Current BiologyNeurosciencePeer-reviewed journal article
Self-generated whisker movements drive state-dependent sensory input to developing barrel cortex
James C. DooleyiD, Ryan M. GlanziD, Greta SokoloffiD, Mark Samuel BLUMBERGiD
Abstract
SO_SCPLOWUMMARYC_SCPLOWCortical development is an activity-dependent process [1-3]. Regarding the role of activity in developing somatosensory cortex, one persistent debate concerns the importance of sensory feedback from self-generated movements. Specifically, recent studies claim that cortical activity is generated intrinsically, independent of movement [3, 4]. However, other studies claim that behavioral state moderates the relationship between movement and cortical activity [5-7]. Thus, perhaps inattention to behavioral state leads to failures to detect movement-driven activity [8]. Here, we resolve this issue by associating local field activity (i.e., spindle bursts) and unit activity in the barrel cortex of 5-day-old rats with whisker movements during wake and myoclonic twitches of the whiskers during active (REM) sleep. Barrel activity increased significantly within 500 ms of whisker movements, especially after twitches. Also, higher-amplitude movements were more likely to trigger barrel activity; when we controlled for movement amplitude, barrel activity was again greater after a twitch than a wake movement. We then inverted the analysis to assess the likelihood that increases in barrel activity were preceded within 500 ms by whisker movements: At least 55% of barrel activity was attributable to sensory feedback from whisker movements. Finally, when periods with and without movement were compared, 70-75% of barrel activity was movement-related. These results confirm the importance of sensory feedback from movements in driving activity in sensorimotor cortex and underscore the necessity of monitoring sleep-wake states to ensure accurate assessments of the contributions of the sensory periphery to activity in developing somatosensory cortex.
- organism: rat
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
- Citations
- 67
- FWCI
- 6.18
- Field percentile
- top 3%
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