Ardid Salva, Vinck Martin, Kaping Daniel, Marquez Susanna, Everling Stefan, Womelsdorf Thilo
Department of Biology, Centre for Vision Research, York University, Toronto, Ontario M6J 1P3, Canada, Center for Computational Neuroscience and Neural Technology (CompNet), Department of Mathematics and Statistics, Boston University, Boston, Massachusetts 02215,
Department of Neurobiology, Yale University School of Medicine, New Haven, Connecticut 06510, and.
J Neurosci. 2015 Feb 18;35(7):2975-91. doi: 10.1523/JNEUROSCI.2700-14.2015.
Microcircuits are composed of multiple cell classes that likely serve unique circuit operations. But how cell classes map onto circuit functions is largely unknown, particularly for primate prefrontal cortex during actual goal-directed behavior. One difficulty in this quest is to reliably distinguish cell classes in extracellular recordings of action potentials. Here we surmount this issue and report that spike shape and neural firing variability provide reliable markers to segregate seven functional classes of prefrontal cells in macaques engaged in an attention task. We delineate an unbiased clustering protocol that identifies four broad spiking (BS) putative pyramidal cell classes and three narrow spiking (NS) putative inhibitory cell classes dissociated by how sparse, bursty, or regular they fire. We speculate that these functional classes map onto canonical circuit functions. First, two BS classes show sparse, bursty firing, and phase synchronize their spiking to 3-7 Hz (theta) and 12-20 Hz (beta) frequency bands of the local field potential (LFP). These properties make cells flexibly responsive to network activation at varying frequencies. Second, one NS and two BS cell classes show regular firing and higher rate with only marginal synchronization preference. These properties are akin to setting tonically the excitation and inhibition balance. Finally, two NS classes fired irregularly and synchronized to either theta or beta LFP fluctuations, tuning them potentially to frequency-specific subnetworks. These results suggest that a limited set of functional cell classes emerges in macaque prefrontal cortex (PFC) during attentional engagement to not only represent information, but to subserve basic circuit operations.
微电路由多种细胞类型组成,这些细胞类型可能执行独特的电路操作。但是细胞类型如何映射到电路功能在很大程度上尚不清楚,特别是在实际目标导向行为期间的灵长类前额叶皮层中。在这个探索过程中的一个困难是在动作电位的细胞外记录中可靠地区分细胞类型。在这里,我们克服了这个问题,并报告说尖峰形状和神经放电变异性为区分参与注意力任务的猕猴前额叶细胞的七种功能类别提供了可靠的标记。我们描绘了一种无偏聚类协议,该协议识别出四种广泛放电(BS)的假定锥体细胞类别和三种窄放电(NS)的假定抑制性细胞类别,它们根据放电的稀疏、爆发或规则程度而有所不同。我们推测这些功能类别映射到典型的电路功能上。首先,两个BS类别表现出稀疏、爆发性放电,并将其尖峰相位同步到局部场电位(LFP)的3 - 7赫兹(θ)和12 - 20赫兹(β)频段。这些特性使细胞能够灵活地响应不同频率的网络激活。其次,一个NS和两个BS细胞类别表现出规则放电且频率较高,只有轻微的同步偏好。这些特性类似于调节兴奋和抑制的平衡。最后,两个NS类别不规则放电,并与θ或β LFP波动同步,可能将它们调整到特定频率的子网。这些结果表明,在猕猴前额叶皮层(PFC)注意力参与过程中出现了一组有限的功能细胞类别,它们不仅代表信息,还服务于基本的电路操作。