Citation

Postle BR. Curr. Opin. Behav. Sci. 2015; 1: 40-46.

Copyright

(Copyright © 2015, Elsevier Publishing)

DOI

10.1016/j.cobeha.2014.08.004

PMID

unavailable

Abstract

Our understanding of the neural bases of visual short-term memory (STM), the ability to mentally retain information over short periods of time, is being reshaped by two important developments: the application of methods from statistical machine learning, often a variant of multivariate pattern analysis (MVPA), to functional magnetic resonance imaging (fMRI) and electroencephalographic (EEG) data sets; and advances in our understanding of the physiology and functions of neuronal oscillations. One consequence is that many commonly observed physiological 'signatures' that have previously been interpreted as directly related to the retention of information in visual STM may require reinterpretation as more general, state-related changes that can accompany cognitive-task performance. Another is important refinements of theoretical models of visual STM.