Author

Hongfei Jiang

Peking University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Neuroscience· 3

Signature Assays, Organisms & Methods

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Assay:imaging· 3 Approach:experimental assay· 2 Organism:non-human primate· 2 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:dimensionality reduction· 1 Assay:electronic health records· 1 Organism:human· 1

Frequent Co-Authors

Shiming TangiD· 3 shared Fang Liu· 1 shared Fang LiuiD· 1 shared Ming LiiD· 1 shared Niansheng JuiD· 1 shared Pinglei BaoiD· 1 shared Qi LuiD· 1 shared Stephen L. MacknikiD· 1 shared

Activity by Year

2018-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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3 shared papersNeuroscience

Shiming TangORCID

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3 papers

Recent·Most cited

Shared and idiosyncratic coding regimes coexist in macaque IT

Qi Lu, Xinyi Xiong, Yang Li, Hongfei Jiang, Pinglei Bao, Shiming Tang

The paper examines coding regimes in macaque inferotemporal cortex, finding both shared low-dimensional representations and sparse, feature-random single-neuron responses that contribute to object recognition.

bioRxiv · Aug 28, 2026 · PreprintNeuroscience

Spatiotemporal functional organization of excitatory synaptic inputs onto macaque V1 neurons

Niansheng Ju, Yang Li, Fang Liu, Hongfei Jiang, Stephen L. Macknik, Susana Martínez‐Conde, Shiming Tang

This study maps excitatory synaptic inputs on V1 neurons in awake macaques, revealing functional clustering and spatial distribution patterns of visual features.

Nature Communications · Feb 4, 2020Peer-reviewedNeuroscience

Large-scale two-photon imaging revealed super-sparse population codes in V1 superficial layer of awake monkeys

Shiming Tang, Yimeng Zhang, Zhihao Li, Ming Li, Fang Liu, Hongfei Jiang, Tai Sing Lee

This study uses two-photon imaging in awake monkeys to show that V1 superficial layer neurons exhibit super-sparse population codes, with only 0.5% responding strongly to any given image.

eLife · Apr 26, 2018Peer-reviewedNeuroscience