校際選修

115-1 選課時程

進行中

  • 初選第一階段 6/15/2026
  • 初選第二階段 6/22/2026
  • 校際選修 8/24/2026
  • 初選第三階段 8/31/2026
  • 開學後加退選 9/7/2026
  • 逾期加退選 9/21/2026
選課資源

跨領域腦科學

Interdisciplinary Brain Science

學期
114-2
學分
1 學分
當期課號
131115
永久課號
MDBS30069
開課單位
腦科學研究所
授課教師
蔡金吾、楊定一、林永煬、郭博昭、陳麗芬、鄭彥甫、盧俊良、鄭菡若、蔡欣融、楊靜修、張家祥
校區
陽明
類別
選修
上課時間表
週二
N
12:20–13:10
跨領域腦科學
YL402

* 根據陽明交大上課時間表所列

概述

跨領域在本所是最重要的學習,本課程是專門為本所的碩、博士生規劃的課程,課程中會邀請來自其他大學、醫院以及公司企業界等教授、研究員或是大師級人物來演講,或是以講座方式以增進同學們對腦科學跨領域相關學習,部分課程邀請本所專任、合聘、兼任教師們進行腦科學研究議題的跨領域座談,希望學生在輕鬆的方式下學習腦科學領域的跨領域研究。 Interdisciplinary learning is the most important aspect in this institute. This course is specifically designed for the master's and doctoral students of our institute. Throughout the course, we invite professors, researchers, or renowned experts from other universities, hospitals, and industries to deliver lectures or conduct seminars, aiming to enhance students' interdisciplinary knowledge related to neuroscience. Additionally, some sessions feature discussions on neuroscience research topics led by our institute’s full-time, jointly appointed, or adjunct faculty members. The goal is to provide students with a relaxed environment to learn about interdisciplinary research in the field of neuroscience.

先修科目

教學方式

1.本課程透過邀請不同領域的專業人士進行講授,旨在拓展學生的視野,培養跨領域的學習能力,引導學生思考如何將新學到的知識與自身學科或未來挑戰相結合。學生需撰寫心得,整理重點內容,以及參與小組討論,以促進彼此的交流與啟發。 2. 關於本學期 3/3、3/17、5/5 的三場演講,因考量資源整合,將改為在 E3 平台觀看 2025 年的精華演講影片。因課程評分包含「發問次數」,這三場改為線上觀看後,將無法提供現場發問加分的機會,改為繳交心得報告等同於發問加分機會。 3.本堂課將會以實體與同步遠距混成教學方式上課,線上課程連結為 https://meet.google.com/twb-jdch-mzt , 無法到場聽課同學可提早5分鐘進入虛擬教室準備上課 This course invites professionals from various fields to deliver lectures, aiming to broaden students' perspectives, develop their interdisciplinary learning skills, and guide them to think about how to integrate newly acquired knowledge with their own disciplines or future challenges. Students are required to write reflections, summarize key points, and participate in group discussions to foster mutual exchange and inspiration. 2.The lectures on 3/3, 3/17, and 5/5 will be replaced by recorded sessions from 2025, which you can access via the E3 platform. As "in-class questioning" is part of the grading criteria. 3.We offer hybrid teaching (both physical and online) for this course. If you cannot attend in person, please join us online through this link: https://meet.google.com/twb-jdch-mzt. Please log in to the virtual classroom 5 minutes early to prepare for the session.

評分方式

評量標準: -演講者: 選兩次演講或座談學習心得報告(40%*2) -上課表現: 上課問問題(20%,每提出一次問題或討論3分。) 加分項目: -其他有助於課程的各種表現±5。 Evaluation Criteria: -Learning Reports (80%):Submit two reflection reports based on selected lectures or seminars.Each report accounts for 40% of the final grade. -Class Participation (20%):Points are earned by asking questions or engaging in discussions during live sessions.Each instance of participation earns 2 points, up to a total of 20%. Extra Credit Bonus: ± 5 points based on overall performance and engagement.

週次計畫
週次主題
第 1 週課程介紹_楊靜修教授 12:10-13:10 (無點心) 邀請演講1-「In situ Proteomics Unveils Specialized Domains for Extrasynaptic Signaling on Neuronal Cilia」 張家祥 助理教授 16:30-17:30 (無點心)
第 2 週邀請演講2-「BUILDING THE CORTEX BY CELLS: The developmental blueprint of the cerebral cortex」, 侯珮珊 助理教授 (無須到場,請上E3觀看影片)
第 3 週
第 4 週邀請演講3-「Toward end to end multimodal assistive oral communication technologies」曹昱研究員 (無須到場,請上E3觀看影片)
第 5 週
第 6 週
第 7 週邀請演講4-「創新TRPM8活化劑之臨床應用 Clinical use of TRPM8 activators」,黃相碩教授。 12:10-13:10 (提供點心)
第 8 週邀請演講5-「腦科學在產業界、精神疾病、健康衛生政策研究——從神經迴路到職涯規劃」, 林煜軒醫師。12:10-13:10 (提供點心)
第 9 週
第 10 週
第 11 週邀請演講6-「From 3T to 7T: Advancing Social Neuroscience and Empathy Research」, 陳麗芬教授 (無須到場,請上E3觀看影片)
第 12 週改到6/23日演講
第 13 週
第 14 週
第 15 週邀請演講8-「精神益生菌:學術到產業」, 蔡英傑教授 。 15:30-17:20 (無點心)
第 16 週
第 17 週邀請演講9-「Overview and update in non-invasive brain stimulation (NIBS) methods: 40 years after the invention of TMS? 」, 賴冠霖醫師。 15:30-17:20 (無點心)
第 18 週邀請演講7-「從電機系學生到外商醫藥生技人:十多年的跌撞與收穫」, illumina有限公司,市場部,台灣、香港及澳門行銷主管 。謝一德博士。13:20-15:10 (無點心) 邀請演講10-「Modeling User Aesthetic Experience in Residential Spaces Through Brain Imaging and Deep Neural Networks」, 郭柏志教授。 15:30-17:20 (無點心)
教科書