Neuronal synchrony reveals working memory networks and predicts individual memory capacity

J. Matias Palva, Simo Monto, Shrikanth Kulashekhar, Satu Palva

Research output: Contribution to journalArticleScientificpeer-review

426 Citations (Scopus)


Visual working memory (VWM) is used tomaintain sensory information for cognitive operations, and its deficits are associated with several neuropsychological disorders. VWM is based on sustained neuronal activity in a complex cortical network of frontal, parietal, occipital, and temporal areas. The neuronal mechanisms that coordinate this distributed processing to sustain coherentmental images and the mechanisms that set the behavioral capacity limit have remained unknown. We mapped the anatomical and dynamic structures of network synchrony supporting VWM by using a neuro informatics approach and combined magnetoencephalography and electroencephalography. Interareal phase synchrony was sustained and stable during the VWM retention period among frontoparietal and visual areas in α- (10-13 Hz), β- (18-24 Hz), and γ- (30-40 Hz) frequency bands. Furthermore, synchrony was strengthened with increasing memory load among the frontoparietal regions known to underlie executive and attentional functions during memory maintenance. On the other hand, the subjects' individual behavioral VWM capacity was predicted by synchrony in a network in which the intraparietal sulcus was the most central hub. These data suggest that interareal phase synchrony in the α-, β-, and γ-frequency bands among frontoparietal and visual regions could be a systems level mechanism for coordinating and regulating the maintenance of neuronal object representations in VWM.

Original languageEnglish
Pages (from-to)7580-7585
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number16
Publication statusPublished - 20 Apr 2010
MoE publication typeA1 Journal article-refereed


  • Cortical synchrony
  • Functional connectivity
  • Graph theory
  • Magnetoencephalography
  • Source modelling


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