Detailed mapping of behavior reveals the formation of prelimbic neural ensembles across operant learning.
Detailed mapping of behavior reveals the formation of prelimbic neural ensembles across operant learning.
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DOI：
10.1016/j.neuron.2021.11.022
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发表时间：
2022-02-16
期刊：
影响因子：
16.2
通讯作者：
Lin DT
中科院分区：
文献类型：
--
作者：
Zhang Y;Denman AJ;Liang B;Werner CT;Beacher NJ;Chen R;Li Y;Shaham Y;Barbera G;Lin DT
前边缘皮层（prelimbic cortex，PrL）参与了操作性行为的组织，但纵向PrL神经活动与操作性学习和操作之间的关系尚不清楚。在这里，我们开发了深度行为映射（DBM）来识别视频记录中的行为微观状态。我们结合DBM与纵向钙成像来量化小鼠学习操作性任务时PrL神经元的行为调谐。我们发现，一个子集的PrL神经元强烈调谐到高度特定的行为微观状态，任务和非任务相关。重叠的神经系综被平铺在响应-响应序列中的连续微观状态上，形成连续的映射。当小鼠学习操作性任务时，弱调谐神经元被招募到新的集合中，倾向于类似于它们最初调谐的行为。总之，我们的数据表明，PrL包含的神经合奏，共同编码的行为状态，这是细粒度的，连续的，并在操作性学习过程中增长的地图。Zhang等人揭示，前边缘系统（PrL）神经元将复杂的奖励驱动行为编码为连续序列，而不仅仅是最突出的任务事件。其他PrL神经元编码非任务行为，而许多其他神经元具有弱/不稳定的调谐，但可能被招募来代表新学习的行为。
The prelimbic cortex (PrL) is involved in the organization of operant behaviors, but the relationship between longitudinal PrL neural activity and operant learning and performance is unknown. Here, we developed deep behavior mapping (DBM) to identify behavioral microstates in video recordings. We combined DBM with longitudinal calcium imaging to quantify behavioral tuning in PrL neurons as mice learned an operant task. We found that a subset of PrL neurons were strongly tuned to highly specific behavioral microstates, both task and non-task related. Overlapping neural ensembles were tiled across consecutive microstates in the response-reinforcer sequence, forming a continuous map. As mice learned the operant task, weakly tuned neurons were recruited into new ensembles, with a bias towards behaviors similar to their initial tuning. In summary, our data suggest that the PrL contains neural ensembles that jointly encode a map of behavioral states which is fine-grained, continuous, and grows during operant learning. Zhang et al. reveal that prelimbic (PrL) neurons encode a complex reward-driven behavior as a continuous sequence, rather than signaling only the most salient task events. Other PrL neurons encode non-task behaviors, while many others possess weak / unstable tuning but may be recruited to represent newly learned behaviors.
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影响因子：
3
作者：
Liang B;Zhang L;Moffitt C;Li Y;Lin DT
通讯作者：
Lin DT
影响因子：
25
作者：
Bossert, Jennifer M.;Stern, Anna L.;Theberge, Florence R. M.;Cifani, Carlo;Koya, Eisuke;Hope, Bruce T.;Shaham, Yavin
通讯作者：
Shaham, Yavin
影响因子：
25
作者：
Mathis, Alexander;Mamidanna, Pranav;Bethge, Matthias
通讯作者：
Bethge, Matthias
影响因子：
7.6
作者：
Madangopal, Rajtarun;Ramsey, Leslie A.;Hope, Bruce T.
通讯作者：
Hope, Bruce T.
DOI：
10.1523/jneurosci.0005-12.2012
发表时间：
2012-04-04
期刊：
The Journal of neuroscience : the official journal of the Society for Neuroscience
影响因子：
--
作者：
Bossert JM;Stern AL;Theberge FR;Marchant NJ;Wang HL;Morales M;Shaham Y
通讯作者：
Shaham Y