Prof. Tang’s group mapped the precise spatiotemporal functional organization of excitatory synaptic inputs onto macaque V1 neurons


On February 4th, 2020, a paper entitled “Spatiotemporal functional organization of excitatory synaptic inputs onto macaque V1 neurons” was online published in Nature Communications by Prof. Shiming Tang’s group at the School of Life Sciences at Peking University, Peking-Tsinghua Center for Life Sciences and the PKU-IDG/McGovern Institute for Brain Research. This study performed two-photon dendritic imaging with a genetically-encoded glutamate sensor in awake monkeys, and mapped the excitatory synaptic inputs on dendrites of individual V1 superficial layer neurons with high spatial and temporal resolution. Such functional observations, in combination with the first successful application of a newly developed glutamate sensor in behaving non-human primates, provide a bridge to deeper understanding of the dendritic mechanisms and computational principles of visual information processing.


Cortical neurons sample from their dendritic synaptic inputs as the basic unit of computation. Whereas in vitro patch-clamp and intracellular recordings have advanced our understanding of how dendritic synaptic integration occurs in single neurons, and in vivo studies have extended those methods to highlight how dendritic activity contributes to cortical functions such as orientation and direction selectivity, sample size and spatial resolution have limited the utility of these methods. High-resolution two-photon calcium imaging of dendrites, in contrast, can achieve long-term functional mapping of individual dendritic inputs in the intact brain. Because the temporal sequence of synaptic inputs has been verified to be of vital importance to dendritic nonlinear integration, high-speed dendritic imaging can provide important new insights into dendritic computational mechanisms. A recently developed genetically encoded glutamate-sensing fluorescent reporter, iGluSnFR, which has a high signal-to-noise ratio (SNR) and fast kinetics, promises to map the spatiotemporal functional organization of dendritic excitatory inputs.

In this study, we performed two-photon dendritic imaging with iGluSnFR in awake macaque monkeys, and obtained fine functional spatiotemporal maps of dendritic excitatory inputs in individual V1 neurons (Fig. 1a). We found a functional integration and trade-off between orientation-selective and color-selective inputs in basal dendrites of individual V1 neurons (Fig. 1b), which presented a direct evidence of dendritic level computations for orientation and color integration mechanisms.


Fig. 1 Excitatory synaptic inputs onto dendrites of macaque V1 neurons. a, The spatial organization of dendritic excitatory inputs on individual V1 neurons. b, Functional integration and trade-off between orientation/color inputs in individual V1 neurons’ basal dendrites.


Synaptic inputs had a propensity to spatially cluster on dendrites with respect to individual visual features, while tending to be tuned across an array of feature dimensions. One local pair of synaptic inputs might share similar orientation preferences while possessing quite dissimilar RFs (Fig. 2a). In contrast, another pair of synaptic inputs might have both different orientations and dissimilar RFs (Fig. 2b), or different orientations and similar RFs. This wide scattering served to maximize the pool of potential matches between dissimilar features within local dendritic branches. As such, it provides a potential computational substrate for multidimensional feature integration at the dendritic level in V1 superficial layer neurons.


Fig. 2 Synaptic inputs are functionally scattered in multidimensional feature space. a, Two ROIs on one dendritic draft share similar orientation preferences while having distinct RFs. b, Another associated ROIs have both different orientation preferences and different RFs.


Furthermore, we found apical dendrite inputs had larger receptive fields and longer response latencies than basal dendrite inputs (Fig. 3), suggesting a dominant role for apical dendrites in integrating feedback in visual information processing. It remains a challenge to directly dissociate feedback vs feedforward inputs, and our results provide indirect evidence for the provenance of the signals. Future studies will aim to obtain direct evidence by combining new techniques, such as optogenetics or electrophysiology, and specific behavioral tasks, such as a top-down modulated selective attention task.


Fig. 3 Comparison of excitatory dendritic inputs on apical dendrites versus those on basal dendrites. a, Apical and basal dendritic shafts of one example neuron. b, Orientation preference and RF of dendritic inputs on AD and BD. c, Summed orientation preference of orientation-selective ROIs on AD and BD of each neuron. d, AD RF size versus BD’s of each neuron. e, Time courses of response on AD versus BD.


Prof. Shiming Tang from the School of Life Sciences of Peking University, Peking-Tsinghua Center for Life Sciences and the PKU-IDG/McGovern Institute for Brain Research is the corresponding author of this article. Niansheng Ju, a Ph.D. student in Professor Tang’s lab, is the first author of this article; Yang Li, Fang Liu, Hongfei Jiang and Prof. Stephen L. Macknik, Prof. Susana Martinez-Conde made important contributions to this research. This work was supported by National Natural Science Foundation of China (grant no. 31730109), National Basic Research Program of China (grant no. 2017YFA0105201), National Natural Science Foundation of China Outstanding Young Researcher Award (grant no. 30525016) and a Project 985 grant of Peking University, Beijing Municipal Commission of Science and Technology (grant no. Z151100000915070), and a U.S. National Science Foundation grant to SLM and SMC (1734887).



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