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

Hashimoto, Hiroaki; Takahashi, Kazutaka; Kameda, Seiji; Yoshida, Fumiaki; Maezawa, Hitoshi; Oshino, Satoru; Tani, Naoki; Khoo, Hui Ming; Yanagisawa, Takufumi; Yoshimine, Toshiki; Kishima, Haruhiko; Hirata, Masayuki

doi:10.1016/j.isci.2021.102786

Cited by 8 publications

(8 citation statements)

References 75 publications

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“…In this study, ISA-HFA PAC increased before the increase in HFA occurred, and this profile that PAC precedes HFA increasing is also reported in previous studies related to motor-related physiological PAC 25 , 26 . A hold-and-release model was proposed, which indicated that physiological coupling restricted the HFA and attenuation of the coupling releases the HFA.…”

Section: Discussionsupporting

confidence: 90%

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

Hashimoto

Khoo

Yanagisawa

et al. 2021

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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.

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Section: Discussionsupporting

confidence: 90%

“…These pathological PACs are usually accompanied by ictal HFA, whereas physiological PACs that are involved in motor-related HFAs (i.e., high γ band) appear before HFA increases 25 , 26 . Physiological PAC precedes physiological HFA; however, whether a preceding seizure-related PAC can be observed before ictal HFA appears is unknown.…”

Section: Introductionmentioning

confidence: 99%

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

Hashimoto

Khoo

Yanagisawa

et al. 2021

Sci Rep

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“…The HFA power is strongly correlated with the neural firing rate (Ray et al, 2008), and, in animal studies, neural spiking was found to be locked to the trough of α oscillations (Haegens et al, 2011). In a previous study of physiological PAC, high gamma amplitude during high PAC values peaked around the trough of α oscillations (Hashimoto et al, 2021c, Yanagisawa et al, 2012. Moreover, in a study of pathological PAC related to epilepsy, the HFA amplitude during high PAC was time-locked to the trough of lower-frequency oscillations (Ibrahim et al, 2014).…”

Section: Discussionmentioning

confidence: 83%

“…PAC has been observed in both physiological and pathological neural processing. The former includes hand movement (Yanagisawa et al, 2012), swallowing (Hashimoto et al, 2021c) and somatosensory processing (Lakatos et al, 2008), and the latter includes epileptic seizures (Hashimoto et al, 2020b, 2021b, Iimura et al, 2018, and Parkinson's disease (de Hemptinne et al, 2015). It was reported that ictal HFA amplitudes are coupled with δ (Iimura et al, 2018, Nariai et al, 2011, θ (Hashimoto et al, 2021b, Ibrahim et al, 2014, and α (Ibrahim et al, 2014) phases, while β-HFA coupling has been reported as a useful marker for seizure detection (Edakawa et al, 2016).…”

Section: Discussionmentioning

confidence: 99%

“…PAC analysis measures the degree of synchronization between phases with low-frequency oscillations and high-frequency amplitudes (Cohen, 2008). PAC can be physiological (Hashimoto et al, 2021c, Yanagisawa et al, 2012 or pathological. Studies related to pathological PAC have demonstrated that ictal HFA amplitude is coupled with δ (Nariai et al, 2011) or θ (Ibrahim et al, 2014) bands.…”

Section: Introductionmentioning

confidence: 99%

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

Hashimoto

Khoo

Yanagisawa

et al. 2021

Preprint

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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–frequency band modulating the HFA shifted from the θ band in the tonic phase to the δ band in the clonic phase. Significance: In FBTCS, low-frequency band coupling with HFA amplitude varies temporally. Especially, the δ band is specific to the clonic phase. These results suggest dynamically neurophysiological changes in the thalamus or basal ganglia throughout FBTCS.

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Clinical features and power spectral entropy of electroencephalography in Wilson's disease with dystonia

et al. 2022

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Objective To study the clinical features and power spectral entropy (PSE) of electroencephalography signals in Wilson's disease (WD) patients with dystonia. Methods Several scale evaluations were performed to assess the clinical features of WD patients. Demographic information and electroencephalography signals were obtained in all subjects. Results 34 WD patients with dystonia were recruited in the case group and 24 patients without dystonia were recruited in the control group. 20 healthy individuals were included in the healthy control group. The mean body mass index (BMI) in the case group was significantly lower than that in the controls (p < .05). The case group had significantly higher SAS, SDS, and Bucco‐Facial‐Apraxia Assessment scores (p < .05). Total BADS scores in the case group were lower than those in the control group (p < .01). Note that 94.11% of the case group presented with dysarthria and 70.59% of them suffered from dysphagia. Dysphagia was mainly related to the oral preparatory stage and oral stage. Mean power spectral entropy (PSE) values in the case group were significantly different (p < .05) from those in the control group and the healthy group across the different tasks. Conclusions The patients with dystonia were usually accompanied with low BMI, anxiety, depression, apraxia, executive dysfunction, dysarthria and dysphagia. The cortical activities of the WD patients with dystonia seemed to be more chaotic during the eyes‐closed and reading tasks but lower during the swallowing stages than those in the control group.

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

Cited by 8 publications

References 75 publications

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

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

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

Clinical features and power spectral entropy of electroencephalography in Wilson's disease with dystonia

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