| Literature DB >> 33356847 |
Link Tejavibulya1, Dustin Scheinost1,2,3,4,5.
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.Entities:
Keywords: Meta-analysis; open-science; predictive modeling; raw data
Mesh:
Year: 2020 PMID: 33356847 PMCID: PMC8222419 DOI: 10.1080/17588928.2020.1866520
Source DB: PubMed Journal: Cogn Neurosci ISSN: 1758-8928 Impact factor: 2.550