title: Formation of Long-Term Locomotor Memories Is Associated with Functional Connectivity Changes in the Cerebellar-Thalamic-Cortical Network.
abstract: Although motor adaptation is typically rapid, accumulating evidence shows that it is also associated with long-lasting behavioral and neuronal changes. Two processes were suggested to explain the formation of long-term motor memories: recall, reflecting a retrieval of previous motor actions, and faster relearning, reflecting an increased sensitivity to errors. Although these manifestations of motor memories were initially demonstrated in the context of adaptation experiments in reaching, indications of long-term motor memories were also demonstrated recently in other kinds of adaptation such as in locomotor adaptation. Little is known about the neural processes that underlie these distinct aspects of memory. We hypothesize that recall and faster relearning reflect different learning processes that operate at the same time and depend on different neuronal networks. Seventeen subjects performed a multisession locomotor adaptation experiment in the laboratory, together with resting-state and localizer fMRI scans, after the baseline and the locomotor adaptation sessions. We report a modulation of the cerebellar-thalamic-cortical and cerebellar-basal ganglia networks after locomotor adaptation. Interestingly, whereas thalamic-cortical baseline connectivity was correlated with recall, cerebellar-thalamic baseline connectivity was correlated with faster relearning. Our results suggest that separate neuronal networks underlie error sensitivity and retrieval components. Individual differences in baseline resting-state connectivity can predict idiosyncratic combination of these components.
  
  
  
  The ability to shape our motor behavior rapidly in everyday activity, such as when walking on sand, suggests the existence of long-term motor memories. It was suggested recently that this ability is achieved by the retrieval of previous motor actions and by enhanced relearning capacity. Little is known about the neural mechanisms that underlie these memory processes. We studied the modularity in long-term motor memories in the context of locomotor adaptation using resting-state fMRI. We show that retrieval and relearning effects are associated with separate locomotor control networks and that intersubject variability in learning and in the generation of motor memories could be predicted from baseline resting-state connectivity in locomotor-related networks.
authors.affiliation: Department of Biomedical Engineering, fmewasi1@jhmi.edu.|Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel, and.|Department of Physical Medicine and Rehabilitation, Johns Hopkins School of Medicine, Baltimore, Maryland 21205.
authors.forename: Firas
authors.identifier: 0000-0002-1005-194X
authors.initials: F
authors.lastname: Mawase
authors.affiliation: Department of Physical Therapy.|Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel, and.
authors.forename: Simona
authors.initials: S
authors.lastname: Bar-Haim
authors.affiliation: Department of Brain and Cognitive Sciences, and.|Department of Physiology and Cell Biology, and.|Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel, and.
authors.forename: Lior
authors.identifier: 0000-0002-4324-8941
authors.initials: L
authors.lastname: Shmuelof
mesh_terms: D000222:Adaptation, Physiological / Q000502:physiology; D000293:Adolescent; D000328:Adult; D002531:Cerebellum / Q000502:physiology*; D005260:Female; D006801:Humans; D008124:Locomotion / Q000502:physiology*; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D057567:Memory, Long-Term / Q000502:physiology*; D009044:Motor Cortex / Q000502:physiology*; D009415:Nerve Net / Q000502:physiology*; D013788:Thalamus / Q000502:physiology*; D055815:Young Adult
keywords: cerebellum–thalamic–M1 network; functional connectivity; locomotor adaptation; long-term memory; resting-state fMRI