Data from: Beyond rhythm - a framework for understanding the frequency spectrum of neural activity

Cognitive and behavioral processes are often accompanied by changes within
well-defined frequency bands of the local field potential (LFP i.e., the
voltage induced by neuronal activity). These changes are detectable in the
frequency domain using the Fourier transform and are often interpreted as
neuronal oscillations. However, aside some well-known exceptions, the
processes underlying such changes are difficult to track in time, making
their oscillatory nature hard to verify. In addition, many non-periodic
neural processes can also have spectra that emphasize specific
frequencies. Thus, the notion that spectral changes reflect oscillations
is likely too restrictive. In this study, we use a simple yet versatile
framework to understand the frequency spectra of neural recordings. Using
simulations, we derive the Fourier spectra of periodic, quasi-periodic and
non-periodic neural processes having diverse waveforms, illustrating how
these attributes shape their spectral signatures. We then show how neural
processes sum their energy in the local field potential in simulated and
real-world recording scenarios. We find that the spectral power of neural
processes is essentially determined by two aspects: 1) the distribution of
neural events in time and 2) the waveform of the voltage induced by single
neural events. Taken together, this work guides the interpretation of the
Fourier spectrum of neural recordings and indicates that power increases
in specific frequency bands do not necessarily reflect periodic neural
activity.

局部场电位（local field potential, LFP，即神经元活动产生的电压）的特定频段内常伴随认知与行为过程的变化。这些变化可通过傅里叶变换（Fourier transform）在频域中检测到，且常被解释为神经元振荡。然而，除了一些众所周知的例外情况外，这些变化背后的过程难以在时间上追踪，使其振荡性质难以验证。此外，许多非周期性神经过程的频谱也可能突出特定频率。因此，认为频谱变化反映振荡的观点可能过于局限。

本研究采用一个简单却多功能的框架来理解神经记录的频谱。通过模拟，我们推导了具有多样波形的周期性、准周期性及非周期性神经过程的傅里叶频谱，阐明了这些属性如何塑造其频谱特征。随后，我们展示了在模拟及真实记录场景中，神经过程如何在局部场电位中叠加能量。研究发现，神经过程的频谱功率本质上由两方面决定：1）神经事件的时间分布；2）单个神经事件产生的电压波形。

综上，本研究为神经记录的傅里叶频谱解释提供了指导，并指出特定频段功率的增加不一定反映周期性神经活动。