Humboldt-Universität zu Berlin, Department of Biology, Institute for Theoretical Biology, 10115 Berlin, Germany.
Bernstein Center for Computational Neuroscience Berlin, 10115 Berlin, Germany.
J Neurosci. 2018 Mar 21;38(12):3124-3146. doi: 10.1523/JNEUROSCI.0188-17.2018. Epub 2018 Feb 16.
Hippocampal ripples are involved in memory consolidation, but the mechanisms underlying their generation remain unclear. Models relying on interneuron networks in the CA1 region disagree on the predominant source of excitation to interneurons: either "direct," via the Schaffer collaterals that provide feedforward input from CA3 to CA1, or "indirect," via the local pyramidal cells in CA1, which are embedded in a recurrent excitatory-inhibitory network. Here, we used physiologically constrained computational models of basket-cell networks to investigate how they respond to different conditions of transient, noisy excitation. We found that direct excitation of interneurons could evoke ripples (140-220 Hz) that exhibited intraripple frequency accommodation and were frequency-insensitive to GABA modulators, as previously shown in experiments. In addition, the indirect excitation of the basket-cell network enabled the expression of intraripple frequency accommodation in the fast-gamma range (90-140 Hz), as In our model, intraripple frequency accommodation results from a hysteresis phenomenon in which the frequency responds differentially to the rising and descending phases of the transient excitation. Such a phenomenon predicts a maximum oscillation frequency occurring several milliseconds before the peak of excitation. We confirmed this prediction for ripples in brain slices from male mice. These results suggest that ripple and fast-gamma episodes are produced by the same interneuron network that is recruited via different excitatory input pathways, which could be supported by the previously reported intralaminar connectivity bias between basket cells and functionally distinct subpopulations of pyramidal cells in CA1. Together, our findings unify competing inhibition-first models of rhythm generation in the hippocampus. The hippocampus is a part of the brain of humans and other mammals that is critical for the acquisition and consolidation of memories. During deep sleep and resting periods, the hippocampus generates high-frequency (∼200 Hz) oscillations called ripples, which are important for memory consolidation. The mechanisms underlying ripple generation are not well understood. A prominent hypothesis holds that the ripples are generated by local recurrent networks of inhibitory neurons. Using computational models and experiments in brain slices from rodents, we show that the dynamics of interneuron networks clarify several previously unexplained characteristics of ripple oscillations, which advances our understanding of hippocampus-dependent memory consolidation.
海马回波涉及记忆巩固，但产生它们的机制仍不清楚。依赖于 CA1 区域中间神经元网络的模型在中间神经元兴奋的主要来源上存在分歧：一种是“直接的”，通过沙斐尔侧支从 CA3 到 CA1 提供前馈输入；另一种是“间接的”，通过 CA1 中的局部锥体神经元，它们嵌入在一个递归兴奋-抑制网络中。在这里，我们使用 basket-cell 网络的生理约束计算模型来研究它们对不同条件的短暂、嘈杂兴奋的反应。我们发现，中间神经元的直接兴奋可以引发表现出涟漪内频率适应的涟漪（140-220 Hz），并且对 GABA 调节剂不敏感，如先前的实验所示。此外，basket-cell 网络的间接兴奋使快速伽马范围内的涟漪内频率适应得以表达（90-140 Hz），如在我们的模型中，涟漪内频率适应是由滞后现象引起的，其中频率对瞬态兴奋的上升和下降阶段的响应不同。这种现象预测了在兴奋峰值前几毫秒发生的最大振荡频率。我们在来自雄性小鼠的脑片上证实了这一预测。这些结果表明，涟漪和快速伽马爆发是由相同的中间神经元网络产生的，该网络通过不同的兴奋输入途径被招募，这可以由先前报道的 CA1 中 basket 细胞和功能上不同的锥体细胞亚群之间的层间连接偏好来支持。总的来说，我们的发现统一了海马中节律产生的竞争抑制优先模型。海马是人类和其他哺乳动物大脑的一部分，对于记忆的获取和巩固至关重要。在深度睡眠和休息期间，海马会产生高频（约 200 Hz）称为涟漪的振荡，这对记忆巩固很重要。涟漪产生的机制尚不清楚。一个突出的假设是，涟漪是由局部兴奋神经元的递归网络产生的。使用计算模型和来自啮齿动物的脑片实验，我们表明中间神经元网络的动力学澄清了涟漪振荡的几个以前未解释的特征，这提高了我们对海马依赖性记忆巩固的理解。
