Review
Neurosciences
Ruoyao Pan, Chunlan Yang, Zhimei Li, Jiechuan Ren, Ying Duan
Summary: Epilepsy is a chronic central nervous system disorder characterized by recurrent seizures. Magnetoencephalography (MEG) is a non-invasive, high temporal and spatial resolution electrophysiological data that provides a valid basis for epilepsy diagnosis. However, identifying subtle changes in MEG is difficult, creating a need for intelligent algorithms for epilepsy recognition.
FRONTIERS IN NEUROSCIENCE
(2023)
Article
Neurosciences
Richard Csaky, Mats W. J. van Es, Oiwi Parker Jones, Mark Woolrich
Summary: This paper explores the application of multivariate pattern analysis in magnetoencephalography and electroencephalography data and proposes an approach that combines supervised dimensionality reduction and permutation feature importance. The results demonstrate that this approach improves decoding performance while estimating relevant spatiotemporal features.
Article
Biology
Viktor J. Olah, Nigel P. Pedersen, Matthew J. M. Rowan
Summary: Understanding the activity of the mammalian brain requires a comprehensive understanding of circuits at different scales, and computational models can help us understand how various parameters synergistically contribute to circuit behavior. However, traditional neuron models are computationally demanding, so we propose a training artificial neural network approach to simulate realistic neural activity. We found that the artificial neural network accurately predicts subthreshold activity and action potential firing, and can generalize to previously unobserved synaptic inputs, with processing times orders of magnitude faster than traditional methods.
Article
Chemistry, Multidisciplinary
Akshay Zadgaonkar, Ravindra Keskar, Omprakash Kakde
Summary: This study proposes a simple method based on lifestyle parameters to assess dementia trends, using machine learning models and data from the National Health and Ageing Trends Study (NHATS). The model accurately identifies dementia-related parameters and offers insights into aging trends and elderly citizens' lifestyles.
APPLIED SCIENCES-BASEL
(2023)
Article
Chemistry, Analytical
Nina Pilyugina, Akihiko Tsukahara, Keita Tanaka
Summary: This study compared the efficiency of various automatic feature selection methods and found that univariate selection combined with support vector machine classification method achieved the highest accuracy. The results will be utilized for further research on the mechanism behind the octave illusion phenomenon and the development of an automatic classification algorithm.
Article
Cell Biology
Yumi Umeda-Kameyama, Masashi Kameyama, Tomoki Tanaka, Bo-Kyung Son, Taro Kojima, Makoto Fukasawa, Tomomichi Iizuka, Sumito Ogawa, Katsuya Iijima, Masahiro Akishita
Summary: The study demonstrated that artificial intelligence, specifically deep learning models like Xception, can differentiate the faces of patients with mild dementia from those without dementia. This paves the way for future research into developing facial biomarkers for dementia.
Article
Biochemistry & Molecular Biology
Ashir Javeed, Ana Luiza Dallora, Johan Sanmartin Berglund, Alper Idrisoglu, Liaqat Ali, Hafiz Tayyab Rauf, Peter Anderberg
Summary: Dementia is a cognitive disorder that primarily affects older adults and currently has no cure or prevention. Machine learning scientists have developed techniques for early dementia prediction, but these methods have limitations in accuracy and bias. To address these issues, a new model (FEB-SVM) utilizing adaptive synthetic sampling (ADASYN), feature extraction battery (FEB), and optimized support vector machine (SVM) with radial basis function (rbf) was proposed. The FEB-SVM model achieved a significant improvement in accuracy compared to conventional SVM and outperformed state-of-the-art ML models for dementia prediction.
Article
Clinical Neurology
Elissa M. Ye, Haoqi Sun, Parimala Krishnamurthy, Noor Adra, Wolfgang Ganglberger, Robert J. Thomas, Alice D. Lam, M. Brandon Westover
Summary: Dementia is a growing problem in the elderly and is often underdiagnosed. Detecting and classifying dementia early can help improve management of the disease. Changes in brain activity during sleep can be used to identify those at risk of cognitive decline.
Review
Clinical Neurology
Laura M. Winchester, Eric L. Harshfield, Liu Shi, Amanpreet Badhwar, Ahmad Al Khleifat, Natasha Clarke, Amir Dehsarvi, Imre Lengyel, Ilianna Lourida, Christopher R. Madan, Sarah J. Marzi, Petroula Proitsi, Anto P. Rajkumar, Timothy Rittman, Edina Silajdzic, Stefano Tamburin, Janice M. Ranson, David J. Llewellyn
Summary: With the increase in large multimodal cohorts and high-throughput technologies, the potential for discovering novel biomarkers is no longer limited by data set size. Artificial intelligence (AI) and machine learning approaches have been developed to detect novel biomarkers and interactions in complex data sets. Remaining challenges include a lack of diversity in the data sets available, the sheer complexity of investigating interactions, the invasiveness and cost of some biomarkers, and poor reporting in some studies.
ALZHEIMERS & DEMENTIA
(2023)
Review
Health Care Sciences & Services
Ashir Javeed, Ana Luiza Dallora, Johan Sanmartin Berglund, Arif Ali, Liaqata Ali, Peter Anderberg
Summary: Nowadays, AI and ML have provided automated solutions to real-world problems. Healthcare is an important area for ML researchers, particularly in developing automated disease prediction systems. This study aims to evaluate ML-based automated diagnostic systems considering different data modalities, such as images, clinical features, and voice data, for dementia prediction.
JOURNAL OF MEDICAL SYSTEMS
(2023)
Article
Medicine, Research & Experimental
Keitaro Makino, Sangyoon Lee, Seongryu Bae, Ippei Chiba, Kenji Harada, Osamu Katayama, Yohei Shinkai, Hiroyuki Shimada
Summary: In this study, a 12-item questionnaire called STAD was developed for predicting dementia risk using telephonic interviews, and its predictive validity was confirmed in a validation study with 4298 community-dwelling older adults. A decision tree model using the CART algorithm showed better performance in dementia prediction accuracy and specificity compared to logistic regression, making STAD a promising screening tool for dementia risk in older adults.
JOURNAL OF TRANSLATIONAL MEDICINE
(2021)
Article
Neurosciences
Jasper E. Hajonides, Freek van Ede, Mark G. Stokes, Anna C. Nobre, Nicholas E. Myers
Summary: Behavioral reports of sensory information are influenced by stimulus history, with both attractive and repulsive biases observed. However, the underlying mechanisms in the human brain are not well understood. In this study, through a working-memory task and analysis of magnetoencephalographic (MEG) data, it was found that neural representations during stimulus encoding were biased away from the previous orientation, despite opposite effects on behavior. These results suggest that repulsive biases occur in sensory processing and can be overridden at postperceptual stages to result in attractive biases in behavior.
JOURNAL OF NEUROSCIENCE
(2023)
Review
Geriatrics & Gerontology
Masashi Kameyama, Yumi Umeda-Kameyama
Summary: The rapid development of artificial intelligence has brought great interest in areas such as image classification and natural language processing, and has been widely applied in the diagnosis and treatment of dementia.
GERIATRICS & GERONTOLOGY INTERNATIONAL
(2023)
Article
Geriatrics & Gerontology
Xiaohan Chen, Zhuo Fang, Yike Zhao, Wenbin Cheng, Honglin Chen, Genru Li, Jin Xu, Jiale Deng, Xiao Cai, Jianhua Zhuang, You Yin
Summary: This study aims to explore the evaluation ability of sleep parameters and plasma biomarkers for cognitive impairment in patients with cerebrovascular disease. The results showed that the integrated models of sleep parameters and plasma biomarkers can accurately assess cognitive status and the severity of cognitive impairment in patients.
JOURNALS OF GERONTOLOGY SERIES B-PSYCHOLOGICAL SCIENCES AND SOCIAL SCIENCES
(2023)
Article
Neurosciences
Zhuo Wang, Jie Wang, Ning Liu, Caiyan Liu, Xiuxing Li, Liling Dong, Rui Zhang, Chenhui Mao, Zhichao Duan, Wei Zhang, Jing Gao, Jianyong Wang
Summary: This study proposes a cognitive-test-based machine learning model that builds interpretable predictive and diagnostic rules for dementia through doctors' selection and analysis. The model achieves a good balance between accuracy and interpretability, with an AUC of 0.904 for predicting mild cognitive impairment conversion and an AUC of 0.863 for diagnosing dementia in subjects with normal Mini-Mental State Exam scores.
JOURNAL OF ALZHEIMERS DISEASE
(2022)
Article
Clinical Neurology
Katrina Moore, Rhian Convery, Martina Bocchetta, Mollie Neason, David M. Cash, Caroline Greaves, Lucy L. Russell, Mica T. M. Clarke, Georgia Peakman, John van Swieten, Lize Jiskoot, Fermin Moreno, Myriam Barandiaran, Raquel Sanchez-Valle, Barbara Borroni, Robert Laforce, Marie-Claire Dore, Mario Masellis, Maria Carmela Tartaglia, Caroline Graff, Daniela Galimberti, James B. Rowe, Elizabeth Finger, Matthis Synofzik, Hans-Otto Karnath, Rik Vandenberghe, Alexandre de Mendonca, Carolina Maruta, Fabrizio Tagliavini, Isabel Santana, Simon Ducharme, Chris Butler, Alex Gerhard, Johannes Levin, Adrian Danek, Markus Otto, Jason D. Warren, Jonathan D. Rohrer, Martin N. Rossor, Nick C. Fox, Ione O. C. Woollacott, Rachelle Shafei, Carolin Heller, Rita Guerreiro, Jose Bras, David L. Thomas, Jennifer Nicholas, Simon Mead, Lieke Meeter, Jessica Panman, Janne Papma, Rick van Minkelen, Yolande Pijnenburg, Begona Indakoetxea, Alazne Gabilondo, Mikel Tainta, Maria de Arriba, Ana Gorostidi, Miren Zulaica, Jorge Villanua, Zigor Diaz, Sergi Borrego-Ecija, Jaume Olives, Albert Llado, Mircea Balasa, Anna Antonell, Nuria Bargallo, Enrico Premi, Maura Cosseddu, Stefano Gazzina, Alessandro Padovani, Roberto Gasparotti, Silvana Archetti, Sandra Black, Sara Mitchell, Ekaterina Rogaeva, Morris Freedman, Ron Keren, David Tang-Wa, Linn Oijerstedt, Christin Andersson, Vesna Jelic, Hakan Thonberg, Andrea Arighi, Chiara Fenoglio, Elio Scarpini, Giorgio Fumagalli, Thomas Cope, Carolyn Timberlake, Timothy Rittman, Christen Shoesmith, Robart Bartha, Rosa Rademakers, Carlo Wilke, Benjamin Bender, Rose Bruffaerts, Philip Van Damme, Mathieu Vandenbulcke, Catarina B. Ferreira, Gabriel Miltenberger, Ana Verdelho, Sonia Afonso, Ricardo Taipa, Paola Caroppo, Giuseppe Di Fede, Giorgio Giaccone, Sara Prioni, Veronica Redaelli, Giacomina Rossi, Pietro Tiraboschi, Diana Duro, Maria Rosario Almeida, Miguel Castelo-Branco, Maria Joao Leitao, Miguel Tabuas-Pereira, Beatriz Santiago, Serge Gauthier, Pedro Rosa-Neto, Michele Veldsman, Toby Flanagan, Catharina Prix, Tobias Hoegen, Elisabeth Wlasich, Sandra Loosli, Sonja Schonecker, Elisa Semler, Sarah Anderl-Straub
Summary: This study investigates semantic cognition in patients with genetic frontotemporal dementia (FTD). The study finds that symptomatic patients scored lower than controls on semantic knowledge, while only late-stage MAPT and C9orf72 mutation carriers scored lower than controls in the presymptomatic groups. Furthermore, the study shows a correlation between mCCT score and brain volume in different regions in different mutation groups.
APPLIED NEUROPSYCHOLOGY-ADULT
(2022)
Review
Clinical Neurology
Barbara Borroni, Caroline Graff, Orla Hardiman, Albert C. Ludolph, Fermin Moreno, Markus Otto, Marco Piccininni, Anne M. Remes, James B. Rowe, Harro Seelaar, Elka Stefanova, Latchezar Traykov, Giancarlo Logroscino
Summary: FRONTIERS is a European research study aimed at improving the understanding of FTLD-related disorders and their epidemiology, with the goal of promoting appropriate public health service policies and treatment strategies.
ALZHEIMERS & DEMENTIA
(2022)
Article
Clinical Neurology
Negin Holland, Maura Malpetti, Timothy Rittman, Elijah E. Mak, Luca Passamonti, Sanne S. Kaalund, Frank H. Hezemans, P. Simon Jones, George Savulich, Young T. Hong, Tim D. Fryer, Franklin Aigbirhio, John T. O'Brien, James B. Rowe
Summary: The relationship between in vivo synaptic density and molecular pathology in primary tauopathies, especially in progressive supranuclear palsy and corticobasal degeneration, is investigated in this study. It is found that there is a biphasic correlation between synaptic density and molecular pathology, with regions rich in synapses more vulnerable to pathological aggregates accumulation, followed by synaptic loss as a response to the molecular pathology. These findings contribute to a better understanding of the pathophysiology of primary tauopathies and may inform the design of future clinical trials.
Article
Clinical Neurology
Georgia Peakman, Lucy L. Russell, Rhian S. Convery, Jennifer M. Nicholas, John C. Van Swieten, Lize C. Jiskoot, Fermin Moreno, Raquel Sanchez-Valle, Robert Laforce, Caroline Graff, Mario Masellis, Maria Carmela Tartaglia, James B. Rowe, Barbara Borroni, Elizabeth Finger, Matthis Synofzik, Daniela Galimberti, Rik Vandenberghe, Alexandre de Mendonca, Chris R. Butler, Alex Gerhard, Simon Ducharme, Isabelle Le Ber, Fabrizio Tagliavini, Isabel Santana, Florence Pasquier, Johannes Levin, Adrian Danek, Markus Otto, Sandro Sorbi, Jonathan D. Rohrer
Summary: The study compared the CDR+NACC FTLD and FRS in genetic forms of FTD, finding that both measures were correlated with disease severity in mutation carriers. However, discrepancies in disease staging were observed between the two scales and with clinician-judged symptomatic status. The study suggests that a new scale incorporating key symptoms in the FTD spectrum may be needed in future assessments.
JOURNAL OF NEUROLOGY NEUROSURGERY AND PSYCHIATRY
(2022)
Letter
Clinical Neurology
Linn Oijerstedt, Christin Andersson, Vesna Jelic, John Cornelis van Swieten, Lize C. Jiskoot, Harro Seelaar, Barbara Borroni, Raquel Sanchez-Valle, Fermin Moreno, Robert Laforce, Matthis Synofzik, Daniela Galimberti, James Benedict Rowe, Mario Masellis, Maria Carmela Tartaglia, Elizabeth Finger, Rik Vandenberghe, Alexandre de Mendonca, Fabrizio Tagliavini, Isabel Santana, Simon Ducharme, Christopher R. Butler, Alexander Gerhard, Johannes Levin, Adrian Danek, Markus Otto, Giovanni Frisoni, Roberta Ghidoni, Sandro Sorbi, Jonathan Daniel Rohrer, Caroline Graff
JOURNAL OF NEUROLOGY NEUROSURGERY AND PSYCHIATRY
(2022)
Article
Clinical Neurology
Carlo Wilke, Selina Reich, John C. van Swieten, Barbara Borroni, Raquel Sanchez-Valle, Fermin Moreno, Robert Laforce, Caroline Graff, Daniela Galimberti, James B. Rowe, Mario Masellis, Maria C. Tartaglia, Elizabeth Finger, Rik Vandenberghe, Alexandre de Mendonca, Fabrizio Tagliavini, Isabel Santana, Simon Ducharme, Chris R. Butler, Alexander Gerhard, Johannes Levin, Adrian Danek, Markus Otto, Giovanni Frisoni, Roberta Ghidoni, Sandro Sorbi, Martina Bocchetta, Emily Todd, Jens Kuhle, Christian Barro, Jonathan D. Rohrer, Matthis Synofzik
Summary: This study provides a biomarker cascade for the conversion stage in presymptomatic frontotemporal dementia, using serum neurofilament levels to stratify individuals in different stages and potentially identify those converting to symptomatic disease. The biomarker cascade may pave the way towards a biomarker-based precision medicine approach to genetic FTD.
ANNALS OF NEUROLOGY
(2022)
Article
Clinical Neurology
Emma L. van der Ende, Esther E. Bron, Jackie M. Poos, Lize C. Jiskoot, Jessica L. Panman, Janne M. Papma, Lieke H. Meeter, Elise G. P. Dopper, Carlo Wilke, Matthis Synofzik, Carolin Heller, Imogen J. Swift, Aitana Sogorb-Esteve, Arabella Bouzigues, Barbara Borroni, Raquel Sanchez-Valle, Fermin Moreno, Caroline Graff, Robert Laforce, Daniela Galimberti, Mario Masellis, Maria Carmela Tartaglia, Elizabeth Finger, Rik Vandenberghe, James B. Rowe, Alexandre de Mendonca, Fabrizio Tagliavini, Isabel Santana, Simon Ducharme, Christopher R. Butler, Alexander Gerhard, Johannes Levin, Adrian Danek, Markus Otto, Yolande A. L. Pijnenburg, Sandro Sorbi, Henrik Zetterberg, Wiro J. Niessen, Jonathan D. Rohrer, Stefan Klein, John C. van Swieten, Vikram Venkatraghavan, Harro Seelaar
Summary: This study aimed to model the sequence of biomarker abnormalities in genetic frontotemporal dementia and determine the disease stages of patients. The results showed that NPTX2 and neurofilament light chain were the earliest biomarkers to change. This model could help select suitable patients for pharmaceutical trials and improve patient stratification and tracking of therapeutic interventions.
Letter
Clinical Neurology
Annita Christodoulidou, Georgina E. McKenna, Simon T. Holden, James B. Rowe, Thomas E. Cope
JOURNAL OF NEUROLOGY
(2022)
Article
Neurosciences
Ece Kocagoncu, David Nesbitt, Tina Emery, Laura E. Hughes, Richard N. Henson, James B. Rowe
Summary: The study focuses on cognitive frailty and compared the structural and neurophysiological properties of cognitively frail adults with Alzheimer’s disease and mild cognitive impairment. The results suggest that cognitive frailty may represent a spectrum of normal aging rather than the onset of Alzheimer’s disease.
JOURNAL OF NEUROSCIENCE
(2022)
Article
Astronomy & Astrophysics
Luca Cacciapuoti, Laura Inno, Giovanni Covone, Veselin B. Kostov, Thomas Barclay, Elisa Quintana, Knicole D. Colon, Keivan G. Stassun, Benjamin Hord, Steven Giacalone, Stephen R. Kane, Kelsey Hoffman, Jason Rowe, Gavin Wang, Kevin Collins, Karen A. Collins, Thiam-Guan Tan, Francesco Gallo, Christian Magliano, Riccardo M. Ienco, Markus Rabus, David R. Ciardi, Elise Furlan, Steve B. Howell, Crystal L. Gnilka, Nicholas J. Scott, Kathryn Lester, Carl Ziegler, Cesar Briceno, Nicholas Law, Andrew W. Mann, Christopher J. Burke, Samuel N. Quinn, Angelo Ciaramella, Pasquale De Luca, Stefano Fiscale, Alessandra Rotundi, Livia Marcellino, Ardelio Galletti, Ida Bifulco, Fabrizio Oliva, Alton Spencer, Lisa Kaltenegger, Scott McDermott, Zahra Essack, Jon M. Jenkins, Bill Wohler, Joshua N. Winn, S. Seager, Roland Vanderspek, George Zhou, Avi Shporer, Diana Dragomir, William Fong
Summary: We report the discovery of a three-planet system around the bright, Sun-like star HD 22946. Two planets have been validated, and a third potential planet has been identified. The system is dynamically stable and may have room for additional planets. Further study of the star and its planets could provide valuable insights into their masses and atmospheres.
ASTRONOMY & ASTROPHYSICS
(2022)
Article
Astronomy & Astrophysics
Antoine Darveau-Bernier, Loic Albert, Geert Jan Talens, David Lafreniere, Michael Radica, Rene Doyon, Neil J. Cook, Jason F. Rowe, Romain Allart, Etienne Artigau, Bjorn Benneke, Nicolas Cowan, Lisa Dang, Nestor Espinoza, Doug Johnstone, Lisa Kaltenegger, Olivia Lim, Tyler Pauly, Stefan Pelletier, Caroline Piaulet, Arpita Roy, Pierre-Alexis Roy, Jared Splinter, Jake Taylor, Jake D. Turner
Summary: The SOSS mode of the NIRISS instrument is specifically designed for characterizing the atmospheres of exoplanets, but due to mechanical constraints, there is a potential contamination signal in the extracted spectrum.
PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF THE PACIFIC
(2022)
Article
Cell Biology
Ashwin V. Venkataraman, Ayla Mansur, Gaia Rizzo, Courtney Bishop, Yvonne Lewis, Ece Kocagoncu, Anne Lingford-Hughes, Mickael Huiban, Jan Passchier, James B. Rowe, Hideo Tsukada, David J. Brooks, Laurent Martarello, Robert A. Comley, Laigao Chen, Adam J. Schwarz, Richard Hargreaves, Roger N. Gunn, Eugenii A. Rabiner, Paul M. Matthews
Summary: This study provides in vivo evidence for the widespread presence of cellular stress and bioenergetic abnormalities in early-stage Alzheimer's disease, which could be helpful for early diagnosis and treatment.
SCIENCE TRANSLATIONAL MEDICINE
(2022)
Article
Astronomy & Astrophysics
James Sikora, Jason Rowe, Daniel Jontof-Hutter, Jack J. J. Lissauer
Summary: Kepler-33 is a star system with five validated planets, with periods ranging from 5 to 41 days. These planets have nearly coplanar orbits and exhibit similar transit durations, indicating similar impact parameters. Photodynamical analysis of transit timing variations provides upper limits on the eccentricity of the planets' orbits and the host star's mean density. By combining observational data and modeling, we were able to determine the masses and envelope mass fractions of the planets.
ASTRONOMICAL JOURNAL
(2022)
Review
Clinical Neurology
Kausar Raheel, Gemma Deegan, Irene Di Giulio, Diana Cash, Katarina Ilic, Valentina Gnoni, K. Ray Chaudhuri, Panagis Drakatos, Rosalyn Moran, Ivana Rosenzweig
Summary: Past research suggests that there are more cases and severe clinical manifestations of alpha-synucleinopathies in men, indicating potential neuroprotective properties of female sex hormones, especially estrogen. However, the underlying mechanisms of this effect are not well understood. This study aimed to systematically review and critically assess the current evidence on sex and gender differences in alpha-synucleinopathies.
FRONTIERS IN NEUROLOGY
(2023)
Article
Clinical Neurology
Joseph Giorgio, Ankeet Tanna, Maura Malpetti, Simon R. White, Jingshen Wang, Suzanne Baker, Susan Landau, Tomotaka Tanaka, Christopher Chen, James B. Rowe, John O'Brien, Jurgen Fripp, Michael Breakspear, William Jagust, Zoe Kourtzi
Summary: This study used a two-stage approach to harmonize cognitive data from different cohorts and derive a cross-cohort score for cognitive impairment due to AD. The results showed that the cognitive composites were robust across cohorts and achieved comparable sensitivity to AD-related cognitive decline. This approach offers a simple and effective way for researchers to harmonize and pool cognitive data for the study of cognitive decline in AD.
ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING
(2023)