Quantitative differences in developmental profiles of spontaneous activity in cortical and hippocampal cultures.
Quantitative differences in developmental profiles of spontaneous activity in cortical and hippocampal cultures.
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DOI：
10.1186/s13064-014-0028-0
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发表时间：
2015-01-28
影响因子：
3.6
通讯作者：
Eglen SJ
中科院分区：
文献类型：
--
作者：
Charlesworth P;Cotterill E;Morton A;Grant SG;Eglen SJ
神经回路在发育过程中可以自发地产生复杂的时空放电模式。这种自发活动被认为有助于指导神经系统的发育。在这项研究中，我们有两个目标。首先，表征与小鼠分离的海马或皮质神经元发育网络培养物中自发活动的变化。其次，评估海马和皮质网络的活动模式是否存在功能差异。我们使用多电极阵列在铺板后的第一个月每 2 或 3 天记录海马或皮质神经元培养网络中自发活动的发展。在培养的几天内，网络表现出自发活动。这种活性在体外增强，然后通常在 21 天左右稳定下来。我们使用 11 个特征量化了海马和皮质网络的活动模式。 11 个特征中的 3 个显示出海马和皮质网络之间的活动存在显着差异：（1）海马培养的尖峰序列中的爆发间隔变化较小； (2) 海马网络具有更高的相关性，(3) 海马网络产生更稳健的 θ 爆发模式。机器学习技术证实，这些模式差异足以将任何给定年龄的记录可靠地分类为海马网络或皮质网络。尽管培养的海马网络和皮质网络都会产生随时间变化的自发活动，但在任何给定时间我们都可以可靠地检测到活动模式的差异。我们预计这种定量框架可以在许多领域得到应用，包括神经毒性测试和表征不同突变小鼠的表型。与本报告相关的所有代码和数据均可免费供其他人使用。
Neural circuits can spontaneously generate complex spatiotemporal firing patterns during development. This spontaneous activity is thought to help guide development of the nervous system. In this study, we had two aims. First, to characterise the changes in spontaneous activity in cultures of developing networks of either hippocampal or cortical neurons dissociated from mouse. Second, to assess whether there are any functional differences in the patterns of activity in hippocampal and cortical networks. We used multielectrode arrays to record the development of spontaneous activity in cultured networks of either hippocampal or cortical neurons every 2 or 3 days for the first month after plating. Within a few days of culturing, networks exhibited spontaneous activity. This activity strengthened and then stabilised typically around 21 days in vitro. We quantified the activity patterns in hippocampal and cortical networks using 11 features. Three out of 11 features showed striking differences in activity between hippocampal and cortical networks: (1) interburst intervals are less variable in spike trains from hippocampal cultures; (2) hippocampal networks have higher correlations and (3) hippocampal networks generate more robust theta-bursting patterns. Machine-learning techniques confirmed that these differences in patterning are sufficient to classify recordings reliably at any given age as either hippocampal or cortical networks. Although cultured networks of hippocampal and cortical networks both generate spontaneous activity that changes over time, at any given time we can reliably detect differences in the activity patterns. We anticipate that this quantitative framework could have applications in many areas, including neurotoxicity testing and for characterising the phenotype of different mutant mice. All code and data relating to this report are freely available for others to use.
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影响因子：
2.9
作者：
Seelke, Adele M. H.;Blumberg, Mark S.
通讯作者：
Blumberg, Mark S.
影响因子：
12.3
作者：
Carpenter AE;Jones TR;Lamprecht MR;Clarke C;Kang IH;Friman O;Guertin DA;Chang JH;Lindquist RA;Moffat J;Golland P;Sabatini DM
通讯作者：
Sabatini DM
影响因子：
16.2
作者：
Mao, BQ;Hamzei-Sichani, F;Yuste, R
通讯作者：
Yuste, R
影响因子：
3.4
作者：
Mack, Cina M.;Lin, Bryant J.;Shafer, Timothy J.
通讯作者：
Shafer, Timothy J.
影响因子：
3.5
作者：
Gullo, Francesca;Manfredi, Irene;Becchetti, Andrea
通讯作者：
Becchetti, Andrea