Deciphering elapsed time and predicting action timing from neuronal population signals.
Deciphering elapsed time and predicting action timing from neuronal population signals.
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DOI：
10.3389/fncom.2011.00029
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发表时间：
2011
影响因子：
3.2
通讯作者：
Tanji J
中科院分区：
文献类型：
--
作者：
Shinomoto S;Omi T;Mita A;Mushiake H;Shima K;Matsuzaka Y;Tanji J
无论是捕猎猎物还是逃离掠食者，正确的行动时机对于动物的生存都是必要的。神经科学领域的研究人员已经开始探索与行为间隔时间相关的神经元信号。在这里，我们尝试从执行多间隔计时任务的猴子额叶皮层记录的神经元群体信号中解码时间的流逝。我们设计了一种贝叶斯算法，可以破译隐藏在分散在单个神经元活动中的噪声信号中的时间信息，这些信号是从经过训练的猴子记录的，以确定开始动作之前的时间流逝。借助该解码器，我们成功地根据前补充运动区 25 个神经元的放电率，以大约 1 秒的精度估计了整个相关行为周期的经过时间。此外，扩展算法使得可以确定每次尝试中需要等待的时间间隔的总长度。这使得观察者能够根据大脑中的神经元活动来预测受试者将采取行动的时刻。一项单独的总体分析表明，神经元集合以相对于预定间隔缩放的方式表示时间的流逝，而不是将其表示为真实的物理时间。
The proper timing of actions is necessary for the survival of animals, whether in hunting prey or escaping predators. Researchers in the field of neuroscience have begun to explore neuronal signals correlated to behavioral interval timing. Here, we attempt to decode the lapse of time from neuronal population signals recorded from the frontal cortex of monkeys performing a multiple-interval timing task. We designed a Bayesian algorithm that deciphers temporal information hidden in noisy signals dispersed within the activity of individual neurons recorded from monkeys trained to determine the passage of time before initiating an action. With this decoder, we succeeded in estimating the elapsed time with a precision of approximately 1 s throughout the relevant behavioral period from firing rates of 25 neurons in the pre-supplementary motor area. Further, an extended algorithm makes it possible to determine the total length of the time-interval required to wait in each trial. This enables observers to predict the moment at which the subject will take action from the neuronal activity in the brain. A separate population analysis reveals that the neuronal ensemble represents the lapse of time in a manner scaled relative to the scheduled interval, rather than representing it as the real physical time.
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影响因子：
5.5
作者：
HODGKIN, AL
通讯作者：
HODGKIN, AL
影响因子：
34.7
作者：
Ascoli, Giorgio A.;Alonso-Nanclares, Lidia;Anderson, Stewart A.;Barrionuevo, German;Benavides-Piccione, Ruth;Burkhalter, Andreas;Buzsaki, Gyoergy;Cauli, Bruno;DeFelipe, Javier;Fairen, Alfonso;Feldmeyer, Dirk;Fishell, Gord;Fregnac, Yves;Freund, Tamas F.;Gardner, Daniel;Gardner, Esther P.;Goldberg, Jesse H.;Helmstaedter, Moritz;Hestrin, Shaul;Karube, Fuyuki;Kisvarday, Zoltan F.;Lambolez, Bertrand;Lewis, David A.;Marin, Oscar;Markram, Henry;Munoz, Alberto;Packer, Adam;Petersen, Carl C. H.;Rockland, Kathleen S.;Rossier, Jean;Rudy, Bernardo;Somogyi, Peter;Staiger, Jochen F.;Tamas, Gabor;Thomson, Alex M.;Toledo-Rodriguez, Maria;Wang, Yun;West, David C.;Yuste, Rafael
通讯作者：
Yuste, Rafael
DOI：
10.1073/pnas.130200797
发表时间：
2000-07-05
影响因子：
11.1
作者：
Azouz, R;Gray, CM
通讯作者：
Gray, CM
影响因子：
5.5
作者：
BAL, T;MCCORMICK, DA
通讯作者：
MCCORMICK, DA
影响因子：
2.9
作者：
Brandman, R;Nelson, ME
通讯作者：
Nelson, ME