Clinical Neurophysiology最新文献

英文中文

Modulating altered sensory prediction using bilateral auditory cortex high-definition transcranial random noise stimulation and acoustic masking 利用双侧听觉皮层高清晰度经颅随机噪声刺激和声掩蔽调节改变的感觉预测。

IF 3.6 3区医学 Q1 CLINICAL NEUROLOGY

Clinical Neurophysiology

Pub Date : 2025-11-16 DOI: 10.1016/j.clinph.2025.2111388

Zino H. Wellauer , Deniza Avdi , Payam S. Shabestari , Allegra Preisig , Jessica Fritzsche , Nicole Peter , Martin Meyer , Tobias Kleinjung , Patrick K.A. Neff

Objective:

To assess the combined effect of high-definition transcranial random noise stimulation (HD-tRNS) of bilateral auditory cortex and acoustic stimulation (AS) on auditory evoked potentials and tinnitus perception.

Methods:

A double-blind, randomized, controlled, within-subject crossover trial was conducted with thirteen adults with chronic tinnitus. Each participant completed four sessions, at least 48 h apart, consisting of active HD-tRNS + AS, active HD-tRNS alone, sham HD-tRNS + sham AS and sham HD-tRNS alone. Auditory evoked potentials (including mismatch negativity) and tinnitus characteristics were measured before and after each session.

Results:

Active electric and bimodal stimulation significantly modulated auditory evoked potentials, unlike their sham equivalents. Bimodal stimulation produced significant changes in MMN amplitude that countered the tinnitus-related alteration in processing intensity deviants. However, these effects did not survive family-wise correction in this complex design. Bimodal and bimodal-sham stimulation reduced objective loudness by >3 dB.

Conclusion:

HD-tRNS, particularly when combined with AS, may induce changes in auditory-system excitability and acutely alter neural processing and loudness perception in tinnitus.

Significance:

Combining acoustic and electric stimulation is a promising approach for basic research and clinical applications in auditory neuroscience, providing new insights into neuroplasticity in an altered auditory system. This is the first study to measure the modifiability of evoked neural correlates in tinnitus.

目的：探讨双侧听觉皮层高清晰度经颅随机噪声刺激（HD-tRNS）和声刺激（AS）对听觉诱发电位和耳鸣感知的联合影响。方法：对13例成人慢性耳鸣患者进行双盲、随机、对照、组内交叉试验。每个参与者完成四个疗程，间隔至少48小时，包括活性HD-tRNS + AS、单独活性HD-tRNS、假HD-tRNS +假AS和单独假HD-tRNS。每次训练前后分别测量听觉诱发电位（包括错配负性）和耳鸣特征。结果：与假刺激不同，主动电刺激和双峰刺激显著调节了听觉诱发电位。双峰刺激产生了MMN振幅的显著变化，抵消了耳鸣相关的加工强度偏差的改变。然而，在这个复杂的设计中，这些影响并没有在家庭明智的纠正中幸存下来。双峰刺激和双峰-假刺激使客观响度降低bb30 dB。结论：HD-tRNS，特别是与AS合并时，可引起耳鸣患者听觉系统兴奋性的改变，并严重改变耳鸣患者的神经加工和响度感知。意义：声电结合刺激是听觉神经科学基础研究和临床应用的一种有前景的方法，为听觉系统改变中的神经可塑性提供了新的见解。这是第一个测量耳鸣中诱发神经相关物可变性的研究。

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引用次数: 0

EEG-based stratification in Alzheimer’s disease: Cognitive progression, pathological marker associations, and therapeutic interventions 基于脑电图的阿尔茨海默病分层：认知进展、病理标志物关联和治疗干预

IF 3.6 3区医学 Q1 CLINICAL NEUROLOGY

Clinical Neurophysiology

Pub Date : 2025-11-15 DOI: 10.1016/j.clinph.2025.2111440

Zian Pei , Lin Zhu , Huixia Ren , Yumei Liu , Xue Shi , Yun Lin , Jing Wang , Pan Li , Pan Wang , Yong Ji , Yuying Zhou , Xiaoying Tang , Xin Jiang , Xiaoguang Tong , Yi Guo

Objective

Clinical cognitive and pathological marker stratification systems have evolved separately, causing mismatches that limit their clinical use. This study retrospectively validated the link between EEG and clinical symptoms, pathological markers, and the therapeutic efficacy of repetitive transcranial magnetic stimulation (rTMS).

Methods

This multicenter study involved 308 Alzheimer’s patients (AD), 176 with Parkinson’s (PD), and 181 normal controls. Resting-state EEG were analyzed to identify four oscillation modes. An EEG-based cognitive risk system was created and validated, also evaluating its effect on rTMS therapy effectiveness.

Results

EEG oscillation changes correlated with cognitive decline, revealing distinct brain network disruptions in AD and PD. These oscillation changes were associated with AD biomarkers, particularly tau hyperphosphorylation. Multicenter validation showed an 83% concordance with the Clinical Dementia Rating Scale, and EEG stratification enhanced rTMS therapeutic efficacy.

Conclusions

This study showed that EEG-based stratification can assess cognitive function, track disease progression, identify key intervention periods, and improve patient selection for better treatment outcomes in clinical settings.

Significance

This study demonstrates that EEG can connect disease processes to clinical symptoms at a molecular level, offering a unified framework for improved dementia management. This method allows for dynamic monitoring and precise neuromodulation, enhancing personalized care for neurodegenerative diseases.

临床认知和病理标记物分层系统已经分开发展，导致不匹配，限制了它们的临床应用。本研究回顾性地验证了脑电图与临床症状、病理标志物和重复经颅磁刺激（rTMS）治疗效果之间的联系。方法本研究纳入308例阿尔茨海默病（AD）患者、176例帕金森病（PD）患者和181例正常对照。静息状态脑电图分析确定了四种振荡模式。建立并验证了基于脑电图的认知风险系统，并评估了其对rTMS治疗效果的影响。结果seeg振荡变化与认知能力下降相关，揭示了AD和PD患者明显的脑网络中断。这些振荡变化与AD生物标志物有关，特别是tau过度磷酸化。多中心验证显示与临床痴呆评定量表的一致性为83%，脑电图分层增强了rTMS的治疗效果。结论：基于脑电图的分层可以评估认知功能，跟踪疾病进展，确定关键干预期，改善患者选择，以获得更好的临床治疗效果。本研究表明脑电图可以在分子水平上将疾病过程与临床症状联系起来，为改善痴呆管理提供统一的框架。这种方法允许动态监测和精确的神经调节，加强对神经退行性疾病的个性化护理。

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引用次数: 0

Decoding alzheimer’s: The role of EEG rhythms and aperiodic components in cognitive decline 解码阿尔茨海默病：脑电图节律和非周期性成分在认知衰退中的作用

IF 3.6 3区医学 Q1 CLINICAL NEUROLOGY

Clinical Neurophysiology

Pub Date : 2025-11-13 DOI: 10.1016/j.clinph.2025.2111437

Mingyang Zhang , Xia Liu , Yanan Ren , Lixuan Li , Ruoyu Wang , Lihui Sun , Qinying Ma

Objective

To investigate detailed alterations in brain electrical activity and their relationship with cognitive decline in Alzheimer’s disease (AD) using electroencephalogram (EEG) power spectrum analysis.

Methods

EEG data from 80 AD patients and 80 healthy control (HC) were analyzed, focusing on theta and alpha band powers, aperiodic offset, and exponent. Topographic and gender-specific analyses were conducted to explore associations with disease progression and cognitive impairment.

Results

AD patients showed increased theta and alpha band powers, with theta band power exhibiting statistically significant differences. Globally elevated theta band power correlated with cognitive impairment severity. Higher aperiodic offsets and exponents were observed in AD patients, exhibiting upward trends with disease progression. Male AD patients displayed more pronounced EEG abnormalities and unique Montreal Cognitive Assessment (MOCA) score patterns.

Conclusions

Our findings highlight the critical role of theta band power in AD pathology and suggest potential EEG biomarkers for neurodegenerative changes. Gender-specific differences emphasize the importance of personalized approaches in AD diagnosis and treatment.

Significance

This study provides novel neurophysiological insights into AD, underscoring the clinical utility of EEG markers and the necessity for gender-specific considerations in precision medicine for AD.

目的利用脑电图（EEG）功率谱分析阿尔茨海默病（AD）脑电活动的详细变化及其与认知能力下降的关系。方法对80例AD患者和80例健康对照（HC）的seeg数据进行分析，重点分析theta和alpha波段功率、非周期偏移和指数。进行地形和性别分析，以探讨疾病进展和认知障碍的关系。结果ad患者theta和alpha波段功率均升高，其中theta波段功率差异有统计学意义。整体θ波段功率升高与认知障碍严重程度相关。在AD患者中观察到较高的非周期性偏移和指数，随着疾病进展呈现上升趋势。男性AD患者表现出更明显的脑电图异常和独特的蒙特利尔认知评估（MOCA）评分模式。结论我们的研究结果强调了θ波段功率在AD病理中的关键作用，并提示了神经退行性改变的潜在EEG生物标志物。性别差异强调了AD诊断和治疗中个性化方法的重要性。这项研究为阿尔茨海默病提供了新的神经生理学见解，强调了脑电图标志物的临床应用，以及在阿尔茨海默病的精准医学中考虑性别的必要性。

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引用次数: 0

Temporal dynamics of electroconvulsive therapy induced seizures 电痉挛疗法诱发癫痫发作的时间动力学。

IF 3.6 3区医学 Q1 CLINICAL NEUROLOGY

Clinical Neurophysiology

Pub Date : 2025-11-12 DOI: 10.1016/j.clinph.2025.2111439

Sven Stuiver , Prejaas K.B. Tewarie , Julia C.M. Pottkämper , Joey P.A.J. Verdijk , Michel J.A.M. van Putten , Jeannette Hofmeijer , Jeroen A. van Waarde

Objective

Electroconvulsive therapy (ECT) is an effective treatment for several psychiatric disorders. The role of cortex and thalamus in seizure expression and termination seems critical. Here we study spatiotemporal dynamics of ECT-induced seizures based on electroencephalogram (EEG) features and biophysical parameters using a corticothalamic mean-field model.

Methods

We analyzed 345 ictal EEGs from 33 patients (19 female). EEG features included the dominant frequency, and temporal and spatial correlations. A corticothalamic biophysical model assessed cortical excitation/inhibition (E/I) balance and effective corticothalamic and intrathalamic loop strengths. We tracked the temporal evolution of each feature and parameter from seizure onset to termination.

Results

ECT-induced seizures showed EEG slowing (i.e., a decrease in dominant frequency) and increased temporal correlations as seizures approached termination. Cortical E/I ratios and corticothalamic loop strength increased, while intrathalamic strength decreased. Both EEG slowing and increase in temporal correlations were associated with increased cortical E/I ratios and decreased intrathalamic loop strength.

Conclusions

ECT-induced seizures show slowing and increased temporal correlations toward termination. These dynamics may be driven by increased cortical E/I ratios and decreased intrathalamic loop strength.

Significance

ECT-induced seizures exhibit characteristic temporal corticothalamic dynamics.

目的：电休克治疗是治疗多种精神疾病的有效方法。皮层和丘脑在癫痫表达和终止中的作用似乎至关重要。本研究采用皮质丘脑平均场模型，基于脑电图特征和生物物理参数研究ect诱发癫痫发作的时空动态。方法：对33例患者345例脑电图进行分析，其中女性19例。脑电特征包括主频率、时间和空间相关性。皮质丘脑生物物理模型评估皮质兴奋/抑制（E/I）平衡和有效的皮质丘脑和丘脑内环路强度。我们跟踪了每个特征和参数从发作到终止的时间演变。结果：随着癫痫发作接近终止，ect诱导的癫痫发作表现为脑电图减慢（即优势频率降低）和时间相关性增加。皮层E/I比值和皮质丘脑回路强度增加，而丘脑内强度降低。脑电图减慢和时间相关性增加都与皮层E/I比值增加和丘脑内环路强度下降有关。结论：ect诱发的癫痫发作表现出缓慢和增加的时间相关性。这些动态可能是由皮质E/I比率增加和丘脑内环路强度下降驱动的。意义：ect诱发的癫痫发作表现出特征性的颞皮质-丘脑动力学。

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引用次数: 0

Optimal parameters for reliable PMv–M1 facilitation identified with dual coil TMS 双线圈TMS鉴定可靠PMv-M1促进的最佳参数

IF 3.6 3区医学 Q1 CLINICAL NEUROLOGY

Clinical Neurophysiology

Pub Date : 2025-11-11 DOI: 10.1016/j.clinph.2025.2111434

N. Bevacqua , S. Turrini , A. Avenanti

引用次数: 0

Towards precision medicine in non-invasive brain stimulation for chronic pain 迈向非侵入性脑刺激治疗慢性疼痛的精准医学

IF 3.6 3区医学 Q1 CLINICAL NEUROLOGY

Clinical Neurophysiology

Pub Date : 2025-11-11 DOI: 10.1016/j.clinph.2025.2111435

Elisa Mantovani, Federico Ranieri, Stefano Tamburin

引用次数: 0

Multiple, not just Beta–Gamma, phase-amplitude couplings are associated with Parkinson’s disease and related intervention effects 多重，而不仅仅是β - γ，相位振幅耦合与帕金森病和相关干预效果有关

IF 3.6 3区医学 Q1 CLINICAL NEUROLOGY

Clinical Neurophysiology

Pub Date : 2025-11-11 DOI: 10.1016/j.clinph.2025.2111425

Alireza Kazemi , Salar Nouri , Maryam S. Mirian , Soojin Lee , Martin J. McKeown

Objective

1) To evaluate the importance of various EEG Phase Amplitude Couplings (PACs) in predicting motor vigor (MV) in Parkinson’s Disease (PD). 2) To determine the effects of dopaminergic medication and non-invasive galvanic vestibular stimulation (GVS) on MV-related PACs.

Methods

EEG data from 18 PD patients in comparison to 20 HC controls, executing a simple overlearned handgrip task was used, to identify PD-specific alterations. A deep learning model, PACNET, based on the VGG-16 architecture, was used to predict MV from a visual representation of different PACs.

Results

Delta-Beta, Theta-, Alpha-, and Beta-Gamma PACs were important for MV prediction. In PD subjects, GVS affected Delta-Beta, and Theta-, Beta- Gamma PAC’s role in MV prediction in a stimulation-specific manner. Delta-Beta and Theta-Gamma PACs were more relevant for PD patients’ MV prediction after L-dopa medication.

Conclusions

Multiple PACs are important for MV in Parkinson’s disease. Therapeutic interventions affect PAC/MV associations.

Significance

Multiple PACs, not just Beta–Gamma, are important for MV in PD and may serve as targets for neuromodulation strategies. A combined assessment of PACs could be a valuable biomarker for both disease evaluation and therapeutic effects in PD.

目的1)评价各种EEG相幅耦合（PACs）在预测帕金森病（PD）运动活力（MV）中的重要性。2)探讨多巴胺能药物治疗和无创前庭电刺激（GVS）对mv相关PACs的影响。方法18例PD患者的seeg数据与20例HC对照，执行简单的过度学习握拳任务，以确定PD特异性改变。基于VGG-16架构的深度学习模型PACNET用于从不同pac的视觉表示中预测MV。结果δ - β、θ -、α -和β - γ PACs对MV预测有重要意义。在PD受试者中，GVS以刺激特异性的方式影响Delta-Beta、Theta-、Beta- Gamma PAC在MV预测中的作用。δ - β和θ - γ PACs与左旋多巴治疗后PD患者的MV预测更相关。结论多个PACs在帕金森病的MV中起重要作用。治疗干预影响PAC/MV关联。多种pac，而不仅仅是β - γ，对PD的MV很重要，可能作为神经调节策略的靶点。PACs的联合评估可能是PD疾病评估和治疗效果的有价值的生物标志物。

{"title":"Multiple, not just Beta–Gamma, phase-amplitude couplings are associated with Parkinson’s disease and related intervention effects","authors":"Alireza Kazemi , Salar Nouri , Maryam S. Mirian , Soojin Lee , Martin J. McKeown","doi":"10.1016/j.clinph.2025.2111425","DOIUrl":"10.1016/j.clinph.2025.2111425","url":null,"abstract":"<div><h3>Objective</h3><div>1) To evaluate the importance of various EEG Phase Amplitude Couplings (PACs) in predicting motor vigor (MV) in Parkinson’s Disease (PD). 2) To determine the effects of dopaminergic medication and non-invasive galvanic vestibular stimulation (GVS) on MV-related PACs.</div></div><div><h3>Methods</h3><div>EEG data from 18 PD patients in comparison to 20 HC controls, executing a simple overlearned handgrip task was used, to identify PD-specific alterations. A deep learning model, PACNET, based on the VGG-16 architecture, was used to predict MV from a visual representation of different PACs.</div></div><div><h3>Results</h3><div>Delta-Beta, Theta-, Alpha-, and Beta-Gamma PACs were important for MV prediction. In PD subjects, GVS affected Delta-Beta, and Theta-, Beta- Gamma PAC’s role in MV prediction in a stimulation-specific manner. Delta-Beta and Theta-Gamma PACs were more relevant for PD patients’ MV prediction after L-dopa medication.</div></div><div><h3>Conclusions</h3><div>Multiple PACs are important for MV in Parkinson’s disease. Therapeutic interventions affect PAC/MV associations.</div></div><div><h3>Significance</h3><div>Multiple PACs, not just Beta–Gamma, are important for MV in PD and may serve as targets for neuromodulation strategies. A combined assessment of PACs could be a valuable biomarker for both disease evaluation and therapeutic effects in PD.</div></div>","PeriodicalId":10671,"journal":{"name":"Clinical Neurophysiology","volume":"182 ","pages":"Article 2111425"},"PeriodicalIF":3.6,"publicationDate":"2025-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145616622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine learning predicts cognitive outcome from preterm infants’ EEG 机器学习预测早产儿脑电图的认知结果

IF 3.6 3区医学 Q1 CLINICAL NEUROLOGY

Clinical Neurophysiology

Pub Date : 2025-11-11 DOI: 10.1016/j.clinph.2025.2111433

Tom A. Campbell

引用次数: 0

EEG in the critical care setting 脑电图在重症监护环境

IF 3.6 3区医学 Q1 CLINICAL NEUROLOGY

Clinical Neurophysiology

Pub Date : 2025-11-11 DOI: 10.1016/j.clinph.2025.2111431

Lawrence J. Hirsch , Margaret T. Gopaul

Continuous EEG (cEEG) is increasingly used in the intensive care unit (ICU), but implementation and interpretation remain variable. To better understand its clinical impact, this review evaluates its role in diagnosis, prognostication, and treatment. To do so, we conducted a narrative review of observational studies, randomized controlled trials, consensus recommendations, and illustrative cases across adult and pediatric critical care populations. In these studies, nonconvulsive seizures occur in ∼10–20 % of ICU patients undergoing cEEG, most without clinical signs, and risk is highest in coma, pediatrics, with prior clinical seizures (recent or remote), and acute structural brain injury. Seizure burden > 12 min/hour (20 % burden) qualifies as status epilepticus (SE). Furthermore, higher seizure burden consistently predicts poor outcomes, including hippocampal injury, functional and cognitive impairment, epilepsy, and increased mortality. Additionally, rapid-response EEG and AI-based tools improve diagnostic efficiency, expand access, and may improve outcomes and length of stay. Quantitative EEG can reliably detect other acute brain events, such as delayed cerebral ischemia after subarachnoid hemorrhage, usually sooner than any other practical method. In summary, cEEG has transformed seizure detection and outcome prediction in the ICU, though gaps persist in access, workforce capacity, interpretation, patient selection, and clinical implementation. Broader standardization, expansion of point-of-care rapid EEG devices, and AI integration are critical to scaling cEEG and improving patient outcomes.

连续脑电图（cEEG）越来越多地用于重症监护病房（ICU），但实施和解释仍然存在变数。为了更好地了解其临床影响，本综述评估了其在诊断、预后和治疗中的作用。为此，我们对观察性研究、随机对照试验、共识建议和成人和儿童重症监护人群的说明性病例进行了叙述性回顾。在这些研究中，非惊厥性癫痫发作发生在10 - 20%的ICU患者中，大多数没有临床症状，在昏迷、儿科、既往临床癫痫发作（近期或远期）和急性结构性脑损伤中风险最高。癫痫发作负担12分钟/小时（20%负担）为癫痫持续状态（SE）。此外，较高的癫痫发作负担始终预示着不良结果，包括海马损伤、功能和认知障碍、癫痫和死亡率增加。此外，快速反应脑电图和基于人工智能的工具提高了诊断效率，扩大了可及性，并可能改善结果和住院时间。定量脑电图可以可靠地检测到其他急性脑事件，如蛛网膜下腔出血后的延迟性脑缺血，通常比任何其他实用方法都要快。综上所述，脑电图已经改变了ICU的癫痫发作检测和结果预测，尽管在获取、劳动力能力、解释、患者选择和临床实施方面仍然存在差距。更广泛的标准化、医疗点快速脑电图设备的扩展和人工智能集成对于扩大脑电图和改善患者预后至关重要。

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引用次数: 0

Automated estimation of EEG maturity in preterm neonates and its association with long-term outcome 早产儿脑电图成熟度的自动估计及其与长期预后的关系

IF 3.6 3区医学 Q1 CLINICAL NEUROLOGY

Clinical Neurophysiology

Pub Date : 2025-11-11 DOI: 10.1016/j.clinph.2025.2111432

Johannes Mader , Manfred Hartmann , Katrin Klebermass-Schrehof , Tobias Werther , Anastasia Dressler , Lisa Oberdorfer , Nadine Pointner , Renate Fuiko , Angelika Berger , Tilmann Kluge , Vito Giordano

Objective

To develop convolutional neural network (CNN) models to estimate EEG maturational age (EMA) from EEG recorded via amplitude-integrated EEG monitors in preterm infants and evaluate its association with long-term neurodevelopmental outcomes.

Methods

Three CNN models were trained on EEG data recorded from aEEG monitors from 92 preterm infants (23–41 weeks postmenstrual age) without major neurological complications and with normal cognitive outcomes at 2 years. The best-performing model based on MAE was applied to a broader cohort of 148 infants to assess the relationship between predicted age difference (PAD = EMA – PMA) and neurodevelopmental outcome using the Bayley Scales of Infant and Toddler Development (BSID-III).

Results

The best models achieved 87 % and 84 % accuracy within ± 1 week of actual PMA and a mean absolute error of 0.63 and 0.55 weeks. Infants with severely abnormal cognitive outcomes had significantly lower PAD scores compared to those with normal outcomes (P < 0.001). PAD and MAE showed moderate predictive value (AUC 0.69 and 0.77, respectively).

Conclusions

CNN-based EMA estimation from EEG recorded via aEEG monitors is accurate and correlates with long-term cognitive outcomes in preterm infants.

Significance

This study demonstrates the clinical potential of automated EEG maturity tracking using EEG as a real-time biomarker for neurodevelopmental risk.

目的建立卷积神经网络（CNN）模型，从幅度积分脑电图监测仪记录的早产儿脑电图中估计脑电图成熟年龄（EMA），并评估其与长期神经发育结局的关系。方法对92例经后23-41周龄早产儿（2岁时无重大神经系统并发症，认知功能正常）进行脑电监护，对3个CNN模型进行训练。将基于MAE的最佳模型应用于148名婴儿的更广泛队列，使用Bayley婴幼儿发育量表（bsidi - iii）评估预测年龄差异（PAD = EMA - PMA）与神经发育结局之间的关系。结果最佳模型在实际PMA±1周内的准确度分别为87%和84%，平均绝对误差分别为0.63和0.55周。与认知结果正常的婴儿相比，认知结果严重异常的婴儿PAD评分显著降低（P < 0.001）。PAD和MAE具有中等预测价值（AUC分别为0.69和0.77）。结论通过aEEG监护仪记录的脑电图中基于scnn的EMA估计是准确的，且与早产儿的长期认知结局相关。意义：本研究证明了利用脑电图作为神经发育风险的实时生物标志物进行脑电图成熟度自动跟踪的临床潜力。

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