Li Anna J, Lu Ziyu, Ladd Alexander E, Matveev Pascha, Shea-Brown Eric, Steinmetz Nicholas A
bioRxiv. 2025 Aug 12:2025.08.08.669442. doi: 10.1101/2025.08.08.669442.
Sensory neuron spiking responses vary across repeated presentations of the same stimuli, but whether this trial-to-trial variability represents noise versus unidentified signals remains unresolved. Some of the variability can be attributed to correlations between neural activity and arousal, locomotion, and other overt movements. We hypothesized that correlations with global activity factors, i.e., patterns of neural activity observable in other brain regions, may explain additional variability in spike count responses of visual cortical neurons. To test this, we used Neuropixels 2.0 probes to record neural activity in mouse primary visual cortex (V1) while subjects passively viewed images. We recorded videos of behavior alongside neural activity from other brain regions, either spiking activity of neural populations in anterior cingulate area (ACA) or widefield calcium signals from across the dorsal cortex. We then used a model based on reduced rank regression to partition the explainable variability of visual cortical responses by source. Some of the trial-to-trial variability in V1 spike counts was attributable to locally shared patterns of activity uncorrelated with either behavior or global activity patterns. Locally shared activity patterns explained trial-to-trial variability that was in excess of Poisson spike generation. Of the parts of variability attributable to non-local sources, global cortical activity predicted significantly more V1 spike count variability than behavioral factors. Additionally, behavioral factors explained little variability uniquely and comprised a geometric subspace of the globally predictable V1 activity. Finally, optogenetically perturbing ACA directly impacted V1 activity, and ACA activity patterns predicted V1 spike count variability even on trials without overt behaviors. Our data indicate that globally shared factors from other cortical areas contribute substantially to shared spike count variability in V1, with only a minority of shared variability confined to local V1 circuits.
感觉神经元的放电反应在相同刺激的重复呈现中会有所不同,但这种逐次试验的变异性是代表噪声还是未识别的信号仍未得到解决。部分变异性可归因于神经活动与觉醒、运动及其他明显动作之间的相关性。我们推测,与全局活动因素(即在其他脑区可观察到的神经活动模式)的相关性可能解释了视觉皮层神经元放电计数反应中的额外变异性。为了验证这一点,我们使用Neuropixels 2.0探针在小鼠初级视觉皮层(V1)记录神经活动,同时让实验对象被动观看图像。我们记录了行为视频以及来自其他脑区的神经活动,要么是前扣带区(ACA)神经群体的放电活动,要么是整个背侧皮层的宽视野钙信号。然后,我们使用基于降秩回归的模型按来源划分视觉皮层反应的可解释变异性。V1放电计数中的一些逐次试验变异性可归因于与行为或全局活动模式均不相关的局部共享活动模式。局部共享活动模式解释了超过泊松放电产生的逐次试验变异性。在可归因于非局部来源的变异性部分中,全局皮层活动比行为因素预测的V1放电计数变异性显著更多。此外,行为因素单独解释的变异性很少,并且构成了全局可预测的V1活动的几何子空间。最后,光遗传学扰动ACA直接影响V1活动,并且即使在没有明显行为的试验中,ACA活动模式也能预测V1放电计数变异性。我们的数据表明,来自其他皮层区域的全局共享因素对V1中共享的放电计数变异性有很大贡献,只有少数共享变异性局限于局部V1回路。