Distractor-resistant Short-Term Memory Is Supported by Transient Changes in Neural Stimulus Representations

被引:8
|
作者
Derrfuss, Jan [1 ,2 ]
Ekman, Matthias [1 ]
Hanke, Michael [3 ,4 ]
Tittgemeyer, Marc [5 ]
Fiebach, Christian J. [1 ,6 ,7 ]
机构
[1] Radboud Univ Nijmegen, Nijmegen, Netherlands
[2] Univ Nottingham, Nottingham, England
[3] Otto Von Guericke Univ, Magdeburg, Germany
[4] Ctr Behav Brain Sci, Magdeburg, Germany
[5] Max Planck Inst Metab Res, Cologne, Germany
[6] Goethe Univ Frankfurt, Frankfurt, Germany
[7] Ctr Individual Dev & Adapt Educ, Frankfurt, Germany
基金
欧洲研究理事会;
关键词
VISUAL WORKING-MEMORY; PREFRONTAL CORTEX; PARIETAL CORTEX; CEREBRAL-CORTEX; FMRI DATA; INFORMATION; MECHANISMS; RETRIEVAL; FACES; REACTIVATION;
D O I
10.1162/jocn_a_01141
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Goal-directed behavior in a complex world requires the maintenance of goal-relevant information despite multiple sources of distraction. However, the brain mechanisms underlying distractor-resistant working or short-term memory (STM) are not fully understood. Although early single-unit recordings in monkeys and fMRI studies in humans pointed to an involvement of lateral prefrontal cortices, more recent studies highlighted the importance of posterior cortices for the active maintenance of visual information also in the presence of distraction. Here, we used a delayed match-to-sample task and multivariate searchlight analyses of fMRI data to investigate STM maintenance across three extended delay phases. Participants maintained two samples (either faces or houses) across an unfilled pre-distractor delay, a distractor-filled delay, and an unfilled post-distractor delay. STM contents (faces vs. houses) could be decoded above-chance in all three delay phases from occipital, temporal, and posterior parietal areas. Classifiers trained to distinguish face versus house maintenance successfully generalized from pre- to post-distractor delays and vice versa, but not to the distractor delay period. Furthermore, classifier performance in all delay phases was correlated with behavioral performance in house, but not face, trials. Our results demonstrate the involvement of distributed posterior, but not lateral prefrontal, cortices in active maintenance during and after distraction. They also show that the neural code underlying STM maintenance is transiently changed in the presence of distractors and reinstated after distraction. The correlation with behavior suggests that active STM maintenance is particularly relevant in house trials, whereas face trials might rely more strongly on contributions from long-term memory.
引用
收藏
页码:1547 / 1565
页数:19
相关论文
共 50 条
  • [31] Short-Term Traffic Prediction Using Long Short-Term Memory Neural Networks
    Abbas, Zainab
    Al-Shishtawy, Ahmad
    Girdzijauskas, Sarunas
    Vlassov, Vladimir
    2018 IEEE INTERNATIONAL CONGRESS ON BIG DATA (IEEE BIGDATA CONGRESS), 2018, : 57 - 65
  • [32] DEVELOPMENTAL CHANGES IN SHORT-TERM RECOGNITION MEMORY
    KIRSNER, K
    BRITISH JOURNAL OF PSYCHOLOGY, 1972, 63 (FEB) : 109 - &
  • [33] Neural waves and short-term memory in a neural net model
    Selesnick, Stephen
    JOURNAL OF BIOLOGICAL PHYSICS, 2023, 49 (02) : 159 - 194
  • [34] Neural waves and short-term memory in a neural net model
    Stephen Selesnick
    Journal of Biological Physics, 2023, 49 : 159 - 194
  • [35] Hierarchical Tree Long Short-Term Memory for Sentence Representations
    Wang, Xiuying
    Li, Changliang
    Xu, Bo
    2018 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2018,
  • [36] Attention Modulates Maintenance of Representations in Visual Short-term Memory
    Kuo, Bo-Cheng
    Stokes, Mark G.
    Nobre, Anna Christina
    JOURNAL OF COGNITIVE NEUROSCIENCE, 2012, 24 (01) : 51 - 60
  • [37] HOW DISTRIBUTED ARE SHORT-TERM MEMORY REPRESENTATIONS OF VISUAL MOTION?
    Riggall, Adam
    Postle, Bradley
    JOURNAL OF COGNITIVE NEUROSCIENCE, 2013, : 193 - 193
  • [38] Object and Spatial Context Representations in Visual Short-Term Memory
    Li, Aedan Y.
    ENEURO, 2021, 8 (02)
  • [39] Battery Remaining Useful Life Prediction Supported by Long Short-Term Memory Neural Network
    Marri, Iacopo
    Petkovski, Emil
    Cristaldi, Loredana
    Faifer, Marco
    2023 IEEE INTERNATIONAL INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE, I2MTC, 2023,
  • [40] Predicting Short-term Traffic Flow by Long Short-Term Memory Recurrent Neural Network
    Tian, Yongxue
    Pan, Li
    2015 IEEE INTERNATIONAL CONFERENCE ON SMART CITY/SOCIALCOM/SUSTAINCOM (SMARTCITY), 2015, : 153 - 158