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
Biology
Adrian Ponce-Alvarez, Morten L. Kringelbach, Gustavo Deco
Summary: Human fMRI and dMRI data were used to test the phenomenological renormalization group (PRG) method and found that the scale invariance of rs-fMRI activity may emerge from criticality and exponentially decaying connectivity between brain regions.
COMMUNICATIONS BIOLOGY
(2023)
Article
Neurosciences
Peishan Dai, Xiaoyan Zhou, Yilin Ou, Tong Xiong, Jinlong Zhang, Zailiang Chen, Beiji Zou, Xin Wei, Ying Wu, Manyi Xiao
Summary: The study investigated the altered effective connectivity (EC) in children and young adults with amblyopia, showing significant impairments in the EC network of amblyopia patients, which may have a stronger correlation with feedback pathways.
FRONTIERS IN NEUROSCIENCE
(2021)
Article
Neurosciences
Serafeim Loukas, Lara Lordier, Djalel-Eddine Meskaldji, Manuela Filippa, Joana Sa de Almeida, Dimitri Van de Ville, Petra S. Hueppi
Summary: Research indicates that even during the newborn period, familiar music and unfamiliar music are processed differently by the brain. After music listening, functional connectivity between brain regions in all newborns is modulated. Premature infants exposed to music experience enhanced functional connectivity between brain regions after listening to music.
HUMAN BRAIN MAPPING
(2022)
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
Behavioral Sciences
Takashi Itahashi, Neda Kosibaty, Ryu-Ichiro Hashimoto, Yuta Y. Aoki
Summary: Better life satisfaction can be predicted from intrinsic functional connectivity, as shown by using resting-state functional magnetic resonance imaging data. The model successfully predicted life satisfaction levels in young adults and contributed towards identifying the neural basis of life satisfaction.
BRAIN AND BEHAVIOR
(2021)
Article
Neurosciences
E. Roger, L. Rodrigues De Almeida, H. Loevenbruck, M. Perrone-Bertolott, E. Cousin, J. L. Schwartz, P. Perrier, M. Dohen, A. Vilain, P. Baraduc, S. Achard, M. Baciu
Summary: Language processing is a complex function that combines linguistic operations and non-linguistic processes, requiring a specialized neural network. Studying brain systems at rest and task-related functional connectivity provides insights into how information is processed in different cognitive states. By establishing a task-based connectivity atlas, distinct language functions and functional connectivity of brain regions can be identified.
Article
Chemistry, Analytical
Cemre Candemir
Summary: Spatial smoothing is a preprocessing step that improves the quality of neuroimaging data by reducing noise and artifacts. However, selecting the right size for smoothing kernel can be challenging as it can lead to undesired changes in final images and functional connectivity networks. This study investigates the impact of kernel size on functional connectivity networks and network parameters in whole-brain resting-state and task-based fMRI analyses of healthy adults.
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
Psychiatry
Xiaoyi Sun, Jin Liu, Qing Ma, Jia Duan, Xindi Wang, Yuehua Xu, Zhilei Xu, Ke Xu, Fei Wang, Yanqing Tang, Yong He, Mingrui Xia
Summary: The study examined the intersubject variability of the functional connectome in schizophrenia patients and healthy controls based on resting-state fMRI data. The schizophrenia group showed higher IVFC in sensorimotor, visual, auditory, and subcortical regions compared to healthy controls, and these alterations were associated with clinical variables. Alterations in the sensorimotor, auditory, and subcortical cortices were specific to schizophrenia, suggesting potential implications for individualized clinical diagnosis and treatment.
SCHIZOPHRENIA BULLETIN
(2021)
Review
Neurosciences
Hongzan Sun, Yong He, Heqi Cao
Summary: NSFC has been funding various research programs related to fMRI over the past two decades, with increasing support particularly in the General Program and Key Program. Leading research institutes in economically developed provinces and municipalities received the most support and established close collaboration relationships. Notable achievements in data analysis methods, brain connectomes, and computational platforms as well as their applications in brain disorders were reviewed.
CNS NEUROSCIENCE & THERAPEUTICS
(2021)
Article
Immunology
Sharmila Thippabhotla, Babatunde Adeyemo, Sarah A. Cooley, June Roman, Nicholas Metcalf, Anna Boerwinkle, Julie Wisch, Robert Paul, Beau M. Ances
Summary: This study examined the differences in resting state functional connectivity (RSFC) between persons with and without HIV. The results showed that HIV status did not affect RSFC. In persons with HIV, there were no differences in RSFC based on detectable viral load or cognitive impairment.
JOURNAL OF INFECTIOUS DISEASES
(2023)
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
Psychiatry
Ling-ling Wang, Xiaoqi Sun, Chui-De Chiu, Patrick W. L. Leung, Raymond C. K. Chan, Suzanne H. W. So
Summary: The research found impaired cortico-striatal connectivity in individuals with a high level of schizotypy, but improvements over time. The connectivity between the dorsal striatum and the insula may serve as a marker for temporal changes in positive schizotypy.
ASIAN JOURNAL OF PSYCHIATRY
(2021)
Article
Neurosciences
Zhi Yang, Xi-Nian Zuo, Katie L. McMahon, R. Cameron Craddock, Clare Kelly, Greig I. de Zubicaray, Ian Hickie, Peter A. Bandettini, F. Xavier Castellanos, Michael P. Milham, Margaret J. Wright
Article
Neurosciences
Alexander Opitz, Michael D. Fox, R. Cameron Craddock, Stan Colcombe, Michael P. Milham
Review
Biology
R. Cameron Craddock, Daniel S. Margulies, Pierre Bellec, B. Nolan Nichols, Sarael Alcauter, Fernando A. Barrios, Yves Burnod, Christopher J. Cannistraci, Julien Cohen-Adad, Benjamin De Leener, Sebastien Dery, Jonathan Downar, Katharine Dunlop, Alexandre R. Franco, Caroline Seligman Froehlich, Andrew J. Gerber, Satrajit S. Ghosh, Thomas J. Grabowski, Sean Hill, Anibal Solon Heinsfeld, R. Matthew Hutchison, Prantik Kundu, Angela R. Laird, Sook-Lei Liew, Daniel J. Lurie, Donald G. McLaren, Felipe Meneguzzi, Maarten Mennes, Salma Mesmoudi, David O'Connor, Erick H. Pasaye, Scott Peltier, Jean-Baptiste Poline, Gautam Prasad, Ramon Fraga Pereira, Pierre-Olivier Quirion, Ariel Rokem, Ziad S. Saad, Yonggang Shi, Stephen C. Strother, Roberto Toro, Lucina Q. Uddin, John D. Van Horn, John W. Van Meter, Robert C. Welsh, Ting Xu
Article
Neurosciences
Pierre Bellec, Carlton Chu, Francois Chouinard-Decorte, Yassine Benhajali, Daniel S. Margulies, R. Cameron Craddock
Article
Neurosciences
Franziskus Liem, Gael Varoquaux, Jana Kynast, Frauke Beyer, Shahrzad Kharabian Masouleh, Julia M. Huntenburg, Leonie Lampe, Mehdi Rahim, Alexandre Abraham, R. Cameron Craddock, Steffi Riedel-Heller, Tobias Luck, Markus Loeffler, Matthias L. Schroeter, Anja Veronica Witte, Arno Villringer, Daniel S. Margulies
Article
Biochemical Research Methods
Krzysztof J. Gorgolewski, Fidel Alfaro-Almagro, Tibor Auer, Pierre Bellec, Mihai Capota, M. Mallar Chakravarty, Nathan W. Churchill, Alexander Li Cohen, R. Cameron Craddock, Gabriel A. Devenyi, Anders Eklund, Oscar Esteban, Guillaume Flandin, Satrajit S. Ghosh, J. Swaroop Guntupalli, Mark Jenkinson, Anisha Keshavan, Gregory Kiar, Franziskus Liem, Pradeep Reddy Raamana, David Raffelt, Christopher J. Steele, Pierre-Olivier Quirion, Robert E. Smith, Stephen C. Strother, Gael Varoquaux, Yida Wang, Tal Yarkoni, Russell A. Poldrack
PLOS COMPUTATIONAL BIOLOGY
(2017)
Article
Neurosciences
Lei Ai, R. Cameron Craddock, Nim Tottenham, Jonathan P. Dyke, Ryan Lim, Stanley Colcombe, Michael Milham, Alexandre R. Franco
Summary: This study compared the MPRAGE and MPRAGE+PMC MRI structural sequences and found that they exhibit high inter-sequence reliability in images with low head motion. The MPRAGE+PMC sequence is recommended for studies targeting hyperkinetic populations due to its robustness to head motion.
Editorial Material
Neurosciences
Remi Gau, Stephanie Noble, Katja Heuer, Katherine L. Bottenhorn, Isil P. Bilgin, Yu-Fang Yang, Julia M. Huntenburg, Johanna M. M. Bayer, Richard A. I. Bethlehem, Shawn A. Rhoads, Christoph Vogelbacher, Valentina Borghesani, Elizabeth Levitis, Hao-Ting Wang, Sofie Van den Bossche, Xenia Kobeleva, Jon Haitz Legarreta, Samuel Guay, Selim Melvin Atay, Gael P. Varoquaux, Dorien C. Huijser, Malin S. Sandstrom, Peer Herholz, Samuel A. Nastase, AmanPreet Badhwar, Guillaume Dumas, Simon Schwab, Stefano Moia, Michael Dayan, Yasmine Bassil, Paula P. Brooks, Matteo Mancini, James M. Shine, David O'Connor, Xihe Xie, Davide Poggiali, Patrick Friedrich, Anibal S. Heinsfeld, Lydia Riedl, Roberto Toro, Cesar Caballero-Gaudes, Anders Eklund, Kelly G. Garner, Christopher R. Nolan, Damion V. Demeter, Fernando A. Barrios, Junaid S. Merchant, Elizabeth A. McDevitt, Robert Oostenveld, R. Cameron Craddock, Ariel Rokem, Andrew Doyle, Satrajit S. Ghosh, Aki Nikolaidis, Olivia W. Stanley, Eneko Urunuela
Summary: Brainhack is an innovative meeting format that promotes scientific collaboration and education in an open, inclusive environment, complementing conventional formats to augment scientific progress.
Article
Neurosciences
Xindi Wang, Xin-Hui Li, Jae Wook Cho, Brian E. Russ, Nanditha Rajamani, Alisa Omelchenko, Lei Ai, Annachiara Korchmaros, Stephen Sawiak, R. Austin Benn, Pamela Garcia-Saldivar, Zheng Wang, Ned H. Kalin, Charles E. Schroeder, R. Cameron Craddock, Andrew S. Fox, Alan C. Evans, Adam Messinger, Michael P. Milham, Ting Xu
Summary: Brain extraction, a crucial step in neuroimaging pipelines, is often challenging when applied to non-human primate (NHP) data. Recent advancements in deep learning have shown promising results in improving the accuracy of brain extraction in NHP imaging. By utilizing a transfer-learning framework and leveraging a large human imaging dataset, we were able to enhance the performance and generalizability of the model across multiple NHP research sites in the PRIME-DE consortium, outperforming traditional brain extraction routines. The publicly available model, code, and dataset repository provide a valuable resource for the neuroimaging community.
Article
Multidisciplinary Sciences
John Virostko, Richard C. Craddock, Jonathan M. Williams, Taylor M. Triolo, Melissa A. Hilmes, Hakmook Kang, Liping Du, Jordan J. Wright, Mara Kinney, Jeffrey H. Maki, Milica Medved, Michaela Waibel, Thomas W. H. Kay, Helen E. Thomas, Siri Atma W. Greeley, Andrea K. Steck, Daniel J. Moore, Alvin C. Powers
Summary: A standardized MRI protocol for pancreas imaging was developed, showing reproducibility of pancreas size, surface area to volume ratio, diffusion, and longitudinal relaxation time measurements. This allows for quantitative MRI of the pancreas to be compared across multiple locations in clinical trials for individuals with type 1 or type 2 diabetes. Non-standardized image processing led to greater variation in MRI measurements.
Article
Biochemical Research Methods
Eric W. Bridgeford, Shangsi Wang, Zeyi Wang, Ting Xu, Cameron Craddock, Jayanta Dey, Gregory Kiar, William Gray-Roncal, Carlo Colantuoni, Christopher Douville, Stephanie Noble, Carey E. Priebe, Brian Caffo, Michael Milham, Xi-Nian Zuo, Joshua T. Vogelstein, Jian Ma, Blake A. Richards, Jian Ma, Blake A. Richards, Jian Ma, Blake A. Richards
Summary: This article emphasizes the importance of replicability in scientific research and the inadequacy of existing replicability statistics. It introduces a new statistic called discriminability and proves that optimizing discriminability can improve the performance of subsequent inference tasks. The suggestion is to design experiments and analyses to optimize discriminability as a crucial step in solving the replicability crisis and mitigating accidental measurement error.
PLOS COMPUTATIONAL BIOLOGY
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Raphael Roger, Melissa A. Hilmes, Jonathan M. Williams, Daniel J. Moore, Alvin C. Powers, R. Cameron Craddock, John Virostko
Summary: Pancreas volume is reduced in individuals with diabetes and those at risk for developing type 1 diabetes. This study developed a deep learning algorithm for automated pancreas volume measurement in individuals with diabetes. Training the algorithm on multiple cohorts showed high overlap and excellent correlation with manual segmentations.
BMC MEDICAL IMAGING
(2022)
Article
Clinical Neurology
Martin Domin, Brenton Hordacre, Pavel Hok, Lara A. Boyd, Adriana B. Conforto, Justin W. Andrushko, Michael R. Borich, Richard C. Craddock, Miranda R. Donnelly, Adrienne N. Dula, Steven J. Warach, Steven A. Kautz, Bethany P. Lo, Christian Schranz, Na Jin Seo, Shraddha Srivastava, Kristin A. Wong, Artemis Zavaliangos-Petropulu, Paul M. Thompson, Sook-Lei Liew, Martin Lotze
Summary: The study found that stroke patients with severe CST damage rely on residual pathways for better upper limb function recovery.
Article
Clinical Neurology
Sook-Lei Liew, Artemis Zavaliangos-Petropulu, Nicolas Schweighofer, Neda Jahanshad, Catherine E. Lang, Keith R. Lohse, Nerisa Banaj, Giuseppe Barisano, Lee A. Baugh, Anup K. Bhattacharya, Bavrina Bigjahan, Michael R. Borich, Lara A. Boyd, Amy Brodtmann, Cathrin M. Buetefisch, Winston D. Byblow, Jessica M. Cassidy, Charalambos C. Charalambous, Valentina Ciullo, Adriana B. Conforto, Richard C. Craddock, Adrienne N. Dula, Natalia Egorova, Wuwei Feng, Kelene A. Fercho, Chris M. Gregory, Colleen A. Hanlon, Kathryn S. Hayward, Jess A. Holguin, Brenton Hordacre, Darryl H. Hwang, Steven A. Kautz, Mohamed Salah Khlif, Bokkyu Kim, Hosung Kim, Amy Kuceyeski, Bethany Lo, Jingchun Liu, David Lin, Martin Lotze, Bradley J. MacIntosh, John L. Margetis, Feroze B. Mohamed, Jan Egil Nordvik, Matthew A. Petoe, Fabrizio Piras, Sharmila Raju, Ander Ramos-Murguialday, Kate P. Revill, Pamela Roberts, Andrew D. Robertson, Heidi M. Schambra, Na Jin Seo, Mark S. Shiroishi, Surjo R. Soekadar, Gianfranco Spalletta, Cathy M. Stinear, Anisha Suri, Wai Kwong Tang, Gregory T. Thielman, Vincent N. Thijs, Daniela Vecchio, Nick S. Ward, Lars T. Westlye, Carolee J. Winstein, George F. Wittenberg, Kristin A. Wong, Chunshui Yu, Steven L. Wolf, Steven C. Cramer, Paul M. Thompson
Summary: The study conducted by Liew et al. examined 828 stroke patients worldwide and found novel associations between post-stroke sensorimotor behavior and specific subcortical nuclei. The integrity of spared brain areas plays a crucial role in recovery from stroke-induced sensorimotor impairments. Reduced volumes of spared deep grey matter structures were associated with worse sensorimotor outcomes, highlighting the importance of cortico-thalamo-striatal circuits in post-stroke rehabilitation.
BRAIN COMMUNICATIONS
(2021)
Review
Psychology, Clinical
Michael P. Milham, R. Cameron Craddock, Arno Klein
DEPRESSION AND ANXIETY
(2017)
