Patterns of modulation in the activity and connectivity of motor cortex during the repeated generation of movement sequences

Ella Gabitov, David Manor, Avi Karni

Research output: Contribution to journalArticlepeer-review


It is not clear how the engagement of motor mnemonic processes is expressed in online brain activity. We scanned participants, using fMRI, during the paced performance of a fingerto- thumb opposition sequence (FOS), intensively trained a day earlier (T-FOS), and a similarly constructed, but novel, untrained FOS (U-FOS). Both movement sequences were performed in pairs of blocks separated by a brief rest interval (30 sec). We have recently shown that in the primary motor cortex (M1) motor memory was not expressed in the average signal intensity but rather in the across-block signal modulations, that is, when comparing the first to the second performance block across the brief rest interval. Here, using an M1 seed, we show that for the T-FOS, the M1–striatum functional connectivity decreased across blocks; however, for the U-FOS, connectivity within the M1 and between M1 and striatum increased. In addition, in M1, the pattern of within-block signal change, but not signal variability per se, reliably differentiated the two sequences. Only for the U-FOS and only within the first blocks in each pair, the signal significantly decreased. No such modulation was found within the second corresponding blocks following the brief rest interval in either FOS. We propose that a network including M1 and striatum underlies online motor working memory. This network may promote a transient integrated representation of a new movement sequence and readily retrieves a previously established movement sequence representation. Averaging over single events or blocks may not capture the dynamics of motor representations that occur over multiple timescales.

Original languageAmerican English
Pages (from-to)736-751
Number of pages16
JournalJournal of Cognitive Neuroscience
Issue number4
StatePublished - 6 Apr 2015

All Science Journal Classification (ASJC) codes

  • Cognitive Neuroscience


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