Neural representations of statistical and rule‐based predictions in Gilles de la Tourette syndrome

• Published in: Human brain mapping 2024-06, Vol.45 (8), p.e26719-n/a
• Main Authors: Takacs, Adam, Toth‐Faber, Eszter, Schubert, Lina, Tarnok, Zsanett, Ghorbani, Foroogh, Trelenberg, Madita, Nemeth, Dezso, Münchau, Alexander, Beste, Christian
• Format: Article
• Language: English
• Subjects: Adult; Cognitive science; Electroencephalography; Female; Gilles de la Tourette syndrome; Humans; Learning - physiology; Male; Middle Aged; multivariate pattern analysis; Neuroscience; predictive processing; Probability Learning; Psychomotor Performance - physiology; sequence learning; statistical learning; temporal decomposition; Tourette Syndrome - physiopathology; Young Adult
• ISSN: 1065-9471; 1097-0193
• DOI: 10.1002/hbm.26719

Gilles de la Tourette syndrome (GTS) is a disorder characterised by motor and vocal tics, which may represent habitual actions as a result of enhanced learning of associations between stimuli and responses (S‐R). In this study, we investigated how adults with GTS and healthy controls (HC) learn two types of regularities in a sequence: statistics (non‐adjacent probabilities) and rules (predefined order). Participants completed a visuomotor sequence learning task while EEG was recorded. To understand the neurophysiological underpinnings of these regularities in GTS, multivariate pattern analyses on the temporally decomposed EEG signal as well as sLORETA source localisation method were conducted. We found that people with GTS showed superior statistical learning but comparable rule‐based learning compared to HC participants. Adults with GTS had different neural representations for both statistics and rules than HC adults; specifically, adults with GTS maintained the regularity representations longer and had more overlap between them than HCs. Moreover, over different time scales, distinct fronto‐parietal structures contribute to statistical learning in the GTS and HC groups. We propose that hyper‐learning in GTS is a consequence of the altered sensitivity to encode complex statistics, which might lead to habitual actions. The formation of habits is a long‐discussed topic in GTS. Through the decoding of neurophysiological data, we show that increased habit formation in GTS is due to increased statistical but not rule‐based learning mechanisms in fronto‐parietal cortices.