Markowitz David A, Collman Forrest, Brody Carlos D, Hopfield John J, Tank David W
Departments of Molecular Biology and Physics, The Lewis Sigler Institute for Integrative Genomics, and Princeton Neuroscience Institute, Carl Icahn Laboratory, Princeton University, Princeton, NJ 08544, USA.
Proc Natl Acad Sci U S A. 2008 Jun 17;105(24):8422-7. doi: 10.1073/pnas.0803183105. Epub 2008 Jun 11.
Although gamma frequency oscillations are common in the brain, their functional contributions to neural computation are not understood. Here we report in vitro electrophysiological recordings to evaluate how noisy gamma frequency oscillatory input interacts with the overall activation level of a neuron to determine the precise timing of its action potentials. The experiments were designed to evaluate spike synchrony in a neural circuit architecture in which a population of neurons receives a common noisy gamma oscillatory synaptic drive while the firing rate of each individual neuron is determined by a slowly varying independent input. We demonstrate that similarity of firing rate is a major determinant of synchrony under common noisy oscillatory input: Near coincidence of spikes at similar rates gives way to substantial desynchronization at larger firing rate differences. Analysis of this rate-specific synchrony phenomenon reveals distinct spike timing "fingerprints" at different firing rates that emerge through a combination of phase shifting and abrupt changes in spike patterns. We further demonstrate that rate-specific synchrony permits robust detection of rate similarity in a population of neurons through synchronous activation of a postsynaptic neuron, supporting the biological plausibility of a Many Are Equal computation. Our results reveal that spatially coherent noisy oscillations, which are common throughout the brain, can generate previously unknown relationships among neural rate codes, noisy interspike intervals, and precise spike synchrony codes. All of these can coexist in a self-consistent manner because of rate-specific synchrony.
尽管伽马频率振荡在大脑中很常见，但其对神经计算的功能贡献尚不清楚。在此，我们报告体外电生理记录，以评估有噪声的伽马频率振荡输入如何与神经元的整体激活水平相互作用，从而确定其动作电位的精确时间。这些实验旨在评估神经回路结构中的峰电位同步性，在该结构中，一群神经元接收共同的有噪声伽马振荡突触驱动，而每个单个神经元的放电率由缓慢变化的独立输入决定。我们证明，在共同的有噪声振荡输入下，放电率的相似性是同步性的主要决定因素：相似放电率下的峰电位近乎同时出现，而在较大的放电率差异时则会出现显著的去同步化。对这种特定速率同步现象的分析揭示了不同放电率下不同的峰电位时间“指纹”，这些指纹通过相移和峰电位模式的突然变化组合而出现。我们进一步证明，特定速率同步允许通过突触后神经元的同步激活在一群神经元中可靠地检测放电率相似性，支持了“多者相等”计算的生物学合理性。我们的结果表明，在整个大脑中常见的空间相干有噪声振荡可以在神经放电率编码、有噪声的峰电位间隔和精确的峰电位同步编码之间产生以前未知的关系。由于特定速率同步，所有这些都可以以自洽的方式共存。
