Article
Neurosciences
Nathaniel Klooster, Stacey Humphries, Eileen Cardillo, Franziska Hartung, Long Xie, Sandhitsu Das, Paul Yushkevich, Arun Pilania, Jieqiong Wang, David A. Wolk, Anjan Chatterjee
Summary: The study found that experimental tests of semantic memory and figurative language were more sensitive to early cognitive impairment in individuals with mild cognitive impairment (MCI), reflecting structural integrity in the medial temporal lobe. These tests showed specificity in distinguishing different cognitive states and could be useful tools for tracking cognitive change in early intervention clinical trials.
JOURNAL OF ALZHEIMERS DISEASE
(2021)
Article
Clinical Neurology
Giulia Buzi, Chiara Fornari, Alessio Perinelli, Veronica Mazza
Summary: This meta-analysis revealed a decrease in alpha synchrony in the brain during the early stages of Mild Cognitive Impairment (MCI), particularly in the temporal-parietal and frontal-parietal regions. These findings suggest that synchrony measures have promise in detecting early pathological markers of connectivity alterations in Alzheimer's disease (AD).
CLINICAL NEUROPHYSIOLOGY
(2023)
Article
Neurosciences
Akram A. Hosseini, Thomas Brown, Luca Mannino, Bruno Gran, Kehinde Junaid, Elizabeta B. Mukaetova-Ladinska
Summary: This study conducted diagnostic lumbar puncture in patients with early onset Alzheimer's or related dementias and evaluated the measurements of amyloid-beta 42 (A beta(42)), total tau, and Thr181-phosphorylated tau (p-tau) in the cerebrospinal fluid (CSF). The results showed that low levels of CSF A beta(42) appear to be more sensitive than total and p-tau measures in differentiating AD MCI from other forms of dementia.
JOURNAL OF ALZHEIMERS DISEASE
(2022)
Article
Clinical Neurology
Alexa Pichet Binette, Sebastian Palmqvist, Divya Bali, Gill Farrar, Christopher J. Buckley, David A. Wolk, Henrik Zetterberg, Kaj Blennow, Shorena Janelidze, Oskar Hansson
Summary: This study found that the combination of plasma p-tau217 and a brief cognitive composite score is strongly associated with the risk of progression to AD dementia in MCI patients. These findings suggest that these measures could be key components of future prognostic algorithms for early AD.
ALZHEIMERS RESEARCH & THERAPY
(2022)
Article
Neurosciences
Paul Loyd Wheeler, Claire Murphy
Summary: Olfactory biomarkers show promise as non-invasive indicators of prodromal AD, particularly in ε4 carriers. Combining odor familiarity and odor identification has higher predictive value for conversion to MCI and AD compared to MMSE.
Article
Physics, Fluids & Plasmas
Rhombik Roy, Barnali Chakrabarti, N. D. Chavda, M. L. Lekala
Summary: This work presents different information theoretic measures for interacting bosons in an optical lattice, including Shannon information entropy, order, disorder, complexity, and their dynamical measure. The many-body Schrodinger equation is solved using the multiconfigurational time-dependent Hartree method to accurately calculate all the measures. The Lopez-Ruiz-Mancini-Calbet (LMC) measure of complexity is found to be the most effective descriptor of superfluid to Mott-insulator transition. The distinct structure of LMC complexity is used to determine the timescale and dynamics of the transition. Fluctuations in LMC complexity measure indicate an incomplete transition for incommensurate filling. Overall, the study concludes that complexity is more sensitive than Shannon information entropy.
Article
Neurosciences
Hamed Azami, Elham Daftarifard, Anne Humeau-Heurtier, Alberto Fernandez, Daniel Abasolo, Tarek K. Rajji
Summary: This study compared the performance of twenty nonlinear dynamical measures in studying Alzheimer's disease (AD) versus mild cognitive impairment (MCI) and healthy control (HC) subjects using magnetoencephalogram (MEG). The results showed that fuzzy dispersion entropy (FuzDispEn) was the most consistent technique in distinguishing MEG dynamical patterns in AD compared with HC and MCI.
JOURNAL OF ALZHEIMERS DISEASE
(2023)
Article
Clinical Neurology
Marina Ritchie, Daniel L. Gillen, Joshua D. Grill
Summary: The study found that longer duration trials are associated with lower completion rates, especially in AD and MCI trials, where the dropout rates in the treatment arms were higher than in the placebo arms.
ALZHEIMERS RESEARCH & THERAPY
(2023)
Review
Biochemistry & Molecular Biology
Vasileios Papaliagkas, Kallirhoe Kalinderi, Patroklos Vareltzis, Despoina Moraitou, Theodora Papamitsou, Maria Chatzidimitriou
Summary: Alzheimer's disease (AD) is a rapidly growing disease that urgently requires early diagnosis and treatment. Cerebrospinal fluid (CSF), which directly contacts the brain's extracellular space, is the most useful biological fluid for reflecting molecular events in the brain. Proteins and molecules that reflect the pathogenesis of AD, including neurodegeneration, accumulation of Abeta, hyperphosphorylation of tau protein, and apoptosis, can be used as biomarkers. The most commonly used CSF biomarkers for AD are total tau, phospho-tau, and Abeta42.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Biochemistry & Molecular Biology
Wenjing Li, Yinhua Zhou, Zhaofan Luo, Rixin Tang, Yuxuan Sun, Qiangsheng He, Bin Xia, Kuiqing Lu, Qinghua Hou, Jinqiu Yuan
Summary: This study aims to construct a lipid score system to predict the risk of progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD). The results showed that the lipid score system based on serum lipidomics can accurately predict the progression risk from MCI to AD.
Article
Computer Science, Information Systems
Taha Khan, Peter G. Jacobs
Summary: This study utilized SVM framework based on movement analysis to predict the onset and progression of mild cognitive impairment. The results showed that the model could detect the onset six months earlier and the feature of cyclomatic complexity significantly contributed to the prediction results.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2021)
Article
Neurosciences
Marina Botello-Marabotto, M. Carmen Martinez-Bisbal, Miguel Calero, Andrea Bernardos, Ana B. Pastor, Miguel Medina, Ramon Martinez-Manez
Summary: This study employed 1H NMR spectroscopy to conduct a metabolomic study in serum samples from patients with Alzheimer's disease (AD), mild cognitive impairment (MCI), and cognitively healthy controls (HC). The aim was to search for potential metabolite biomarkers. The results highlight the potential of 1H NMR metabolomics to support the diagnosis of dementia in a less invasive way, and provide a starting point for the study of potential biomarkers to identify MCI or HC subjects at risk of developing AD in the future.
NEUROBIOLOGY OF DISEASE
(2023)
Article
Clinical Neurology
Egle Audronyte, Vaiva Sutnikiene, Gyte Pakulaite-Kazliene, Gintaras Kaubrys
Summary: This study investigated olfactory memory and its relationship with verbal memory and other clinical features in patients with early-stage Alzheimer's disease (AD). The results showed that olfactory memory was significantly impaired in patients with AD compared to individuals with mild cognitive impairment due to AD and cognitively normal older participants. Furthermore, the duration of AD symptoms was a strong predictor of olfactory recognition memory scores.
FRONTIERS IN NEUROLOGY
(2023)
Article
Geriatrics & Gerontology
Hillary J. Rouse, Zahinoor Ismail, Ross Andel, Victor A. Molinari, John A. Schinka, Brent J. Small
Summary: This study examined the impact of mild behavioral impairment (MBI) on cognitive performance among cognitively healthy older adults and those with mild cognitive impairment (MCI). The results showed that individuals with MBI performed worse on tasks of attention, episodic memory, executive function, language, and processing speed, and exhibited greater decline over time. The presence of MBI was also associated with poorer performance on tasks of visuospatial ability, executive function, and processing speed among individuals with MCI.
JOURNALS OF GERONTOLOGY SERIES A-BIOLOGICAL SCIENCES AND MEDICAL SCIENCES
(2023)
Article
Geriatrics & Gerontology
Eun Jin Yoon, Jun-Young Lee, Seyul Kwak, Yu Kyeong Kim
Summary: Mild behavioral impairment (MBI) is a neurobehavioral syndrome associated with a higher risk of progression to Alzheimer's disease (AD) in individuals with amnestic mild cognitive impairment (MCI). The presence of multiple MBI domains is also associated with cortical thinning in specific brain regions.
FRONTIERS IN AGING NEUROSCIENCE
(2023)
Article
Clinical Neurology
Ricardo Bruna, David Lopez-Sanz, Fernando Maestu, Ann D. Cohen, Anto Bagic, Ted Huppert, Tae Kim, Rebecca E. Roush, Betz Snitz, James T. Becker
Summary: This study investigated the mechanisms behind Alzheimer's disease and found that patients with amnestic MCI showed a slowing of brain activity, which was not observed in individuals without subjective complaints. This raises interesting questions about this particular group of individuals and the underlying brain mechanisms behind their cognitive impairment.
CLINICAL EEG AND NEUROSCIENCE
(2023)
Article
Clinical Neurology
Yasunori Aoki, Hiroaki Kazui, Roberto D. Pascual-Marqui, Ricardo Bruna, Kenji Yoshiyama, Tamiki Wada, Hideki Kanemoto, Yukiko Suzuki, Takashi Suehiro, Yuto Satake, Maki Yamakawa, Masahiro Hata, Leonides Canuet, Ryouhei Ishii, Masao Iwase, Manabu Ikeda
Summary: This study applied the NPV analysis method to analyze iNPH patients and found significant differences between shunt responders and non-responders. NPV, as a sensitive early warning signal, can be used to represent cortical impairment.
CLINICAL EEG AND NEUROSCIENCE
(2023)
Article
Geriatrics & Gerontology
Brenda Chino, Pablo Cuesta, Javier Pacios, Jaisalmer de Frutos-Lucas, Lucia Torres-Simon, Sandra Doval, Alberto Marcos, Ricardo Bruna, Fernando Maestu
Summary: Delayed recall (DR) impairment is a significant predictive factor for the progression to Alzheimer's disease (AD). Changes in brain functional connectivity (FC) accompany the decline in DR performance, and the relationship between the two phenomena has attracted interest. The APOE genotype may play a moderator role in this association. Higher FC in the beta band in the right occipital region is associated with lower DR scores, with an anteroposterior link observed in MCI. APOE genotype moderates the association between beta FC and DR performance in the CI group.
Article
Computer Science, Interdisciplinary Applications
Eduardo Santamaria-Vazquez, Victor Martinez-Cagigal, Diego Marcos-Martinez, Victor Rodriguez-Gonzalez, Sergio Perez-Velasco, Selene Moreno-Calderon, Roberto Hornero
Summary: This study aimed to propose a novel software ecosystem called MEDUSA to overcome the barriers in bringing neurotechnologies to the general public. MEDUSA (c) provides a complete suite of signal processing functions and ready-to-use BCI and neuroscience experiments, making it one of the most complete solutions nowadays. It also facilitates the development of custom experiments and encourages community participation for the progress of these fields.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2023)
Article
Biology
Adrian Martin-Montero, Pablo Armanc-Julian, Eduardo Gil, Leila Kheirandish-Gozal, Daniel Alvarez, Jesus Lazaro, Raquel Bailon, David Gozal, Pablo Laguna, Roberto Hornero, Gonzalo C. Gutierrez-Tobal
Summary: Heart rate variability (HRV) is influenced by sleep stages and apneic events. Previous studies in children have compared classical HRV parameters during sleep stages between obstructive sleep apnea (OSA) and control groups. However, there has been no comprehensive study that incorporates both sleep stages and apneic events to characterize HRV. Additionally, novel OSA-specific HRV parameters have not been evaluated.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Biology
Diego Marcos-Martinez, Eduardo Santamaria-Vazquez, Victor Martinez-Cagigal, Sergio Perez-Velasco, Victor Rodriguez-Gonzalez, Ana Martin-Fernandez, Selene Moreno-Calderon, Roberto Hornero
Summary: ITACA is an open-source framework for designing, implementing, and evaluating neurofeedback (NF) training paradigms. It offers a variety of features, including gamified training scenarios and real-time feedback based on different brain activity metrics. Computational efficiency analysis and an NF training protocol support the effectiveness of ITACA in NF research studies.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Engineering, Biomedical
Marcos Revilla-Vallejo, Carlos Gomez, Javier Gomez-Pilar, Roberto Hornero, Miguel Angel Tola-Arribas, Monica Cano, Yoshihito Shigihara, Hideyuki Hoshi, Jesus Poza
Summary: This study aims to introduce a new methodology to evaluate network robustness and apply it to assess the brain activity in Alzheimer's disease (AD) patients. By simulating attacks on functional connectivity networks and evaluating the network changes through Spearman's correlation, significant differences in network robustness were found between controls, mild cognitive impairment subjects, and AD patients in three different databases. Furthermore, the changes in network robustness were found to be associated with the progressive deterioration in brain functioning due to AD.
JOURNAL OF NEURAL ENGINEERING
(2023)
Article
Biology
Fernando Vaquerizo-Villar, Gonzalo C. Gutierrez-Tobal, Eva Calvo, Daniel Alvarez, Leila Kheirandish-Gozal, Felix del Campo, David Gozal, Roberto Hornero
Summary: This study developed an accurate and interpretable deep-learning model for sleep staging in children using single-channel EEG data. The results showed that a standard CNN demonstrated the highest performance for automated sleep stage detection, and the CNN-based estimation of total sleep time exhibited strong agreement in the clinical dataset. The study also used the explainable AI algorithm Grad-CAM to highlight the EEG features associated with each sleep stage.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Neurosciences
Victor Rodriguez-Gonzalez, Pablo Nunez, Carlos Gomez, Yoshihito Shigihara, Hideyuki Hoshi, Miguel Angel Tola-Arribas, Monica Cano, Angel Guerrero, David Garcia-Azorin, Roberto Hornero, Jesus Poza
Summary: This study introduces a new data-driven method to automatically identify frequency ranges based on the topological similarity of the frequency-dependent functional neural network. The analysis of resting-state neural activity from 195 cognitively healthy subjects showed that the traditional approaches to band segmentation align with the underlying network topologies at a group level for MEG signals, but lack individual idiosyncrasies. EEG signals, on the other hand, have limited sensitivity to reflect the underlying frequency-dependent network structure.
Article
Chemistry, Analytical
Ricardo Bruna, Giorgio Fuggetta, Ernesto Pereda
Summary: This work examines several different definitions for the electrical lead field of a four concentric spheres conduction model and finds contradictory results. Through a thorough exploration of mathematics, errors in some formulas are identified and a formulation to solve the lead field in a head model built from arbitrary concentric spheres is developed.
Article
Computer Science, Artificial Intelligence
Victor Martinez-Cagigal, Eduardo Santamaria-Vazquez, Sergio Perez-Velasco, Diego Marcos-Martinez, Selene Moreno-Calderon, Roberto Hornero
Summary: This study proposes the use of non-binary p-ary m-sequences as a more pleasant alternative to traditional binary codes. It is found that all p-ary m-sequences are suitable for achieving high speed and high accuracy in c-VEP-based BCIs, and they can reduce visual fatigue as the base increases.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Biology
Clara Garcia-Vicente, Gonzalo C. Gutierrez-Tobal, Jorge Jimenez-Garcia, Adrian Martin-Montero, David Gozal, Roberto Hornero
Summary: A novel deep-learning approach using raw electrocardiogram tracing (ECG) was proposed to simplify the diagnosis of pediatric OSA. A convolutional neural network (CNN) regression model was implemented to predict pediatric OSA and derive severity categories. The diagnostic performance of the CNN model outperformed previous algorithms relying on ECG-derived features. The proposed CNN model provides a simpler, faster, and more accessible diagnostic test for pediatric OSA.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Engineering, Biomedical
Jorge Jimenez-Garcia, Maria Garcia, Gonzalo C. Gutierrez-Tobal, Leila Kheirandish-Gozal, Fernando Vaquerizo-Villar, Daniel Alvarez, Felix del Campo, David Gozal, Roberto Hornero
Summary: In this study, an explainable architecture that combines convolutional and recurrent neural networks (CNN + RNN) was assessed to detect pediatric obstructive sleep apnea (OSA) and its severity. By analyzing overnight airflow (AF) and oximetry (SpO(2)) signals, the model provides an alternative diagnostic approach with high accuracy.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Victor Rodriguez-Gonzalez, Pablo Nunez, Carlos Gomez, Hideyuki Hoshi, Yoshihito Shigihara, Roberto Hornero, Jesus Poza
Summary: This study used a novel methodology called Connectivity-based Meta-Bands (CMB) to analyze individual MEG data and found that mild cognitive impairment and Alzheimer's disease could alter the neural network topology and dilute the frequency structure progressively.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)