A Compact Chopper Stabilized Δ-ΔΣ Neural Readout IC With Input Impedance Boosting

Abstract

This paper presents a scalable neural recording analog front-end architecture enabling simultaneous acquisition of action potentials, local field potentials, electrode DC offsets and stimulation artifacts without saturation. By combining a DC-coupled <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Delta $ </tex-math></inline-formula> - <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Delta \Sigma $ </tex-math></inline-formula> architecture with new bootstrapping and chopping schemes, the proposed readout IC achieves an area of 0.0077 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> per channel, an input-referred noise of 5.53 ± 0.36 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{V}_{\mathrm{ rms}}$ </tex-math></inline-formula> in the action potential band and 2.88 ± 0.18 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{V}_{\mathrm{ rms}}$ </tex-math></inline-formula> in the local field potential band, a dynamic range of 77 dB, an electrode-DC-offset tolerance of ±70 mV and an input impedance of 663 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{M}\Omega $ </tex-math></inline-formula> . To validate this neural readout architecture, we fabricated a 16-channel proof of-concept IC and validated it in an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in vitro</i> setting, demonstrating the capability to record extracellular signals even when using small, high-impedance electrodes. Because of the small area achieved, this architecture can be used to implement ultra-high-density neural probes for large-scale electrophysiology.