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在静态fMRI中实施综合信息理论

Idan E Nemirovsky¹, Nicholas J M Popiel², Jorge Rudas³

¹Western Institute for Neuroscience, Department of Physics and Astronomy, University of Western Ontario, 1151 Richmond St, London, ON, N6A 3K7, Canada. inemiro@uwo.ca.

Communications biology

|July 5, 2023

概括

综合信息理论 (IIT) 3.0使用 Φmax.测量意识. 这项研究发现,在镇静期间,特定大脑网络的Fmax变化反映了意识水平的改变.

科学领域:

神经科学是一个神经科学.
认知科学认知科学
信息理论信息理论

背景情况:

综合信息理论 (IIT) 为量化意识提供了一个框架.
意识系统的特点是整合的因果性质.
在改变状态期间评估意识对于理解大脑功能至关重要.

研究的目的:

使用功能性MRI (fMRI) 数据实施和评估综合信息理论3.0 (IIT 3.0) .
为了研究在醇诱导的镇静下,综合信息 (Φmax) 的测量如何变化.
为了将 IIT 3.0 的 Φmax 与其他意识水平测量方法进行比较.

主要方法:

获取了来自17名健康受试者接受普罗波镇静的休息状态fMRI数据.
使用PyPhi软件包计算Fmax,一个关键的IIT指标.
将Fmax与格兰杰因果关系和基于关联的功能连接性进行比较.

主要成果:

普罗波福尔镇静诱导了 Φmax 的各种网络特异性变化.
额前双侧和背侧注意力网络的Φmax变化与意识水平的变化相关.
IIT 3.0对镇静诱导的意识变化表现出敏感性.

结论:

来自 IIT 3.0 的 Φmax 显示为神经成像生物标志物,可用于意识水平.
这些发现凸显了IIT 3.0在药理学挑战下研究意识的实用性.
这项研究为未来的神经成像研究的意识及其测量提供了洞察力.

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