Latent Inhibition

Associative Learning

Latent Inhibition describes the reduction in associative learning ability when a stimulus is applied in a pre-exposure session without any consequences before it is paired with an unconditioned stimulus (foot shock) in a subsequent associative learning paradigm. Learning of CS-US association is then impaired as compared to animals that have not been pre-exposed to the CS. This phenomenon is supposed to act as filter mechanism, i.e. an adaptive advantage that protects subjects from irrelevant environmental stimuli and is typically studied in rodent models of schizophrenia.

Latent inhibition experiments are performed with the Multi Conditioning  System “2-compartment paradigms” software using the multi-purpose 2-compartment Active Avoidance arena. Present the CS alone or in a customized combination with other stimuli in the Pre-Exposure session – light, sound and/or noise – individually, in parallel or randomized – all software-controlled. Or pre-expose to context, before or after CS-pre-exposure to study the influence of context on learning.

In the Active Avoidance paradigm that uses the former neutral stimulus as conditioned stimulus a variety of experimental parameters can be customized to fulfill your test requirements. Analyze the learning performance of the animal by evaluating avoidance and response reactions and use the large collection of movement parameters for a comprehensive evaluation of animal behavior.

Please note that a modified Latent Inhibition paradigm also can be performed with the Fear Conditioning module of the Multi Conditioning System.


Utilizes universal Active Avoidance test arena.
Combination of Pre-Exposure and Active Avoidance sessions.
Flexible application of stimuli during Pre-Exposure – all software-controlled.
Trial-by-trial movement & activity analysis in the Active Avoidance paradigm .
Ready-to-use export files for further statistical calculations.
Simultaneous camera observation under any light conditions.


Cognitive Functions..

Disease model