Coupling between infraslow activities and high-frequency oscillations precedes seizure onset

Hashimoto H., Khoo H.M., Yanagisawa T., et al. Coupling between infraslow activities and high-frequency oscillations precedes seizure onset. Epilepsia Open 5, 501 (2020); https://doi.org/10.1002/epi4.12425.Infraslow activities and high-frequency oscillations (HFOs) are observed in seizure-onset zones. However, the relation between them remains unclear. In this study, we investigated phase-amplitude coupling between infraslow phase (0.016-1 Hz) and HFOs' amplitude of focal impaired awareness seizures followed by focal to bilateral tonic-clonic seizures, in a 28-year-old right-handed man with a dysembryoplastic neuroepithelial tumor. We recorded five habitual seizures. After the time of seizure onset, a significant increase in the power of HFOs was observed, and the power was significantly coupled with θ (4-8 Hz) phase. In contrast, coupling of infraslow activities and HFOs surged a few minutes before the seizure-onset time, and ictal HFOs discharged after that. Collectively, our results show that coupling of infraslow activities and HFOs precedes the seizure-onset time. We infer that such coupling may be a potential biomarker for seizure prediction

Phase-amplitude coupling of ripple activities during seizure evolution with theta phase

Hashimoto H., Khoo H.M., Yanagisawa T., et al. Phase-amplitude coupling of ripple activities during seizure evolution with theta phase. Clinical Neurophysiology 132, 1243 (2021); https://doi.org/10.1016/j.clinph.2021.03.007.Objective: High-frequency activities (HFAs) and phase-amplitude coupling (PAC) are key neurophysiological biomarkers for studying human epilepsy. We aimed to clarify and visualize how HFAs are modulated by the phase of low-frequency bands during seizures. Methods: We used intracranial electrodes to record seizures of focal epilepsy (12 focal-to-bilateral tonic-clonic seizures and three focal-aware seizures in seven patients). The synchronization index, representing PAC, was used to analyze the coupling between the amplitude of ripples (80–250 Hz) and the phase of lower frequencies. We created a video in which the intracranial electrode contacts were scaled linearly to the power changes of ripple. Results: The main low frequency band modulating ictal-ripple activities was the θ band (4–8 Hz), and after completion of ictal-ripple burst, δ (1–4 Hz)-ripple PAC occurred. The ripple power increased simultaneously with rhythmic fluctuations from the seizure onset zone, and spread to other regions. Conclusions: Ripple activities during seizure evolution were modulated by the θ phase. The PAC phenomenon was visualized as rhythmic fluctuations. Significance: Ripple power associated with seizure evolution increased and spread with fluctuations. The θ oscillations related to the fluctuations might represent the common neurophysiological processing involved in seizure generation

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

Hashimoto H., Khoo H.M., Yanagisawa T., et al. Phase-amplitude coupling between infraslow and high-frequency activities well discriminates between the preictal and interictal states. Scientific Reports 11, 17405 (2021); https://doi.org/10.1038/s41598-021-96479-1.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 preictal and interictal states, with an area under the curve of 0.926. This study demonstrated the novel insight that ISA-HFA PAC increases before the onset of seizures. Our findings indicate that ISA-HFA PAC could be a useful biomarker for discriminating between the preictal and interictal states

Frequency band coupling with high-frequency activities in tonic-clonic seizures shifts from θ to δ band

Hashimoto H., Khoo H.M., Yanagisawa T., et al. Frequency band coupling with high-frequency activities in tonic-clonic seizures shifts from θ to δ band. Clinical Neurophysiology 137, 122 (2022); https://doi.org/10.1016/j.clinph.2022.02.015.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 at Osaka University Hospital (July 2018–July 2019). We recorded 11 FBTCS. The synchronization index (SI) and receiver-operating characteristic (ROC) analysis were used to analyze the coupling between HFA amplitude (80–250 Hz) and lower frequencies phase. Results: In the tonic phase, the θ (4–8 Hz)-HFA coupling peaked, and the HFA power occurred at baseline (0 μV) of θ oscillations. In contrast, in the clonic phase, the δ (2–4 Hz)-HFA coupling peaked, and the HFA power occurred at the trough of δ oscillations. ROC analysis indicated that the δ-HFA SI discriminated well the clonic from the tonic phase. Conclusions: The main low-frequency band modulating the HFA shifted from the θ band in the tonic phase to the δ band in the clonic phase. Significance: Neurophysiological key frequency bands were implied to be the θ band and δ band in tonic and clonic seizures, respectively, which improves our understanding of FBTCS

A Swallowing Decoder Based on Deep Transfer Learning: AlexNet Classification of the Intracranial Electrocorticogram

Electronic version of an article published as International Journal of Neural Systems, 31(11), 2021, 2050056. https://doi.org/10.1142/S0129065720500562 © 2021 World Scientific Publishing Company. https://www.worldscientific.com/worldscinet/ijnsTo realize a brain-machine interface to assist swallowing, neural signal decoding is indispensable. Eight participants with temporal-lobe intracranial electrode implants for epilepsy were asked to swallow during electrocorticogram (ECoG) recording. Raw ECoG signals or certain frequency bands of the ECoG power were converted into images whose vertical axis was electrode number and whose horizontal axis was time in milliseconds, which were used as training data. These data were classified with four labels (Rest, Mouth open, Water injection, and Swallowing). Deep transfer learning was carried out using AlexNet, and power in the high-γ band (75-150Hz) was the training set. Accuracy reached 74.01%, sensitivity reached 82.51%, and specificity reached 95.38%. However, using the raw ECoG signals, the accuracy obtained was 76.95%, comparable to that of the high-γ power. We demonstrated that a version of AlexNet pre-trained with visually meaningful images can be used for transfer learning of visually meaningless images made up of ECoG signals. Moreover, we could achieve high decoding accuracy using the raw ECoG signals, allowing us to dispense with the conventional extraction of high-γ power. Thus, the images derived from the raw ECoG signals were equivalent to those derived from the high-γ band for transfer deep learning

Evaluating the Safety of Simultaneous Intracranial Electroencephalography and Functional Magnetic Resonance Imaging Acquisition Using a 3 Tesla Magnetic Resonance Imaging Scanner

Background: The unsurpassed sensitivity of intracranial electroencephalography (icEEG) and the growing interest in understanding human brain networks and ongoing activities in health and disease have make the simultaneous icEEG and functional magnetic resonance imaging acquisition (icEEG-fMRI) an attractive investigation tool. However, safety remains a crucial consideration, particularly due to the impact of the specific characteristics of icEEG and MRI technologies that were safe when used separately but may risk health when combined. Using a clinical 3-T scanner with body transmit and head-receive coils, we assessed the safety and feasibility of our icEEG-fMRI protocol. Methods: Using platinum and platinum-iridium grid and depth electrodes implanted in a custom-made acrylic-gel phantom, we assessed safety by focusing on three factors. First, we measured radio frequency (RF)-induced heating of the electrodes during fast spin echo (FSE, as a control) and the three sequences in our icEEG-fMRI protocol. Heating was evaluated with electrodes placed orthogonal or parallel to the static magnetic field. Using the configuration with the greatest heating observed, we then measured the total heating induced in our protocol, which is a continuous 70-min icEEG-fMRI session comprising localizer, echo-planar imaging (EPI), and magnetization-prepared rapid gradient-echo sequences. Second, we measured the gradient switching-induced voltage using configurations mimicking electrode implantation in the frontal and temporal lobes. Third, we assessed the gradient switching-induced electrode movement by direct visual detection and image analyses. Results: On average, RF-induced local heating on the icEEG electrode contacts tested were greater in the orthogonal than parallel configuration, with a maximum increase of 0.2°C during EPI and 1.9°C during FSE. The total local heating was below the 1°C safety limit across all contacts tested during the 70-min icEEG-fMRI session. The induced voltage was within the 100-mV safety limit regardless of the configuration. No gradient switching-induced electrode displacement was observed. Conclusion: We provide evidence that the additional health risks associated with heating, neuronal stimulation, or device movement are low when acquiring fMRI at 3 T in the presence of clinical icEEG electrodes under the conditions reported in this study. High specific absorption ratio sequences such as FSE should be avoided to prevent potential inadvertent tissue heating

Aging male symptoms scale (AMS) for health-related quality of life in aging men: translation and adaptation in Malay

The Aging Male Symptoms Scale (AMS) measures health-related quality of life in aging men. The objective of this paper is to describe the translation and validation of the AMS into Bahasa Melayu (BM). The original English version of the AMS was translated into BM by 2 translators to produce BM1 and BM2, and subsequently harmonized to produce BM3. Two other independent translators, blinded to the English version, back-translated BM3 to yield E2 and E3. All versions (BM1, BM2, BM3, E2, E3) were compared with the English version. The BM pre-final version was produced, and pre-tested in 8 participants. Proportion Agreement, Weighted Kappa, Spearman Rank Correlation Coefficient, and verbatim responses were used. The English and the BM versions showed excellent equivalence (weighted Kappa and Spearman Rank Coefficients, ranged from 0.72 to 1.00, and Proportion Agreement values ranged from 75.0% to 100%). In conclusion, the BM version of the AMS was successfully translated and adapted

Motor and sensory cortical processing of neural oscillatory activities revealed by human swallowing using intracranial electrodes

Hashimoto H., Takahashi K., Kameda S., et al. Motor and sensory cortical processing of neural oscillatory activities revealed by human swallowing using intracranial electrodes. iScience 24, 102786 (2021); https://doi.org/10.1016/j.isci.2021.102786.Swallowing is attributed to the orchestration of motor output and sensory input. We hypothesized that swallowing can illustrate differences between motor and sensory neural processing. Eight epileptic participants fitted with intracranial electrodes over the orofacial cortex were asked to swallow a water bolus. Mouth opening and swallowing were treated as motor tasks, whereas water injection was treated as a sensory task. Phase-amplitude coupling between lower-frequency and high γ (HG) bands (75–150 Hz) was investigated. An α (10–16 Hz)-HG coupling appeared before motor-related HG power increases (burst), and a θ (5–9 Hz)-HG coupling appeared during sensory-related HG bursts. The peaks of motor-related coupling were 0.6–0.7 s earlier than that of HG power. The motor-related HG was modulated at the trough of the α oscillation, and the sensory-related HG amplitude was modulated at the peak of the θ oscillation. These contrasting results can help to elucidate the brain's sensory motor functions

Swallowing-related neural oscillation: an intracranial EEG study

Hashimoto H., Takahashi K., Kameda S., et al. Swallowing-related neural oscillation: an intracranial EEG study. Annals of Clinical and Translational Neurology 8, 1224 (2021); https://doi.org/10.1002/acn3.51344.Objective: Swallowing is a unique movement due to the indispensable orchestration of voluntary and involuntary movements. The transition from voluntary to involuntary swallowing is executed within milliseconds. We hypothesized that the underlying neural mechanism of swallowing would be revealed by high-frequency cortical activities. Methods: Eight epileptic participants fitted with intracranial electrodes over the orofacial cortex were asked to swallow a water bolus and cortical oscillatory changes, including the high γ band (75–150 Hz) and β band (13–30 Hz), were investigated at the time of mouth opening, water injection, and swallowing. Results: Increases in high γ power associated with mouth opening were observed in the ventrolateral prefrontal cortex (VLPFC) with water injection in the lateral central sulcus and with swallowing in the region along the Sylvian fissure. Mouth opening induced a decrease in β power, which continued until the completion of swallowing. The high γ burst of activity was focal and specific to swallowing; however, the β activities were extensive and not specific to swallowing. In the interim between voluntary and involuntary swallowing, swallowing-related high γ power achieved its peak, and subsequently, the power decreased. Interpretation: We demonstrated three distinct activities related to mouth opening, water injection, and swallowing induced at different timings using high γ activities. The peak of high γ power related to swallowing suggests that during voluntary swallowing phases, the cortex is the main driving force for swallowing as opposed to the brain stem