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The Ouroboros Model, selected facets.

Knud Thomsen

Advances in experimental medicine and biology 2011 DOI: 10.1007/978-1-4614-0164-3_19 (opens in new tab)

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AI-extracted from the abstract
Characteristics Theoretical or philosophical paper Peer reviewed
Key points Proposes that cognition can be modeled as a self-referential recursive process in which schema-based expectations are continuously compared with incoming data through 'consumption analysis', with mismatches directing attention and a goodness-of-fit signal providing self-monitoring. Argues this architecture can account for phenomena including attention, emotions, priming, masking, learning, sleep, and consciousness.

Abstract

The Ouroboros Model features a biologically inspired cognitive architecture. At its core lies a self-referential recursive process with alternating phases of data acquisition and evaluation. Memory entries are organized in schemata. The activation at a time of part of a schema biases the whole structure and, in particular, missing features, thus triggering expectations. An iterative recursive monitor process termed 'consumption analysis' is then checking how well such expectations fit with successive activations. Mismatches between anticipations based on previous experience and actual current data are highlighted and used for controlling the allocation of attention. A measure for the goodness of fit provides feedback as (self-) monitoring signal. The basic algorithm works for goal directed movements and memory search as well as during abstract reasoning. It is sketched how the Ouroboros Model can shed light on characteristics of human behavior including attention, emotions, priming, masking, learning, sleep and consciousness.

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