Abstract:
Time courses of neural responses underlie real-time sensory processing and perception. How these temporal dynamics change may be fundamental to how sensory systems adapt to different perceptual demands. By simultaneously recording from hundreds of neurons in mouse primary visual cortex, we examined neural population responses to visual stimuli at sub-second timescales, during different behavioural states. We discovered that during active behavioural states characterised by locomotion, single-neurons shift from transient to sustained response modes, facilitating rapid emergence of visual stimulus tuning. Differences in single-neuron response dynamics were associated with changes in temporal dynamics of neural correlations, including faster stabilisation of stimulus-evoked changes in the structure of correlations during locomotion. Using Factor Analysis, we examined temporal dynamics of latent population responses and discovered that trajectories of population activity make more direct transitions between baseline and stimulus-encoding neural states during locomotion. This could be partly explained by dampening of oscillatory dynamics present during stationary behavioural states. Functionally, changes in temporal response dynamics collectively enabled faster, more stable and more efficient encoding of new visual information during locomotion. These findings reveal a principle of how sensory systems adapt to perceptual demands, where flexible neural population dynamics govern the speed and stability of sensory encoding.
摘要:
神经反应的时间过程是实时感官处理和感知的基础。这些时间动态如何变化可能是感官系统如何适应不同感知需求的基础。通过同时记录小鼠初级视觉皮层的数百个神经元,我们在亚秒时间尺度上检查了神经群体对视觉刺激的反应,在不同的行为状态下。我们发现,在以运动为特征的活动行为状态下,单神经元从瞬时反应模式转变为持续反应模式,促进视觉刺激调谐的快速出现。单神经元反应动力学的差异与神经相关性的时间动力学变化有关,包括在运动过程中刺激诱发的相关性结构变化的更快稳定。使用因子分析,我们研究了潜在群体反应的时间动态,发现在运动过程中,群体活动的轨迹在基线和刺激编码神经状态之间进行更直接的转换.这可以通过抑制静止行为状态下存在的振荡动力学来部分解释。功能上,时间响应动力学的变化集体启用更快,在运动过程中对新的视觉信息进行更稳定和更有效的编码。这些发现揭示了感官系统如何适应感知需求的原理,其中灵活的神经种群动力学控制着感觉编码的速度和稳定性。