Rats recognize spatial and temporal attributes in a new object recognition memory task with multiple trials.

BACKGROUND: Episodic-like memory tasks based on the spontaneous exploration of objects are commonly applied in one-trial protocols. However, multiple-trial designs are known to reduce animal numbers and data variance, providing faster accumulation of data. NEW METHOD: In this study, we devised a new object recognition memory task for rats that carry out multiple trials per session. We developed three types of continual trial tasks: a longer protocol, a shorter protocol, and a protocol in which the experimental session was divided into two days. RESULTS: In our design, rats expressed temporal and spatial memory, but not what-where-when content integration. We found that shorter protocols were more efficient to evaluate memory capabilities. COMPARISON WITH EXISTING METHODS: To the best of our knowledge, it is the first object recognition task with multiple trials that simultaneously assess the temporal and spatial aspects of episodic-like memory. CONCLUSIONS: We suggest that our task is suitable for the simultaneous measurements of brain functions related to spatial and temporal attributes in rats.

Rats hippocampal field potentials feature extraction of wake and sleep stages in Euclidean space.

This paper presents a new methodology of feature extraction of sleep and wake stages of a freely behaving rat based on Continuous Wavelet Transform (CWT). The automatic separation of those stages is very useful for experiments related to learning and memory consolidation since recent scientific evidence indicates that sleep is strongly involved with offline reprocessing of acquired information during waking. Our approach transforms hippocampal Local Field Potentials (LFP) in data vectors that describe the energy distribution pattern of the signal on scaled Morlet wavelets projections. Results indicate that the mathematical analysis used in this work can sensibly describe brain signal patterns that correlate to states of behaviour and that our method can be used for a wider range of applications in neuroscience research.