Neural Pattern Similarity in the Left IFG and Fusiform Is Associated with Novel Word Learning.

Jing Qu,Liu Qian,Chuansheng Chen,Gui Xue,Peng Xie,Leilei Mei,Huiling Li

doi:10.3389/fnhum.2017.00424

Abstract

Previous studies have revealed that greater neural pattern similarity across repetitions is associated with better subsequent memory. In this study, we used an artificial language training paradigm and representational similarity analysis to examine whether neural pattern similarity across repetitions before training was associated with post-training behavioral performance. Twenty-four native Chinese speakers were trained to learn a logographic artificial language for 12 days and behavioral performance was recorded using the word naming and picture naming tasks. Participants were scanned while performing a passive viewing task before training, after 4-day training and after 12-day training. Results showed that pattern similarity in the left pars opercularis (PO) and fusiform gyrus (FG) before training was negatively associated with reaction time (RT) in both word naming and picture naming tasks after training. These results suggest that neural pattern similarity is an effective neurofunctional predictor of novel word learning in addition to word memory.

Highlights

Cognitive neuroscientists are generally interested in identifying effective neural predictors of individuals’ learning ability
The whole brain analysis revealed that the typical reading network, including the bilateral prefrontal cortex, the occipitoparietal cortex and the occipitotemporal cortex, was involved in the processing of both Chinese and artificial language words
Because the Gaussian random field (GRF)-based cluster statistics used in this study might have inflated false positive rates (Eklunda et al, 2016), we performed an additional analysis by using a randomization procedure (FSL’s randomize, non-parametric permutation test) repeated 5000 times to examine the training effects

Summary

Introduction

Cognitive neuroscientists are generally interested in identifying effective neural predictors of individuals’ learning ability. A number of previous studies have found that preexisting individual differences in neural activity might serve as neurofunctional predictors of learning (Xue et al, 2006a; Chen et al, 2007; Wong et al, 2007; Asaridou et al, 2015; Chai et al, 2016; Kepinska et al, 2017). Mei et al (2008) found that preexisting individual differences in neural activity in the left posterior superior temporal sulcus predicted the efficiency in learning auditory words in a new language. These results suggest that preexisting individual differences in neural responses predict subsequent learning performance. Pattern similarity may be an effective marker of individuals’ memory encoding ability, and predictive of the learning outcomes

Methods

Results

Conclusion