Lower‐level associations in Gilles de la Tourette syndrome: Convergence between hyperbinding of stimulus and response features and procedural hyperfunctioning theories. (7th July 2021)

• Record Type: Journal Article
• Authors: Takacs, Adam; Münchau, Alexander; Nemeth, Dezso; Roessner, Veit; Beste, Christian
• Is Part Of: European journal of neuroscience. Volume 54:Number 3(2021)
• Page Start: 5143
• Page End: 5160
• Publication Date: 2021-07-07
• Subjects: Gilles de la Tourette syndrome -- habits -- procedural memory -- sequence learning -- theory of event coding; Nervous system -- Periodicals; 612.8
• DOI: 10.1111/ejn.15366
• Languages: English
• ISSNs: 0953-816X

Abstract

Abstract: Gilles de la Tourette syndrome (GTS) can be characterized by enhanced cognitive functions related to creating, modifying and maintaining connections between stimuli and responses (S‐R links). Specifically, two areas, procedural sequence learning and, as a novel finding, also event file binding, show converging evidence of hyperfunctioning in GTS. In this review, we describe how these two enhanced functions can be considered as cognitive mechanisms behind habitual behaviour, such as tics in GTS. Moreover, the presence of both procedural sequence learning and event file binding hyperfunctioning in the same disorder can be treated as evidence for their functional connections, even beyond GTS. Importantly though, we argue that hyperfunctioning of event file binding and procedural learning are not interchangeable: they have different time scales, different sensitivities to potential impairment in action sequencing and distinguishable contributions to the cognitive profile of GTS. An integrated theoretical account of hyperbinding and hyperlearning in GTS allows to formulate predictions for the emergence, activation and long‐term persistence of tics in GTS. Abstract : Enhanced binding of event files forms stronger S‐R connections in GTS. Chunking in the procedural memory then organizes the event files into sequential structures, based on the perceived probabilities in the S‐R stream. Stronger representations of S‐R connections likely contribute to better learning performance in GTS than in typically developing (TD) controls. Similarly, better learning of sequential regularities would lead to stronger interference when probabilities in the environment change (i.e., another sequence is presented). Finally, hyperlearning may lead to atypically stable procedural memories that persist long after their original significance.