WEKO3
アイテム
Activity-dependent organization of prefrontal hub-networks for associative learning and signal transformation
https://repo.qst.go.jp/records/2002039
https://repo.qst.go.jp/records/200203908d3f302-11a1-4faf-bfaa-b04c3d475970
| アイテムタイプ | 会議発表用資料 / Presentation(1) | |||||||
|---|---|---|---|---|---|---|---|---|
| 公開日 | 2025-05-08 | |||||||
| タイトル | ||||||||
| タイトル | Activity-dependent organization of prefrontal hub-networks for associative learning and signal transformation | |||||||
| 言語 | en | |||||||
| 言語 | ||||||||
| 言語 | eng | |||||||
| 資源タイプ | ||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_c94f | |||||||
| 資源タイプ | conference presentation | |||||||
| 著者 |
揚妻 正和
× 揚妻 正和
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| 抄録 | ||||||||
| 内容記述 | Associative learning is crucial for adapting to environmental changes. Interactions among neuronal populations involving the dorso-medial prefrontal cortex (dmPFC) in rodents are proposed to regulate associative memory. However, how these neuronal populations store and process information about the association remains unclear. Here we developed a pipeline for longitudinal two-photon imaging and computational dissection of neural population activities in male mouse dmPFC during fear-conditioning procedures, enabling us to detect learning-dependent changes in the dmPFC network topology. After confirming that the dmPFC contributes to the expression of the conditioned responses (CR) by chemogenetic silencing, we analyzed neural population activities by regularized regression methods and graphical modeling. We found that fear conditioning drove dmPFC reorganization to generate a neuronal ensemble encoding CR, which was characterized by enhanced internal coactivity and functional connectivity. Importantly, neurons strongly responding to unconditioned stimuli during fear conditioning subsequently became hubs of this novel network and revealed enhanced association with conditioned stimuli (CS), which may work as an information-processing neural network implementing CS-triggered CR (i.e., a neural network for the CS-to-CR transformation). Altogether, we demonstrate learning-dependent dynamic modulation of population coding structured on the activity-dependent formation of the hub network within the dmPFC.Currently, we are developing a new imaging method to enhance brightness and spatial resolution in the deep mPFC, enabling simultaneous imaging across broader regions and multiple layers to further investigate the neural mechanisms underlying long-term memory and extinction. | |||||||
| 会議概要（会議名, 開催地, 会期, 主催者等） | ||||||||
| 内容記述 | Optical Interrogation of Neural Structure and Dynamics Underlying Behavior | |||||||
| 発表年月日 | ||||||||
| 日付 | 2025-04-23 | |||||||
