Shirin Mahdavi , Axel Lindner , Carsten Schmidt-Samoa , Anna-Lena Müsch , Peter Dechent , Melanie Wilke
{"title":"Neural correlates of sensorimotor adaptation: Thalamic contributions to learning from sensory prediction error","authors":"Shirin Mahdavi , Axel Lindner , Carsten Schmidt-Samoa , Anna-Lena Müsch , Peter Dechent , Melanie Wilke","doi":"10.1016/j.neuroimage.2024.120927","DOIUrl":null,"url":null,"abstract":"<div><div>Understanding the neural mechanism of sensorimotor adaptation is essential to reveal how the brain learns from errors, a process driven by sensory prediction errors. While the previous literature has focused on cortical and cerebellar changes, the involvement of the thalamus has received less attention. This functional magnetic resonance imaging study aims to explore the neural substrates of learning from sensory prediction errors with an additional focus on the thalamus. Thirty participants adapted their goal-directed reaches to visual feedback rotations introduced in a step-wise manner, while reporting their predicted visual consequences of their movements intermittently. We found that adaptation initially engaged the cerebellum and fronto-parietal cortical regions, which persisted as adaptation progressed. By the end of adaptation, additional regions within the fronto-parietal cortex and medial pulvinar of the thalamus were recruited. Another finding was the involvement of bilateral medial dorsal nuclei, which showed a positive correlation with the level of motor adaptation. Notably, the gradual shift in the predicted hand movement consequences was associated with activity in the cerebellum, motor cortex and thalamus (ventral lateral, medial dorsal, and medial pulvinar). Our study presents clear evidence for an involvement of the thalamus, both classical ‘motor’ and higher-order nuclei, in error-based motor learning.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"303 ","pages":"Article 120927"},"PeriodicalIF":4.7000,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"NeuroImage","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1053811924004245","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROIMAGING","Score":null,"Total":0}
引用次数: 0
Abstract
Understanding the neural mechanism of sensorimotor adaptation is essential to reveal how the brain learns from errors, a process driven by sensory prediction errors. While the previous literature has focused on cortical and cerebellar changes, the involvement of the thalamus has received less attention. This functional magnetic resonance imaging study aims to explore the neural substrates of learning from sensory prediction errors with an additional focus on the thalamus. Thirty participants adapted their goal-directed reaches to visual feedback rotations introduced in a step-wise manner, while reporting their predicted visual consequences of their movements intermittently. We found that adaptation initially engaged the cerebellum and fronto-parietal cortical regions, which persisted as adaptation progressed. By the end of adaptation, additional regions within the fronto-parietal cortex and medial pulvinar of the thalamus were recruited. Another finding was the involvement of bilateral medial dorsal nuclei, which showed a positive correlation with the level of motor adaptation. Notably, the gradual shift in the predicted hand movement consequences was associated with activity in the cerebellum, motor cortex and thalamus (ventral lateral, medial dorsal, and medial pulvinar). Our study presents clear evidence for an involvement of the thalamus, both classical ‘motor’ and higher-order nuclei, in error-based motor learning.
期刊介绍:
NeuroImage, a Journal of Brain Function provides a vehicle for communicating important advances in acquiring, analyzing, and modelling neuroimaging data and in applying these techniques to the study of structure-function and brain-behavior relationships. Though the emphasis is on the macroscopic level of human brain organization, meso-and microscopic neuroimaging across all species will be considered if informative for understanding the aforementioned relationships.