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Denver City Hall Examiner Series home•Public Feed Reversal learning is a task which, unlike elemental learning, requires solving ambiguities about the links between events. In Pavlovian learning, for instance, two levels of stimulus ambiguity are represented by differential and reversal conditioning. In differential conditioning, a conditioned stimulus A is associated univocally with an Unconditioned Stimulus (US) while a distinct conditioned stimulus B is unambiguously associated with the absence of US (A+ B-). In reversal conditioning, a first conditioning phase (A+ B-) is followed by a second conditioning phase, which introduces an inversion of stimulus contingencies (A- B+). Thus, the addition of the second phase generates transient stimulus ambiguity (A+ A- and B- B+) that needs to be overcome to solve the problem.
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40%↑ https://vimeo.com/user47401474 Cognition is built on dedicated subsystems: sensory input, evaluation, memory, action selection and ultimately behavioral control. In the olfactory system, attributing a meaning to an olfactory stimulus relies on odor identification. Odor meaning can be coded in evolution (innate systems), or in a lifetime (learned odors), with both systems working in parallel within most animals. However, no sensory system can be understood without understanding all of the sensory input that reaches the brain. This is particularly true for a system that is fundamentally combinatorial, such as the olfactory system. Even though there are situations where all the relevant information about the outside world resides in single information channels (e.g. by activating a pheromone receptor, the presence of that pheromone is conveyed without ambiguity), in most cases, the picture is more complex (e.g., the same pheromone in the wrong olfactory environment will not elicit the same response). The combinatorial nature of olfactory coding has one difficult consequence: no lab will be able to record all responses in all neurons to all possible olfactory stimuli. Therefore, we need a platform that can combine data from different laboratories, using different recording approaches, in order to build a consensus database.
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