Suppressing Sensation during Action across Species and Sensory Modalities: Predictive and Nonpredictive Mechanisms of Sensory Modulation.

  • Published In: Journal of Neuroscience, 2025, v. 45, n. 46. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Kilteni, Konstantina; Cullen, Kathleen; Schneider, David M.; Schwarz, Cornelius 3 of 3

Abstract

Perception and action are deeply intertwined processes that require the nervous system to distinguish between self-generated (reafferent) and externally generated (exafferent) sensory inputs. To maintain accurate perception during movement, the brain must attenuate predictable sensory consequences of its own actions while remaining sensitive to unexpected external events. Reafference attenuation is a temporally precise process that suppresses expected feedback, facilitating the detection of novel stimuli. This review examines reafference attenuation across species (rodents, nonhuman primates, and humans) and sensory systems (vestibular, auditory, and tactile). We also discuss sensory gating (or sensory suppression), a broader and often less selective mechanism that inhibits both self- and externally generated inputs. Although both mechanisms reduce sensory inflow during movement, they differ in function, specificity, and temporal dynamics, and despite growing insight into their underlying circuitry, important questions remain about their generality and implementation. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Neuroscience. 2025/11, Vol. 45, Issue 46, p1
  • Document Type:Article
  • Subject Area:Anatomy and Physiology
  • Publication Date:2025
  • ISSN:0270-6474
  • DOI:10.1523/JNEUROSCI.1351-25.2025
  • Accession Number:189542927
  • Copyright Statement:Copyright of Journal of Neuroscience is the property of Society for Neuroscience and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.