Local temporal variability reflects functional integration in the human brain

Neuroimage. 2018 Dec;183:776-787. doi: 10.1016/j.neuroimage.2018.08.019. Epub 2018 Aug 24.

Abstract

Local moment-to-moment variability exists at every level of neural organization, but its driving forces remain opaque. Inspired by animal work demonstrating that local temporal variability may reflect synaptic input rather than locally-generated "noise," we used publicly-available high-temporal-resolution fMRI data (N = 100 adults; 33 males) to test in humans whether greater BOLD signal variability in local brain regions was associated with functional integration (estimated via spatiotemporal PCA dimensionality). Using a multivariate partial least squares analysis, we indeed found that individuals with higher local temporal variability had a more integrated (lower dimensional) network fingerprint. Notably, temporal variability in the thalamus showed the strongest negative association with PCA dimensionality. Previous animal work also shows that local variability may upregulate from thalamus to visual cortex; however, such principled upregulation from thalamus to cortex has not been demonstrated in humans. In the current study, we rather establish a more general putative dynamic role of the thalamus by demonstrating that greater within-person thalamo-cortical upregulation in variability is itself a unique hallmark of greater functional integration that cannot be accounted for by local fluctuations in several other well-known integrative-hub regions. Our findings indicate that local variability primarily reflects functional integration, and establish a fundamental role for the thalamus in how the brain fluctuates and communicates across moments.

Keywords: Brain signal variability; Network dimensionality; Neural dynamics; fMRI.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Brain / physiology*
  • Brain Mapping / methods*
  • Datasets as Topic
  • Female
  • Humans
  • Image Processing, Computer-Assisted / methods
  • Magnetic Resonance Imaging / methods
  • Male
  • Middle Aged
  • Nerve Net / physiology*
  • Young Adult