Reconfiguration dynamics of a language-and-memory network in healthy participants and patients with temporal lobe epilepsy.
Reconfiguration dynamics of a language-and-memory network in healthy participants and patients with temporal lobe epilepsy.
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DOI：
10.1016/j.nicl.2021.102702
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Baciu M
中科院分区：
文献类型：
--
作者：
Banjac S;Roger E;Pichat C;Cousin E;Mosca C;Lamalle L;Krainik A;Kahane P;Baciu M
基于LMN网络，语言和记忆作为一个复合函数相互作用。LMN的配置依赖于状态和条件（健康-病理）。LMN重构体现在网络分离和集成的变化上。HC中LMN的重构取决于关键语言和存储区域的灵活性。LMN在TLE中的重构显示出隔离增加和更紧密的模块。目前的理论框架表明，人类行为是基于认知过程之间强大而复杂的相互作用，例如正常人群和神经系统人群中潜在的语言和记忆功能。我们对健康对照（HC, N = 19）和颞叶癫痫患者（TLE, N = 16）的语言和陈述性记忆之间相互作用的动态脑底物（即复合功能）进行了研究。我们的假设是，语言和陈述性记忆的整合是基于语言和记忆网络（LMN），它是动态的，并根据任务需求和大脑状态重新配置。因此，我们探索了两种类型的LMN动态，一种是状态重构（与句子回忆任务评估的外在状态相比的内在静止状态），另一种是状态重构（与HC相比的TLE）。根据隔离（社区或模块检测）和集成（连接器集线器）来评估动态。在HC中，两种状态的分离程度是相同的，LMN状态重构的机制是通过关键语言和具有整合作用的陈述性记忆区域的模块变化来体现的。在TLE患者中，LMN状态重构的重组表现为分离增加和基于更短距离连接的外部模块。虽然侧颞区和内侧颞区能够在HC中实现状态重构，但这些区域在TLE中表现出较低的灵活性。我们从连接组的角度讨论了我们的结果，并提出了语言和陈述性记忆功能的动态模型。我们认为，复杂和互动的认知功能，如语言和陈述性记忆，应该动态地研究，考虑到认知网络之间的相互作用。
Language and memory interact as a composite function based on the LMN network. LMN configuration is state- and condition-dependent (healthy–pathological). LMN reconfiguration is reflected in network segregation and integration changes. LMN reconfiguration in HC depends on flexibility of key language and memory regions. LMN reconfiguration in TLE shows increased segregation and closer modules. Current theoretical frameworks suggest that human behaviors are based on strong and complex interactions between cognitive processes such as those underlying language and memory functions in normal and neurological populations. We were interested in assessing the dynamic cerebral substrate of such interaction between language and declarative memory, as the composite function, in healthy controls (HC, N = 19) and patients with temporal lobe epilepsy (TLE, N = 16). Our assumption was that the language and declarative memory integration is based on a language-and-memory network (LMN) that is dynamic and reconfigures according to task demands and brain status. Therefore, we explored two types of LMN dynamics, a state reconfiguration (intrinsic resting-state compared to extrinsic state assessed with a sentence recall task) and a reorganization of state reconfiguration (TLE compared to HC). The dynamics was evaluated in terms of segregation (community or module detection) and integration (connector hubs). In HC, the level of segregation was the same in both states and the mechanism of LMN state reconfiguration was shown through module change of key language and declarative memory regions with integrative roles. In TLE patients, the reorganization of LMN state reconfiguration was reflected in segregation increase and extrinsic modules that were based on shorter-distance connections. While lateral and mesial temporal regions enabled state reconfiguration in HC, these regions showed reduced flexibility in TLE. We discuss our results in a connectomic perspective and propose a dynamic model of language and declarative memory functioning. We claim that complex and interactive cognitive functions, such as language and declarative memory, should be investigated dynamically, considering the interaction between cognitive networks.
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