A Biologically Interfaced Evolvable Organic Pattern Classifier.

ABSTRACT: Future brain-computer interfaces will require local and highly individualized signal processing of fully integrated electronic circuits within the nervous system and other living tissue. New devices will need to be developed that can receive data from a sensor array, process these data into meaningful information, and translate that information into a format that can be interpreted by living systems. Here, the first example of interfacing a hardware-based pattern classifier with a biological nerve is reported. The classifier implements the Widrow-Hoff learning algorithm on an array of evolvable organic electrochemical transistors (EOECTs). The EOECTs' channel conductance is modulated in situ by electropolymerizing the semiconductor material within the channel, allowing for low voltage oper

SUBMITTER: Gerasimov JY 

PROVIDER: S-EPMC10190637 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature