Characterization of neocortical principal cells and Interneurons by network interactions and extracellular features
Characterization of neocortical principal cells and Interneurons by network interactions and extracellular features
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DOI：
10.1152/jn.01170.2003
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发表时间：
2004-07-01
影响因子：
2.5
通讯作者：
Buzsáki, G
中科院分区：
文献类型：
--
作者：
Barthó, P;Hirase, H;Buzsáki, G
皮层中大多数神经元的相互作用发生在局部回路中。由于主细胞和gaba能中间神经元对皮层操作的贡献不同，因此它们的实验鉴定和分离至关重要。采用64位二维硅探针对大鼠体感皮层和前额叶皮层第5层局部神经元进行高密度记录。对单元的多地点监测可以确定它们在大脑中的二维空间位置。在记录的近6万对细胞中，0.2%表现出强劲的短期相互作用。交叉相关图中动作电位后出现明显的短潜伏期（< 3 ms）峰的单位被认为是兴奋性（锥体）细胞。具有显著抑制同伴尖峰的单位被认为是假定的gaba能中间神经元。一部分假定的中间神经元与锥体细胞相互连接。生理上鉴定为抑制性和兴奋性细胞的神经元被用作所有记录神经元分类的模板。在测试的几个参数中，未过滤（1hz至5khz）尖峰的持续时间提供了最可靠的种群聚类。神经元活动的高密度并行记录，确定它们的物理位置，并将它们分为锥体和中间神经元类，为局部电路分析提供了必要的工具。
Most neuronal interactions in the cortex occur within local circuits. Because principal cells and GABAergic interneurons contribute differently to cortical operations, their experimental identification and separation is of utmost important. We used 64-site two-dimensional silicon probes for high-density recording of local neurons in layer 5 of the somatosensory and prefrontal cortices of the rat. Multiple-site monitoring of units allowed for the determination of their two-dimensional spatial position in the brain. Of the similar to60,000 cell pairs recorded, 0.2% showed robust short-term interactions. Units with significant, short-latency ( < 3 ms) peaks following their action potentials in their cross-correlograms were characterized as putative excitatory ( pyramidal) cells. Units with significant suppression of spiking of their partners were regarded as putative GABAergic interneurons. A portion of the putative interneurons was reciprocally connected with pyramidal cells. Neurons physiologically identified as inhibitory and excitatory cells were used as templates for classification of all recorded neurons. Of the several parameters tested, the duration of the unfiltered ( 1 Hz to 5 kHz) spike provided the most reliable clustering of the population. High-density parallel recordings of neuronal activity, determination of their physical location and their classification into pyramidal and interneuron classes provide the necessary tools for local circuit analysis.