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首页> 美国卫生研究院文献>Frontiers in Neuroscience >Brain–Computer Interface (BCI) Applications in Mapping of Epileptic Brain Networks Based on Intracranial-EEG: An Update
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Brain–Computer Interface (BCI) Applications in Mapping of Epileptic Brain Networks Based on Intracranial-EEG: An Update

机译：脑-计算机接口（BCI）在基于颅内EEG的癫痫性脑网络映射中的应用：更新

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The main applications of the Brain–Computer Interface (BCI) have been in the domain of rehabilitation, control of prosthetics, and in neuro-feedback. Only a few clinical applications presently exist for the management of drug-resistant epilepsy. Epilepsy surgery can be a life-changing procedure in the subset of millions of patients who are medically intractable. Recording of seizures and localization of the Seizure Onset Zone (SOZ) in the subgroup of “surgical” patients, who require intracranial-EEG (icEEG) evaluations, remain to date the best available surrogate marker of the epileptogenic tissue. icEEG presents certain risks and challenges making it a frontier that will benefit from optimization. Despite the presentation of several novel biomarkers for the localization of epileptic brain regions (HFOs-spikes vs. Spikes for instance), integration of most in practices is not at the prime time as it requires a degree of knowledge about signal and computation. The clinical care remains inspired by the original practices of recording the seizures and expert visual analysis of rhythms at onset. It is becoming increasingly evident, however, that there is more to infer from the large amount of EEG data sampled at rates in the order of less than 1 ms and collected over several days of invasive EEG recordings than commonly done in practice. This opens the door for interesting areas at the intersection of neuroscience, computation, engineering and clinical care. Brain–Computer interface (BCI) has the potential of enabling the processing of a large amount of data in a short period of time and providing insights that are not possible otherwise by human expert readers. Our practices suggest that implementation of BCI and Real-Time processing of EEG data is possible and suitable for most standard clinical applications, in fact, often the performance is comparable to a highly qualified human readers with the advantage of producing the results in real-time reliably and tirelessly. This is of utmost importance in specific environments such as in the operating room (OR) among other applications. In this review, we will present the readers with potential targets for BCI in caring for patients with surgical epilepsy.
机译：脑机接口（BCI）的主要应用领域是康复，假肢控制和神经反馈。目前仅存在一些用于治疗耐药性癫痫的临床应用。癫痫手术可以改变数百万名医学上难治的患者的生活。癫痫发作的记录和癫痫发作区（SOZ）在需要接受颅内脑电图（icEEG）评估的“外科”患者亚组中，至今仍是癫痫发生组织的最佳替代指标。 icEEG面临着一定的风险和挑战，使其从优化中受益匪浅。尽管已经提出了一些新颖的生物标记物来定位癫痫脑区域（例如，HFOs-spikes与Spikes），但大多数实践中的整合并不是黄金时间，因为它需要一定程度的信号和计算知识。临床护理仍然受到记录癫痫发作和对发作时节律进行专业视觉分析的原始做法的启发。然而，越来越明显的是，从大量以不到1 ms的速率采样并在几天的侵入性EEG记录中收集到的EEG数据比实际中可以推断出的更多。这为神经科学，计算，工程和临床护理相交的有趣领域打开了大门。脑机接口（BCI）具有潜力，可以在短时间内处理大量数据，并提供人类专家读者无法获得的见解。我们的实践表明，BCI的实现和EEG数据的实时处理是可能的，并且适合大多数标准临床应用，实际上，其性能通常可以与高质量的人类读者相媲美，并且具有实时产生结果的优势。可靠而孜孜不倦。在特定环境中，例如在手术室（OR）和其他应用程序中，这至关重要。在这篇综述中，我们将向读者介绍BCI在治疗外科癫痫患者方面的潜在目标。

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