Towards a software architecture for neurophysiological experiments

Abstract

Despite their wide adoption for conducting experiments in numerous domains, neurophysiological measurements often are time consuming and challenging to interpret because of the inherent complexity of deriving measures from raw signal data and mapping measures to theoretical constructs. While significant efforts have been undertaken to support neurophysiological experiments, the existing software solutions are non-trivial to use because often these solutions are domain specific or their analysis processes are opaque to the researcher. This paper proposes an architecture for a software platform that supports experiments with multi-modal neurophysiological tools through extensible, transparent and repeatable data analysis and enables the comparison between data analysis processes to develop more robust measures. The identified requirements and the proposed architecture are intended to form a basis of a software platform capable of conducting experiments using neurophysiological tools applicable to various domains.