AD) genetic risk using a data-driven approach. The results showed that AD genetic risk is related to a weakening of connectivity within the visual sensory network (VSN) and spending more time in a state with reduced VSN connectivity.
NEUROIMAGE-CLINICAL
(2023)