Data Transformation in the Processing of Neuronal Signals: A Powerful Tool to Illuminate Informative Contents

Neuroscientists seek efficient solutions for deciphering the sophisticated unknowns of the brain. Effective development of complicated brain-related tools is the focal point of research in neuroscience and neurotechnology. Thanks to today’s technological advancements, the physical development of high-density and high-resolution neural interfaces has been made possible. This is where the critical bottleneck in receiving the expected functionality from such devices shifts to transferring, processing, and subsequently analyzing the massive neurophysiological extra-cellular data recorded. To respond to this inevitable concern, a spectrum of neuronal signal processing techniques have been proposed to extract task-related informative content of the signals conveying neuronal activities, and eliminate the irrelevant contents. Such techniques provide powerful tools for a wide range of neuroscience research, from low-level perception to high-level cognition. Data transformations are among the most efficient processing techniques that serve this purpose by properly changing the data representation. Mapping the data from its original domain (i.e., the time-space domain) to a new representational domain, data transformations change the viewing angle of observing the informative content of the data. This paper reviews the employment of data transformations in order to process neuronal signals and their three key applications, including spike detection, spike sorting, and data compression.

I. Introduction

In The brain, information flows through a network of around 80-100 billion massively-interconnected neurons [1], [2]. Neuroscientists study the brain network in order to discover a broad spectrum of neuronal codes, from low level (e.g., sensory [3], [4]) to high level (e.g., cognitive and behavioral [5], [6]), treat neural disorders (e.g., epilepsy [7], [8]), and restore lost brain functions (e.g., neural prosthesis [9], [10]). For these purposes, monitoring brain activities and connections is usually conducted over a rather long period of time, in the order of weeks to months [3], [11], even up to a few years [10], [12]. Moreover, researchers investigate brain functions as well as their correspondence with sensory information (e.g., for brain mapping) through the modulation of brain activities. Therefore, the techniques and devices developed for brain function monitoring and modulation play a critical role in the progress of neuroscientific research.