Manley Jason, Vaziri Alipasha
Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA.
The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA.
bioRxiv. 2025 Jan 20:2024.03.03.583208. doi: 10.1101/2024.03.03.583208.
Animals engaged in naturalistic behavior can exhibit a large degree of behavioral variability even under sensory invariant conditions. Such behavioral variability can include not only variations of the same behavior, but also variability across qualitatively different behaviors driven by divergent cognitive states, such as fight-or-flight decisions. However, the neural circuit mechanisms that generate such divergent behaviors across trials are not well understood. To investigate this question, here we studied the visual-evoked responses of larval zebrafish to moving objects of various sizes, which we found exhibited highly variable and divergent responses across repetitions of the same stimulus. Given that the neuronal circuits underlying such behaviors span sensory, motor, and other brain areas, we built a novel Fourier light field microscope which enables high-resolution, whole-brain imaging of larval zebrafish during behavior. This enabled us to screen for neural loci which exhibited activity patterns correlated with behavioral variability. We found that despite the highly variable activity of single neurons, visual stimuli were robustly encoded at the population level, and the visual-encoding dimensions of neural activity did not explain behavioral variability. This robustness despite apparent single neuron variability was due to the multi-dimensional geometry of the neuronal population dynamics: almost all neural dimensions that were variable across individual trials, i.e. the "noise" modes, were nearly orthogonal to those encoding for sensory information. Investigating this neuronal variability further, we identified two sparsely-distributed, brain-wide neuronal populations whose pre-motor activity predicted whether the larva would respond to a stimulus and, if so, which direction it would turn on a single-trial level. These populations predicted single-trial behavior seconds before stimulus onset, indicating they encoded time-varying internal modulating behavior, perhaps organizing behavior over longer timescales or enabling flexible behavior routines dependent on the animal's internal state. Our results provide the first whole-brain confirmation that sensory, motor, and internal variables are encoded in a highly mixed fashion throughout the brain and demonstrate that de-mixing each of these components at the neuronal population level is critical to understanding the mechanisms underlying the brain's remarkable flexibility and robustness.
即使在感官不变的条件下，表现出自然行为的动物也会展现出很大程度的行为变异性。这种行为变异性不仅可以包括同一行为的变化，还包括由不同认知状态驱动的质的不同行为之间的变异性，例如战斗或逃跑决策。然而，在不同试验中产生这种不同行为的神经回路机制尚未得到很好的理解。为了研究这个问题，我们在此研究了幼体斑马鱼对各种大小移动物体的视觉诱发反应，我们发现相同刺激的重复呈现中，这些反应表现出高度可变且不同的特征。鉴于此类行为背后的神经元回路跨越感觉、运动和其他脑区，我们构建了一种新型傅里叶光场显微镜，它能够在行为过程中对幼体斑马鱼进行高分辨率的全脑成像。这使我们能够筛选出表现出与行为变异性相关活动模式的神经位点。我们发现，尽管单个神经元的活动高度可变，但视觉刺激在群体水平上得到了稳健的编码，并且神经活动的视觉编码维度并不能解释行为变异性。尽管单个神经元明显存在变异性，但这种稳健性是由于神经元群体动力学的多维几何结构：几乎所有在个体试验中可变的神经维度，即“噪声”模式，几乎都与编码感觉信息的维度正交。进一步研究这种神经元变异性时，我们确定了两个稀疏分布的全脑神经元群体，其运动前活动预测幼体是否会对刺激做出反应，如果是，它会在单次试验水平上转向哪个方向。这些群体在刺激开始前几秒预测单次试验行为，表明它们编码随时间变化的内部调节行为，也许在更长的时间尺度上组织行为，或者实现依赖于动物内部状态的灵活行为程序。我们的结果首次提供了全脑层面的证实，即感觉、运动和内部变量在整个大脑中以高度混合的方式编码，并表明在神经元群体水平上分离这些成分中的每一个对于理解大脑卓越的灵活性和稳健性背后的机制至关重要。
