Power-Efficient LFP-Adaptive Dynamic Zoom-and-Track Incremental ΔΣ Front-End for Dual-Band Subcortical Recordings

Area of Science:

• Neuroscience
• Electrical Engineering
• Biomedical Engineering

Background:

• Subcortical recordings require high-resolution, low-power integrated circuits.
• Existing methods often struggle with power efficiency and signal fidelity.

Purpose of the Study:

• To develop a power-efficient analog front-end integrated circuit (IC) for multi-channel, dual-band subcortical recordings.
• To improve the resolution and reduce power consumption in neural recording devices.

Main Methods:

• Implemented an incremental ΔΣ analog-to-digital converter (IADC) with a dynamic zoom-and-track scheme.
• The scheme adaptively adjusts the input dynamic range to resolve small action potentials.
• Fabricated a prototype four-channel front-end IC using 180 nm standard CMOS processes.

Main Results:

• Achieved 11.3-bit effective number of bits (ENOB) at 6.8 μW, setting new benchmarks for Walden and SNDR figures of merit (FoMs).
• Demonstrated superior performance compared to state-of-the-art neural recording front-ends and similar zooming/tracking ADCs.
• Reduced post-processing FPGA resources for subcortical signal separation by over 45.8% due to intrinsic dual-band recording.
• Front-end IC showed an NEF of 5.9 with input-referred noise of 8.2 μVrms, suitable for subcortical recordings.
• Validated performance through in vivo animal experiments.

Conclusions:

• The developed power-efficient analog front-end IC with a zoom-and-track IADC is highly suitable for high-resolution subcortical recordings.
• The novel IADC scheme offers significant power savings and improved signal resolution.
• The intrinsic dual-band recording capability simplifies signal processing.