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An all 2D bio-inspired gustatory circuit for mimicking physiology and psychology of feeding behavior

Author

Listed:
  • Subir Ghosh

    (Penn State University)

  • Andrew Pannone

    (Penn State University)

  • Dipanjan Sen

    (Penn State University)

  • Akshay Wali

    (Penn State University)

  • Harikrishnan Ravichandran

    (Penn State University)

  • Saptarshi Das

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

Abstract

Animal behavior involves complex interactions between physiology and psychology. However, most AI systems neglect psychological factors in decision-making due to a limited understanding of the physiological-psychological connection at the neuronal level. Recent advancements in brain imaging and genetics have uncovered specific neural circuits that regulate behaviors like feeding. By developing neuro-mimetic circuits that incorporate both physiology and psychology, a new emotional-AI paradigm can be established that bridges the gap between humans and machines. This study presents a bio-inspired gustatory circuit that mimics adaptive feeding behavior in humans, considering both physiological states (hunger) and psychological states (appetite). Graphene-based chemitransistors serve as artificial gustatory taste receptors, forming an electronic tongue, while 1L-MoS2 memtransistors construct an electronic-gustatory-cortex comprising a hunger neuron, appetite neuron, and feeding circuit. This work proposes a novel paradigm for emotional neuromorphic systems with broad implications for human health. The concept of gustatory emotional intelligence can extend to other sensory systems, benefiting future humanoid AI.

Suggested Citation

  • Subir Ghosh & Andrew Pannone & Dipanjan Sen & Akshay Wali & Harikrishnan Ravichandran & Saptarshi Das, 2023. "An all 2D bio-inspired gustatory circuit for mimicking physiology and psychology of feeding behavior," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-41046-7
    DOI: 10.1038/s41467-023-41046-7
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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. Sarbashis Das & Akhil Dodda & Saptarshi Das, 2019. "A biomimetic 2D transistor for audiomorphic computing," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    4. 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.
    5. 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.
    6. 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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