About the Yang Lab

The Yang Lab investigates the brain’s role in health and disease using interdisciplinary approaches in Neuroscience, Psychology, and Psychiatry. We employ mouse models and advanced techniques like AI-based analytic tools, optogenetics, neuroimaging, and behavioral assays to explore neural mechanisms at molecular, circuit, and behavioral levels.

Our research focuses on:

Cognition and Behavior – Studying neural circuits underlying learning, memory, decision-making, and social interactions.
Mental Disorders – Investigating the neurobiology of depression, anxiety, and addiction to identify biomarkers and therapeutic targets.
Brain-Liver-Gut Axis – Exploring metabolic and gut-derived signals that influence brain function and neuropsychiatric disorders.

We are committed to rigorous and ethical animal research and welcome collaborations to advance neuroscience and mental health studies.

關於楊老師實驗室

楊老師實驗室致力於透過神經科學、心理學與精神醫學等跨領域方法，探討大腦在健康與疾病中的關鍵角色。我們以小鼠為模型，結合人工智慧分析工具、光遺傳學、神經影像技術及行為實驗等，從分子、神經迴路到行為層面深入研究神經機制。

我們的研究聚焦於以下三大方向：

認知與行為：解析大腦中負責學習、記憶、決策與社會互動的神經迴路。
精神疾病：探討憂鬱、焦慮與成癮等心理疾病的神經生物學基礎，尋找生物標誌與潛在治療靶點。
腦-肝-腸軸：研究代謝與腸道來源訊號如何影響大腦功能及神經精神疾病。

我們堅持嚴謹且符合倫理的動物實驗，並積極尋求合作，共同推動神經科學與心理健康領域的前瞻研究。

Translational Animal Models

轉譯醫學動物模式

Our lab uses mouse models to study brain function and diseases/disorders. These models help us understand how the brain controls behavior and how diseases develop. By using tools like imaging and AI-powered systems, we explore mechanisms and new treatments, aiming to bridge basic research and clinical applications. We aim to expand the current colonies and collaborate with experts from various research disciplines.

本實驗室運用小鼠模式研究大腦功能，以及神經與精神疾病的相關機制。透過這些動物模型，我們得以深入了解大腦如何調控行為，並揭示疾病的發生與進展過程。我們結合神經影像技術與人工智慧分析系統，探索神經機制並開發潛在的治療策略。研究室目前正擴充動物族群，並積極與各領域專家合作，期望促進基礎研究與臨床應用之間的連結。

Animal facility in the International Research building. We utilize mouse models for translational research.

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Open field test with automated AI-based labeling.

Beam walk test to assess general motor and balance function. With Matlab programming, we are able to quantify whether the animal is 'balanced' or 'unbalanced' based on the estimated areas.

Open field test equipped with a depth camera, acquiring both RGB and depth videos. These videos will then be analyzed with AI-based tools for behavioral assessment.

AI-based analysis tools

人工智慧影像分析系統

We integrate AI-based tools to enhance research efficiency and support the 3R principles (Replacement, Reduction, and Refinement) in animal studies. AI helps us analyze behavior, automate data collection, and develop computational models to simulate brain function. These approaches minimize animal use while improving research accuracy and reproducibility.

我們整合人工智慧工具以提升研究效率，同時落實動物實驗中的3R原則（替代、減量、精緻化）。AI技術協助我們進行行為分析、自動化資料蒐集，並建構模擬大腦功能的計算模型。這些方法不僅能減少實驗動物的使用量，也有助於提升研究的準確性與再現性。

Behavior reconstruction based on automatic AI-labeled body parts.

Exploratory entropy; higher the entropy implies more exploratory behavior.

Angular entropy; indicates heading directions.

Clinical Applications

臨床應用

The AI-based analytic tool could also be used to apply automated analysis to patient videos for objective, scalable assessment of neurological and psychological conditions. (Video adapted from Nonnekes et al., 2015)

此AI影像分析技術亦可應用於臨床上，藉由影像來自動化、快速建立個人化資料，協助醫護人員快速評估神經退化相關的行為症狀(影像來源: Nonnekes et al., 2015)

FOG_Trim.mp4

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