Journal of Neuroscience Methods 

TL;DR: EELAB as mentioned in this paper is a toolbox and graphic user interface for processing collections of single-trial and/or averaged EEG data of any number of channels, including EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), Independent Component Analysis (ICA) and time/frequency decomposition including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling.

TL;DR: Developments of an open-field water-maze procedure in which rats learn to escape from opaque water onto a hidden platform are described, suggesting that they may lend themselves to a variety of behavioural investigations, including pharmacological work and studies of cerebral function.

TL;DR: Threshold measurement using the up-down paradigm, in combination with the neuropathy pain model, represents a powerful tool for analyzing the effects of manipulations of the neuropathic pain state.

TL;DR: This paper forms a null hypothesis and shows that the nonparametric test controls the false alarm rate under this null hypothesis, enabling neuroscientists to construct their own statistical test, maximizing the sensitivity to the expected effect.

TL;DR: A novel test for the selective identification of anxiolytic and anxiogenic drug effects in the rat is described, using an elevated + -maze consisting of two open arms and two enclosed arms, which showed that behaviour on the maze was not clearly correlated either with exploratory head-dipping or spontaneous locomotor activity.