Scaglione Alessandro, Resta Francesco, Goretti Francesco, Pavone Francesco S
Department of Physics and Astronomy, University of Florence, Florence, Italy.
European Laboratory for Non-Linear Spectroscopy (LENS), Florence, Italy.
Front Cell Neurosci. 2024 May 10;18:1258793. doi: 10.3389/fncel.2024.1258793. eCollection 2024.
Large-scale cortical dynamics play a crucial role in many cognitive functions such as goal-directed behaviors, motor learning and sensory processing. It is well established that brain states including wakefulness, sleep, and anesthesia modulate neuronal firing and synchronization both within and across different brain regions. However, how the brain state affects cortical activity at the mesoscale level is less understood. This work aimed to identify the cortical regions engaged in different brain states. To this end, we employed group ICA (Independent Component Analysis) to wide-field imaging recordings of cortical activity in mice during different anesthesia levels and the awake state. Thanks to this approach we identified independent components (ICs) representing elements of the cortical networks that are common across subjects under decreasing levels of anesthesia toward the awake state. We found that ICs related to the retrosplenial cortices exhibited a pronounced dependence on brain state, being most prevalent in deeper anesthesia levels and diminishing during the transition to the awake state. Analyzing the occurrence of the ICs we found that activity in deeper anesthesia states was characterized by a strong correlation between the retrosplenial components and this correlation decreases when transitioning toward wakefulness. Overall these results indicate that during deeper anesthesia states coactivation of the posterior-medial cortices is predominant over other connectivity patterns, whereas a richer repertoire of dynamics is expressed in lighter anesthesia levels and the awake state.
大规模皮层动力学在许多认知功能中起着关键作用，如目标导向行为、运动学习和感觉处理。众所周知，包括清醒、睡眠和麻醉在内的脑状态会调节不同脑区内部及之间的神经元放电和同步。然而，脑状态如何在中尺度水平上影响皮层活动却鲜为人知。这项工作旨在确定参与不同脑状态的皮层区域。为此，我们将独立成分分析（ICA）应用于小鼠在不同麻醉水平和清醒状态下皮层活动的宽场成像记录。通过这种方法，我们识别出了代表皮层网络元素的独立成分（IC），这些成分在麻醉水平降低直至清醒状态的过程中在不同个体间是共有的。我们发现，与压后皮质相关的IC对脑状态表现出明显的依赖性，在较深麻醉水平时最为普遍，在向清醒状态转变过程中逐渐减少。通过分析IC的出现情况，我们发现较深麻醉状态下的活动特征是压后成分之间存在强相关性，而在向清醒状态转变时这种相关性会降低。总体而言，这些结果表明，在较深麻醉状态下，后内侧皮层的共同激活比其他连接模式更为突出，而在较浅麻醉水平和清醒状态下则表现出更丰富的动力学特征。
