Big data approaches to identifying sex differences in long-term memory

Cogn Neurosci. 2021 Jul-Oct;12(3-4):185-186. doi: 10.1080/17588928.2020.1866520. Epub 2020 Dec 24.

Abstract

Whether in neurotransmitters or large-scale circuits, sex differences have long been of interest in neuroscience. Spets and Slotnick conducted a meta-analysis of fMRI studies of long-term memory to identify sex differences in brain-behavior associations, demonstrating that sex differences are pervasive across many sub-types of long-term memory. Meta-analyses are a workhorse toward aggregating larger sample sizes to arrive at a more comprehensive understanding of such topics. However, more research is crucial to elucidate complex relationships in how fMRI signals translate to behavioral outcomes. We propose big data and open-science as a solution toward finding robust sex differences in brain-behavior associations.

Keywords: Meta-analysis; open-science; predictive modeling; raw data.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Comment

MeSH terms

  • Big Data*
  • Brain / diagnostic imaging
  • Female
  • Humans
  • Magnetic Resonance Imaging
  • Male
  • Memory, Long-Term
  • Sex Characteristics*