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首页> 外文期刊>The European Journal of Neuroscience >Characterizing synchrony patterns across cognitive task stages of associative recognition memory
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Characterizing synchrony patterns across cognitive task stages of associative recognition memory

机译：在关联识别存储器的认知任务阶段表征同步模式

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Abstract Numerous studies seek to understand the role of oscillatory synchronization in cognition. This problem is particularly challenging in the context of complex cognitive behavior, which consists of a sequence of processing steps with uncertain duration. In this study, we analyzed oscillatory connectivity measures in time windows that previous computational models had associated with a specific sequence of processing steps in an associative memory recognition task (visual encoding, familiarity, memory retrieval, decision making, and motor response). The timing of these processing steps was estimated on a single‐trial basis with a novel hidden semi‐Markov model multivariate pattern analysis ( HSMM ‐ MVPA ) method. We show that different processing stages are associated with specific patterns of oscillatory connectivity. Visual encoding is characterized by a dense network connecting frontal, posterior, and temporal areas as well as frontal and occipital phase locking in the 4–9?Hz theta band. Familiarity is associated with frontal phase locking in the 9–14?Hz alpha band. Decision making is associated with frontal and temporo‐central interhemispheric connections in the alpha band. During decision making, a second network in the theta band that connects left‐temporal, central, and occipital areas bears similarity to the neural signature for preparing a motor response. A similar theta band network is also present during the motor response, with additionally alpha band connectivity between right‐temporal and posterior areas. This demonstrates that the processing stages discovered with the HSMM ‐ MVPA method are indeed linked to distinct synchronization patterns, leading to a closer understanding of the functional role of oscillations in cognition.
机译：摘要众多研究寻求了解振荡同步在认知中的作用。在复杂的认知行为的背景下，这个问题特别具有挑战性，这包括一系列具有不确定持续时间的处理步骤。在这项研究中，我们分析了以前的计算模型与关联存储器识别任务（视觉编码，熟悉，存储器检索，决策和电机响应的特定处理步骤的特定处理步骤相关联的振荡连接措施。这些处理步骤的定时估计了单一试验基础，具有新的隐藏半马尔可夫模型多变量模式分析（HSMM - MVPA）方法。我们表明不同的处理阶段与振荡连通性的特定模式相关联。视觉编码的特征在于连接前部，后部和颞区域的密集网络以及在4-9的常规区域锁定的额定和枕骨锁定。熟悉程度与9-14个Hz Alpha频带中的额相锁相相关。决策与alpha频段中的额头和颞 - 中央互撞性联系相关联。在决策期间，将左侧时间，中心和枕骨区域连接的θ中的第二网络与用于准备电动机响应的神经签名相似。在电动机响应期间也存在类似的THETA频带网络，右侧区域和后部区域之间的alpha带连接。这表明用HSMM - MVPA方法发现的处理阶段确实与不同的同步模式相关联，这导致对认知中振荡的功能作用更仔细了解。

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