Article
Neurosciences
Marie-Stephanie Cahart, Owen O'Daly, Vincent Giampietro, Maarten Timmers, Johannes Streffer, Steven Einstein, Fernando Zelaya, Flavio Dell'Acqua, Steven C. R. Williams
Summary: This study compared the reliability of conventional single-band fMRI and different multiband (MB) fMRI acquisitions with and without in-plane acceleration across multiple scanning sessions. It found that for cortical areas, MB factor 4 without in-plane acceleration had the highest reliability, while for subcortical areas, conventional single-band fMRI was more reliable.
HUMAN BRAIN MAPPING
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Ajay Nemani, Mark J. Lowe
Summary: This study assessed the test-retest reliability of functional connectivity in different field strengths by scanning subjects at 3T and 7T. Results showed that the reliability of intrinsic networks was significantly greater at 7T compared to 3T, with the greatest improvement seen in intra-network reliability. The findings support the trend of migrating functional imaging studies to ultrahigh field strengths.
Article
Multidisciplinary Sciences
Yulin Wang, Wei Duan, Debo Dong, Lihong Ding, Xu Lei
Summary: Here, we provide a test-retest dataset of electroencephalogram (EEG) measurements obtained in various resting and cognitive states. The dataset includes short-term and long-term designs, allowing for the investigation of both intra- and inter-session variability in electrophysiological changes, as well as alterations in resting and cognitive states. Additionally, this dataset contributes to the reliability and validity of EEG measurements by providing an open resource.
Article
Neurosciences
Aman Taxali, Mike Angstadt, Saige Rutherford, Chandra Sripada
Summary: Recent studies have shown that the use of predictive models can improve the reliability of functional magnetic resonance imaging (fMRI), with the predicted outcomes of these models being more reliable than individual imaging features, reaching good levels of reliability for some methods.
Article
Neurosciences
Yizhou Ma, Angus W. MacDonald
Summary: Research suggests that applying independent component analysis to resting-state functional connectivity at different dimensionalities can improve the reliability of certain brain networks, particularly cognitive networks. However, the reliability of different networks varies with increased dimensionality, and one's networks of interest can impact analytical decisions.
BRAIN CONNECTIVITY
(2021)
Article
Neurosciences
Lan Yang, Jing Wei, Ying Li, Bin Wang, Hao Guo, Yanli Yang, Jie Xiang
Summary: This study examined the test-retest reliabilities of synchrony and metastability using data from the Human Connectome Project. The results showed good reliability for these indexes, with factors such as field strength and denoising affecting their values. The study provides methodological reference for exploring dynamic neural activity in the brain using synchrony and metastability in fMRI signals.
Article
Neurosciences
Faezeh Vedaei, Mahdi Alizadeh, Victor Romo, Feroze B. Mohamed, Chengyuan Wu
Summary: This study investigates the test-retest reliability of rs-fMRI in neuroscience, showing that reliability of measurements is higher under anesthesia and increases with longer scan lengths.
FRONTIERS IN NEUROSCIENCE
(2022)
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
Marlena Duda, Danai Koutra, Chandra Sripada
Summary: This study investigates the presence of dynamic functional connectivity during rest and proposes a data-driven framework for studying cognitive neuroscience questions using connectivity changes. The framework outperforms the traditional sliding window approach in accuracy and computational efficiency when applied to working memory task data. Additionally, when applied to resting state fMRI data, the method consistently identifies five reliable FC states which show significant correlation with behavioral phenotypes.
HUMAN BRAIN MAPPING
(2021)
Article
Neurosciences
Qianying Wu, Hui Lei, Tianxin Mao, Yao Deng, Xiaocui Zhang, Yali Jiang, Xue Zhong, John A. Detre, Jianghong Liu, Hengyi Rao
Summary: Resting-state functional magnetic resonance imaging (fMRI) with graph theoretical modeling is used to assess whole brain network topological organization, and the test-retest reliability of different metrics is examined. The characteristic path length and nodal efficiency are the most reliable metrics, while network small-worldness and betweenness centrality are the least reliable. Weighted global network metrics and AAL90 atlas provide better reliability. Global signal regression slightly impairs nodal metric reliability. These findings have important implications for the future use of graph theoretical modeling in brain network analyses.
Article
Neurosciences
Farzad Farahani, Waldemar Karwowski, Mark D'Esposito, Richard F. Betzel, Pamela K. Douglas, Anna Maria Sobczak, Bartosz Bohaterewicz, Tadeusz Marek, Magdalena Fafrowicz
Summary: Circadian rhythms have an impact on brain function, particularly on functional connectivity patterns and local/regional changes. Time of day affects areas associated with somatomotor, attention, frontoparietal, and default networks. The somatomotor, ventral attention, and visual networks are highly connected areas that show changes between morning and evening sessions.
Article
Cell Biology
Damion Demeter, Evan M. Gordon, Tehila Nugiel, AnnaCarolina Garza, Tyler L. Larguinho, Jessica A. Church
Summary: During childhood, neural systems supporting high-level cognitive processes undergo rapid growth and refinement, relying on successful coordination of activation across the brain. We identified four distinct hub categories in a large youth sample, each exhibiting more diverse connectivity profiles than adults. The split in youth hubs suggests a need for segregating sensory stimuli during rapid development of functional networks.
Article
Biochemical Research Methods
Camarin E. Rolle, Manjari Narayan, Wei Wu, Russ Toll, Noriah Johnson, Trevor Caudle, Marvin Yan, Mallissa Watts, Michelle Eisenberg, Amit Etkin, Dawlat El-Said
Summary: This study extensively examines the test-retest reliability and methodological agreement of various options for regional measures of functional connectivity in high density electroencephalography (hdEEG). The results reveal that power envelope connectivity shows higher reliability than imaginary coherence across all frequency bands. Channel density does not strongly affect reliability or agreement, but source localization methods produce systematically different functional connectivity, posing a challenge for result replication. Importantly, reliability and agreement often plateau after 6 minutes of acquisition, exceeding the typical duration of 3 minutes. Finally, the study demonstrates that resting EEG can be as or more reliable than resting fMRI acquired in the same individuals.
JOURNAL OF NEUROSCIENCE METHODS
(2022)
Article
Neurosciences
Xin Zhang, Jiayue Liu, Yang Yang, Shijie Zhao, Lei Guo, Junwei Han, Xintao Hu
Summary: The study examined the test-retest reliability of dynamic functional connectivity (dFC) in functional magnetic resonance imaging (fMRI) under natural viewing condition, revealing significantly improved reliability compared to resting state. This suggests that naturalistic paradigms may enhance the study of functional brain networks using fMRI.
HUMAN BRAIN MAPPING
(2022)
Article
Neurosciences
Hengyi Cao, Anita D. Barber, Jose M. Rubio, Miklos Argyelan, Juan A. Gallego, Todd Lencz, Anil K. Malhotra
Summary: This study investigates the influence of phase encoding direction (PED) on the test-retest reliability of functional connectome in fMRI studies. The results show that PA scans have significantly higher intraclass correlation coefficients (ICCs) for global, nodal, and edge connectivity compared to AP scans. Better temporal signal-to-noise ratio (tSNR) reliability is also observed in PA scans. Averaging the connectivity outcome from both PEDs can increase ICCs, especially at the nodal and edge levels.
Review
Psychiatry
Antonio Napolitano, Sara Schiavi, Piergiorgio La Rosa, Maria Camilla Rossi-Espagnet, Sara Petrillo, Francesca Bottino, Emanuela Tagliente, Daniela Longo, Elisabetta Lupi, Laura Casula, Giovanni Valeri, Fiorella Piemonte, Viviana Trezza, Stefano Vicari
Summary: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder with a prevalence of about 1%, characterized by impairments in social interaction, communication, repetitive behaviors, and sensory reactivity. It is more common in males and can be associated with anxiety, depression, hyperactivity, and attention problems.
FRONTIERS IN PSYCHIATRY
(2022)
Article
Clinical Neurology
Nathan T. Cohen, Xiaozhen You, Manu Krishnamurthy, Leigh N. Sepeta, Anqing Zhang, Chima Oluigbo, Matthew T. Whitehead, Taha Gholipour, Torsten Baldeweg, Konrad Wagstyl, Sophie Adler, William D. Gaillard
Summary: This study found that co-localization of FCD with distributed functional cortical networks is associated with age of epilepsy onset, with sensory neural networks (such as somatomotor and visual) linked to earlier onset and cognitive networks linked to later onset.
ANNALS OF NEUROLOGY
(2022)
Article
Clinical Neurology
Hannah Spitzer, Mathilde Ripart, Kirstie Whitaker, Felice D'Arco, Kshitij Mankad, Andrew A. Chen, Antonio Napolitano, Luca De Palma, Alessandro De Benedictis, Stephen Foldes, Zachary Humphreys, Kai Zhang, Wenhan Hu, Jiajie Mo, Marcus Likeman, Shirin Davies, Christopher Guttler, Matteo Lenge, Nathan T. Cohen, Yingying Tang, Shan Wang, Aswin Chari, Martin Tisdall, Nuria Bargallo, Estefania Conde-Blanco, Jose Carlos Pariente, Saul Pascual-Diaz, Ignacio Delgado-Martinez, Carmen Perez-Enriquez, Ilaria Lagorio, Eugenio Abela, Nandini Mullatti, Jonathan O'Muircheartaigh, Katy Vecchiato, Yawu Liu, Maria Eugenia Caligiuri, Ben Sinclair, Lucy Vivash, Anna Willard, Jothy Kandasamy, Ailsa McLellan, Drahoslav Sokol, Mira Semmelroch, Ane G. Kloster, Giske Opheim, Leticia Ribeiro, Clarissa Yasuda, Camilla Rossi-Espagnet, Khalid Hamandi, Anna Tietze, Carmen Barba, Renzo Guerrini, William Davis Gaillard, Xiaozhen You, Irene Wang, Sofia Gonzalez-Ortiz, Mariasavina Severino, Pasquale Striano, Domenico Tortora, Reetta Kalviainen, Antonio Gambardella, Angelo Labate, Patricia Desmond, Elaine Lui, Terence O'Brien, Jay Shetty, Graeme Jackson, John S. Duncan, Gavin P. Winston, Lars H. Pinborg, Fernando Cendes, Fabian J. Theis, Russell T. Shinohara, J. Helen Cross, Torsten Baldeweg, Sophie Adler, Konrad Wagstyl
Summary: One of the challenges in applying machine learning to diagnostic biomedical imaging is the interpretability of algorithms. This study developed an open-source and interpretable machine-learning algorithm to automatically identify FCDs from structural MRI data, improving the confidence of physicians in identifying subtle MRI lesions in individuals with epilepsy.
Review
Pediatrics
Giulia Lucignani, Alessia Guarnera, Maria Camilla Rossi-Espagnet, Giulia Moltoni, Amanda Antonelli, Lorenzo Figa Talamanca, Chiara Carducci, Francesca Ippolita Calo Carducci, Antonio Napolitano, Carlo Gandolfo, Francesca Campi, Cinzia Auriti, Cecilia Parazzini, Daniela Longo
Summary: Congenital infections can lead to brain damage in fetuses and newborns, resulting in a wide range of clinical manifestations. The early detection and accurate diagnosis through neuroimaging are crucial for prognosis and timely treatment.
Article
Physics, Multidisciplinary
Claudia Polito, Davide Ciucci, Federica Martire, Salvatore Donatiello, Antonio Napolitano, Milena Pizzoferro, Maria Felicia Villani, Claudio Altini, Maria Carmen Garganese, Vittorio Cannata
Summary: The aim of this study is to investigate a protocol for discharging patients undergoing treatment with I-131-NaI, I-131-MIBG, and Lu-177-DOTATATE based on patient-specific biokinetics. The study analyzed dose rates and evaluated radiation protection prescriptions for both the public and caregivers. The results showed that radiation protection measures are necessary, especially for patients undergoing I-131-MIBG therapies.
EUROPEAN PHYSICAL JOURNAL PLUS
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Alberto Di Napoli, Emanuela Tagliente, Luca Pasquini, Enrica Cipriano, Filomena Pietrantonio, Piermaria Ortis, Simona Curti, Alessandro Boellis, Teseo Stefanini, Antonio Bernardini, Chiara Angeletti, Sofia Chiatamone Ranieri, Paola Franchi, Ioan Paul Voicu, Carlo Capotondi, Antonio Napolitano
Summary: Chest CT is useful for assessing lung damage in COVID-19 patients, and AI-powered predictive models can aid in resource allocation. This study developed a deep-learning model using 3D chest CT images at hospital admission to predict the outcome of COVID-19 patients, achieving good performance.
JOURNAL OF DIGITAL IMAGING
(2023)
Article
Clinical Neurology
Serena Capelli, Anna Caroli, Antonino Barletta, Alberto Arrigoni, Angela Napolitano, Giulio Pezzetti, Luca Giovanni Longhi, Rosalia Zangari, Ferdinando Luca Lorini, Maria Sessa, Andrea Remuzzi, Simonetta Gerevini
Summary: Despite being a common neurological complication of COVID-19, the pathogenesis of olfactory disorders remains unclear. This study used MRI to provide evidence of olfactory system alterations in COVID-19 patients with neurological symptoms, including olfactory dysfunction. The findings showed damage to the olfactory bulb in these patients.
JOURNAL OF NEUROLOGY
(2023)
Article
Neuroimaging
Anna Caroli, Serena Capelli, Angela Napolitano, Giulia Cabrini, Alberto Arrigoni, Giulio Pezzetti, Mattia Previtali, Luca Giovanni Longhi, Rosalia Zangari, Ferdinando Luca Lorini, Maria Sessa, Andrea Remuzzi, Simonetta Gerevini
Summary: This study assessed and quantified brain diffusion alterations in COVID-19 patients with neurological manifestations, and found significantly increased ADC values in the white matter and gray matter regions of COVID-19 patients. These findings suggest that diffusion-weighted imaging may be a non-invasive marker of neuroinflammation in COVID-19.
NEUROIMAGE-CLINICAL
(2023)
Article
Psychiatry
Stefano Ferracuti, Antonio Del Casale, Andrea Romano, Ida Gualtieri, Martina Lucignani, Antonio Napolitano, Martina Nicole Modesti, Andrea Buscajoni, Teodolinda Zoppi, Georgios D. Kotzalidis, Lorenza Manelfi, Eleonora de Pisa, Paolo Girardi, Gabriele Mandarelli, Giovanna Parmigiani, Maria Camilla Rossi-Espagnet, Maurizio Pompili, Alessandro Bozzao
Summary: The severity of symptoms in schizophrenia is associated with abnormal cortical gyrification, especially in the frontal and temporal lobes. Patients with low hostility symptoms showed lower local gyrification index in these areas compared to patients with high hostility symptoms.
FRONTIERS IN PSYCHIATRY
(2023)
Article
Computer Science, Interdisciplinary Applications
Rosella Tro, Monica Roascio, Gabriele Arnulfo, Domenico Tortora, Mariasavina Severino, Andrea Rossi, Antonio Napolitano, Marco M. Fato
Summary: Choosing the most appropriate denoising method is crucial for improving the quality of diagnostic images in the pre-processing of diffusion MRI images. This study compared two adaptive techniques, Patch2Self and Nlsam, and found that Patch2Self framework is specifically suitable for DKI data, demonstrating better performance at 7T.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2023)
Article
Endocrinology & Metabolism
Diego Martinelli, Giulio Catesini, Benedetta Greco, Alessia Guarnera, Chiara Parrillo, Evelina Maines, Daniela Longo, Antonio Napolitano, Francesca De Nictolis, Sara Cairoli, Daniela Liccardo, Stefania Caviglia, Anna Sidorina, Giorgia Olivieri, Barbara Siri, Roberto Bianchi, Gionata Spagnoletti, Luca Dello Strologo, Marco Spada, Carlo Dionisi-Vici
Summary: Liver and liver/kidney transplantation have positive effects on the neurological outcome of patients with methylmalonic aciduria. Improved biomarkers were observed in plasma, while biomarkers of mitochondrial dysfunction decreased in cerebrospinal fluid. Neurocognitive evaluation showed significant cognitive improvement and brain changes at MRI. Early transplantation is recommended due to long-term complications and low quality of life.
JOURNAL OF INHERITED METABOLIC DISEASE
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Paolo Bosco, Marta Lancione, Alessandra Retico, Anna Nigri, Domenico Aquino, Francesca Baglio, Irene Carne, Stefania Ferraro, Giovanni Giulietti, Antonio Napolitano, Fulvia Palesi, Luigi Pavone, Giovanni Savini, Fabrizio Tagliavini, Gandini Wheeler-Kingshott, Michela Tosetti, Laura Biagi
Summary: This study assessed the brain anatomical variability of MRI-derived measurements obtained from T1-weighted images according to standardized procedures. The results indicated some variability in the measurements obtained from multi-site and multi-vendor datasets, but no systematic biases were detected.
PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS
(2023)
Article
Pediatrics
Alessia Guarnera, Giulia Lucignani, Chiara Parrillo, Maria Camilla Rossi-Espagnet, Chiara Carducci, Giulia Moltoni, Immacolata Savarese, Francesca Campi, Andrea Dotta, Francesco Milo, Simona Cappelletti, Teresa Capitello Grimaldi, Carlo Gandolfo, Antonio Napolitano, Daniela Longo
Summary: This study aimed to identify the associations between perinatal and outcome parameters with morphological anomalies and ADC values from MRI. The results showed that ADC values can be used as predictive biomarkers for children's neurodevelopmental outcomes. Further studies are needed to validate these results.
Review
Biotechnology & Applied Microbiology
Rossella Di Bidino, Davide Piaggio, Martina Andellini, Beatriz Merino-Barbancho, Laura Lopez-Perez, Tianhui Zhu, Zeeshan Raza, Melody Ni, Andra Morrison, Simone Borsci, Giuseppe Fico, Leandro Pecchia, Ernesto Iadanza
Summary: Artificial intelligence and machine learning are increasingly important in the field of medical devices, but the Health Technology Assessment process still lacks a common methodology for assessing AI/ML-based devices. A meta-review conducted by the International Federation of Medical and Biological Engineering collected existing evidence on methods used to assess AI-based devices, with a focus on heart failure management. The findings showed that deep learning is commonly used, and electronic health records and registries are prevalent data sources for AI/ML algorithms.
BIOENGINEERING-BASEL
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Luca Pasquini, Onur Yildirim, Patrick Silveira, Christel Tamer, Antonio Napolitano, Martina Lucignani, Mehrnaz Jenabi, Kyung K. Peck, Andrei Holodny
Summary: This study explores the relationship between tumor-related variables (grade, genetics, location) and patient-related variables (age, sex, handedness) with fMRI language laterality. The findings suggest that tumor genetics, pathology, and location have an impact on language organization and plasticity.
EUROPEAN RADIOLOGY
(2023)
Article
Biochemical Research Methods
Aline Silva da Cruz, Maria Margarida Drehmer, Wagner Baetas-da-Cruz, Joao Carlos Machado
Summary: This study quantified microcirculation cerebral blood flow in a rat model of ischemic stroke using ultrasound biomicroscopy and ultrasound contrast agents. The results showed high sensitivity and specificity of this method, making it a valuable tool for preclinical studies.
JOURNAL OF NEUROSCIENCE METHODS
(2024)
Article
Biochemical Research Methods
Christina Dalla, Ivana Jaric, Pavlina Pavlidi, Georgia E. Hodes, Nikolaos Kokras, Anton Bespalov, Martien J. Kas, Thomas Steckler, Mohamed Kabbaj, Hanno Wuerbel, Jordan Marrocco, Jessica Tollkuhn, Rebecca Shansky, Debra Bangasser, Jill B. Becker, Margaret McCarthy, Chantelle Ferland-Beckham
Summary: Many funding agencies have emphasized the importance of considering sex as a biological variable in experimental design to improve the reproducibility and translational relevance of preclinical research. Omitting the female sex from experimental designs in neuroscience and pharmacology can result in biased or limited understanding of disease mechanisms. This article provides methodological considerations for incorporating sex as a biological variable in in vitro and in vivo experiments, including the influence of age and hormone levels, and proposes strategies to enhance methodological rigor and translational relevance in preclinical research.
JOURNAL OF NEUROSCIENCE METHODS
(2024)
Article
Biochemical Research Methods
Wenyu Gu, Dongxu Li, Jia-Hong Gao
Summary: We developed a precise and rapid method for positioning and labelling triaxial OPMs on a wearable magnetoencephalography (MEG) system, improving the efficiency of OPM positioning and labelling.
JOURNAL OF NEUROSCIENCE METHODS
(2024)
Article
Biochemical Research Methods
Kai Lin, Linhang Zhang, Jing Cai, Jiaqi Sun, Wenjie Cui, Guangda Liu
Summary: The article introduces an EEG feature map processing model for emotion recognition, which achieves significantly improved accuracy by fusing EEG information at different spatial scales and introducing a channel attention mechanism.
JOURNAL OF NEUROSCIENCE METHODS
(2024)
Article
Biochemical Research Methods
John E. Parker, Asier Aristieta, Aryn H. Gittis, Jonathan E. Rubin
Summary: This work presents a toolbox that implements a methodology for automated classification of neural responses based on spike train recordings. The toolbox provides a user-friendly and efficient approach to detect various types of neuronal responses that may not be identified by traditional methods.
JOURNAL OF NEUROSCIENCE METHODS
(2024)
Article
Biochemical Research Methods
Yun Liang, Ke Bo, Sreenivasan Meyyappan, Mingzhou Ding
Summary: This study compared the performance of SVM and CNN on the same datasets and found that CNN achieved consistently higher classification accuracies. The classification accuracies of SVM and CNN were generally not correlated, and the heatmaps derived from them did not overlap significantly.
JOURNAL OF NEUROSCIENCE METHODS
(2024)
Article
Biochemical Research Methods
Antonino Visalli, Maria Montefinese, Giada Viviani, Livio Finos, Antonino Vallesi, Ettore Ambrosini
Summary: This study introduces an analytical strategy that allows the use of mixed-effects models (LMM) in mass univariate analyses of EEG data. The proposed method overcomes the computational costs and shows excellent performance properties, making it increasingly important in the field of neuroscience.
JOURNAL OF NEUROSCIENCE METHODS
(2024)
Article
Biochemical Research Methods
Xavier Cano-Ferrer, Alexandra Tran -Van -Minh, Ede Rancz
Summary: This study developed a novel rotation platform for studying neural processes and spatial navigation. The platform is modular, affordable, and easy to build, and can be driven by the experimenter or animal movement. The research demonstrated the utility of the platform, which combines the benefits of head fixation and intact vestibular activity.
JOURNAL OF NEUROSCIENCE METHODS
(2024)
