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A bio-inspired visuotactile neuron for multisensory integration

Author

Listed:
  • Muhtasim Ul Karim Sadaf

    (Penn State University)

  • Najam U Sakib

    (Penn State University)

  • Andrew Pannone

    (Penn State University)

  • Harikrishnan Ravichandran

    (Penn State University)

  • Saptarshi Das

    (Penn State University
    Penn State University
    Penn State University
    Penn State University)

Abstract

Multisensory integration is a salient feature of the brain which enables better and faster responses in comparison to unisensory integration, especially when the unisensory cues are weak. Specialized neurons that receive convergent input from two or more sensory modalities are responsible for such multisensory integration. Solid-state devices that can emulate the response of these multisensory neurons can advance neuromorphic computing and bridge the gap between artificial and natural intelligence. Here, we introduce an artificial visuotactile neuron based on the integration of a photosensitive monolayer MoS2 memtransistor and a triboelectric tactile sensor which minutely captures the three essential features of multisensory integration, namely, super-additive response, inverse effectiveness effect, and temporal congruency. We have also realized a circuit which can encode visuotactile information into digital spiking events, with probability of spiking determined by the strength of the visual and tactile cues. We believe that our comprehensive demonstration of bio-inspired and multisensory visuotactile neuron and spike encoding circuitry will advance the field of neuromorphic computing, which has thus far primarily focused on unisensory intelligence and information processing.

Suggested Citation

  • Muhtasim Ul Karim Sadaf & Najam U Sakib & Andrew Pannone & Harikrishnan Ravichandran & Saptarshi Das, 2023. "A bio-inspired visuotactile neuron for multisensory integration," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-40686-z
    DOI: 10.1038/s41467-023-40686-z
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    References listed on IDEAS

    as
    1. Amritanand Sebastian & Andrew Pannone & Shiva Subbulakshmi Radhakrishnan & Saptarshi Das, 2019. "Gaussian synapses for probabilistic neural networks," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
    2. Pin-Chun Shen & Cong Su & Yuxuan Lin & Ang-Sheng Chou & Chao-Ching Cheng & Ji-Hoon Park & Ming-Hui Chiu & Ang-Yu Lu & Hao-Ling Tang & Mohammad Mahdi Tavakoli & Gregory Pitner & Xiang Ji & Zhengyang Ca, 2021. "Ultralow contact resistance between semimetal and monolayer semiconductors," Nature, Nature, vol. 593(7858), pages 211-217, May.
    3. Rui Yuan & Qingxi Duan & Pek Jun Tiw & Ge Li & Zhuojian Xiao & Zhaokun Jing & Ke Yang & Chang Liu & Chen Ge & Ru Huang & Yuchao Yang, 2022. "A calibratable sensory neuron based on epitaxial VO2 for spike-based neuromorphic multisensory system," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    4. Sarbashis Das & Akhil Dodda & Saptarshi Das, 2019. "A biomimetic 2D transistor for audiomorphic computing," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    5. Akhil Dodda & Nicholas Trainor & Joan. M. Redwing & Saptarshi Das, 2022. "All-in-one, bio-inspired, and low-power crypto engines for near-sensor security based on two-dimensional memtransistors," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    6. Chengpeng Jiang & Jiaqi Liu & Yao Ni & Shangda Qu & Lu Liu & Yue Li & Lu Yang & Wentao Xu, 2023. "Mammalian-brain-inspired neuromorphic motion-cognition nerve achieves cross-modal perceptual enhancement," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    7. Akhil Dodda & Aaryan Oberoi & Amritanand Sebastian & Tanushree H. Choudhury & Joan M. Redwing & Saptarshi Das, 2020. "Stochastic resonance in MoS2 photodetector," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
    8. Yikai Zheng & Harikrishnan Ravichandran & Thomas F. Schranghamer & Nicholas Trainor & Joan M. Redwing & Saptarshi Das, 2022. "Hardware implementation of Bayesian network based on two-dimensional memtransistors," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
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