Neuronal Multi Unit Activity Processing with Metal Oxide Memristive Devices DOI Creative Commons
Caterina Sbandati, Xiongfei Jiang, Deepika Yadav

et al.

Advanced Electronic Materials, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 6, 2024

Abstract Intra‐cortical brain‐machine interfaces (BMIs), able to decode neural activity in real‐time, represent a revolutionary opportunity for treating medical conditions. However, traditional systems focusing on single‐neuron spike detection require high processing rates and power, hindering the up‐scaling neurons‐population monitoring clinical application. An intriguing proposition is memristive integrating sensor (MIS) approach, which uses resistive RAM (RRAM) threshold‐based detection. MIS leverages analogue multi‐state switching properties of metal‐oxide RRAM compress inputs by encoding above‐threshold events resistance displacement, facilitating efficient data down‐sampling post‐processing, enabling low‐power, high‐channel systems. Initially tested spikes local field potentials, here adapted process multi‐unit envelope (eMUA)—the entire spiking activity—which has recently been proposed as crucial input real‐time neuro‐prosthetic control. Prior necessary modifications effective operation, this adaptation achieved over 95% sensitivity across two types devices: Pt/TiO x /Pt TiN/HfO /TiN, proving its platform‐agnostic capabilities. Furthermore, towards integration with silicon chips, it shown that can reduce total system power consumption below 1 µW, stage relaxes signal preservation noise requirements challenge complementary metal‐oxide‐semiconductor (CMOS) front‐ends. This eMUA‐MIS offers viable pathway developing more scalable BMIs use.

Language: Английский

Investigation of in vitro neuronal activity processing using a CMOS-integrated ZrO2(Y)-based memristive crossbar DOI
M. N. Koryazhkina, Albina Lebedeva,

Darina D. Pakhomova

et al.

Chaos Solitons & Fractals, Journal Year: 2024, Volume and Issue: 191, P. 115959 - 115959

Published: Dec. 28, 2024

Language: Английский

Citations

1
Neuronal Multi Unit Activity Processing with Metal Oxide Memristive Devices DOI Creative Commons
Caterina Sbandati, Xiongfei Jiang, Deepika Yadav

et al.

Advanced Electronic Materials, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 6, 2024

Abstract Intra‐cortical brain‐machine interfaces (BMIs), able to decode neural activity in real‐time, represent a revolutionary opportunity for treating medical conditions. However, traditional systems focusing on single‐neuron spike detection require high processing rates and power, hindering the up‐scaling neurons‐population monitoring clinical application. An intriguing proposition is memristive integrating sensor (MIS) approach, which uses resistive RAM (RRAM) threshold‐based detection. MIS leverages analogue multi‐state switching properties of metal‐oxide RRAM compress inputs by encoding above‐threshold events resistance displacement, facilitating efficient data down‐sampling post‐processing, enabling low‐power, high‐channel systems. Initially tested spikes local field potentials, here adapted process multi‐unit envelope (eMUA)—the entire spiking activity—which has recently been proposed as crucial input real‐time neuro‐prosthetic control. Prior necessary modifications effective operation, this adaptation achieved over 95% sensitivity across two types devices: Pt/TiO x /Pt TiN/HfO /TiN, proving its platform‐agnostic capabilities. Furthermore, towards integration with silicon chips, it shown that can reduce total system power consumption below 1 µW, stage relaxes signal preservation noise requirements challenge complementary metal‐oxide‐semiconductor (CMOS) front‐ends. This eMUA‐MIS offers viable pathway developing more scalable BMIs use.

Language: Английский

Citations

0