Pattern dynamics and stochasticity of the brain rhythms.
Pattern dynamics and stochasticity of the brain rhythms.
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DOI：
10.1073/pnas.2218245120
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发表时间：
2023-04-04
影响因子：
11.1
通讯作者：
Dabaghian, Yuri
中科院分区：
文献类型：
--
作者：
Hoffman, Clarissa;Cheng, Jingheng;Ji, Daoyun;Dabaghian, Yuri
波形通常根据其瞬时特性（不知道是否存在长期行为）或其时间平均特性（突出平均趋势）进行描述。因此，在有限的时间尺度上，波的实际形状和模式仍然没有被探索。我们提出了一种方法，允许量化波形作为单个实体，并归因于波的“规律性”，“典型性”或“有序性”的直观概念的精确含义。因此，它成为可能，以区分统计平凡的模式，从越轨的，并捕捉模式类型之间的过渡。我们使用这些仪器来证明小鼠海马节律的模式在行为和空间环境中动态地与运动活动相耦合，这为海马回路的动力学和功能提供了一个新的视角。我们目前对脑节律的理解是基于量化其瞬时或时间平均特征。波的实际结构--它们在有限时间尺度上的形状和模式--仍然没有被探索。在这里，我们使用两种独立的方法研究不同生理背景下的脑电波模式：第一种是基于量化相对于潜在平均行为的随机性，第二种是评估波特征的“有序性”。相应的措施捕捉波的特征和异常行为，如非典型的周期性或过度聚类，并展示模式的动态和动物的位置，速度和加速度之间的耦合。具体来说，我们研究了在小鼠大脑中记录的θ波、γ波和涟漪波的模式，并观察了波的节奏的速度调制变化、有序性和加速度之间的反相关系以及模式的空间选择性。总之，我们的研究结果提供了一个互补的中尺度的角度来看，脑电波的结构，动力学和功能。
Waveforms are commonly described in terms of their instantaneous properties, which are agnostic of protracted behaviors, or their time-averaged characteristics, which highlight mean trends. The actual shapes and patterns of waves over finite timescales thus remain unexplored. We propose an approach that allows quantifying waveforms as single entities and attributing precise meaning to intuitive notions of waves’ “regularity,” “typicality,” or “orderliness.” Thus, it becomes possible to distinguish statistically mundane patterns from deviant ones and to capture transitions between pattern types. We use these instruments to demonstrate that patterns of hippocampal rhythms in mice are dynamically coupled to motor activity in both behavioral and spatial contexts, which offers a fresh perspective on hippocampal circuit dynamics and functionality. Our current understanding of brain rhythms is based on quantifying their instantaneous or time-averaged characteristics. What remains unexplored is the actual structure of the waves—their shapes and patterns over finite timescales. Here, we study brain wave patterning in different physiological contexts using two independent approaches: The first is based on quantifying stochasticity relative to the underlying mean behavior, and the second assesses “orderliness” of the waves’ features. The corresponding measures capture the waves’ characteristics and abnormal behaviors, such as atypical periodicity or excessive clustering, and demonstrate coupling between the patterns’ dynamics and the animal’s location, speed, and acceleration. Specifically, we studied patterns of θ, γ, and ripple waves recorded in mice hippocampi and observed speed-modulated changes of the wave’s cadence, an antiphase relationship between orderliness and acceleration, as well as spatial selectiveness of patterns. Taken together, our results offer a complementary—mesoscale—perspective on brain wave structure, dynamics, and functionality.
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影响因子：
16.2
作者：
Carr MF;Karlsson MP;Frank LM
通讯作者：
Frank LM
DOI：
10.1523/jneurosci.5110-11.2012
发表时间：
2012-05-23
期刊：
The Journal of neuroscience : the official journal of the Society for Neuroscience
影响因子：
--
作者：
Ahmed OJ;Mehta MR
通讯作者：
Mehta MR
影响因子：
--
作者：
Berger, H
通讯作者：
Berger, H
影响因子：
3.5
作者：
Buzsáki, G
通讯作者：
Buzsáki, G
影响因子：
7.7
作者：
Cheng J;Ji D
通讯作者：
Ji D