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域适应增强搜索灯:使大脑状态从视觉感知到心理图像的分类
Alexander Olza1, David Soto2,3, Roberto Santana4
1Intelligent Systems Group, University of the Basque Country (UPV/EHU), Donostia-San Sebastián, Spain. alexander.olza@ehu.eus.
Brain informatics
|June 28, 2025
概括
域适应 (DA) 显著改善了使用fMRI数据预测想象中的视觉刺激. 这种脑-计算机接口研究提高了各种大脑区域的图像解码精度.
科学领域:
- 认知神经科学 认知神经科学
- 大脑与计算机的接口
- 机器学习 机器学习
背景情况:
- 准确地预测想象中的刺激对认知神经科学和脑计算机界面 (BCI) 研究至关重要.
- 当前的方法在从神经成像数据中可靠地解码心理图像时面临挑战.
研究的目的:
- 调查域调整 (DA) 技术在提高想象的视觉刺激的预测准确性的有效性.
- 为了比较不同的DA方法来改善大脑图像解码.
主要方法:
- 利用功能性磁共振成像 (fMRI) 来自18名受试者的数据,专注于视觉刺激.
- 训练了基线并开发了几个DA模型用于图像预测,分析了来自14个大脑区域的数据.
- 进行了DA增强的搜索灯分析和基于 permutation 的统计测试来识别大脑区域.
主要成果:
- 域调整在二进制和多类分类任务中显著提高了图像预测的准确性.
- 用 DA 增强的搜索灯分析确定了一个分布式的大脑区域网络,包括视觉皮层和前双相皮层,用于图像解码.
- 在预测想象中的内容方面,DA方法的性能优于标准的跨领域分类方法.
结论:
- 域适应是一种高度有效的策略,用于增强BCI应用中的大脑图像预测.
- 这项研究强调了DA在从神经成像数据中改善复杂认知状态的解码方面的潜力.
- 开放式可用的代码和数据促进了认知神经科学和BCI开发的进一步研究.
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