Objective. Spike detection from extracellular recordings is a crucial preprocessing step when
analyzing neuronal activity. The decision whether a specific part of the signal is a spike or …

Background Damage to the hippocampus will result in the loss of ability to form new long-
term memories and cognitive disorders. At present, there is no effective medical treatment for …

Neuronal spike detection is a technical challenge because of large amounts of background
noise and contributions of many neurons to recorded signals. In this paper, we propose an …

Spike detection in extracellular recordings is a difficult problem, especially when there are
several noise sources. In this paper, three new approaches based on fractal dimension (FD) …

This paper presents a novel spike detection algorithm in nonstationary signals using a time–
frequency (t–f) approach. The proposed algorithm exploits the direction of signal energy in …

The nonlinear energy operator (NEO) algorithm has been commonly implemented in
hardware for neural spike detection. However, the traditional method to set the threshold is …

Implantable microsystems for monitoring or manipulating brain activity typically require on-
chip real-time processing of multichannel neural data using ultra low-power, miniaturized …

Objective. We aim to increase the number of neural spikes that can be detected in a single
channel extracellular neural recording. Approach. We propose a pre-emphasis method …

This paper models in vivo neural signals and noise for extracellular spike detection.
Although the recorded data approximately follow Gaussian distribution, they clearly deviate …

Background The information obtained from signal recorded with extracellular electrodes is
essential in many research fields with scientific and clinical applications. These signals are …