Takufumi Yanagisawa - Academia.edu (original) (raw)

Papers by Takufumi Yanagisawa

Research paper thumbnail of Fast, accurate, and interpretable decoding of electrocorticographic signals using dynamic mode decomposition

Communications biology, May 18, 2024

Research paper thumbnail of Endogenous controllability of closed-loop brain-machine interfaces for pain

Research paper thumbnail of Hippocampal neural fluctuation between memory encoding and retrieval states during a working memory task in humans

bioRxiv (Cold Spring Harbor Laboratory), Apr 28, 2023

Research paper thumbnail of Beta rhythmicity in human motor cortex reflects neural population coupling that modulates subsequent finger coordination stability

Communications biology, Dec 15, 2022

Research paper thumbnail of Neural decoding of electrocorticographic signals using dynamic mode decomposition

Journal of Neural Engineering, 2020

Objective. Brain-computer interfaces (BCIs) using electrocorticographic (ECoG) signals have been ... more Objective. Brain-computer interfaces (BCIs) using electrocorticographic (ECoG) signals have been developed to restore the communication function of severely paralyzed patients. However, the limited amount of information derived from ECoG signals hinders their clinical applications. We aimed to develop a method to decode ECoG signals using spatiotemporal patterns characterizing movement types to increase the amount of information gained from these signals. Approach. Previous studies have demonstrated that motor information could be decoded using powers of specific frequency bands of the ECoG signals estimated by fast Fourier transform (FFT) or wavelet analysis. However, because FFT is evaluated for each channel, the temporal and spatial patterns among channels are difficult to evaluate. Here, we used dynamic mode decomposition (DMD) to evaluate the spatiotemporal pattern of ECoG signals and evaluated the accuracy of motor decoding with the DMD modes. We used ECoG signals during three...

Research paper thumbnail of S109 Magnetoencephalographic-based brain–machine interface robotic hand for controlling sensorimotor cortical plasticity and phantom limb pain

Clinical Neurophysiology, 2017

Research paper thumbnail of Hippocampal sharp-wave ripples correlate with periods of naturally occurring self-generated thoughts in humans

Nature communications, May 22, 2024

Research paper thumbnail of ヒト頭蓋内電極を用いた嚥下関連High γ帯域活動の解析

Japanese Journal of Clinical Neurophysiology

Research paper thumbnail of RESEARCH ARTICLE Closed-Loop Control of a Neuroprosthetic Hand by Magnetoencephalographic Signals

Objective A neuroprosthesis using a brain–machine interface (BMI) is a promising therapeutic opti... more Objective A neuroprosthesis using a brain–machine interface (BMI) is a promising therapeutic option for severely paralyzed patients, but the ability to control it may vary among individual patients and needs to be evaluated before any invasive procedure is undertaken. We have developed a neuroprosthetic hand that can be controlled by magnetoencephalographic (MEG) signals to noninvasively evaluate subjects ’ ability to control a neuroprosthesis. Method Six nonparalyzed subjects performed grasping or opening movements of their right hand while the slow components of the MEG signals (SMFs) were recorded in an open-loop con-dition. The SMFs were used to train two decoders to infer the timing and types of movement by support vector machine and Gaussian process regression. The SMFs were also used to calculate estimated slow cortical potentials (eSCPs) to identify the origin of motor informa-tion. Finally, using the trained decoders, the subjects controlled a neuroprosthetic hand in a clos...

Research paper thumbnail of Contour Fitting High Density Personalized 3 Dimensional Cortical Electrodes

Morris Shayne, M.D.1); Masayuki Hirata, M.D., Ph.D.1, 2); Tetsu Goto, M.D., Ph.D.1, 2); Kojiro Ma... more Morris Shayne, M.D.1); Masayuki Hirata, M.D., Ph.D.1, 2); Tetsu Goto, M.D., Ph.D.1, 2); Kojiro Matsushita1), Ph.D., Takufumi Yanagisawa, M.D., Ph.D.1); Youichi Saitoh, M.D., Ph.D.1); Haruhiko Kishima, M.D., Ph.D. 1); and Toshiki Yoshimine, M.D., Ph.D.1) 1) Department of Neurosurgery and 2) Division of Functional Diagnostic Sciences, Osaka University Graduate School of Medicine, Suita, Osaka, Japan

Research paper thumbnail of Decoding Visual Stimulus in Semantic Space from Electrocorticography Signals

2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2018

Recent studies using functional magnetic resonance imaging (fMRI) have enabled quantitative evalu... more Recent studies using functional magnetic resonance imaging (fMRI) have enabled quantitative evaluation of the semantic space during processing of visual stimuli. In the semantic space of the natural language processing model, called a skip-gram, decoders were shown to generalize to natural scenes of a movie that was not included in the training data of the decoders. Combined with electrocorticography (ECoG), which has a higher sampling rate than fMRI, this approach is expected to aid the development of a practical brain-machine interface. Here, we decoded vector representations of scenes within the semantic space of a skip-gram model to assess whether a decoder trained using ECoG features still generalizes to scenes new to the decoder.

Research paper thumbnail of Phase-amplitude coupling between infraslow and high-frequency activities well discriminates between the preictal and interictal states

Scientific Reports, 2021

Infraslow activity (ISA) and high-frequency activity (HFA) are key biomarkers for studying epilep... more Infraslow activity (ISA) and high-frequency activity (HFA) are key biomarkers for studying epileptic seizures. We aimed to elucidate the relationship between ISA and HFA around seizure onset. We enrolled seven patients with drug-resistant focal epilepsy who underwent intracranial electrode placement. We comparatively analyzed the ISA, HFA, and ISA-HFA phase-amplitude coupling (PAC) in the seizure onset zone (SOZ) or non-SOZ (nSOZ) in the interictal, preictal, and ictal states. We recorded 15 seizures. HFA and ISA were larger in the ictal states than in the interictal or preictal state. During seizures, the HFA and ISA of the SOZ were larger and occurred earlier than those of nSOZ. In the preictal state, the ISA-HFA PAC of the SOZ was larger than that of the interictal state, and it began increasing at approximately 87 s before the seizure onset. The receiver-operating characteristic curve revealed that the ISA-HFA PAC of the SOZ showed the highest discrimination performance in the p...

Research paper thumbnail of Frequency band coupling with high-frequency activities during seizures shifts from θ band in tonic phase to δ band in clonic phase

Objective: To clarify variations in the relationship between high-frequency activities (HFAs) and... more Objective: To clarify variations in the relationship between high-frequency activities (HFAs) and low frequency bands from the tonic to the clonic phase in focal to bilateral tonic-clonic seizures (FBTCS), using phase-amplitude coupling. Methods: This retrospective study enrolled six patients with drug-resistant focal epilepsy who underwent intracranial electrode placement for presurgical invasive electroencephalography at Osaka University Hospital (July 2018–July 2019). We used intracranial electrodes to record seizures in focal epilepsy (11 FBTCS). The magnitude of synchronization index (SIm) and receiver operating characteristic (ROC) analysis were used to analyze the coupling between HFA amplitude (80–250 Hz) and lower frequencies phase. Results: The θ (4–8 Hz)-HFA SIm peaked in the tonic phase, whereas the δ (2–4 Hz)-HFA SIm peaked in the clonic phase. ROC analysis indicated that the δ-HFA SIm discriminated well the clonic from the tonic phase. Conclusions: The main low–frequen...

Research paper thumbnail of Precise Discrimination for Multiple Underlying Pathologies of Dementia Cases Based on Deep-Learning with Electroencephalography

Background: Developing accurate and universally available biomarkers for dementia diseases is dem... more Background: Developing accurate and universally available biomarkers for dementia diseases is demanded under world-wide rapid increasing of patients with dementia. Electroencephalogram (EEG) offers promising examinations due to their inexpensiveness, high availability, and sensitiveness to neural functions. EEG applicability can be expanded by deep-learning.Methods: We analyzed EEG signals based on novel deep neural network in healthy volunteers (HV, N=55), patients with Alzheimer's disease (AD, N=101), dementia with Lewy bodies (DLB, N=75), and idiopathic normal pressure hydrocephalus (iNPH, N=60) to evaluate the discriminative accuracy of these diseases.Results: High discriminative accuracies were archived between HV and patients with dementia, yielding 81.7 %(vs AD), 93.9% (vs DLB), and 93.1% (vs iNPH).Conclusions: This study revealed that the EEG data of patients with dementia were successfully discriminated from healthy volunteers based on deep learning and could produce a ...

Research paper thumbnail of Motor and Sensory Cortical Processing of Neural Oscillatory Activities revealed by Human Swallowing using Intracranial Electrodes

Swallowing is a unique movement because orchestration of voluntary and involuntary movement, and ... more Swallowing is a unique movement because orchestration of voluntary and involuntary movement, and coordination between sensory input and motor output are indispensable. We hypothesized that neural mechanism of them were revealed by cortical oscillatory changes. Eight epileptic participants fitted with intracranial electrodes over the orofacial cortex were asked to swallow a water bolus, and cortical oscillatory changes were investigated. At the boundary time between voluntary and involuntary swallowing, high γ (75-150 Hz) power achieved the peak, and subsequently, the power decreased. High γ power increases (burst) were associated with both sensory input and motor output. However, phase-amplitude coupling (PAC) revealed that sensory-related coupling appeared during high γ-bursts, and motor-related coupling appeared before high γ-bursts. The peak of high γ power suggests switching of swallowing driving force from the cortex to the brain stem, and PAC findings suggest that motor-relate...

Research paper thumbnail of Frequency-specific genetic influence on inferior parietal lobule activation commonly observed during action observation and execution

Scientific Reports, Dec 1, 2017

Research paper thumbnail of A randomized controlled trial of 5 daily sessions and continuous trial of 4 weekly sessions of repetitive transcranial magnetic stimulation for neuropathic pain

Research paper thumbnail of Quantitative Understanding of How the Brain sees the World : Present Status and Future Outlook

Japanese Journal of Neurosurgery, 2018

Research paper thumbnail of P520: High gamma oscillatory changes of magnetic fields in hippocampus detected by memory task using magnetoencephalography

Clinical Neurophysiology, 2014

Research paper thumbnail of Efficacy of repetitive transcranial stimulation with H-coil for treatment of intractable neuropathic pain in lower extremities

Clinical Neurophysiology, 2016

Research paper thumbnail of Fast, accurate, and interpretable decoding of electrocorticographic signals using dynamic mode decomposition

Communications biology, May 18, 2024

Research paper thumbnail of Endogenous controllability of closed-loop brain-machine interfaces for pain

Research paper thumbnail of Hippocampal neural fluctuation between memory encoding and retrieval states during a working memory task in humans

bioRxiv (Cold Spring Harbor Laboratory), Apr 28, 2023

Research paper thumbnail of Beta rhythmicity in human motor cortex reflects neural population coupling that modulates subsequent finger coordination stability

Communications biology, Dec 15, 2022

Research paper thumbnail of Neural decoding of electrocorticographic signals using dynamic mode decomposition

Journal of Neural Engineering, 2020

Objective. Brain-computer interfaces (BCIs) using electrocorticographic (ECoG) signals have been ... more Objective. Brain-computer interfaces (BCIs) using electrocorticographic (ECoG) signals have been developed to restore the communication function of severely paralyzed patients. However, the limited amount of information derived from ECoG signals hinders their clinical applications. We aimed to develop a method to decode ECoG signals using spatiotemporal patterns characterizing movement types to increase the amount of information gained from these signals. Approach. Previous studies have demonstrated that motor information could be decoded using powers of specific frequency bands of the ECoG signals estimated by fast Fourier transform (FFT) or wavelet analysis. However, because FFT is evaluated for each channel, the temporal and spatial patterns among channels are difficult to evaluate. Here, we used dynamic mode decomposition (DMD) to evaluate the spatiotemporal pattern of ECoG signals and evaluated the accuracy of motor decoding with the DMD modes. We used ECoG signals during three...

Research paper thumbnail of S109 Magnetoencephalographic-based brain–machine interface robotic hand for controlling sensorimotor cortical plasticity and phantom limb pain

Clinical Neurophysiology, 2017

Research paper thumbnail of Hippocampal sharp-wave ripples correlate with periods of naturally occurring self-generated thoughts in humans

Nature communications, May 22, 2024

Research paper thumbnail of ヒト頭蓋内電極を用いた嚥下関連High γ帯域活動の解析

Japanese Journal of Clinical Neurophysiology

Research paper thumbnail of RESEARCH ARTICLE Closed-Loop Control of a Neuroprosthetic Hand by Magnetoencephalographic Signals

Objective A neuroprosthesis using a brain–machine interface (BMI) is a promising therapeutic opti... more Objective A neuroprosthesis using a brain–machine interface (BMI) is a promising therapeutic option for severely paralyzed patients, but the ability to control it may vary among individual patients and needs to be evaluated before any invasive procedure is undertaken. We have developed a neuroprosthetic hand that can be controlled by magnetoencephalographic (MEG) signals to noninvasively evaluate subjects ’ ability to control a neuroprosthesis. Method Six nonparalyzed subjects performed grasping or opening movements of their right hand while the slow components of the MEG signals (SMFs) were recorded in an open-loop con-dition. The SMFs were used to train two decoders to infer the timing and types of movement by support vector machine and Gaussian process regression. The SMFs were also used to calculate estimated slow cortical potentials (eSCPs) to identify the origin of motor informa-tion. Finally, using the trained decoders, the subjects controlled a neuroprosthetic hand in a clos...

Research paper thumbnail of Contour Fitting High Density Personalized 3 Dimensional Cortical Electrodes

Morris Shayne, M.D.1); Masayuki Hirata, M.D., Ph.D.1, 2); Tetsu Goto, M.D., Ph.D.1, 2); Kojiro Ma... more Morris Shayne, M.D.1); Masayuki Hirata, M.D., Ph.D.1, 2); Tetsu Goto, M.D., Ph.D.1, 2); Kojiro Matsushita1), Ph.D., Takufumi Yanagisawa, M.D., Ph.D.1); Youichi Saitoh, M.D., Ph.D.1); Haruhiko Kishima, M.D., Ph.D. 1); and Toshiki Yoshimine, M.D., Ph.D.1) 1) Department of Neurosurgery and 2) Division of Functional Diagnostic Sciences, Osaka University Graduate School of Medicine, Suita, Osaka, Japan

Research paper thumbnail of Decoding Visual Stimulus in Semantic Space from Electrocorticography Signals

2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2018

Recent studies using functional magnetic resonance imaging (fMRI) have enabled quantitative evalu... more Recent studies using functional magnetic resonance imaging (fMRI) have enabled quantitative evaluation of the semantic space during processing of visual stimuli. In the semantic space of the natural language processing model, called a skip-gram, decoders were shown to generalize to natural scenes of a movie that was not included in the training data of the decoders. Combined with electrocorticography (ECoG), which has a higher sampling rate than fMRI, this approach is expected to aid the development of a practical brain-machine interface. Here, we decoded vector representations of scenes within the semantic space of a skip-gram model to assess whether a decoder trained using ECoG features still generalizes to scenes new to the decoder.

Research paper thumbnail of Phase-amplitude coupling between infraslow and high-frequency activities well discriminates between the preictal and interictal states

Scientific Reports, 2021

Infraslow activity (ISA) and high-frequency activity (HFA) are key biomarkers for studying epilep... more Infraslow activity (ISA) and high-frequency activity (HFA) are key biomarkers for studying epileptic seizures. We aimed to elucidate the relationship between ISA and HFA around seizure onset. We enrolled seven patients with drug-resistant focal epilepsy who underwent intracranial electrode placement. We comparatively analyzed the ISA, HFA, and ISA-HFA phase-amplitude coupling (PAC) in the seizure onset zone (SOZ) or non-SOZ (nSOZ) in the interictal, preictal, and ictal states. We recorded 15 seizures. HFA and ISA were larger in the ictal states than in the interictal or preictal state. During seizures, the HFA and ISA of the SOZ were larger and occurred earlier than those of nSOZ. In the preictal state, the ISA-HFA PAC of the SOZ was larger than that of the interictal state, and it began increasing at approximately 87 s before the seizure onset. The receiver-operating characteristic curve revealed that the ISA-HFA PAC of the SOZ showed the highest discrimination performance in the p...

Research paper thumbnail of Frequency band coupling with high-frequency activities during seizures shifts from θ band in tonic phase to δ band in clonic phase

Objective: To clarify variations in the relationship between high-frequency activities (HFAs) and... more Objective: To clarify variations in the relationship between high-frequency activities (HFAs) and low frequency bands from the tonic to the clonic phase in focal to bilateral tonic-clonic seizures (FBTCS), using phase-amplitude coupling. Methods: This retrospective study enrolled six patients with drug-resistant focal epilepsy who underwent intracranial electrode placement for presurgical invasive electroencephalography at Osaka University Hospital (July 2018–July 2019). We used intracranial electrodes to record seizures in focal epilepsy (11 FBTCS). The magnitude of synchronization index (SIm) and receiver operating characteristic (ROC) analysis were used to analyze the coupling between HFA amplitude (80–250 Hz) and lower frequencies phase. Results: The θ (4–8 Hz)-HFA SIm peaked in the tonic phase, whereas the δ (2–4 Hz)-HFA SIm peaked in the clonic phase. ROC analysis indicated that the δ-HFA SIm discriminated well the clonic from the tonic phase. Conclusions: The main low–frequen...

Research paper thumbnail of Precise Discrimination for Multiple Underlying Pathologies of Dementia Cases Based on Deep-Learning with Electroencephalography

Background: Developing accurate and universally available biomarkers for dementia diseases is dem... more Background: Developing accurate and universally available biomarkers for dementia diseases is demanded under world-wide rapid increasing of patients with dementia. Electroencephalogram (EEG) offers promising examinations due to their inexpensiveness, high availability, and sensitiveness to neural functions. EEG applicability can be expanded by deep-learning.Methods: We analyzed EEG signals based on novel deep neural network in healthy volunteers (HV, N=55), patients with Alzheimer's disease (AD, N=101), dementia with Lewy bodies (DLB, N=75), and idiopathic normal pressure hydrocephalus (iNPH, N=60) to evaluate the discriminative accuracy of these diseases.Results: High discriminative accuracies were archived between HV and patients with dementia, yielding 81.7 %(vs AD), 93.9% (vs DLB), and 93.1% (vs iNPH).Conclusions: This study revealed that the EEG data of patients with dementia were successfully discriminated from healthy volunteers based on deep learning and could produce a ...

Research paper thumbnail of Motor and Sensory Cortical Processing of Neural Oscillatory Activities revealed by Human Swallowing using Intracranial Electrodes

Swallowing is a unique movement because orchestration of voluntary and involuntary movement, and ... more Swallowing is a unique movement because orchestration of voluntary and involuntary movement, and coordination between sensory input and motor output are indispensable. We hypothesized that neural mechanism of them were revealed by cortical oscillatory changes. Eight epileptic participants fitted with intracranial electrodes over the orofacial cortex were asked to swallow a water bolus, and cortical oscillatory changes were investigated. At the boundary time between voluntary and involuntary swallowing, high γ (75-150 Hz) power achieved the peak, and subsequently, the power decreased. High γ power increases (burst) were associated with both sensory input and motor output. However, phase-amplitude coupling (PAC) revealed that sensory-related coupling appeared during high γ-bursts, and motor-related coupling appeared before high γ-bursts. The peak of high γ power suggests switching of swallowing driving force from the cortex to the brain stem, and PAC findings suggest that motor-relate...

Research paper thumbnail of Frequency-specific genetic influence on inferior parietal lobule activation commonly observed during action observation and execution

Scientific Reports, Dec 1, 2017

Research paper thumbnail of A randomized controlled trial of 5 daily sessions and continuous trial of 4 weekly sessions of repetitive transcranial magnetic stimulation for neuropathic pain

Research paper thumbnail of Quantitative Understanding of How the Brain sees the World : Present Status and Future Outlook

Japanese Journal of Neurosurgery, 2018

Research paper thumbnail of P520: High gamma oscillatory changes of magnetic fields in hippocampus detected by memory task using magnetoencephalography

Clinical Neurophysiology, 2014

Research paper thumbnail of Efficacy of repetitive transcranial stimulation with H-coil for treatment of intractable neuropathic pain in lower extremities

Clinical Neurophysiology, 2016