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How do our brains enable us to see the many shapes of objects in the world? One idea posed by neuroscientists is that there are different types of neurons in the brain that recognize different elements of shape, such as straight lines, curves, and corners, and that shapes are the result of integrating these different basic elements. However, where these neurons are and how their information is integrated is not well understood. 


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In the late 1960s, Nobel Laureates Hubel and Wiesel discovered that the first stage of visual information processing in the cortex (primary visual cortex) contains submillimeter-sized functional units called orientation columns. They showed that each column contained neurons responsive to only a certain contour orientation (e.g. neurons in a ‘vertical’ orientation column would respond to the vertical contour of a tall tree but not to the contour of a horizontal tree branch). It was later discovered that the set of all possible orientation columns (0-180 deg) shifted systematically around a point in a ‘pinwheel-like’ fashion. This concept of a single orientation column encoding a single contour orientation has been a cornerstone of sensory systems neuroscience.


In this study, two research teams cooperated to develop a novel, highly precise method of targeting electrodes in the orientation column and accurately determinng their position, so that different regions within single orientation columns could be probed. Using intrinsic signal optical imaging to map the orientation columns, researchers conducted systematic and comprehensive study of the functional properties of neurons in different parts of individual orientation columns. For the first time, they found that within single orientation columns there is a clear distribution of neurons with different functional preferences. Specifically, they found three subdomains, whose functional responses were consistent with the encoding of straight lines, curves, and complex contours, respectively. This suggested that single orientation columns may contain multiple basic elements for building shapes and led to a new concept of the ‘pinwheel-centered orientation hypercolumn’. Thus, their technical advance has led to a new view of the orientation column and of cortical functional architecture. This new finding will also be useful for computational models of shape encoding in the brain.

 

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Online Paperhttps://advances.sciencemag.org/content/5/6/eaaw0807


2019-06-06 READ MORE

How do our brains enable us to see the many shapes of objects in the world? One idea posed by neuroscientists is that there are different types of neurons in the brain that recognize different elements of shape, such as straight lines, curves, and corners, and that shapes are the result of integrating these different basic elements. However, where these neurons are and how their information is integrated is not well understood. 


图片1.png  

  

In the late 1960s, Nobel Laureates Hubel and Wiesel discovered that the first stage of visual information processing in the cortex (primary visual cortex) contains submillimeter-sized functional units called orientation columns. They showed that each column contained neurons responsive to only a certain contour orientation (e.g. neurons in a ‘vertical’ orientation column would respond to the vertical contour of a tall tree but not to the contour of a horizontal tree branch). It was later discovered that the set of all possible orientation columns (0-180 deg) shifted systematically around a point in a ‘pinwheel-like’ fashion. This concept of a single orientation column encoding a single contour orientation has been a cornerstone of sensory systems neuroscience.


In this study, two research teams cooperated to develop a novel, highly precise method of targeting electrodes in the orientation column and accurately determinng their position, so that different regions within single orientation columns could be probed. Using intrinsic signal optical imaging to map the orientation columns, researchers conducted systematic and comprehensive study of the functional properties of neurons in different parts of individual orientation columns. For the first time, they found that within single orientation columns there is a clear distribution of neurons with different functional preferences. Specifically, they found three subdomains, whose functional responses were consistent with the encoding of straight lines, curves, and complex contours, respectively. This suggested that single orientation columns may contain multiple basic elements for building shapes and led to a new concept of the ‘pinwheel-centered orientation hypercolumn’. Thus, their technical advance has led to a new view of the orientation column and of cortical functional architecture. This new finding will also be useful for computational models of shape encoding in the brain.

 

图片2.png 

 

Online Paperhttps://advances.sciencemag.org/content/5/6/eaaw0807


2019-06-06 READ MORE
2019-06-04 READ MORE

为给全国高校优秀大学生创建神经科学、生物医学、信息科学等交叉学科学术交流平台,提供与该领域专家教授交流的机会,帮助青年学生更好地了解当前学科发展热点问题,浙江大学系统神经与认知科学研究所定于2019710-12日在景色宜人的杭州举办2019年优秀大学生夏令营。

浙江大学系统神经与认知科学研究所(Zhejiang University Interdisciplinary Institute of Neuroscience and Technology, ZIINT)是由国家“千人计划”入选者,神经领域著名科学家Anna Wang Roe(王菁)教授于2013年在浙江大学华家池校区创立,以交叉学科、高度国际化为主要特色。ZIINT的成立主要为解决认知与行为神经科学领域的重大问题,探索脑高级功能的神经网络机制,在脑功能和脑疾病等相关研究中取得重大突破;为相关医学、神经科学、工程学以及其他领域交叉学科的沟通搭建了桥梁;同时致力于跨学科研究,通过与在浙知名医院紧密合作,真正的推动神经科学从实验室到临床应用的转化。

2020年系统神经与认知科学研究所研究生招生学科为:生物医学工程,神经生物学、人体解剖与组织胚胎学、影像医学与核医学、光学工程,欢迎考生跨学科报考。

一、申请资格

1.具有浓厚的科学研究兴趣,较强的科研能力,有志于生物医学工程、神经生物学等专业的研究,并有继续深造意向。

2.2020届本科毕业生,学业成绩优秀,满足母校“免试推荐”研究生标准,或有志参加全国研究生招生考试报考我所的三年级本科生。

3.英语良好,要求国家六级水平考试480分及以上(460-480分之间,在其他方面有突出表现的,也可予以考虑)或有较好的托福80分及以上)或雅思(5.5分及以上)成绩。

4.专业要求:神经生物学、生物医学工程、计算机科学、光学工程、生物技术、材料科学、信息电子工程、电子、电气、控制类相关专业(包括医学、生物学、药学、数学、物理、化学等)三年级本科生(2020届毕业生)。

二、申请报名

     报名截止日期:201962317:00,请扫描微信二维码报名,填写相关报名信息。

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三、材料审核及录取

1.专家小组审核相关材料后,择优录取25名营员,由浙江大学系统神经与认知科学研究所发放录取名单,录取名单将于626日前在系统神经与认知科学研究所网站上公布(http://www.ziint.zju.edu.cn/),请及时查看。

2.确认参加者请在630日前将回执返回(届时邮件通知)。

四、夏令营日程

本次活动内容包括专家讲座、实验室参观与实验操作、师生座谈等精彩活动。日程安排:

710日下午(13:30后):学员报道登记、安排住宿;

711-712日:专家讲座、实验室参观与实验操作、师生座谈、营员报告与优秀营员选拔。

五、资助条件

    1.营员的食宿由研究所承担并统一安排,并为入选营员报销来杭单程车票(高铁二等座、火车硬座、汽车票),营员请自行预定车票,报销时须提供来程车票。

2.保险:研究所统一购买在浙大活动期间的团体意外保险。

六、注意事项:

1.参加暑期夏令营的学生必须遵守浙江大学的相关规定,按照统一安排参加活动,并注意安全;

2.由于实验室属于高洁净环境,确认参加者须进行结核菌测试(胸透),可经由胸片、皮测或血液等不同方法取得,须于72日前寄回电子版结核菌测试结果(fengxinwei@zju.edu.cn)。

3.凡参加夏令营者,报到时须携带以下材料:

1)身份证及复印件;

2)申请表中所涉及的相关证书证明材料的原件;

3)英语六级成绩或其他外语成绩;

4)本科学习成绩总表原件。

七、联系方式:

1.浙江大学华家池校区科学楼203办公室,联系人:冯老师,邮箱fengxinwei@zju.edu.cn电话0571-86971735

2.系统神经与认知科学研究所网站:http://www.ziint.zju.edu.cn/

 

2019-05-31 READ MORE
2019-05-23 READ MORE
2019-05-28 READ MORE

Columnar connectome: towards a mathematics of brain function

https://www.mitpressjournals.org/doi/abs/10.1162/netn_a_00088


Summary:

What makes the brain unique is its vast network of connections. It is the SYSTEMATIC PATTERNs of functional connections lead to behavior, thoughts, and feelings. This article proposes that there are common repeated patterns of connectivity and that these patterns can be represented mathematically. Such brain math opens doors to understanding biological thought, design of new targeted brain-machine interfaces, and a new generation of artificial intelligence.


Abstract

Understanding brain networks is important for many fields, including neuroscience, psychology, medicine, and artificial intelligence. To address this fundamental need, there are multiple ongoing connectome projects in the US, Europe, and Asia producing brain connection maps with resolutions at macro-, meso-, and micro-scales. This viewpoint focuses on the mesoscale connectome (the columnar connectome). Here, I summarize the need for such a connectome, a method for achieving such data rapidly on a largescale, and a proposal about how one might use such data to achieve a mathematics of brain function.

2019-05-07 READ MORE

Columnar connectome: towards a mathematics of brain function

https://www.mitpressjournals.org/doi/abs/10.1162/netn_a_00088


Summary:

What makes the brain unique is its vast network of connections. It is the SYSTEMATIC PATTERNs of functional connections lead to behavior, thoughts, and feelings. This article proposes that there are common repeated patterns of connectivity and that these patterns can be represented mathematically. Such brain math opens doors to understanding biological thought, design of new targeted brain-machine interfaces, and a new generation of artificial intelligence.


Abstract

Understanding brain networks is important for many fields, including neuroscience, psychology, medicine, and artificial intelligence. To address this fundamental need, there are multiple ongoing connectome projects in the US, Europe, and Asia producing brain connection maps with resolutions at macro-, meso-, and micro-scales. This viewpoint focuses on the mesoscale connectome (the columnar connectome). Here, I summarize the need for such a connectome, a method for achieving such data rapidly on a largescale, and a proposal about how one might use such data to achieve a mathematics of brain function.

2019-05-07 READ MORE
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