Cellier Dillan, Riddle Justin, Hammonds Ryan, Frohlich Flavio, Voytek Bradley
Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA 92093.
Department of Psychology, Florida State University, Tallahassee, FL, USA, 32306.
bioRxiv. 2025 May 13:2025.04.21.649913. doi: 10.1101/2025.04.21.649913.
Navigating everyday environments requires that the brain perform information processing at multiple different timescales. For example, while watching a movie we use sensory information from every video frame to construct the current movie scene, which itself is continuously integrated into the narrative arc of the film. This critical function is supported by sensory inputs propagating from dynamic sensory cortices to association cortices, where neural activity remains more stable over time. The hierarchical organization of cortex is therefore reflected in a gradient of neural timescales. While this propagation of inputs up the cortical hierarchy is facilitated by both rhythmic (oscillatory) and non-rhythmic (aperiodic) neural activity, traditional measures of oscillations are often confounded by the influence of aperiodic signals. The reverse is also true: traditional measures of aperiodic neural timescales are influenced by oscillations. This makes it difficult to distinguish between oscillatory and timescale effects in cognition. Here, we analyzed electroencephalography (EEG) data from participants performing a cognitive control task that manipulated the amount of task-relevant contextual information, called task abstraction. Critically, we separated aperiodic neural timescales from the confounding influence of oscillatory power. We hypothesized that neural timescales would increase during the task, and more so in high-abstraction conditions. We found that task abstraction dilated the aperiodic neural timescale, as estimated from the autocorrelation function, over prefrontal cortical regions. Our findings suggests that neural timescales are a dynamic feature of the cerebral cortex that change to meet task demands.
在日常环境中活动要求大脑在多个不同的时间尺度上进行信息处理。例如,在观看电影时,我们利用来自每个视频帧的感官信息来构建当前的电影场景,而这个场景本身又会不断地融入到电影的叙事脉络中。这一关键功能由从动态感觉皮层传播到联合皮层的感觉输入所支持,在联合皮层中,神经活动随时间保持相对稳定。因此,皮层的层次组织反映在神经时间尺度的梯度上。虽然输入在皮层层次结构中的向上传播由节律性(振荡性)和非节律性(非周期性)神经活动共同促进,但传统的振荡测量方法常常受到非周期性信号影响的干扰。反之亦然:传统的非周期性神经时间尺度测量方法也受到振荡的影响。这使得在认知过程中难以区分振荡效应和时间尺度效应。在这里,我们分析了参与者在执行一项认知控制任务时的脑电图(EEG)数据,该任务操纵了与任务相关的上下文信息的数量,即任务抽象度。关键的是,我们将非周期性神经时间尺度与振荡功率的混杂影响区分开来。我们假设在任务过程中神经时间尺度会增加,在高抽象度条件下更是如此。我们发现,根据自相关函数估计,任务抽象度在前额叶皮层区域扩展了非周期性神经时间尺度。我们的研究结果表明,神经时间尺度是大脑皮层的一个动态特征,会根据任务需求而变化。