Task-dependent changes in cross-level coupling between single neurons and oscillatory activity in multiscale networks.
Task-dependent changes in cross-level coupling between single neurons and oscillatory activity in multiscale networks.
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DOI：
10.1371/journal.pcbi.1002809
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发表时间：
2012
影响因子：
4.3
通讯作者：
Carmena JM
中科院分区：
文献类型：
--
作者：
Canolty RT;Ganguly K;Carmena JM
了解大脑功能网络动态协调的原理仍然是神经科学中一个重要的未实现的目标。分布的神经元集合如何在不同的空间和时间尺度上短暂地协调它们的活动？虽然这一过程的完整机制仍然难以捉摸，但有证据表明，神经元振荡可能在这一过程中发挥关键作用，不同的节奏影响本地计算和远程通信。为了研究这个问题，我们记录了多个单一的单位和局部场电位（LFP）的活动，从微电极阵列植入双侧猕猴运动区。猴子执行延迟的中心外伸任务，或者手动使用它们的自然手臂（手动控制，MC），或者通过脑机接口（脑控制，BC）在直接神经控制下进行。与先前的工作雅阁，我们发现在MC和BC期间，单个神经元的尖峰活动与正在进行的运动β节律（10-45 Hz）的多个方面相耦合，神经元表现出多种耦合偏好。然而，在这里，我们表明，对于已识别的单个神经元，这种β-速率映射可以以可逆和任务依赖的方式发生变化。例如，随着β功率增加，给定神经元可以在MC期间增加尖峰，但在BC期间减少尖峰，或者在优选的激发阶段中表现出可逆的移位。任务内耦合的稳定性，结合可逆的跨任务耦合的变化，表明任务依赖性的变化在β-速率映射中发挥作用的短暂功能重组的神经系综。我们的特征的范围内的任务依赖性的变化，从β振幅，相位和半球间的相位差的映射到一个合奏的错误记录的神经元的尖峰率，并讨论了潜在的影响，动态重新映射从振荡活动的尖峰率和定时可能持有分布式功能脑网络的计算和通信模型。一个特定的神经元在一个整体中的功能是如何确定的？神经调谐曲线的概念-从输入变量（如运动方向）到输出放电率的映射-已被证明在研究神经功能方面很有用。然而，先前的工作表明，调谐曲线是不固定的，但可能会重新映射为任务需求的函数-大概是通过高层次的认知控制机制。这是如何实现的？脑节律可能在这一过程中发挥因果作用，但单细胞与网络活动的耦合仍然知之甚少。我们研究了猕猴执行两种不同任务时节律性β活动和尖峰之间的耦合。这种耦合可以用将振荡幅度和相位映射到瞬时尖峰速率的函数来描述。与方向调整类似，这种“内部”调整曲线也表现出与任务相关的变化。我们在一个大的合奏的错误记录的细胞，这些变化的特点，并考虑一些神经计算的影响，单细胞和大规模网络之间的跨级耦合。特别是，相对于缓慢的时间尺度的行为，所观察到的β-速率映射可以证明是有用的调制赢家通吃的动态上的中间时间尺度和相对尖峰时间上的快速时间尺度。
Understanding the principles governing the dynamic coordination of functional brain networks remains an important unmet goal within neuroscience. How do distributed ensembles of neurons transiently coordinate their activity across a variety of spatial and temporal scales? While a complete mechanistic account of this process remains elusive, evidence suggests that neuronal oscillations may play a key role in this process, with different rhythms influencing both local computation and long-range communication. To investigate this question, we recorded multiple single unit and local field potential (LFP) activity from microelectrode arrays implanted bilaterally in macaque motor areas. Monkeys performed a delayed center-out reach task either manually using their natural arm (Manual Control, MC) or under direct neural control through a brain-machine interface (Brain Control, BC). In accord with prior work, we found that the spiking activity of individual neurons is coupled to multiple aspects of the ongoing motor beta rhythm (10–45 Hz) during both MC and BC, with neurons exhibiting a diversity of coupling preferences. However, here we show that for identified single neurons, this beta-to-rate mapping can change in a reversible and task-dependent way. For example, as beta power increases, a given neuron may increase spiking during MC but decrease spiking during BC, or exhibit a reversible shift in the preferred phase of firing. The within-task stability of coupling, combined with the reversible cross-task changes in coupling, suggest that task-dependent changes in the beta-to-rate mapping play a role in the transient functional reorganization of neural ensembles. We characterize the range of task-dependent changes in the mapping from beta amplitude, phase, and inter-hemispheric phase differences to the spike rates of an ensemble of simultaneously-recorded neurons, and discuss the potential implications that dynamic remapping from oscillatory activity to spike rate and timing may hold for models of computation and communication in distributed functional brain networks. How is the functional role of a particular neuron established within an ensemble? The concept of a neural tuning curve – the mapping from input variables such as movement direction to output firing rate – has proven useful in investigating neural function. However, prior work shows that tuning curves are not fixed but may be remapped as a function of task demands – presumably via high-level mechanisms of cognitive control. How is this accomplished? Brain rhythms may play a causal role in this process, but the coupling of single cells to network activity remains poorly understood. We investigated the coupling between rhythmic beta activity and spiking as macaques performed two different tasks. This coupling can be described in terms of a function that maps oscillatory amplitude and phase to instantaneous spike rate. Similarly to direction tuning, this “internal” tuning curve also exhibits task-dependent changes. We characterize these changes across a large ensemble of simultaneously-recorded cells, and consider some of the neuro-computational implications presented by cross-level coupling between single cells and large-scale networks. In particular, relative to the slow time-scale of behavior, the observed beta-to-rate mappings may prove useful for modulating winner-take-all dynamics on intermediate time-scales and relative spike timing on fast time-scales.
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DOI：
10.1073/pnas.1011284108
发表时间：
2011-07-05
影响因子：
11.1
作者：
Buffalo, Elizabeth A.;Fries, Pascal;Desimone, Robert
通讯作者：
Desimone, Robert
DOI：
10.1073/pnas.0308538101
发表时间：
2004-06-29
影响因子：
11.1
作者：
Brovelli, A;Ding, MZ;Bressler, SL
通讯作者：
Bressler, SL
影响因子：
4.3
作者：
Friston K
通讯作者：
Friston K
影响因子：
25
作者：
Fujisawa, Shigeyoshi;Amarasingham, Asohan;Buzsaki, Gyoergy
通讯作者：
Buzsaki, Gyoergy
影响因子：
16.2
作者：
Dean HL;Hagan MA;Pesaran B
通讯作者：
Pesaran B