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Emergent neuro-mimetic oscillations in engineered granular assemblies
Ankur Bhaumik1, Uddipan Ghosh1, Hridesh Kumar Gupta1
1Solid State and Structural Chemistry Unit, Indian Institute of Science, Bangalore, Karnataka, India. anshup@iisc.ac.in.
Materials Horizons
|May 22, 2026
Summary
Researchers developed a novel oxide nanoparticle system that mimics global brain dynamics like neuronal oscillations and memory. This brain-inspired hardware offers a new path toward efficient computing by emulating collective brain functions.
Area of Science:
- Neuroscience
- Materials Science
- Computer Engineering
Background:
- Conventional computing struggles with power efficiency and mimicking global brain functions like synchronization and memory.
- Existing brain-inspired hardware often focuses on local neural features (spiking, plasticity) but lacks global dynamics emulation.
Purpose of the Study:
- To demonstrate a non-memristive material system capable of emulating collective neuronal oscillations and memory.
- To engineer a system that replicates global brain dynamics using principles of excitatory and inhibitory neuronal interactions.
Main Methods:
- Engineered an oxide nanoparticle system exhibiting spontaneous current oscillations under DC bias.
- Analyzed oscillation characteristics (spectral entropy) at varying electrode separations.
- Investigated system response to external stimuli to demonstrate memory effects.
- Utilized Kinetic Monte Carlo simulations to model and validate experimental dynamics.
Main Results:
- The oxide nanoparticle system showed spontaneous current oscillations with low spectral entropy, mimicking coherent neuronal rhythms.
- Observed scale-dependent synchronization, with random fluctuations at small separations and coherent oscillations at larger ones.
- Demonstrated stimulation-history-dependent memory by reconfiguring oscillatory dynamics in response to stimuli.
- Simulations confirmed collective synchronization and reproduced experimental dynamics.
Conclusions:
- A novel non-memristive material system successfully emulates global brain dynamics, specifically collective neuronal oscillations and memory.
- The engineered system provides a proof-of-principle for brain-inspired hardware that goes beyond local neural features.
- This work opens new avenues for developing power-efficient computing hardware inspired by complex brain functions.
