Researchers Achieve Communication Between Artificial Neurons and Living Brain Tissue

What if machines didn't just mimic the brain-but could actually talk to it?

Engineers at Northwestern University have developed printed artificial neurons that can directly communicate with real brain cells, marking a major step forward in brain-inspired technology. Unlike earlier attempts that only simulated neural activity, these flexible, low-cost devices generate electrical signals that closely match those of living neurons—and can trigger responses in actual brain tissue.

The study was published in the journal Nature Nanotechnology.

In laboratory experiments, the artificial neurons were tested on slices of mouse brain and successfully activated real neurons. This breakthrough demonstrates a new level of compatibility between electronics and biology, opening the door to advanced brain-machine interfaces and neuroprosthetics. In the future, such systems could help restore lost functions like movement, vision, or hearing by seamlessly connecting devices to the nervous system.

The innovation also has major implications for artificial intelligence. Today’s AI systems rely on massive data processing and consume enormous amounts of energy. In contrast, the human brain performs complex tasks using far less power. By mimicking how neurons naturally communicate, this new technology could lead to ultra-efficient computing systems that dramatically reduce energy use.

At the core of the invention are printable electronic materials, including graphene and molybdenum disulfide, layered onto flexible surfaces using advanced printing techniques. These materials allow the artificial neurons to produce a wide range of brain-like signals—from single spikes to complex firing patterns—without requiring large networks of components.

By bridging the gap between machines and living neurons, this research doesn’t just improve technology—it redefines how closely electronics can integrate with the human body and brain.

REFERENCE: Shreyash S. Hadke, Carol N. Klingler, Spencer T. Brown, Meghana Holla, Xudong Zhuang, Linda Li, M. Iqbal Bakti Utama, Santiago Diaz-Arauzo, Anurag Chapagain, Siyang Li, Jung Hun Lee, Indira M. Raman, Vinod K. Sangwan, Mark C. Hersam. Printed MoS2 memristive nanosheet networks for spiking neurons with multi-order complexity. Nature Nanotechnology, 2026; DOI: 10.1038/s41565-026-02149-6