Isoflurane is one of the most widely used anesthetic agents in rodent imaging studies. However, the impact of isoflurane on brain metabolism has not been fully characterized to date, primarily due to a scarcity of noninvasive technologies to quantitatively measure the brain\'s metabolic rate in vivo. In this study, using noncontrast MRI techniques, we dynamically measured cerebral metabolic rate of oxygen (CMRO2) under varying doses of isoflurane anesthesia in mice. Concurrently, systemic parameters of heart and respiration rates were recorded alongside CMRO2. Additionally, electroencephalogram (EEG) recording was used to identify changes in neuronal activities under the same anesthetic regimen employed in the MRI experiments. We found suppression of the CMRO2 by isoflurane in a dose-dependent manner, concomitant with a diminished high-frequency EEG activity. The degree of metabolic suppression by isoflurane was strongly correlated with the respiration rate, which offers a potential approach to calibrate CMRO2 measurements. Furthermore, the metabolic level associated with neural responses of the somatosensory and motor cortices in mice was estimated as 308.2 μmol/100 g/min. These findings may facilitate the integration of metabolic parameters into future studies involving animal disease models and anesthesia usage.

OBJECTIVE: Various artifacts in electroencephalography (EEG) are a big hurdle to prevent brain-computer interfaces from real-life usage. Recently, deep learning-based EEG denoising methods have shown excellent performance. However, existing deep network designs inadequately leverage inter-channel relationships in processing multichannel EEG signals. Typically, most methods process multi-channel signals in a channel-by-channel way. Considering the correlations among EEG channels during the same brain activity, this paper proposes utilizing channel relationships to enhance denoising performance.
METHODS: We explicitly model the inter-channel relationships using the self attention mechanism, hypothesizing that these correlations can support and improve the denoising process. Specifically, we introduce a novel denoising network, named Spatial-Temporal Fusion Network (STFNet), which integrates stacked multi-dimension feature extractor to explicitly capture both temporal dependencies and spatial relationships.
RESULTS: The proposed network exhibits superior denoising performance, with a 24.27% reduction in relative root mean squared error compared to other methods on a public benchmark. STFNet proves effective in cross-dataset denoising and downstream classification tasks, improving accuracy by 1.40%, while also offering fast processing on CPU.
CONCLUSIONS: The experimental results demonstrate the importance of integrating spatial and temporal characteristics. The computational efficiency of STFNet makes it suitable for real-time applications and a potential tool for deployment in realistic environments.

BACKGROUND: Studies show that the two peak heights of electroencephalographic bicoherence (pBIC-high, pBIC-low) decrease after incision and are restored by fentanyl administration. We investigated whether pBICs are good indicators for adequacy of analgesia during surgery.
METHODS: After local ethical committee approval, we enrolled 50 patients (27-65 years, ASA-PS I or II) who were scheduled elective surgery. Besides standard anesthesia monitors, to assess pBICs, we used a BIS monitor and freeware Bispectrum Analyzer for A2000. Fentanyl 5 µg/kg was completely administered before incision, and anesthesia was maintained with sevoflurane. After skin incision, when the peak of pBIC-high or pBIC-low decreased by 10% in absolute value (named LT10-high and LT10-low groups in order) or when either peak decreased to below 20% (BL20-high and BL20-low groups), an additional 1 g/kg of fentanyl was administered to examine its effect on the peak that showed a decrease.
RESULTS: The mean values and standard deviation for pBIC-high 5 min before fentanyl administration, at the time of fentanyl administration, and 5 min after fentanyl administration for LT10-high group were 39.8% (10.9%), 26.9% (10.5%), and 35.7% (12.5%). And those for pBIC-low for LT10-low group were 39.5% (6.0%), 26.8% (6.4%) and 35.0% (7.0%). Those for pBIC-high for BL20-high group were 26.3% (5.6%), 16.5% (2.6%), and 25.7% (7.0%). And those for pBIC-low for BL20-low group were 26.7% (4.8%), 17.4% (1.8%) and 26.9% (5.7%), respectively. Meanwhile, at these trigger points, hemodynamic parameters didn\'t show significant changes.
CONCLUSIONS: Superior to standard anesthesia monitoring, pBICs are better indicators of analgesia during surgery.
BACKGROUND: Clinical trial Number and registry URL: UMIN ID: UMIN000042843 https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno  = R000048907.

This paper summarizes the history and evolution of the electroencephalogram (EEG). The EEG, used to record the electrical activity of the brain, is a pivotal tool in neuroscience and medicine. Its history and evolution reflect significant advancements in our understanding of brain function and our ability to diagnose and treat neurological conditions. This tool has revolutionized our understanding of the brain\'s electrical activity and is the cornerstone for the diagnosis and treatment of epilepsy and related disorders. The evolution of the EEG from early experimental observations to sophisticated modern applications highlights the profound progress in our ability to monitor and interpret brain activity. The EEG remains an invaluable tool in clinical and research settings, continually evolving with technological advancements to expand our understanding of the human brain. This review traces the journey of this iconic tool.

Background: Holmes tremor (HT) is a rare motor disorder characterized by high-amplitude and low-frequency resting, intentional, and postural tremors. HT typically arises from disruptions in neural pathways, including the dopaminergic system. Its causes include cerebrovascular incidents, neoplasms, demyelination, and infections. Diagnosis involves thorough clinical, neurophysiological, and neuroimaging assessments. Our report details the clinical profile, neuroimaging and EEG results and levodopa treatment response of an HT patient after cerebral arteriovenous malformation (AVM) surgery. Case Report: A female patient who underwent AVM surgery developed head tremor and dystonia. Neuroimaging revealed left thalamus involvement. Video electroencephalography (EEG) revealed high-amplitude, low-frequency tremors. The patient responded well to levodopa treatment. Conclusions: Involuntary rhythmic or non-rhythmic movements are a primary clinical feature of HT. A differential diagnosis of epilepsy and HT can be achieved through neurophysiological monitoring, avoiding the overuse of antiepileptic drugs. Symptoms can be alleviated with levodopa intervention.

Near-death experience (NDE) is a transcendent mental event of uncertain etiology that arises on the cusp of biological death. Since the discovery of NDE in the mid-1970s, multiple neuroscientific theories have been developed in an attempt to account for it in strictly materialistic or reductionistic terms. Therefore, in this conception, NDE is at most an extraordinary hallucination without any otherworldly, spiritual, or supernatural denotations. During the last decade or so, a number of animal and clinical studies have emerged which reported that about the time of death, there may be a surge of high frequency electroencephalogram (EEG) at a time when cortical electrical activity is otherwise at a very low ebb. This oscillatory rhythm falls within the range of the enigmatic brain wave-labelled gamma-band activity (GBA). Therefore, it has been proposed that this brief, paradoxical, and perimortem burst of the GBA may represent the neural foundation of the NDE. This study examines three separate but related questions concerning this phenomenon. The first problem pertains to the electrogenesis of standard GBA and the extent to which authentic cerebral activity has been contaminated by myogenic artifacts. The second problem involves the question of whether agents that can mimic NDE are also underlain by GBA. The third question concerns the electrogenesis of the surge in GBA itself. It has been contended that this is neither cortical nor myogenic in origin. Rather, it arises in a subcortical (amygdaloid) location but is recorded at the cortex via volume conduction, thereby mimicking standard GBA. Although this surge of GBA contains genuine electrophysiological activity and is an intriguing and provocative finding, there is little evidence to suggest that it could act as a kind of neurobiological skeleton for a phenomenon such as NDE.

BACKGROUND: Electroencephalography (EEG) is a promising tool for identifying the physiological biomarkers of fibromyalgia (FM). Evidence suggests differences in power band and density between individuals with FM and healthy controls. EEG changes appear to be associated with pain intensity; however, their relationship with the quality of pain has not been examined. We aimed to investigate whether abnormal EEG in the frontal and central points of the 10-20 EEG system in individuals with FM is associated with pain\'s sensory-discriminative and affective-motivational dimensions. The association between EEG and the two dimensions of emotional disorders (depression and anxiety) was also investigated.
METHODS: In this cross-sectional pilot study, pain experience (pain rating index [PRI]) and two dimensions of emotional disorders (depression and anxiety) were assessed using the McGill Pain Questionnaire (PRI-sensory and PRI-affective) and Hospital Anxiety and Depression Scale (HADS), respectively. In quantitative EEG analysis, the relative spectral power of each frequency band (delta, theta, alpha, and beta) was identified in the frontal and central points during rest.
RESULTS: A negative correlation was found between the relative spectral power for the delta bands in the frontal (r= -0.656; p = 0.028) and central points (r= -0.624; p = 0.040) and the PRI-affective scores. A positive correlation was found between the alpha bands in the frontal (r = 0.642; p = 0.033) and central points (r = 0.642; p = 0.033) and the PRI-affective scores. A negative correlation between the delta bands in the central points and the anxiety subscale of the HADS (r = -0.648; p = 0.031) was detected.
CONCLUSIONS: The affective-motivational dimension of pain and mood disorders may be related to abnormal patterns of electrical activity in patients with FM.
BACKGROUND: Retrospectively registered on ClinicalTrials.gov (NCT05962658).

UNASSIGNED: Stroke is the second leading cause of global deaths. Post-stroke seizures (PSS) can lead to lasting complications, such as prolonged hospitalizations, increased disability rates, and higher mortality. Our study investigates the associated factors that contribute to post-stroke seizures in patients at a local tertiary hospital.
UNASSIGNED: We designed a case-control study where patients admitted with PSS were recruited with consent. Controls admitted for stroke without seizure were then included. Suitability based on exclusion criteria was ensured before recording their sociodemographic and clinical data. An EEG was performed and read by two certified neurologists before the data was analyzed.
UNASSIGNED: We recruited 180 participants, 90 cases and 90 matched controls. Gender (p=0.013), race (p=0.015), dyslipidemia (p<0.001), prior stroke (p<0.031), large artery atherosclerosis (p<0.001), small vessel occlusions (p<0.001), blood pressure on presentation (p<0.028) and thrombolysis administration (p<0.029) were significantly associated with the occurrence of PSS. An increase in odds of PSS was observed in the male gender (1.974), dyslipidemia (3.480), small vessel occlusions (4.578), and in participants with epileptiform changes on EEG (3.630). Conversely, lower odds of PSS were seen in participants with high blood pressure on presentation (0.505), large artery atherosclerosis (0.266), and those who underwent thrombolysis (0.319).
UNASSIGNED: This study emphasized that identifying post-stroke seizures may be aided by EEGs and recognizing at-risk groups, which include males of Chinese descent in Asia, dyslipidemia, small vessel occlusions, those with low to normal blood pressure on presentation, and epileptiform changes in EEGs.
The research aims to establish the risk factors associated with post-stroke seizures in an Asian population and their similarity to the Western literature. Our findings highlight the critical risk factors to identify in at-risk patients, which may prompt changes in guidelines in future to enhance patient outcomes and improve the quality of care.

Individuals with motor dysfunction caused by damage to the central nervous system are unable to transmit voluntary movement commands to their muscles, resulting in a reduced ability to control their limbs. However, traditional rehabilitation methods have problems such as long treatment cycles and high labor costs. Functional electrical stimulation (FES) based on brain-computer interface (BCI) connects the patient\'s intentions with muscle contraction, and helps to promote the reconstruction of nerve function by recognizing nerve signals and stimulating the moving muscle group with electrical impulses to produce muscle convulsions or limb movements. It is an effective treatment for sequelae of neurological diseases such as stroke and spinal cord injury. This article reviewed the current research status of BCI-based FES from three aspects: BCI paradigms, FES parameters and rehabilitation efficacy, and looked forward to the future development trend of this technology, in order to improve the understanding of BCI-based FES.
中枢神经系统损伤导致的运动功能障碍个体无法将自主运动的命令传递给肌肉，进而导致控制四肢的能力下降，而传统的康复手段存在治疗周期长且人工成本较高等问题。基于脑机接口（BCI）的功能性电刺激（FES）将患者意图与肌肉收缩联系起来，通过识别神经信号并对运动肌肉群进行电脉冲刺激以产生肌肉抽搐或肢体运动，有助于促进神经功能的重建，是脑卒中、脊髓损伤等神经系统疾病后遗症的有效治疗方法。本文从脑机接口范式、功能性电刺激参数以及康复疗效三个方面对基于脑机接口的功能性电刺激研究现状进行梳理，并对未来该项技术的发展趋势进行展望，以期增进对基于脑机接口的功能性电刺激系统的理解。.

Aims/Background Backward walking is gaining traction in rehabilitation therapy, showing promise as an intervention for stroke patients with walking difficulties. However, the brain activity patterns (neurophysiological mechanisms) underlying backward walking in these patients remain unclear. This study investigated the neurophysiological mechanism in stroke patients within 1 year of their stroke. Methods Twenty-four subjects walked forward and backward for 5 min on an 8-m track while their electroencephalographic signals were collected. The power values of each frequency band were compared during forward and backward walking, and the delta to alpha power ratio (DAR) was calculated. Results The results showed a significant increase in α-band activity within the frontal cortex during backward walking (p < 0.05). This increase correlated positively with scores on the Fugl-Meyer lower extremity motor function assessment scale. Similarly, α-band activity showed significant enhancement within the right parietal cortex during backward walking (p < 0.05). There were no significant differences between forward and backward walking states in δ, θ, and β wavebands across the entire brain region (p > 0.05). Additionally, the DAR was significantly lower during backward walking than during forward walking (p < 0.05). Conclusion This study suggests that backward walking may more effectively activate neural activity in the prefrontal and right posterior parietal cortices. This finding supports the potential of backward walking to enhance motor execution and walking function in stroke patients, thereby supporting its application as a rehabilitation method.