Techniques for extracting single-trial activity patterns from large-scale neural recordings

被引:117
|
作者
Churchland, Mark M. [1 ,2 ]
Yu, Byron M. [1 ,2 ,3 ]
Sahani, Maneesh [3 ]
Shenoy, Krishna V. [1 ,2 ]
机构
[1] Stanford Univ, Neurosci Program, CISX, Stanford, CA 94305 USA
[2] Stanford Univ, Dept Elect Engn, CISX, Stanford, CA 94305 USA
[3] UCL, Gatsby Computat Neurosci Unit, London WC1N 3AR, England
关键词
D O I
10.1016/j.conb.2007.11.001
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Large, chronically implanted arrays of microelectrodes are an increasingly common tool for recording from primate cortex and can provide extracellular recordings from many (order of 100) neurons. While the desire for cortically based motor prostheses has helped drive their development, such arrays also offer great potential to advance basic neuroscience research. Here we discuss the utility of array recording for the study of neural dynamics. Neural activity often has dynamics beyond that driven directly by the stimulus. While governed by those dynamics, neural responses may nevertheless unfold differently for nominally identical trials, rendering many traditional analysis methods ineffective. We review recent studies - some employing simultaneous recording, some not - indicating that such variability is indeed present both during movement generation and during the preceding premotor computations. In such cases, large-scale simultaneous recordings have the potential to provide an unprecedented view of neural dynamics at the level of single trials. However, this enterprise will depend not only on techniques for simultaneous recording but also on the use and further development of analysis techniques that can appropriately reduce the dimensionality of the data, and allow visualization of single-trial neural behavior.
引用
收藏
页码:609 / 618
页数:10
相关论文
共 50 条
  • [21] Discovering Precise Temporal Patterns in Large-Scale Neural Recordings through Robust and Interpretable Time Warping
    Williams, Alex H.
    Poole, Ben
    Maheswaranathan, Niru
    Dhawale, Ashesh K.
    Fisher, Tucker
    Wilson, Christopher D.
    Brann, David H.
    Trautmann, Eric M.
    Ryu, Stephen
    Shusterman, Roman
    Rinberg, Dmitry
    Olveczky, Bence P.
    Shenoy, Krishna V.
    Ganguli, Surya
    NEURON, 2020, 105 (02) : 246 - +
  • [22] Single-trial discrimination of type and speed of wrist movements from EEG recordings
    Gu, Ying
    Dremstrup, Kim
    Farina, Dario
    CLINICAL NEUROPHYSIOLOGY, 2009, 120 (08) : 1596 - 1600
  • [23] Building population models for large-scale neural recordings: Opportunities and pitfalls
    Hurwitz, Cole
    Kudryashova, Nina
    Onken, Arno
    Hennig, Matthias H.
    CURRENT OPINION IN NEUROBIOLOGY, 2021, 70 : 64 - 73
  • [24] Inferring presynaptic population spiking from single-trial membrane potential recordings
    Yasar, Tansel Baran
    Wright, Nathaniel Caleb
    Wessel, Ralf
    JOURNAL OF NEUROSCIENCE METHODS, 2016, 259 : 13 - 21
  • [25] Exoskeleton empowers large-scale neural recordings in freely roaming mice
    Kodandaramaiah, Suhasa B.
    Beckerle, Travis
    NATURE METHODS, 2024, 21 (11) : 1994 - 1995
  • [26] Extracting large-scale knowledge bases from the web
    Kumar, R
    Raghavan, P
    Rajagopalan, S
    Tomkins, A
    PROCEEDINGS OF THE TWENTY-FIFTH INTERNATIONAL CONFERENCE ON VERY LARGE DATA BASES, 1999, : 639 - 650
  • [27] Extracting Human Activity Areas from Large-Scale Spatial Data with Varying Densities
    Shen, Xiaoqi
    Shi, Wenzhong
    Liu, Zhewei
    Zhang, Anshu
    Wang, Lukang
    Zeng, Fanxin
    ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2022, 11 (07)
  • [28] Deep Neural Networks for Forecasting Single-Trial Event-Related Neural Activity
    Ibagon, Gabriel
    Kothe, Christian A.
    Bidgely-Shamlo, Nima
    Mullen, Tim
    2018 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2018, : 1070 - 1075
  • [29] Large-scale neural recordings call for new insights to link brain and behavior
    Anne E. Urai
    Brent Doiron
    Andrew M. Leifer
    Anne K. Churchland
    Nature Neuroscience, 2022, 25 : 11 - 19
  • [30] Large-scale neural recordings call for new insights to link brain and behavior
    Urai, Anne E.
    Doiron, Brent
    Leifer, Andrew M.
    Churchland, Anne K.
    NATURE NEUROSCIENCE, 2022, 25 (01) : 11 - 19