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- W2018350046 abstract "Insects possess miniature brains but exhibit a sophisticated behavioral repertoire. Recent studies have reported the existence of unsuspected cognitive capabilities in various insect species that go beyond the traditionally studied framework of simple associative learning. Here, I focus on capabilities such as attentional modulation and concept learning and discuss their mechanistic bases. I analyze whether these behaviors, which appear particularly complex, can be explained on the basis of elemental associative learning and specific neural circuitries or, by contrast, require an explanatory level that goes beyond simple associative links. In doing this, I highlight experimental challenges and suggest future directions for investigating the neurobiology of higher-order learning in insects, with the goal of uncovering the basic neural architectures underlying cognitive processing. Insects possess miniature brains but exhibit a sophisticated behavioral repertoire. Recent studies have reported the existence of unsuspected cognitive capabilities in various insect species that go beyond the traditionally studied framework of simple associative learning. Here, I focus on capabilities such as attentional modulation and concept learning and discuss their mechanistic bases. I analyze whether these behaviors, which appear particularly complex, can be explained on the basis of elemental associative learning and specific neural circuitries or, by contrast, require an explanatory level that goes beyond simple associative links. In doing this, I highlight experimental challenges and suggest future directions for investigating the neurobiology of higher-order learning in insects, with the goal of uncovering the basic neural architectures underlying cognitive processing. a case of classical conditioning in which a single stimulus A is learned through its association with reinforcement (+). learning about relations between objects rather than about absolute physical features of objects (e.g., color, shape, size). Extracting such relations allows transferring a choice to unknown objects that may differ dramatically in terms of their physical features but that may fulfill the learned relation. Learning about concepts therefore comprises extracting from a series of problems the rule or relation that grants the common solution to these problems. a training protocol used to determine whether a subject can learn the concept of sameness. The subject must match its choice to a stimulus that corresponds to a sample previously presented. Because the sample is regularly changed during the training, animals must learn the concept of sameness; that is ‘always choose what is shown (the sample), independently of what else is shown’. a training protocol used to determine whether a subject can learn the concept of difference. The subject must choose a stimulus that is explicitly different from a sample previously presented. Because the sample is regularly changed during the training, animals must learn the concept of difference; that is, ‘always choose the opposite of what is shown (the sample), independently of what else is shown’. a case of classical conditioning in which, in its simplest form, a stimulus A is learned through its association with reinforcement (+) and a stimulus B through its association with absence of reinforcement (−). learning that is mediated by simple, univocal links between two (or more) events. For instance, an animal may learn an elemental link between a tone and a food reward and another elemental link and between a light and an electric shock as a punishment. Associations learned are unambiguous and specific for the sensory cues learned and their respective outcomes. a process by which a new stimulus evokes a response instead of a previous known stimulus that evoked originally the same response." @default.
- W2018350046 created "2016-06-24" @default.
- W2018350046 creator A5022615273 @default.
- W2018350046 date "2013-05-01" @default.
- W2018350046 modified "2023-10-13" @default.
- W2018350046 title "Cognition with few neurons: higher-order learning in insects" @default.
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