Bidirectionally connected cores in a mouse connectome: towards extracting the brain subnetworks essential for consciousness.
Bidirectionally connected cores in a mouse connectome: towards extracting the brain subnetworks essential for consciousness.
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DOI：
10.1093/cercor/bhac143
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发表时间：
2023-02-07
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影响因子：
--
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意识在大脑中的位置仍然不清楚。有人认为，支持意识的子网络应该是双向（循环）连接的，因为前馈和反馈处理都是有意识的经验所必需的。因此，评估哪些子网络是双向连接的，以及这些连接的强度可能有助于识别对意识至关重要的区域。在这里，我们提出了一种方法，用于分层分解网络成具有不同强度的双向连接的核心，作为揭示复杂的大脑网络的结构的一种手段。我们将该方法应用于全脑小鼠连接体。我们发现，具有强双向连接的核心由可能对意识至关重要的区域组成（例如等皮层和丘脑区域，以及屏状核），并且不包括可能与意识无关的区域（例如小脑）。显然，当我们应用其他忽略双向性的简单方法时，我们无法找到核心和意识之间的这种对应关系。这些发现表明，我们的方法为双向脑网络结构和意识之间的关系提供了新的见解。
Where in the brain consciousness resides remains unclear. It has been suggested that the subnetworks supporting consciousness should be bidirectionally (recurrently) connected because both feed-forward and feedback processing are necessary for conscious experience. Accordingly, evaluating which subnetworks are bidirectionally connected and the strength of these connections would likely aid the identification of regions essential to consciousness. Here, we propose a method for hierarchically decomposing a network into cores with different strengths of bidirectional connection, as a means of revealing the structure of the complex brain network. We applied the method to a whole-brain mouse connectome. We found that cores with strong bidirectional connections consisted of regions presumably essential to consciousness (e.g. the isocortical and thalamic regions, and claustrum) and did not include regions presumably irrelevant to consciousness (e.g. cerebellum). Contrarily, we could not find such correspondence between cores and consciousness when we applied other simple methods that ignored bidirectionality. These findings suggest that our method provides a novel insight into the relation between bidirectional brain network structures and consciousness.
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影响因子：
3
作者：
Aru, Jaan;Suzuki, Mototaka;Bachmann, Talis
通讯作者：
Bachmann, Talis
DOI：
10.1073/pnas.0931349100
发表时间：
2003-04-29
影响因子：
11.1
作者：
Edelman, GM
通讯作者：
Edelman, GM
DOI：
10.1073/pnas.1513302113
发表时间：
2016-02-02
影响因子：
11.1
作者：
Fulcher, Ben D.;Fornito, Alex
通讯作者：
Fornito, Alex
影响因子：
3.4
作者：
Cohen D;van Swinderen B;Tsuchiya N
通讯作者：
Tsuchiya N
影响因子：
56.9
作者：
KIRKPATRICK, S;GELATT, CD;VECCHI, MP
通讯作者：
VECCHI, MP