Neurobiology and Cognitive Role of Slow Brain Network Fluctuations

中心摘要：持续的思维模式随着时间的推移而变化， 表明认知通常与正在进行的任务脱钩。一个传统的假设是， 认知反映了认知错误。另一种新的观点是，在"任务外"和"任务内"之间切换， 任务状态是人类认知的基本特征，有助于实现长期目标和心理健康。 过去几十年的实验结果表明，任务外认知伴随着缓慢， 神经/自主神经信号和行为的相关波动，这些与缓慢的 大规模大脑网络激活的准周期性变化。这个康特中心探讨了关闭的成本/效益- 任务认知，同时测试相关的神经活动的缓慢波动的总体假设， 低于1 Hz，低至至少0.01 Hz（秒至数十秒的时间尺度）是关键的 情感、认知和行为的决定因素。我们提出了一组关联假设（概述，b.2.a.），两 其中与神经慢波动特征有关的信息可能代表了大脑运作的组织原则。 首先，局部慢神经波动与更大规模的慢脑网络波动（SBNF）有关， 显著影响认知过程，如注意力，行为指数，如反应时间和自主神经 比如心脏变异性和瞳孔直径第二，神经元之间存在因果层次耦合， 跨从次声延伸到动作电位频率范围的频率的活动;即，的相位 较低的频率控制较高频率的活动幅度。这种"相位振幅耦合"（PAC） 为神经元的分布式集合中的兴奋性状态的网络编排提供了可能的机制， 根据定义，它是跨时间尺度的集成。一方面，SBNF可能是大脑可以用来 根据临时需要或任务要求部署和转移/重新部署PAC和其他资源。上 另一方面，当内源性触发的SBNFs可以为大脑提供避免截留的手段时， 它的资源由一个直接的任务或上下文的要求。尽管我们越来越微妙的 理解个体大脑网络状态及其转换，精确的认知/行为功能 并且SBNFs的潜在生理机制仍然是很大程度上开放的问题。我们解决这两个问题 广泛的问题与研究的综合方案相结合：1）功能磁共振成像/脑电图和颅内（i）脑电图在 人类，非人类灵长类动物（NHP）的fMRI/EEG和场电位/单位记录，以及自主神经功能 所有情况下的测量，2）局部细胞电路和网络生物物理建模，3）实验条件 从结构化的任务到完全没有脚本的会议，以及4）旨在确定因果关系的方法 网络动力学中的元素。该中心的发现将有助于综合机制 对大脑的理解和改善神经精神疾病的治疗。

CENTER ABSTRACT: Patterns of ongoing thought vary over time, and experiences like “mind-wandering” show that cognition is often decoupled from an ongoing task. A traditional assumption is that states of off-task cognition reflects a cognitive error. An emerging alternative view is that switching between “off-task” and on- task states is a fundamental feature of human cognition, facilitating long term goals and mental health. Experimental findings over the past several decades show that off-task cognition is accompanied by slow, correlated fluctuations in neural/autonomic signals and behavior, and that these are strongly linked to slow quasiperiodic shifts in large scale brain network activations. This Conte Center explores the cost/benefits of off- task cognition while testing the overarching hypothesis that related slow fluctuations of neural activity extending below 1 Hz, down to at least 0.01 Hz (timescales of seconds to 10’s of seconds) are critical determinants of affect, cognition and behavior. We pose a set of linking hypotheses (Overview, b.2.a.), two of which relate to features of slow neural fluctuations may represent organizing principles for brain operation. First, local slow neural fluctuations link to larger scale slow brain network fluctuations (SBNFs) that significantly impact cognitive processes like attention, behavioral indices like reaction times and autonomic measures like cardiac variability and pupil diameter. Second, there is causal hierarchical coupling of neural activity across frequencies extending from infraslow up to action potential frequency ranges; i.e., the phase of lower frequency controls the amplitude of activity in higher frequencies. This “phase-amplitude coupling” (PAC) provides a likely mechanism for network orchestration of excitability states in distributed ensembles of neurons, that by definition, integrates across time scales. On one hand, the SBNF may be a tool the brain can use to deploy and shift/re-deploy PAC and other resources according to momentary needs or task demands. On the other hand, when endogenously-triggered SBNFs may provide the brain with a means of avoiding entrapment of its resources by the demands of an immediate task or context. Despite our increasingly nuanced understanding of individual brain network states and their transitions, the precise cognitive/behavioral functions and the underlying physiological mechanisms of SBNFs remain largely open questions. We address these two broad questions with an integrative program of research combining: 1) fMRI/EEG and intracranial (i)EEG in humans, with fMRI/EEG and field potential/unit recordings in nonhuman primates (NHPs), and with autonomic measures in all cases, 2) local cell circuit and network biophysical modeling, 3) experimental conditions ranging from structured tasks to completely unscripted sessions and 4) approaches aimed at identifying causal elements in network dynamics. The Center’s discoveries will contribute to the integrated mechanistic understanding of the brain and to improved treatment of neuropsychiatric disorders.