logLIRA: a method for reliable suppression of electrical stimulation artifacts enabling short-latency neural response recovery

This dataset provides a semisynthetic benchmark for evaluating methods that detect and remove electrical stimulation artifacts in neural recordings, often referred to as Stimulus Artifact Rejection (SAR) algorithms. The dataset is organized into a ZIP archive containing the following components: lookup_table.xlsx: an Excel file mapping each item of the dataset to its corresponding data source, enabling traceability and reproducibility. basal: a folder containing 2.5-minute chunks of basal neural activity. These segments are randomly selected to meet a target mean firing rate (MFR) and are checked to be free of recording artifacts (e.g., movement). templates: a library of clustered and averaged stimulation artifacts extracted from single channels belonging to recordings with Activity-Dependent Stimulation (ADS). These templates serve as the basis for generating semisynthetic stimulation artifacts in the benchmarking snippets. snippets: semisynthetic neural activity snippets that include stimulation artifacts. These are generated by superimposing artifact templates onto basal activity, simulating realistic conditions for stimulation artifact removal.本数据集为一款半合成基准测试集，用于评估神经记录中电刺激伪影的检测与去除方法，这类方法通常被称为刺激伪影剔除（Stimulus Artifact Rejection, SAR）算法。 该数据集以ZIP压缩包形式封装，包含以下组件： lookup_table.xlsx：一份Excel表格，用于将数据集中的每个条目与其对应数据源建立映射，可实现数据可追溯性与实验可复现性。 basal文件夹：内含时长为2.5分钟的基础神经活动片段。这些片段为满足目标平均放电率（mean firing rate, MFR）的要求随机选取，并经检查确保无记录伪影（如运动伪影）。 templates文件夹：一个聚类并经平均化处理的刺激伪影库，该库中的伪影均从依赖活动刺激（Activity-Dependent Stimulation, ADS）的单通道神经记录中提取得到。这些伪影模板将作为基准测试片段中生成半合成刺激伪影的基础。 snippets文件夹：包含嵌入刺激伪影的半合成神经活动片段。这些片段通过将伪影模板叠加至基础神经活动之上生成，以模拟刺激伪影去除任务的真实应用场景。