Department of Computing, Imperial College London, London, United Kingdom.
PLoS One. 2013 Apr 16;8(4):e62234. doi: 10.1371/journal.pone.0062234. Print 2013.
Groups of neurons firing synchronously are hypothesized to underlie many cognitive functions such as attention, associative learning, memory, and sensory selection. Recent theories suggest that transient periods of synchronization and desynchronization provide a mechanism for dynamically integrating and forming coalitions of functionally related neural areas, and that at these times conditions are optimal for information transfer. Oscillating neural populations display a great amount of spectral complexity, with several rhythms temporally coexisting in different structures and interacting with each other. This paper explores inter-band frequency modulation between neural oscillators using models of quadratic integrate-and-fire neurons and Hodgkin-Huxley neurons. We vary the structural connectivity in a network of neural oscillators, assess the spectral complexity, and correlate the inter-band frequency modulation. We contrast this correlation against measures of metastable coalition entropy and synchrony. Our results show that oscillations in different neural populations modulate each other so as to change frequency, and that the interaction of these fluctuating frequencies in the network as a whole is able to drive different neural populations towards episodes of synchrony. Further to this, we locate an area in the connectivity space in which the system directs itself in this way so as to explore a large repertoire of synchronous coalitions. We suggest that such dynamics facilitate versatile exploration, integration, and communication between functionally related neural areas, and thereby supports sophisticated cognitive processing in the brain.
神经元群同步放电被认为是许多认知功能的基础，如注意力、联想学习、记忆和感觉选择。最近的理论表明，同步和去同步的短暂时期为动态整合和形成功能相关的神经区域联盟提供了一种机制，并且在这些时候，信息传递的条件是最佳的。振荡神经元群体表现出大量的频谱复杂性，几个节律在不同的结构中同时存在并相互作用。本文使用二次积分-点火神经元和 Hodgkin-Huxley 神经元模型探索了神经振荡器之间的带间频率调制。我们在神经振荡器网络中改变结构连接，评估频谱复杂性，并将带间频率调制相关联。我们将这种相关性与亚稳联盟熵和同步性的度量进行对比。我们的结果表明，不同神经群体的振荡相互调制以改变频率，而网络中这些波动频率的相互作用能够使不同的神经群体进入同步状态。此外，我们在连接空间中找到了一个区域，系统以这种方式引导自身，以便探索广泛的同步联盟。我们认为，这种动力学促进了功能相关的神经区域之间的灵活探索、整合和通信，从而支持大脑中复杂的认知处理。
