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Distinguishing cognitive state with multifractal complexity of hippocampal interspike interval sequences

机译:区分认知状态与海马突刺间隔序列的多重分形复杂性

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摘要

Fractality, represented as self-similar repeating patterns, is ubiquitous in nature and the brain. Dynamic patterns of hippocampal spike trains are known to exhibit multifractal properties during working memory processing; however, it is unclear whether the multifractal properties inherent to hippocampal spike trains reflect active cognitive processing. To examine this possibility, hippocampal neuronal ensembles were recorded from rats before, during and after a spatial working memory task following administration of tetrahydrocannabinol (THC), a memory-impairing component of cannabis. Multifractal detrended fluctuation analysis was performed on hippocampal interspike interval sequences to determine characteristics of monofractal long-range temporal correlations (LRTCs), quantified by the Hurst exponent, and the degree/magnitude of multifractal complexity, quantified by the width of the singularity spectrum. Our results demonstrate that multifractal firing patterns of hippocampal spike trains are a marker of functional memory processing, as they are more complex during the working memory task and significantly reduced following administration of memory impairing THC doses. Conversely, LRTCs are largest during resting state recordings, therefore reflecting different information compared to multifractality. In order to deepen conceptual understanding of multifractal complexity and LRTCs, these measures were compared to classical methods using hippocampal frequency content and firing variability measures. These results showed that LRTCs, multifractality, and theta rhythm represent independent processes, while delta rhythm correlated with multifractality. Taken together, these results provide a novel perspective on memory function by demonstrating that the multifractal nature of spike trains reflects hippocampal microcircuit activity that can be used to detect and quantify cognitive, physiological, and pathological states.
机译:分形,表现为自相似的重复模式,在自然界和大脑中无处不在。已知海马突波序列的动态模式在工作记忆处理过程中表现出多重分形特性。然而,尚不清楚海马突波序列固有的多重分形特性是否反映了主动的认知过程。为了检验这种可能性,在进行四氢大麻酚(THC)(大麻的一种损害记忆的成分)后,在进行空间工作记忆任务之前,期间和之后,从大鼠中记录了海马神经元整合体。对海马棘突间期序列进行多分形去趋势波动分析,以确定由Hurst指数量化的单形长时程相关性(LRTC)的特征,以及由奇异谱的宽度量化的多形复杂度/程度。我们的研究结果表明,海马突波序列的多重分形发射模式是功能记忆处理的标志,因为它们在工作记忆任务期间更为复杂,并且在给予记忆损害THC剂量后显着减少。相反,LRTC在静止状态记录期间最大,因此与多重分形相比反映了不同的信息。为了加深对多重分形复杂度和LRTC的概念理解,将这些测量与使用海马频率含量和射击变异性测量的经典方法进行了比较。这些结果表明,LRTC,多重分形和θ节奏代表独立的过程,而δ节奏与多重分形相关。综上所述,这些结果证明了穗序列的多重分形性质反映了可用于检测和量化认知,生理和病理状态的海马微电路活动,从而为记忆功能提供了新颖的视角。

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