This book is an autobiography by Michael S. Gazzaniga. Something I learned from the book. 

For outsiders, scientific discoveries 

作者讲述了自己在麻省理工学院从事裂脑研究的经历，他以讲故事的方式将他对科学发现的认知娓娓道来，破除了普通人对所谓科学家的迷信。

Ordinary people would naively assume that scientists are the ones purely motivated by their desire for truth: E.O. Wilson who spent his childhood observing the jellyfish in clear waters of the Gulf of Mexico, Richard Feynman who was enthralled by the mystery of the universe. These romantic conceptions are at once ideal and idealistic, rendering the profession of scientist elusive yet enthralling. Michael S. Gazzaniga's narrative, however, tinted public imagination with more realism without tarnishing it. 

It's not all about knowledge. Those throwing themselves into the cause of science are motivated by myriad factors, hormone maybe. Gazzaniga himself came to Caltech not largely because he wanted to be near to his girlfriend. But we have to admit, Gazzaniga indeed developed a deep affinity with the human brain and devoted his whole life to this cause. 

It's not all about hardwork. It's also about serenpidity. The culture around us tend to exaggerate the importance of hard work, claiming success is 99% of hard work plus 1% luck. Similar formulas in self-help books all, more or less, play up the ethic of hard-working. Gazzaniga came out and say that it's not the case at all-- luck is an important factor. Science doesn't advance by pushing forward the boundaries step by step, it leaped by hitting on unintentional blocks. He shared the view of Kuhn: "scientific advance should not be understood as isolated individuals making great discoveries but in terms of the scientific community and the intellectual environment of the day allowing the reinterpretation of existing data."

What I appreciate most is his pioneering spirit, the sense of getting something out of nothing. 

Also dark side: academic bullying 

双脑记是认知神经科学之父加扎尼加的自传，他在书中讲述了自己的科研人生，他所了大脑两侧半球是如何分工与合作，人意识的起源种种问题。书中比较有洞见的一点是，加扎尼加强调了运气在成功以及科研进步中的角色，正如他所言：科学进步不应该被理解为独立的个体做出伟大的发现，而应该是科学团体和当时的知识环境允许下，对现有数据进行重新解释。