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Optoelectronic graded neurons for bioinspired in-sensor motion perception


Motion processing has proven to be a computational challenge and demands considerable computational resources. Contrast this with the fact that flying insects can agilely perceive real-world motion with their tiny vision system. Here we show that phototransistor arrays can directly perceive different types of motion at sensory terminals, emulating the non-spiking graded neurons of insect vision systems. The charge dynamics of the shallow trapping centres in MoS2 phototransistors mimic the characteristics of graded neurons, showing an information transmission rate of 1,200 bit s−1 and effectively encoding temporal light information. We used a 20 × 20 photosensor array to detect trajectories in the visual field, allowing the efficient perception of the direction and vision saliency of moving objects and achieving 99.2% recognition accuracy with a four-layer neural network. By modulating the charge dynamics of the shallow trapping centres of MoS2, the sensor array can recognize motion with a temporal resolution ranging from 101 to 106 ms.

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Fig. 1: Agile motion perception of the insect visual system.
Fig. 2: Artificially graded neurons for encoding temporal vision.
Fig. 3: In-sensor motion perception with an optoelectronic graded neuron array.
Fig. 4: Action recognition based on bioinspired vision sensors and conventional image sensors.

Data availability

The datasets are available from the corresponding authors upon reasonable request. Source data are provided with this paper.

Code availability

The codes used for neuromorphic computing are available from the corresponding authors upon reasonable request.


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This work was supported by the Research Grant Council of Hong Kong (CRS_PolyU502/22), the Shenzhen Science and Technology Innovation Commission (SGDX2020110309540000), the Innovation Technology Fund (ITS/047/20) and The Hong Kong Polytechnic University (1-ZE1T and CD42). J.-H.A. acknowledges support from the National Research Foundation of Korea (NRF-2015R1A3A2066337).

Author information

Authors and Affiliations



Y.C. conceived the concept and supervised the project. J.C. designed the test protocol and performed the experiments. B.J.K. and J.-H.A. fabricated the devices. J.C., Z.W., T.W. and J.Y. analysed the experimental data. Z.Z., Z.W. and Y.Z. performed the simulations. J.C., Z.Z. and Y.C. co-wrote the paper. All the authors discussed the results and commented on the manuscript.

Corresponding authors

Correspondence to Jong-Hyun Ahn or Yang Chai.

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The authors declare no competing interests.

Peer review

Peer review information

Nature Nanotechnology thanks Feng Miao, Guozhen Shen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Notes I–XI, Figs. 1–20, Table 1 and references.

Supplementary Video 1

Raw video of typical actions from the moving balls’ database.

Supplementary Video 2

Time evolution of a left-moving ball and the corresponding neuromorphic recognition.

Source data

Source Data Fig. 1

Schematic figures.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Simulation results.

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Chen, J., Zhou, Z., Kim, B.J. et al. Optoelectronic graded neurons for bioinspired in-sensor motion perception. Nat. Nanotechnol. (2023).

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