Advancing neurocomputing with engineered neuronal networks and high-content electrophysiology
June 25, 2026 | 16:00 CEST
7:00 PDT | 10:00 EDT | 15:00 BST
Webinar Hightlights
- Engineering modular connectivity in cultured cortical networks using microfluidic devices
- How network architecture shapes neural dynamics and the computations a network can support
- Harnessing high-dimensional neuronal dynamics for neurocomputing applications
- Closed-loop reservoir computing with living neuronal networks
- Why HD-MEAs are uniquely suited for large-scale, bidirectional neurocomputing interfaces
The webinar covered
- Engineering modular connectivity in cultured cortical networks using microfluidic devices
- The relationship between network architecture, neural dynamics, and computational capacity
- Autonomous temporal pattern generation through closed-loop reservoir computing
- How living neuronal networks can serve as functional reservoirs for neurocomputing
- The role of HD-MEAs in enabling high-resolution, bidirectional interfacing at scale
Agenda
Closed-loop reservoir computing with engineered neuronal networks on HD-MEAs
Abstract
Cultured neuronal networks offer a unique platform for constructively investigating cortical computation: by engineering their structure, one can probe how network architecture shapes the dynamics of the network and the computations it can support. In this talk, I will describe our work on engineering modular connectivity of cultured cortical networks with microfluidic devices (Murota et al., Adv Mater Technol 2025) and on harnessing their high-dimensional dynamics for autonomous temporal pattern generation within a closed-loop reservoir computing framework (Sono et al., PNAS 2026). These experiments are made possible by the unique combination of spatial scale, sub-millisecond temporal resolution, and bidirectional interfacing offered by high-density microelectrode arrays (HD-MEAs).
