Navigating the Neural Space in Search of the Neural Code

被引:146
|
作者
Jazayeri, Mehrdad [1 ]
Afraz, Arash [1 ]
机构
[1] MIT, Dept Brain & Cognit Sci, McGovern Inst Brain Res, E25-618, Cambridge, MA 02139 USA
关键词
POSTERIOR PARIETAL CORTEX; ELECTRICAL MICROSTIMULATION; CORTICAL-NEURONS; DECISION-MAKING; PREFRONTAL CORTEX; VISUAL-CORTEX; MOTOR CORTEX; IN-VIVO; AREA MT; TIME;
D O I
10.1016/j.neuron.2017.02.019
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
The advent of powerful perturbation tools, such as optogenetics, has created new frontiers for probing causal dependencies in neural and behavioral states. These approaches have significantly enhanced the ability to characterize the contribution of different cells and circuits to neural function in health and disease. They have shifted the emphasis of research toward causal interrogations and increased the demand for more precise and powerful tools to control and manipulate neural activity. Here, we clarify the conditions under which measurements and perturbations support causal inferences. We note that the brain functions at multiple scales and that causal dependencies may be best inferred with perturbation tools that interface with the system at the appropriate scale. Finally, we develop a geometric framework to facilitate the interpretation of causal experiments when brain perturbations do or do not respect the intrinsic patterns of brain activity. We describe the challenges and opportunities of applying perturbations in the presence of dynamics, and we close with a general perspective on navigating the activity space of neurons in the search for neural codes.
引用
下载
收藏
页码:1003 / 1014
页数:12
相关论文
共 50 条
  • [21] How environmental movement constraints shape the neural code for space
    Jeffery, Kate J.
    COGNITIVE PROCESSING, 2021, 22 (SUPPL 1) : 97 - 104
  • [22] EvoPrompting: Language Models for Code-Level Neural Architecture Search
    Chen, Angelica
    Dohan, David M.
    So, David R.
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 36 (NEURIPS 2023), 2023,
  • [23] Semantic Code Search in Software Repositories using Neural Machine Translation
    Papathomas, Evangelos
    Diamantopoulos, Themistoklis
    Symeonidis, Andreas
    FUNDAMENTAL APPROACHES TO SOFTWARE ENGINEERING, FASE 2022, 2022, 13241 : 225 - 244
  • [24] Constructing Multilingual Code Search Dataset Using Neural Machine Translation
    Sekizawa, Ryo
    Duan, Nan
    Lu, Shuai
    Yanaka, Hitomi
    PROCEEDINGS OF THE 61ST ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, ACL-SRW 2023, VOL 4, 2023, : 69 - 75
  • [25] One-shot Graph Neural Architecture Search with Dynamic Search Space
    Li, Yanxi
    Wen, Zean
    Wang, Yunhe
    Xu, Chang
    THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2021, 35 : 8510 - 8517
  • [26] Multi-Objective Neural Architecture Search by Learning Search Space Partitions
    Zhao, Yiyang
    Wang, Linnan
    Guo, Tian
    JOURNAL OF MACHINE LEARNING RESEARCH, 2024, 25
  • [27] Analyses of degeneracy in neural system and neural code
    Zhang Hong
    Liu Shu-Fang
    Qian Ming-Qi
    Tong Qin-Ye
    ACTA PHYSICA SINICA, 2009, 58 (10) : 7322 - 7329
  • [28] Neural Oscillations: Understanding a Neural Code of Pain
    Kim, Junseok A.
    Davis, Karen D.
    NEUROSCIENTIST, 2021, 27 (05): : 544 - 570
  • [29] Channel Configuration for Neural Architecture: Insights from the Search Space
    Thomson, Sarah L.
    Ochoa, Gabriela
    Veerapen, Nadarajen
    Michalak, Krzysztof
    PROCEEDINGS OF THE 2023 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, GECCO 2023, 2023, : 1267 - 1275
  • [30] TextNAS: A Neural Architecture Search Space Tailored for Text Representation
    Wang, Yujing
    Yang, Yaming
    Chen, Yiren
    Bai, Jing
    Zhang, Ce
    Su, Guinan
    Kou, Xiaoyu
    Tong, Yunhai
    Yang, Mao
    Zhou, Lidong
    THIRTY-FOURTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THE THIRTY-SECOND INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE AND THE TENTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2020, 34 : 9242 - 9249