Center for Neural Science, New York University, New York, New York 10003, and.
Courant Institute of Mathematical Sciences, New York University, New York, New York 10012.
J Neurosci. 2018 Oct 3;38(40):8621-8634. doi: 10.1523/JNEUROSCI.0675-18.2018. Epub 2018 Aug 17.
We studied mechanisms for cortical gamma-band activity in the cerebral cortex and identified neurobiological factors that affect such activity. This was done by analyzing the behavior of a previously developed, data-driven, large-scale network model that simulated many visual functions of monkey V1 cortex (Chariker et al., 2016). Gamma activity was an emergent property of the model. The model's gamma activity, like that of the real cortex, was (1) episodic, (2) variable in frequency and phase, and (3) graded in power with stimulus variables like orientation. The spike firing of the model's neuronal population was only partially synchronous during multiple firing events (MFEs) that occurred at gamma rates. Detailed analysis of the model's MFEs showed that gamma-band activity was multidimensional in its sources. Most spikes were evoked by excitatory inputs. A large fraction of these inputs came from recurrent excitation within the local circuit, but feedforward and feedback excitation also contributed, either through direct pulsing or by raising the overall baseline. Inhibition was responsible for ending MFEs, but disinhibition led directly to only a small minority of the synchronized spikes. As a potential explanation for the wide range of gamma characteristics observed in different parts of cortex, we found that the relative rise times of AMPA and GABA synaptic conductances have a strong effect on the degree of synchrony in gamma. Canonical computations used throughout the cerebral cortex are performed in primary visual cortex (V1). Providing theoretical mechanisms for these computations will advance understanding of computation throughout cortex. We studied one dynamical feature, gamma-band rhythms, in a large-scale, data-driven, computational model of monkey V1. Our most significant conclusion is that the sources of gamma band activity are multidimensional. A second major finding is that the relative rise times of excitatory and inhibitory synaptic potentials have strong effects on spike synchrony and peak gamma band power. Insight gained from studying our V1 model can shed light on the functions of other cortical regions.
我们研究了大脑皮层中伽马波段活动的机制，并确定了影响这种活动的神经生物学因素。这是通过分析一个以前开发的、数据驱动的、大规模网络模型的行为来实现的，该模型模拟了猴子 V1 皮层的许多视觉功能（Chariker 等人，2016）。伽马活动是模型的一个突现属性。模型的伽马活动，就像真实皮层一样，（1）是间歇性的，（2）在频率和相位上是可变的，（3）随着刺激变量（如方向）而分级。模型神经元群体的尖峰发射在发生在伽马率的多次发射事件（MFEs）中仅部分同步。对模型 MFEs 的详细分析表明，伽马波段活动在其来源上是多维的。大多数尖峰是由兴奋性输入引发的。这些输入的很大一部分来自局部回路中的递归兴奋，但前馈和反馈兴奋也有贡献，要么通过直接脉冲要么通过提高整体基线。抑制负责结束 MFEs，但去抑制直接导致只有一小部分同步尖峰。作为对在皮层不同部位观察到的广泛伽马特征的潜在解释，我们发现 AMPA 和 GABA 突触电导的相对上升时间对伽马同步的程度有很强的影响。整个大脑皮层中使用的典型计算是在初级视觉皮层（V1）中进行的。为这些计算提供理论机制将有助于理解皮层中的计算。我们在一个猴子 V1 的大规模、数据驱动的计算模型中研究了一个动态特征，即伽马波段节律。我们最显著的结论是，伽马波段活动的来源是多维的。第二个主要发现是，兴奋性和抑制性突触电位的相对上升时间对尖峰同步和峰值伽马波段功率有很强的影响。从研究我们的 V1 模型中获得的洞察力可以揭示其他皮层区域的功能。
