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
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.
Review
Neurosciences
Laurentius Huber (Renzo), Emily S. Finn, Yuhui Chai, Rainer Goebel, Ruediger Stirnberg, Tony Stoecker, Sean Marrett, Kamil Uludag, Seong-Gi Kim, SoHyun Han, Peter A. Bandettini, Benedikt A. Poser
Summary: Recent advances in fMRI technology have enabled researchers to study information processing in the cortical layers more effectively, particularly in terms of connectivity. However, layer-fMRI still faces challenges that require more flexible and precise methods to address. This article describes newly developed acquisition methodologies that can provide more comprehensive data for investigating brain network connections.
PROGRESS IN NEUROBIOLOGY
(2021)
Article
Physics, Multidisciplinary
Yasaman Shahhosseini, Michelle F. Miranda
Summary: This paper provides an overview of the most common methods for estimating and characterizing functional connectivity in fMRI data. It illustrates these methods with example data from the Human Connectome Project, providing insights on implementation details and result interpretations. The aim is to assist researchers new to the field of neuroimaging in estimating and characterizing brain circuitry.
Article
Neurosciences
Sanjay Ghosh, Ashish Raj, Srikantan S. Nagarajan
Summary: This article introduces a computational framework that reconstructs functional connectivity from structural connectivity by identifying a joint subspace of eigenmodes. It is found that a small number of these eigenmodes are sufficient for reconstruction and the proposed algorithm shows competitive performance and better interpretability compared to existing methods.
Article
Neurosciences
Anurima Mummaneni, Omid Kardan, Andrew J. Stier, Taylor A. Chamberlain, Alfred F. Chao, Marc G. Berman, Monica D. Rosenberg
Summary: Sleep is crucial for cognitive functions and inadequate sleep can affect mood and behavior. This study used functional connectivity patterns to predict sleep duration and found that common functional brain networks are associated with sleep duration in both youth and young adults.
HUMAN BRAIN MAPPING
(2023)
Article
Neurosciences
Yicheng Long, Xuan Ouyang, Chaogan Yan, Zhipeng Wu, Xiaojun Huang, Weidan Pu, Hengyi Cao, Zhening Liu, Lena Palaniyappan
Summary: This study investigated the test-retest reliability and demographic-related effects on the temporal clustering coefficient using data from the Human Connectome Project. The results showed moderate test-retest reliability of the temporal clustering coefficient at both global and subnetwork levels. Female subjects had higher temporal clustering coefficient than males, particularly in the default-mode and subcortical regions. The temporal clustering coefficient of the subcortical subnetwork was positively correlated with age in young adults.
HUMAN BRAIN MAPPING
(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
Zhiying Long, Xuanping Liu, Yantong Niu, Huajie Shang, Hui Lu, Junying Zhang, Li Yao
Summary: Dynamic functional connectivity (DFC) analysis is a method used to study the time-varying functional interactions between brain regions. In this study, an alternating HMM (aHMM) method was proposed, which showed better estimation of DFC with improved robustness to noise, parameter number, and sample size compared to the sliding window (SW) method and the standard hidden Markov model (HMM). Analysis of real fMRI data from patients with cerebral small vessel disease (CSVD) revealed that aHMM was able to detect significant differences in connectivity amplitude and fluctuations between patient groups, while HMM and SW failed to do so.
COGNITIVE NEURODYNAMICS
(2022)
Article
Behavioral Sciences
Zhihao Zhu, Hongwei Wang, Hui Bi, Jidong Lv, Xiaotong Zhang, Suhong Wang, Ling Zou
Summary: This study investigates the dynamic changes in brain networks of ADHD patients using resting-state fMRI data. The results show abnormal increases in mean dwell time and fraction of time spent in a specific state for ADHD patients. Correlations between different brain networks are weaker in ADHD patients compared to typically developing children.
BEHAVIOURAL BRAIN RESEARCH
(2023)
Article
Neurosciences
Liangwei Fan, Qi Zhong, Jian Qin, Na Li, Jianpo Su, Ling-Li Zeng, Dewen Hu, Hui Shen
Summary: A new computational method based on dynamic functional connectivity degree (dFCD) was proposed to derive brain parcellations capturing functional homogeneous regions. The method showed better capability in capturing interindividual variability in functional connectivity and predicting individual cognitive performance compared to commonly used brain atlases. The study also emphasized the importance of dFC-driven and voxel-wise functional homogeneous parcellation for network dynamics analyses in neuroscience.
HUMAN BRAIN MAPPING
(2021)
Article
Neurosciences
Zhiying Long, Yuanhang Xu, Wenyan Zou, Yongjie Duan, Li Yao
Summary: The extended NMF method was successfully applied to DFC analysis of both simulated and real resting fMRI data, decomposing the mixed-sign matrix into a positive matrix and a mixed-sign matrix. It outperformed the traditional K-means method in accuracy and sensitivity in extracting brain state patterns and detecting intergroup differences in DFC.
COGNITIVE NEURODYNAMICS
(2023)
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)
Article
Multidisciplinary Sciences
Gokce Sarar, Bhaskar Rao, Thomas Liu
Summary: Shallow feedforward neural networks relying solely on rsfMRI correlation matrices can achieve high accuracy in individual identification within short data segments, and perform well when the total number of data points is large.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Neurosciences
Elijah Agoalikum, Benjamin Klugah-Brown, Hang Yang, Pan Wang, Shruti Varshney, Bochao Niu, Bharat Biswal
Summary: In this study, dynamic functional network connectivity differences in adult, adolescent, and child ADHD were investigated using resting-state functional magnetic resonance imaging data. The findings suggest that there are connectivity differences among the three age groups, providing new insights for future case-control studies and treatment strategies.
FRONTIERS IN HUMAN NEUROSCIENCE
(2021)
Article
Public, Environmental & Occupational Health
Lei Zhang, Jinmei Du, Tingting Chen, Rongrong Sheng, Juncheng Ma, Gongjun Ji, Fengqiong Yu, Jianguo Ye, Dandan Li, Zhenjing Li, Chunyan Zhu, Kai Wang
Summary: This study aimed to assess the impact of COVID-19 on the mental health of Chinese medical students over a 1-year follow-up. Three waves of online research were conducted from February 2, 2020, to February 23, 2021 (T1 = during outbreak, T2 = controlling period, T3 = 1 year after outbreak). The survey included demographic data and self-report questionnaires measuring depressive, anxiety, and stress symptoms. A total of 4002 participants completed all phases of the research. The study found that major, grade level, and gender were significant factors associated with psychological distress caused by the COVID-19 crisis. Importantly, medical knowledge had a protective effect on medical students' psychological distress during the COVID-19 period.
PSYCHOLOGY HEALTH & MEDICINE
(2023)
Article
Psychiatry
Gong-Jun Ji, Andrew Zalesky, Yingru Wang, Kongliang He, Lu Wang, Rongrong Du, Jinmei Sun, Tongjian Bai, Xingui Chen, Yanghua Tian, Chunyan Zhu, Kai Wang
Summary: The study found highly heterogeneous personalized brain atrophy maps among schizophrenia patients. Results indicated that the functional connectivity of personalized atrophy maps with rTMS targets was significantly associated with symptom outcomes of schizophrenia patients. This suggests that normative modeling can help in mapping the personalized atrophy network associated with treatment outcomes of patients with schizophrenia.
SCHIZOPHRENIA BULLETIN
(2023)
Article
Neurosciences
Gong-Jun Ji, Jiao Li, Wei Liao, Yingru Wang, Lei Zhang, Tongjian Bai, Ting Zhang, Wen Xie, Kongliang He, Chuyan Zhu, Juergen Dukart, Chris Baeken, Yanghua Tian, Kai Wang
Summary: Electroconvulsive therapy (ECT) is effective for treating major depressive disorder (MDD) and induces changes in brain structure and function. A study found that the cortical thickness changes following ECT were associated with neuroplasticity-related genes and dopamine receptor density.
MOLECULAR NEUROBIOLOGY
(2023)
Article
Neurosciences
Geraldine Rodriguez-Nieto, Oron Levin, Lize Hermans, Akila Weerasekera, Anca Croitor Sava, Astrid Haghebaert, Astrid Huybrechts, Koen Cuypers, Dante Mantini, Uwe Himmelreich, Stephan P. Swinnen
Summary: Aging is associated with structural and metabolic changes in the brain. Previous research has focused on individual brain regions, but the relationship among metabolites across the brain has been less studied. Using 1H-MRS, this study investigated the relationship among metabolite concentrations in different brain regions in young and older adults. The results showed age-related differences in metabolite concentrations and revealed associative patterns between metabolites across brain regions, which differed between age groups.
Article
Computer Science, Information Systems
Renping Yu, Han Zhang, Xuehai Wu, Xuan Fei, Qing Yang, Zhiwei Ma, Zengxin Qi, Di Zang, Weijun Tang, Ying Mao, Dinggang Shen
Summary: This study aims to predict the outcome of unconscious acquired brain injury patients and differentiate consciousness levels using brain functional imaging and machine learning techniques. The researchers construct functional networks based on resting-state fMRI and use connection strengths as features for outcome prediction and consciousness level differentiation. The study achieves improved classification accuracy for consciousness levels (84.78%) and recovery outcome prediction (89.74%) compared to other methods, and identifies contributive connections across the entire brain. These findings provide potential biomarkers for understanding consciousness and developing diagnostic, prognostic, and therapeutic guidelines for ABI patients.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2023)
Article
Neurosciences
Nigel Colenbier, Ekansh Sareen, Tamara del-Aguila Puntas, Alessandra Griffa, Giovanni Pellegrino, Dante Mantini, Daniele Marinazzo, Giorgio Arcara, Enrico Amico
Summary: The use of human brain connectivity data as a fingerprint for individual identification has become a popular area of research in neuroscience. Recent studies have found that brain signatures can be extracted from resting-state MEG recordings, but their effectiveness in task-related conduct is still uncertain. This study demonstrates that identification improves during tasks compared to resting-state, particularly in controlled tasks, and the brain regions contributing to identification also change during task activities.
Article
Geriatrics & Gerontology
Sonia Montemurro, Nicola Filippini, Giulio Ferrazzi, Dante Mantini, Giorgio Arcara, Marco Marino
Summary: In healthy aging, education plays a role in differentiating cognitive and neural profiles in older adults. Higher education is associated with better cognitive performance in aging. This study investigates the influence of education on age-related differences in cognition and resting state functional connectivity.
FRONTIERS IN AGING NEUROSCIENCE
(2023)
Article
Biochemistry & Molecular Biology
Zaira Romeo, Marco Marino, Dante Mantini, Alessandro Angrilli, Chiara Spironelli
Summary: Abnormalities in the Language Network (LN) have been observed in various psychiatric conditions, such as schizophrenia and bipolar disorder, suggesting a continuum of shared neural alterations. In this study, the LN architecture was analyzed during resting state and a language task in bipolar disorder patients. The findings indicate reduced language lateralization in bipolar patients which may serve as a biological marker for different psychotic disorders.
Article
Multidisciplinary Sciences
Amirhossein Rasooli, Hamed Zivari Adab, Peter Van Ruitenbeek, Akila Weerasekera, Sima Chalavi, Koen Cuypers, Oron Levin, Thijs Dhollander, Ronald Peeters, Stefan Sunaert, Dante Mantini, Stephan P. Swinnen
Summary: Aging is associated with changes in the central nervous system and leads to reduced life quality. Magnetic resonance spectroscopy and diffusion MRI were used to investigate the age-related differences in the CNS underlying motor performance deficits. The study found that aging was associated with increased reaction time, reduced fiber density (FD), and N-acetyl aspartate (NAA) concentration in the sensorimotor voxel. Both FD and NAA mediated the association between age and reaction time, and NAA concentration mediated the association between age and FD in the sensorimotor voxel. The decrease in NAA concentration may result in reduced axonal fiber density, which ultimately accounts for the response slowness of older participants.
Article
Neurosciences
Simon Titone, Jessica Samogin, Philippe Peigneux, Stephan P. Swinnen, Dante Mantini, Genevieve Albouy
Summary: This study used high-density electroencephalography (hdEEG) to investigate the fluctuation of frequency-dependent network-level functional connectivity (FC) during nocturnal sleep in healthy young adults. The results showed that FC within and between all resting-state networks decreased from NREM2 to NREM3 sleep in multiple frequency bands and all sleep cycles. The study also found a complex modulation of connectivity patterns during the transition to REM sleep, with a persistence of connectivity breakdown in certain frequency bands and networks. However, a reconnection occurred in the default mode and attentional networks in frequency bands characterizing their organization during wakefulness.
EUROPEAN JOURNAL OF NEUROSCIENCE
(2023)
Article
Psychology, Biological
Alessandro Botta, Mingqi Zhao, Jessica Samogin, Elisa Pelosin, Gaia Bonassi, Giovanna Lagravinese, Dante Mantini, Alessio Avenanti, Laura Avanzino
Summary: Using high-density electroencephalography (hd-EEG), this study found that the processing of fearful emotional body language (EBL) activates somatosensory areas early on and suppresses motor activity in healthy individuals. These findings provide high-temporal resolution evidence of the interplay between somatosensory and motor areas during the observation of EBL, shedding light on the sensorimotor mechanism supporting freezing behavior.
Article
Geriatrics & Gerontology
Silvia Salvalaggio, Andrea Turolla, Martina Ando, Rita Barresi, Francesca Burgio, Pierpaolo Busan, Anna Maria Cortese, Daniela D'Imperio, Laura Danesin, Giulio Ferrazzi, Lorenza Maistrello, Eleonora Mascotto, Ilaria Parrotta, Rachele Pezzetta, Elena Rigon, Anna Vedovato, Sara Zago, Marco Zorzi, Giorgio Arcara, Dante Mantini, Nicola Filippini
Summary: This article introduces cross-modality protocols to investigate the effects of rehabilitation treatment in stroke survivors. The protocols include rehabilitation programs, clinical assessments, and physiological/imaging techniques. The integration of advanced techniques and assessment measures will help develop a predictive model of recovery in stroke patients.
FRONTIERS IN AGING NEUROSCIENCE
(2023)
Review
Biotechnology & Applied Microbiology
Toon T. de Beukelaar, Dante Mantini
Summary: Resistance training is a popular exercise modality that uses weights or resistance to strengthen and tone muscles. Wearable technology has emerged as a promising tool for monitoring and optimizing resistance training programs, providing detailed physiological and biomechanical information. It has the potential to revolutionize resistance training research and provide new insights and opportunities for developing optimized training programs.
BIOENGINEERING-BASEL
(2023)
Article
Computer Science, Artificial Intelligence
Mianxin Liu, Han Zhang, Feng Shi, Dinggang Shen
Summary: This study proposes a novel framework for multiscale functional connectivity network (FCN) analysis in brain disorder diagnosis. The proposed method computes multiscale FCNs using a set of well-defined multiscale atlases and performs nodal pooling across multiple spatial scales based on biologically meaningful brain hierarchical relationships. Experiments on neuroimaging data demonstrate the effectiveness of the proposed method in diagnosing Alzheimer's disease (AD), mild cognitive impairment (MCI), and autism spectrum disorder (ASD). The study highlights the feasibility of using deep learning and functional interactions in multiscale brain hierarchy for better understanding the neuropathology of brain disorders.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Neurosciences
Gaia Bonassi, Marianna Semprini, Paola Mandich, Lucia Trevisan, Roberta Marchese, Giovanna Lagravinese, Federico Barban, Elisa Pelosin, Michela Chiappalone, Dante Mantini, Laura Avanzino
Summary: Using high-density electroencephalography, we found decreased modulation of neural oscillations in early symptomatic HD and pre-HD, even though the dynamics of modulation were preserved.