Selective Entrainment of Theta Oscillations in the Dorsal Stream Causally Enhances Auditory Working Memory Performance

被引：153

作者：

Albouy, Philippe ^{[1
,2
,3
]}

Weiss, Aurelien ^{[1
,2
]}

Baillet, Sylvain ^{[2
]}

Zatorre, Robert J. ^{[1
,3
]}

机构：

[1] McGill Univ, Montreal Neurol Inst, Cognit Neurosci Unit, Montreal, PQ, Canada

[2] McGill Univ, Montreal Neurol Inst, McConnell Brain Imaging Ctr, Montreal, PQ, Canada

[3] Int Lab Brain Mus & Sound Res BRAMS, Montreal, PQ H2V 2J2, Canada

来源：

NEURON | 2017年 / 94卷 / 01期

基金：

加拿大自然科学与工程研究理事会;

关键词：

TRANSCRANIAL MAGNETIC STIMULATION; PHASE SYNCHRONIZATION; INDIVIDUAL-DIFFERENCES; POSTERIOR PARIETAL; ALPHA FREQUENCY; BRAIN; EEG; CORTEX; PERCEPTION; ACTIVATION;

D O I：

10.1016/j.neuron.2017.03.015

中图分类号：

Q189 [神经科学];

学科分类号：

071006 ;

摘要：

The implication of the dorsal stream in manipulating auditory information in working memory has been recently established. However, the oscillatory dynamics within this network and its causal relationship with behavior remain undefined. Using simultaneous MEG/ EEG, we show that theta oscillations in the dorsal stream predict participants' manipulation abilities during memory retention in a task requiring the comparison of two patterns differing in temporal order. We investigated the causal relationship between brain oscillations and behavior by applying thetarhythmic TMS combined with EEG over the MEGidentified target (left intraparietal sulcus) during the silent interval between the two stimuli. Rhythmic TMS entrained theta oscillation and boosted participants' accuracy. TMS-induced oscillatory entrainment scaled with behavioral enhancement, and both gains varied with participants' baseline abilities. These effects were not seen for a melody-comparison control task and were not observed for arrhythmic TMS. These data establish theta activity in the dorsal stream as causally related to memory manipulation.

引用

页码：193 / +

页数：19

共 82 条

[1] Altered retrieval of melodic information in congenital amusia: insights from dynamic causal modeling of MEG data [J].