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Periodic Forcing of Inhibition-Stabilized Networks: Nonlinear Resonances and Phase-Amplitude Coupling

机译:抑制稳定网络的周期性强迫:非线性共振和相幅耦合

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摘要

Inhibition-stabilized networks (ISNs) are neural architectures with strong positive feedback among pyramidal neurons balanced by strong negative feedback from inhibitory interneurons, a circuit element found in the hippocampus and the primary visual cortex. In their working regime, ISNs produce damped oscillations in the γ-range in response to inputs to the inhibitory population. In order to understand the properties of interconnected ISNs, we investigated periodic forcing of ISNs. We show that ISNs can be excited over a range of frequencies and derive properties of the resonance peaks. In particular, we studied the phase-locked solutions, the torus solutions, and the resonance peaks. Periodically forced ISNs respond with (possibly multistable) phase-locked activity, whereas networks with sustained intrinsic oscillations respond more dynamically to periodic inputs with tori. Hence, the dynamics are surprisingly rich, and phase effects alone do not adequately describe the network response. This strengthens the importance of phaseamplitude coupling as opposed to phase-phase coupling in providing multiple frequencies for multiplexing and routing information.
机译:抑制稳定网络(ISN)是在锥体神经元之间具有强正反馈的神经体系结构,而锥体神经元之间的强负反馈来自抑制性中间神经元(在海马和主要视觉皮层中发现的回路元件)的强烈负反馈。在其工作方式下,ISN响应于抑制群体的输入而在γ范围内产生阻尼振荡。为了了解互连的ISN的属性,我们研究了ISN的周期性强迫。我们表明,ISN可以在一定频率范围内被激发并得出共振峰的特性。特别是,我们研究了锁相解,环解和共振峰。周期性强迫的ISN以(可能是多稳定的)锁相活动来响应,而具有持续固有振荡的网络对带有tori的周期性输入的响应更加动态。因此,动态令人惊讶地丰富,并且仅相位效应不足以描述网络响应。与相位-相位耦合相反,在提供用于多路复用和路由信息的多个频率时,这增强了相位振幅耦合的重要性。

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  • 期刊名称 other
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  • 年(卷),期 -1(27),12
  • 年度 -1
  • 页码 2477–2509
  • 总页数 38
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