A Dual-Mode Neural Amplifier Array for Biopotential and FSCV-Based Neurochemical Measurements

The simultaneous measurement of biopotential and neurochemical signals provides a comprehensive view of the brain. Yet, most neural interfaces record solely biopotential or neurochemical activity. This work presents a complementary metal-oxide-semiconductor (CMOS) analog front-end (AFE) chip that integrates 32 biopotential amplifiers and 32 neurochemical amplifiers for parallel recording from 64 electrodes. The biopotential amplifier is a two-stage design providing a gain of 57.1 dB, a bandwidth of 0.4 Hz–6.2 kHz, and 6.7 µVRMS input-referred noise (20 kHz sampling rate). The neurochemical amplifier is a rail-to-rail folded-cascode operational amplifier with selectable transimpedance gain (91.9 kΩ to 851.9 kΩ), a dynamic range of ±15 μA to ±2 μA, respectively, a bandwidth of 12.6 kHz, and input-referred noise as low as 46.3 pARMS (20 kHz sampling rate). The neurochemical amplifiers are designed for fast-scan cyclic voltammetry (FSCV) measurements. I/O complexity is minimized using a time-division multiplexing scheme for readout, enabling straightforward scalability. The chip is fabricated using a 0.35-µm CMOS process and occupies a 3.0 × 8.3 mm2 area. In vitro recordings of catecholamines and neural spikes validate the chip’s function. The chip enables scalable, low-noise, bimodal neural recording, supporting investigations into the dynamics between neuronal biopotential activity and neurochemical signaling.

Authors

Institutions

Publication Details

Journal
Biosensors
Published
2026-08-26
DOI
https://doi.org/10.3390/bios16090466
Primary Topic
Neuroscience and Neural Engineering
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Dual-Mode Neural Amplifier Array for Biopotential and FSCV-Based Neurochemical Measurements

Matthew A. Crocker, Kevin A. White, Mahdieh Darroudi, Brian N. Kim et al.
Biosensors
Neuroscience and Neural Engineering
article

A Dual-Mode Neural Amplifier Array for Biopotential and FSCV-Based Neurochemical Measurements

Matthew A. Crocker, Kevin A. White, Mahdieh Darroudi, Brian N. Kim, Vishnu Saket S. Bapanapalli, Benjamin S. John, Charles S. Lipscomb
article en

Abstract

The simultaneous measurement of biopotential and neurochemical signals provides a comprehensive view of the brain. Yet, most neural interfaces record solely biopotential or neurochemical activity. This work presents a complementary metal-oxide-semiconductor (CMOS) analog front-end (AFE) chip that integrates 32 biopotential amplifiers and 32 neurochemical amplifiers for parallel recording from 64 electrodes. The biopotential amplifier is a two-stage design providing a gain of 57.1 dB, a bandwidth of 0.4 Hz–6.2 kHz, and 6.7 µVRMS input-referred noise (20 kHz sampling rate). The neurochemical amplifier is a rail-to-rail folded-cascode operational amplifier with selectable transimpedance gain (91.9 kΩ to 851.9 kΩ), a dynamic range of ±15 μA to ±2 μA, respectively, a bandwidth of 12.6 kHz, and input-referred noise as low as 46.3 pARMS (20 kHz sampling rate). The neurochemical amplifiers are designed for fast-scan cyclic voltammetry (FSCV) measurements. I/O complexity is minimized using a time-division multiplexing scheme for readout, enabling straightforward scalability. The chip is fabricated using a 0.35-µm CMOS process and occupies a 3.0 × 8.3 mm2 area. In vitro recordings of catecholamines and neural spikes validate the chip’s function. The chip enables scalable, low-noise, bimodal neural recording, supporting investigations into the dynamics between neuronal biopotential activity and neurochemical signaling.

BiosensorsVol. 16(9)
The University of Texas at Dallas (US)
National Institute on Drug Abuse, Air Force Office of Scientific Research
Affordable and clean energy
Openalex Percentile: Top 15%
Neuroscience and Neural Engineering
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.