Takufumi Yanagisawa
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View article: Correction: Accurate deep-learning model to differentiate dementia severity and diagnosis using a portable electroencephalography device
Correction: Accurate deep-learning model to differentiate dementia severity and diagnosis using a portable electroencephalography device Open
View article: Effects of publicly available non-invasive brain stimulation on attentional functions in healthy adults: A systematic review and meta-analysis
Effects of publicly available non-invasive brain stimulation on attentional functions in healthy adults: A systematic review and meta-analysis Open
Public interest in attention enhancement is increasing. However, the efficacy of publicly available non-invasive brain stimulation (NIBS), such as transcranial direct current stimulation (tDCS), remains uncertain. We conducted a pre-regist…
View article: EvoBrain: Dynamic Multi-Channel EEG Graph Modeling for Time-Evolving Brain Networks
EvoBrain: Dynamic Multi-Channel EEG Graph Modeling for Time-Evolving Brain Networks Open
Dynamic GNNs, which integrate temporal and spatial features in Electroencephalography (EEG) data, have shown great potential in automating seizure detection. However, fully capturing the underlying dynamics necessary to represent brain sta…
View article: Microendovascular Neural Recording from Cortical and Deep Vessels with High Precision and Minimal Invasiveness
Microendovascular Neural Recording from Cortical and Deep Vessels with High Precision and Minimal Invasiveness Open
Intravascular electroencephalography (ivEEG) with microintravascular electrodes enhances neural monitoring, functional mapping, and brain–computer interfaces (BCIs), offering a minimally invasive approach to assess cortical activities; how…
View article: Inferring amyloid pathologies among patients with mild cognitive impairment using phase‒amplitude coupling of electroencephalography: A case‒control study
Inferring amyloid pathologies among patients with mild cognitive impairment using phase‒amplitude coupling of electroencephalography: A case‒control study Open
Theta-high gamma PAC in resting-state EEG can distinguish amyloid PET-positive patients with MCI from PET-negative patients, thereby providing a feasible, noninvasive biomarker for AD pathology. Integrating PAC analysis into routine EEG co…
View article: Accurate deep-learning model to differentiate dementia severity and diagnosis using a portable electroencephalography device
Accurate deep-learning model to differentiate dementia severity and diagnosis using a portable electroencephalography device Open
Mild cognitive impairment (MCI) and dementia pose significant health challenges in aging societies, emphasizing the need for accessible, cost-effective, and noninvasive diagnostic tools. Electroencephalography (EEG) is a promising biomarke…
View article: Intrinsic frequency distribution characterises neural dynamics
Intrinsic frequency distribution characterises neural dynamics Open
Decomposing multivariate time series with certain basic dynamics is crucial for understanding, predicting and controlling nonlinear spatiotemporally dynamic systems such as the brain. Dynamic mode decomposition (DMD) is a method for decomp…
View article: Wirelessly transmitted subthalamic nucleus signals predict endogenous pain levels in Parkinson's disease patients
Wirelessly transmitted subthalamic nucleus signals predict endogenous pain levels in Parkinson's disease patients Open
Parkinson disease (PD) patients experience pain fluctuations that significantly reduce their quality of life. Despite the vast knowledge of the subthalamic nucleus (STN) role in PD, the STN biomarkers for pain fluctuations and the relation…
View article: Neurofeedback modulation of insula activity via MEG-based brain-machine interface: a double-blind randomized controlled crossover trial
Neurofeedback modulation of insula activity via MEG-based brain-machine interface: a double-blind randomized controlled crossover trial Open
Insula activity has often been linked to pain perception, making it a potential target for therapeutic neuromodulation strategies such as neurofeedback. However, it is not known whether insula activity is under cognitive control and, if so…
View article: Decoding cortical responses from visual input using an endovascular brain–computer interface
Decoding cortical responses from visual input using an endovascular brain–computer interface Open
Objective. Implantable neural interfaces enable recording of high-quality brain signals that can improve our understanding of brain function. This work examined the feasibility of using a minimally invasive endovascular neural interface (E…
View article: Abnormal Synchronization Between Cortical Delta Power and Ripples in Hippocampal Sclerosis
Abnormal Synchronization Between Cortical Delta Power and Ripples in Hippocampal Sclerosis Open
Objective Discriminating between epileptogenic and physiological ripples in the hippocampus is important for identifying epileptogenic (EP) zones; however, distinguishing these ripples on the basis of their waveforms is difficult. We hypot…
View article: Beta-gamma phase-amplitude coupling of scalp electroencephalography during walking preparation in Parkinson’s disease differs depending on the freezing of gait
Beta-gamma phase-amplitude coupling of scalp electroencephalography during walking preparation in Parkinson’s disease differs depending on the freezing of gait Open
Introduction Despite using beta oscillations within the subthalamic nucleus as a biomarker of akinesia or rigidity in Parkinson’s disease, a specific biomarker for freezing of gait (FOG) remains unclear. Recently, scalp phase-amplitude cou…
View article: Accurate deep-learning model to differentiate dementia severity and diagnosis using a portable electroencephalography device
Accurate deep-learning model to differentiate dementia severity and diagnosis using a portable electroencephalography device Open
Mild cognitive impairment (MCI) and dementia present critical health challenges in aging populations, highlighting the need for prompt and accurate diagnostic methods. Current diagnostic approaches for dementia are constrained by limited a…
View article: M/EEG source localization for both subcortical and cortical sources using a convolutional neural network with a realistic head conductivity model
M/EEG source localization for both subcortical and cortical sources using a convolutional neural network with a realistic head conductivity model Open
While electroencephalography (EEG) and magnetoencephalography (MEG) are well-established noninvasive methods in neuroscience and clinical medicine, they suffer from low spatial resolution. Electrophysiological source imaging (ESI) addresse…
View article: SplitSEE: A Splittable Self-supervised Framework for Single-Channel EEG Representation Learning
SplitSEE: A Splittable Self-supervised Framework for Single-Channel EEG Representation Learning Open
While end-to-end multi-channel electroencephalography (EEG) learning approaches have shown significant promise, their applicability is often constrained in neurological diagnostics, such as intracranial EEG resources. When provided with a …
View article: A microendovascular system can record precise neural signals from cortical and deep vessels with minimal invasiveness
A microendovascular system can record precise neural signals from cortical and deep vessels with minimal invasiveness Open
Minimally invasive intravascular electroencephalography (ivEEG) signals are a promising tool for developing clinically feasible brain–computer interfaces (BCIs) that restore communication and motor functions in paralyzed patients. However,…
View article: Image retrieval based on closed-loop visual–semantic neural decoding
Image retrieval based on closed-loop visual–semantic neural decoding Open
Neural decoding via the latent space of deep neural network models can infer perceived and imagined images from neural activities, even when the image is novel for the subject and decoder. Brain-computer interfaces (BCIs) using the latent …
View article: Nocturnal synchronization between hippocampal ripples and cortical delta power is a biomarker of hippocampal epileptogenicity
Nocturnal synchronization between hippocampal ripples and cortical delta power is a biomarker of hippocampal epileptogenicity Open
Objective Hippocampal ripples are biomarkers of epileptogenicity in patients with epilepsy, and physiological features characterize memory function in healthy individuals. Discriminating between pathological and physiological ripples is im…
View article: Hippocampal sharp-wave ripples correlate with periods of naturally occurring self-generated thoughts in humans
Hippocampal sharp-wave ripples correlate with periods of naturally occurring self-generated thoughts in humans Open
Core features of human cognition highlight the importance of the capacity to focus on information distinct from events in the here and now, such as mind wandering. However, the brain mechanisms that underpin these self-generated states rem…
View article: Fast, accurate, and interpretable decoding of electrocorticographic signals using dynamic mode decomposition
Fast, accurate, and interpretable decoding of electrocorticographic signals using dynamic mode decomposition Open
Dynamic mode (DM) decomposition decomposes spatiotemporal signals into basic oscillatory components (DMs). DMs can improve the accuracy of neural decoding when used with the nonlinear Grassmann kernel, compared to conventional power featur…
View article: Neurofeedback modulation of insula activity via MEG-based brain-machine interface: A double-blind randomized controlled crossover trial
Neurofeedback modulation of insula activity via MEG-based brain-machine interface: A double-blind randomized controlled crossover trial Open
Insula activity has often been linked to pain perception, making it a potential target for therapeutic neuromodulation strategies such as neurofeedback. However, it is not known whether insula activity is under cognitive control and, if so…
View article: Text and image generation from intracranial electroencephalography using an embedding space for text and images
Text and image generation from intracranial electroencephalography using an embedding space for text and images Open
Objective. Invasive brain–computer interfaces (BCIs) are promising communication devices for severely paralyzed patients. Recent advances in intracranial electroencephalography (iEEG) coupled with natural language processing have enhanced …
View article: Brain-aligning of semantic vectors improves neural decoding of visual stimuli
Brain-aligning of semantic vectors improves neural decoding of visual stimuli Open
The development of algorithms to accurately decode neural information has long been a research focus in the field of neuroscience. Brain decoding typically involves training machine learning models to map neural data onto a preestablished …
View article: Is Phantom Limb Awareness Necessary for the Treatment of Phantom Limb Pain?
Is Phantom Limb Awareness Necessary for the Treatment of Phantom Limb Pain? Open
Phantom limb pain is attributed to abnormal sensorimotor cortical representations. Various feedback treatments have been applied to induce the reorganization of the sensorimotor cortical representations to reduce pain. We developed a train…
View article: A deep learning model for the detection of various dementia and MCI pathologies based on resting-state electroencephalography data: A retrospective multicentre study
A deep learning model for the detection of various dementia and MCI pathologies based on resting-state electroencephalography data: A retrospective multicentre study Open
Dementia and mild cognitive impairment (MCI) represent significant health challenges in an aging population. As the search for noninvasive, precise and accessible diagnostic methods continues, the efficacy of electroencephalography (EEG) c…
View article: Fast, accurate, and interpretable decoding of electrocorticographic signals using dynamic mode decomposition
Fast, accurate, and interpretable decoding of electrocorticographic signals using dynamic mode decomposition Open
Dynamic mode (DM) decomposition decomposes spatiotemporal signals into basic oscillatory components (DMs). DMs can improve the accuracy of neural decoding when used with the nonlinear Grassmann kernel, compared to conventional power featur…
View article: Characteristics of Changes in Intrathecal Baclofen Dosage over Time due to Causative Disease
Characteristics of Changes in Intrathecal Baclofen Dosage over Time due to Causative Disease Open
Intrathecal baclofen (ITB) therapy effectively treats spasticity caused by brain or spinal cord lesions. However, only a few studies compare the course of treatment for different diseases. We investigated the change in daily dose of baclof…
View article: Hippocampal sharp-wave ripples correlate with naturally occurring self-generated thoughts in humans
Hippocampal sharp-wave ripples correlate with naturally occurring self-generated thoughts in humans Open
Core features of human cognition, for example, the experience of mind wandering, highlight the importance of the capacity to focus on information separate from the here and now. However, the brain mechanisms that underpin these self-genera…
View article: Hippocampal sharp-wave ripples correlate with naturally occurring self-generated thoughts in humans
Hippocampal sharp-wave ripples correlate with naturally occurring self-generated thoughts in humans Open
Core features of human cognition, for example, the experience of mind wandering, highlight the importance of the capacity to focus on information separate from the here and now. However, the brain mechanisms that underpin these self-genera…
View article: Hippocampal neural fluctuation between memory encoding and retrieval states during a working memory task in humans
Hippocampal neural fluctuation between memory encoding and retrieval states during a working memory task in humans Open
Background Working memory (WM) is essential for everyday life, yet its neural mechanism remains unclear. Although the hippocampus plays a critical role in memory consolidation and retrieval, its role in WM tasks has yet to be fully elucida…