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ORCIDFrontiers in Neuroinformatics, Volume 18
Volume 18, 2024
- Vergil Haynes, Yi Zhou, Sharon M. Crook:
Discovering optimal features for neuron-type identification from extracellular recordings. - Cristiana Dimulescu, Leonhard Donle
, Caglar Cakan, Thomas Goerttler, Liliia Khakimova, Julia Ladenbauer, Agnes Flöel, Klaus Obermayer:
Improving the detection of sleep slow oscillations in electroencephalographic data. - Antonio Fernández-Caballero, Michel Le Van Quyen:
Editorial: Innovative methods for sleep staging using neuroinformatics. - Sahaj Anilbhai Patel, Rachel June Smith, Abidin Yildirim:
Gershgorin circle theorem-based feature extraction for biomedical signal analysis. - Kai-Yi Hsu, Chi-Tin Shih, Nan-Yow Chen, Chung-Chuan Lo:
LYNSU: automated 3D neuropil segmentation of fluorescent images for Drosophila brains. - Peter A. Tass, Hemant Bokil:
Editorial: Neuromodulation using spatiotemporally complex patterns. - Abdullah S. Alharthi:
Interpretable machine learning comprehensive human gait deterioration analysis. - Marlis Ontivero-Ortega, Jorge Iglesias-Fuster, Jhoanna Perez-Hidalgo, Daniele Marinazzo, Mitchell Valdés-Sosa, Pedro A. Valdés-Sosa:
Intra-V1 functional networks and classification of observed stimuli. - Rok Ister, Marko Sternak, Sinisa Skokic, Srecko Gajovic:
suMRak: a multi-tool solution for preclinical brain MRI data analysis. - Camilla H. Blixhavn, Ingrid Reiten, Heidi Kleven, Martin Øvsthus, Sharon C. Yates, Ulrike Schlegel, Maja A. Puchades, Oliver Schmid, Jan G. Bjaalie, Ingvild Elise Bjerke, Trygve B. Leergaard:
The Locare workflow: representing neuroscience data locations as geometric objects in 3D brain atlases. - Guanqing Kong, Chuanfu Wu, Zongqiu Zhang, Chuansheng Yin, Dawei Qin:
M3: using mask-attention and multi-scale for multi-modal brain MRI classification. - Zongya Zhao, Yifan Feng, Menghan Wang, Jiarong Wei, Tao Tan, Ruijiao Li, Heshun Hu, Mengke Wang, Peiqi Chen, Xudong Gao, Yinping Wei, Chang Wang, Zhixian Gao, Wenshuai Jiang, Xuezhi Zhou, Mingcai Li, Chong Wang, Ting Pang, Yi Yu:
Investigating cortical complexity and connectivity in rats with schizophrenia. - Matteo Ferrante, Tommaso Boccato, Nicola Toschi:
Enabling uncertainty estimation in neural networks through weight perturbation for improved Alzheimer's disease classification. - Scott Makeig, Kay Robbins:
Events in context - The HED framework for the study of brain, experience and behavior. - Km Bhavna, Azman Akhter, Romi Banerjee, Dipanjan Roy:
Explainable deep-learning framework: decoding brain states and prediction of individual performance in false-belief task at early childhood stage. - Anass B. El-Yaagoubi, Moo K. Chung, Hernando Ombao:
Dynamic topological data analysis: a novel fractal dimension-based testing framework with application to brain signals. - Hongxian Gu, Yuting Yan, Xiaodong He, Yuyun Xu, Yuguo Wei, Yuan Shao:
Predicting the clinical prognosis of acute ischemic stroke using machine learning: an application of radiomic biomarkers on non-contrast CT after intravascular interventional treatment. - Éléonore Chamberland, Seyedadel Moravveji, Nicolas Doyon, Simon Duchesne:
A computational model of Alzheimer's disease at the nano, micro, and macroscales. - Lionel Kusch, Sandra Diaz-Pier, Wouter Klijn, Kim Sontheimer, Christophe Bernard, Abigail Morrison, Viktor K. Jirsa:
Multiscale co-simulation design pattern for neuroscience applications. - Patrick G. McPhee, Anthony L. Vaccarino, Sibel Naska, Kirk Nylen, Jose Arturo Santisteban, Rachel Chepesiuk, Andrea Andrade, Stelios Georgiades, Brendan Behan, Alana Iaboni, Flora Wan, Sabrina Aimola, Heena Cheema, Jan Willem Gorter:
Harmonizing data on correlates of sleep in children within and across neurodevelopmental disorders: lessons learned from an Ontario Brain Institute cross-program collaboration. - Amy L. Cherry, Michael J. Wheeler, Karolina Mathisova, Mathieu Di Miceli:
In silico analyses of the involvement of GPR55, CB1R and TRPV1: response to THC, contribution to temporal lobe epilepsy, structural modeling and updated evolution. - Maaike M. H. van Swieten, Christian Haselgrove:
Editorial: Navigating the landscape of FAIR data sharing and reuse: repositories, standards, and resources. - Marta Gaviraghi, Antonio Ricciardi, Fulvia Palesi, Wallace Brownlee, Paolo Vitali, Ferran Prados, Baris Kanber, Claudia A. M. Gandini Wheeler-Kingshott:
Finding the limits of deep learning clinical sensitivity with fractional anisotropy (FA) microstructure maps. - Javier V. Juan, Rubén Martínez, Eduardo Iáñez, Mario Ortíz, Jesús Tornero, José Maria Azorín:
Exploring EEG-based motor imagery decoding: a dual approach using spatial features and spectro-spatial Deep Learning model IFNet. - Benedikt Holm, Gabriel Jouan, Emil Hardarson, Sigríður Sigurðardóttir, Kenan Hoelke, Conor Murphy, Erna Sif Arnardóttir, María Óskarsdóttir, Anna Sigríður Islind:
An optimized framework for processing multicentric polysomnographic data incorporating expert human oversight. - S. M. Shayez Karim, Md. Shah Fahad, R. S. Rathore:
Identifying discriminative features of brain network for prediction of Alzheimer's disease using graph theory and machine learning. - Seyedadel Moravveji, Nicolas Doyon, Javad Mashreghi, Simon Duchesne:
A scoping review of mathematical models covering Alzheimer's disease progression. - Marc Stawiski, Vittoria Bucciarelli, Dorian Vogel, Simone Hemm:
Optimizing neuroscience data management by combining REDCap, BIDS and SQLite: a case study in Deep Brain Stimulation. - Retraction: NeuroSuites: an online platform for running neuroscience, statistical, and machine learning tools.
- Imene Jemal, Lina Abou-Abbas, Khadidja Henni, Amar Mitiche, Neila Mezghani:
Domain adaptation for EEG-based, cross-subject epileptic seizure prediction. - Xin Liu, Chunyang Li, Xicheng Lou, Haohuan Kong, Xinwei Li, Zhangyong Li, Lisha Zhong:
Epileptic seizure prediction based on EEG using pseudo-three-dimensional CNN. - Horea-Ioan Ioanas, Austin Macdonald, Yaroslav O. Halchenko:
Neuroimaging article reexecution and reproduction assessment system. - Marvin Kaster, Fabian Czappa, Markus Butz-Ostendorf, Felix Wolf:
Building a realistic, scalable memory model with independent engrams using a homeostatic mechanism. - Bishal Thapaliya, Riyasat Ohib, Eloy Geenjaar, Jingyu Liu, Vince D. Calhoun, Sergey M. Plis:
Efficient federated learning for distributed neuroimaging data. - Jiacheng Sun, Freda Werdiger, Christopher Blair, Chushuang Chen, Qing Yang, Andrew Bivard, Longting Lin, Mark Parsons:
Automatic segmentation of hemorrhagic transformation on follow-up non-contrast CT after acute ischemic stroke. - Syed Saad Azhar Ali:
Brain MRI sequence and view plane identification using deep learning. - Jianwei Shi, Xun Gong, Ziang Song, Wenkai Xie, Yanfeng Yang, Xiangjie Sun, Penghu Wei, Changming Wang, Guoguang Zhao:
EPAT: a user-friendly MATLAB toolbox for EEG/ERP data processing and analysis. - Jaime F. Aguayo-González, Hanna Ehrlich-Lopez, Luis Concha, Mariano Rivera:
Light-weight neural network for intra-voxel structure analysis. - Raul Fernandez Rojas, Calvin Joseph, Ghazal Bargshady, Keng-Liang Ou:
Empirical comparison of deep learning models for fNIRS pain decoding. - Erratum: NeuroDecodeR: a package for neural decoding in R.
- Michelle F. Miranda:
A canonical polyadic tensor basis for fast Bayesian estimation of multi-subject brain activation patterns. - Roy Cox, Frederik D. Weber, Eus J. W. van Someren:
Customizable automated cleaning of multichannel sleep EEG in SleepTrip. - Pragya Rai, Andrew Knight, Matias Hiillos, Csaba Kertész, Elizabeth Morales, Daniella Terney, Sidsel Armand Larsen, Tim Østerkjerhuus, Jukka Peltola, Sándor Beniczky:
Automated analysis and detection of epileptic seizures in video recordings using artificial intelligence. - James L. Evans, Matthew T. Bramlet, Connor Davey, Eliot B. Bethke, Aaron T. Anderson, Graham Huesmann, Yogatheesan Varatharajah, Andrés Maldonado, Jennifer R. Amos, Bradley P. Sutton:
SEEG4D: a tool for 4D visualization of stereoelectroencephalography data. - Palani Thanaraj Krishnan, Pradeep Krishnadoss, Mukund Khandelwal, Devansh Gupta, Anupoju Nihaal, T. Sunil Kumar:
Enhancing brain tumor detection in MRI with a rotation invariant Vision Transformer. - Marius N. Vieth, Ali Rahimi, Ashena Gorgan Mohammadi, Jochen Triesch, Mohammad Ganjtabesh:
Accelerating spiking neural network simulations with PymoNNto and PymoNNtorch. - Sidsel Winther, Oscar Peulicke, Mariam Andersson, Hans Martin Kjer, Jakob Andreas Bærentzen, Tim B. Dyrby:
Exploring white matter dynamics and morphology through interactive numerical phantoms: the White Matter Generator. - Noelia Martínez-Molina, Yonatan Sanz Perl, Anira Escrichs, Morten L. Kringelbach, Gustavo Deco:
Turbulent dynamics and whole-brain modeling: toward new clinical applications for traumatic brain injury. - Rene Miedema, Christos Strydis:
ExaFlexHH: an exascale-ready, flexible multi-FPGA library for biologically plausible brain simulations. - Ekaterina Proshina, Olga Martynova, Galina Portnova, Guzal Khayrullina, Olga Sysoeva:
Long-range temporal correlations in resting state alpha oscillations in major depressive disorder and obsessive-compulsive disorder. - Marvin Kaster, Fabian Czappa, Markus Butz-Ostendorf, Felix Wolf:
Corrigendum: Building a realistic, scalable memory model with independent engrams using a homeostatic mechanism. - Rossella Capotorto, Vincenzo Ronca, Nicolina Sciaraffa, Gianluca Borghini, Gianluca Di Flumeri, Lorenzo Mezzadri, Alessia Vozzi, Andrea Giorgi, Daniele Germano, Fabio Babiloni, Pietro Aricò:
Cooperation objective evaluation in aviation: validation and comparison of two novel approaches in simulated environment. - Dorsa Shekouh, Helia Sadat Kaboli, Mohammadreza Ghaffarzadeh-Esfahani, Mohammadmahdi Khayamdar, Zeinab Hamedani, Saeed Oraee-Yazdani, Alireza Zali, Elnaz Amanzadeh:
Artificial intelligence role in advancement of human brain connectome studies. - Bing Zhang, Xishun Zhu, Fadia Ali Khan, Sajjad Shaukat Jamal, Alanoud Al Mazroa, Rab Nawaz:
Research on ECG signal reconstruction based on improved weighted nuclear norm minimization and approximate message passing algorithm. - Mindi Ruan, Na Zhang, Xiangxu Yu, Wenqi Li, Chuanbo Hu, Paula Webster, Lynn K. Paul, Shuo Wang, Xin Li:
Can micro-expressions be used as a biomarker for autism spectrum disorder? - Maryam Naseri, Sreekrishna Ramakrishnapillai, Owen T. Carmichael:
Reproducible brain PET data analysis: easier said than done. - Alejandra P. Pérez-González, Aidee Lashmi García-Kroepfly, Keila Adonai Pérez-Fuentes, Roberto Isaac García-Reyes, Fryda Fernanda Solis-Roldan, Jennifer Alejandra Alba-González, Enrique Hernández-Lemus, Guillermo de Anda-Jáuregui:
The ROSMAP project: aging and neurodegenerative diseases through omic sciences. - Giles Winchester, Oliver G. Steele, Samuel Liu, André Maia Chagas, Wajeeha Aziz, Andrew C. Penn:
Reproducible supervised learning-assisted classification of spontaneous synaptic waveforms with Eventer.
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