Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, United States.
Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, Utrecht, Netherlands.
Elife. 2019 Nov 8;8:e47035. doi: 10.7554/eLife.47035.
Gamma oscillations in visual cortex have been hypothesized to be critical for perception, cognition, and information transfer. However, observations of these oscillations in visual cortex vary widely; some studies report little to no stimulus-induced narrowband gamma oscillations, others report oscillations for only some stimuli, and yet others report large oscillations for most stimuli. To better understand this signal, we developed a model that predicts gamma responses for arbitrary images and validated this model on electrocorticography (ECoG) data from human visual cortex. The model computes variance across the outputs of spatially pooled orientation channels, and accurately predicts gamma amplitude across 86 images. Gamma responses were large for a small subset of stimuli, differing dramatically from fMRI and ECoG broadband (non-oscillatory) responses. We propose that gamma oscillations in visual cortex serve as a biomarker of gain control rather than being a fundamental mechanism for communicating visual information.
视觉皮层中的伽马振荡被假设对于感知、认知和信息传递至关重要。然而，对视觉皮层中这些振荡的观察结果差异很大；一些研究报告几乎没有或没有刺激诱导的窄带伽马振荡，其他研究报告只有一些刺激的振荡，还有一些研究报告大多数刺激的大振荡。为了更好地理解这种信号，我们开发了一个模型，可以预测任意图像的伽马响应，并在人类视觉皮层的脑电描记术（ECoG）数据上验证了该模型。该模型计算了空间池化方向通道输出之间的方差，并准确预测了 86 张图像的伽马幅度。伽马响应对于一小部分刺激很大，与 fMRI 和 ECoG 宽带（非振荡）响应有很大的不同。我们提出，视觉皮层中的伽马振荡是增益控制的生物标志物，而不是传递视觉信息的基本机制。
