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Resting state networks in the conscious mouse brain: a large-scale c-Fos mapping studyстатья Исследовательская статья
- Авторы: Toropova Ksenia, Ivashkina Olga, Sukhinin Dmitry, Pospelov Nikita, Ivanova Anna Andreevna, Konovalova Elena, Anokhin Konstantin
- Сборник: 2022 Fourth International Conference Neurotechnologies and Neurointerfaces (CNN)
- Год издания: 2022
- Первая страница: 202
- Последняя страница: 205
- DOI: 10.1109/CNN56452.2022.9912533
- Аннотация: A resting state network is a correlated activity of many neural structures in absence of external stimulation or functional tasks, and it is a fundamental endogenous feature of the human and animal brain. However, the nature and function of such spontaneous activity remain poorly understood. One of the hypothesis suggest that they reflect background replay and consolidation of individually acquired neural networks of prior experience. However, classical non-invasive methods used for resting state network detection cannot tag specific cellular elements of the neural network at the time when individual experience is acquired so that their activity can be subsequently investigated in the resting state. To overcome this limitation, we started a project on cellular imaging of mouse resting state networks and relating their activity to animal’s past experiences. We used a large-scale c-Fos imaging of resting state neuronal activity in the mouse brain combined with graph analysis methods to get deeper insights into structure and functional significance of resting state brain networks. We characterized resting-state activity of 104 mouse brain structures and found that there was no direct relationship between anatomical attributes of examined areas and the level of their activity. We also analyzed individual variability of brain areas activity and showed that resting-state networks identified by c-Fos expression were stable and reproducible in all the animals. Next, c-Fos activity of 42 selected brain areas (sensory and motor cortices, hippocampus, parahippocampal cortex, amygdala, basal nuclei, associative and sensory thalamic nuclei, hypothalamic nuclei and midbrain) to characterize the major components and analyze functional connectivity of the resting state network. we identified several major groups of functionally connected areas in the resting state network of awake mouse brain: a cluster of medial prefrontal cortex and other medial associative neocortical areas, a cluster of visual areas, a tightly connected cluster of sensorimotor areas and basal nuclei, and a fully isolated cluster of auditory areas. Importantly, activity of structures known for their relationship to fear and threat learning (such as hippocampus, amygdala, and prelimbic cortex) was not correlated and did not comprise any functional group. This high variability in the activity of fear-related brain structures will be used at the next stage of the project to examine changes in the resting state network activity in relation to prior threat experience.
- Добавил в систему: Ивашкина Ольга Игоревна
Прикрепленные файлы
| № | Имя | Описание | Имя файла | Размер | Добавлен |
|---|---|---|---|---|---|
| 1. | Toropova_IEEE_2022.pdf | Toropova_IEEE_2022.pdf | 481,4 КБ | 14 ноября 2022 [xen.alexander] |