Phasic dopamine release identification using ensemble of AlexNet

TL;DR

This paper introduces a CNN-based method using an ensemble of AlexNet to identify phasic dopamine releases from FSCV data, aiming to automate and improve the analysis process.

Contribution

It presents a novel application of ensemble AlexNet CNNs for detecting phasic dopamine release events in FSCV measurements.

Findings

CNN ensemble achieves high accuracy in dopamine detection

Method reduces analysis time compared to traditional techniques

Demonstrates robustness across different experimental conditions

Abstract

Dopamine (DA) is an organic chemical that influences several parts of behaviour and physical functions. Fast-scan cyclic voltammetry (FSCV) is a technique used for in vivo phasic dopamine release measurements. The analysis of such measurements, though, requires notable effort. In this paper, we present the use of convolutional neural networks (CNNs) for the identification of phasic dopamine releases.