School of Neurobiology, Biochemistry, and Biophysics, Tel Aviv University, Tel Aviv, Israel.
School of Physics & Astronomy, Faculty of Exact Sciences, Tel Aviv University, Tel Aviv, Israel.
Elife. 2024 Mar 7;12:RP92254. doi: 10.7554/eLife.92254.
Numerous studies have identified traveling waves in the cortex and suggested they play important roles in brain processing. These waves are most often measured using macroscopic methods that are unable to assess the local spiking activity underlying wave dynamics. Here, we investigated the possibility that waves may not be traveling at the single neuron scale. We first show that sequentially activating two discrete brain areas can appear as traveling waves in EEG simulations. We next reproduce these results using an analytical model of two sequentially activated regions. Using this model, we were able to generate wave-like activity with variable directions, velocities, and spatial patterns, and to map the discriminability limits between traveling waves and modular sequential activations. Finally, we investigated the link between field potentials and single neuron excitability using large-scale measurements from turtle cortex ex vivo. We found that while field potentials exhibit wave-like dynamics, the underlying spiking activity was better described by consecutively activated spatially adjacent groups of neurons. Taken together, this study suggests caution when interpreting phase delay measurements as continuously propagating wavefronts in two different spatial scales. A careful distinction between modular and wave excitability profiles across scales will be critical for understanding the nature of cortical computations.
大量研究已经确定了皮质中的行波，并提出它们在大脑处理中发挥重要作用。这些波通常使用无法评估波动力学基础下局部尖峰活动的宏观方法来测量。在这里，我们研究了波可能不在单个神经元尺度上传播的可能性。我们首先表明，依次激活两个离散的脑区可以在 EEG 模拟中表现出行波。我们接下来使用两个依次激活区域的分析模型再现了这些结果。使用该模型，我们能够生成具有可变方向、速度和空间模式的波状活动，并绘制出行波与模块顺序激活之间的可分辨性极限。最后，我们使用海龟皮质离体的大规模测量来研究场电位和单个神经元兴奋性之间的联系。我们发现，虽然场电位表现出行波动力学，但基础的尖峰活动更好地由空间上相邻的连续激活的神经元群来描述。总的来说，这项研究表明，在两个不同的空间尺度上，当将相位延迟测量解释为连续传播的波阵面时需要谨慎。在不同尺度上对模块和波兴奋性分布进行仔细区分，对于理解皮质计算的本质将至关重要。
