Micromap: A low-cost multi-channel electrophysiology acquisition system
Abstract
To develop an accessible, low-cost, and open-source system for multi-channel electrophysiological recordings across multiple brain regions, facilitating the investigation of neural dynamics and information flow in long-range integration. Approach: We designed a digital signal acquisition system that integrates two programmable analog-to-digital converter chipsets -- Intan RHD and Texas Instruments ADS -- with an Arduino-based microcontroller. In addition, we introduce a custom-designed headstage and a methodology for spatially distributed electrode placement using a perforated printed circuit board, which interfaces directly with the system to enable local field potential recordings from multiple brain regions. The system successfully recorded biopotentials without significant sample loss and performed comparably to gold-standard systems, enabling recordings across 32 channels at a 2 kHz sampling frequency. We verified signal integrity and stability under both experimental and simulated conditions, confirming the platform’s suitability for electrophysiology. Main results: We present a comprehensive, low-cost bioengineering solution for distributed electrophysiological recordings, enabling detailed investigation of brain dynamics through synchronized neural activity across regions. Significance: This open-source platform enables neuroscience laboratories to investigate large-scale neural interactions with high temporal precision, expanding access to systems neuroscience tools essential for understanding interregional brain connectivity. • Presents MicroMAP, a low-cost, open-source system for LFP recording • Replaces expensive FPGAs with an Arduino microcontroller for control • Includes a novel assembly method for precise multi-site electrode arrays • System validated against Open Ephys with comparable results • Supports both Intan RHD and Texas Instruments ADS series chipsets
Fields of Study & Subjects
Neuroscience and Neural Engineering
Embedded Systems and FPGA Design
Undergraduate Neuroscience Education and Research
Publication details
- Journal / source
- Journal of Neuroscience Methods
- Volume
- 429
- Pages
- 110691–110691
- Publication date
- 16 January 2026
- Language
- EN