Outlook on deep neural networks in computational cognitive neuroscience

被引:5
|
作者
Turner, Brandon M. [1 ]
Miletic, Steven [2 ]
Forstmann, Birte U. [2 ]
机构
[1] Ohio State Univ, Columbus, OH 43210 USA
[2] Univ Amsterdam, Amsterdam, Netherlands
关键词
MODEL;
D O I
10.1016/j.neuroimage.2017.12.078
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
引用
收藏
页码:117 / 118
页数:2
相关论文
共 50 条
  • [41] Computational analyses in cognitive neuroscience: In defense of biological implausibility
    Dror, IE
    Gallogly, DP
    PSYCHONOMIC BULLETIN & REVIEW, 1999, 6 (02) : 173 - 182
  • [42] The computational perspective: A catalyst for research questions in cognitive neuroscience?
    Trapp, Sabrina
    Whitney, David
    Pascucci, David
    NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS, 2025, 169
  • [43] Enhanced Computational Imaging with Encoding Masks Optimized by Deep Neural Networks
    Vogel, Bryan, I
    Finch, Michael F.
    Miller, Kevin J.
    INFRARED IMAGING SYSTEMS: DESIGN, ANALYSIS, MODELING, AND TESTING XXXII, 2021, 11740
  • [44] A tutorial on computational cognitive neuroscience: Modeling the neurodynamics of cognition
    Ashby, F. Gregory
    Helie, Sebastien
    JOURNAL OF MATHEMATICAL PSYCHOLOGY, 2011, 55 (04) : 273 - 289
  • [45] Cascading photonic reservoirs with deep neural networks increases computational performance
    Bauwens, Ian
    Van der Sande, Guy
    Bienstman, Peter
    Verschaffelt, Guy
    MACHINE LEARNING IN PHOTONICS, 2024, 13017
  • [46] Computational modeling of mRNA degradation dynamics using deep neural networks
    Yaish, Ofir
    Orenstein, Yaron
    BIOINFORMATICS, 2022, 38 (04) : 1087 - 1101
  • [47] Computational memory-based inference and training of deep neural networks
    Sebastian, A.
    Boybat, I.
    Dazzi, M.
    Giannopoulos, I.
    Jonnalagadda, V.
    Joshi, V.
    Karunaratne, G.
    Kersting, B.
    Khaddam-Aljameh, R.
    Nandakumar, S. R.
    Petropoulos, A.
    Piveteau, C.
    Antonakopoulos, T.
    Rajendran, B.
    Le Gallo, M.
    Eleftheriou, E.
    2019 SYMPOSIUM ON VLSI CIRCUITS, 2019, : T168 - T169
  • [48] Deep neural networks are not a single hypothesis but a language for expressing computational hypotheses
    Golan, Tal
    Taylor, Johnmark
    Schutt, Heiko
    Peters, Benjamin
    Sommers, Rowan P.
    Seeliger, Katja
    Doerig, Adrien
    Linton, Paul
    Konkle, Talia
    van Gerven, Marcel
    Kording, Konrad
    Richards, Blake
    Kietzmann, Tim C.
    Lindsay, Grace W.
    Kriegeskorte, Nikolaus
    BEHAVIORAL AND BRAIN SCIENCES, 2023, 46
  • [49] Towards Efficient Visual Simplification of Computational Graphs in Deep Neural Networks
    Pan, Rusheng
    Wang, Zhiyong
    Wei, Yating
    Gao, Han
    Ou, Gongchang
    Cao, Caleb Chen
    Xu, Jingli
    Xu, Tong
    Chen, Wei
    IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2024, 30 (07) : 3359 - 3373
  • [50] Editorial: Machine and deep-learning for computational neuroscience
    Dhiman, Gaurav
    Viriyasitavat, Wattana
    Nagar, Atulya K. K.
    FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, 2023, 17