Summary
Highlights
Kanwisher shares a true story about her friend Bob, who experienced a fall and was later diagnosed with a brain tumor. She recounts the mysterious navigational deficits Bob exhibited for years prior, which she, despite her expertise in brain modularity, had subconsciously dismissed.
Nancy Kanwisher welcomes students to 9.13, 'The Human Brain', and outlines the day's agenda: a personal story, discussion of 'why, how, and what' of brain study, and course mechanics.
After several ER visits and tests, Kanwisher insists on a brain scan. A "lime-sized" tumor is found near the parahippocampal place area, a region her lab discovered to be involved in navigation. Earlier scans showed the tumor was grape-sized, indicating slow growth and a less aggressive type.
The tumor is identified as a meningioma, a non-cancerous but serious growth. Before surgery, Bob's drawing abilities are tested, revealing a specific deficit in spatial layout (houses) but not object composition (bicycles, lobsters), highlighting a functional modularity. The story underscores the importance of finding the best neurosurgeon, a privilege not universally available.
Bob undergoes an 11-hour surgery to remove the tumor, which was intertwined with the vein of Galen. Thanks to excellent medical care, he recovers quickly physically, even returning to work within days. However, his navigational abilities do not return, consistent with brain damage literature—adult brains have limited plasticity for recovery compared to children. Bob now relies on his iPhone GPS for navigation, demonstrating a specific spatial impairment despite intact other spatial and cognitive functions.
The story illustrates several core themes of the course: the brain's structured organization, the specificity of some brain functions, the brain's architecture echoing the mind's architecture, how brains change over time (development, learning, injury), and the diverse methods for studying the brain (behavioral observation, anatomical imaging, functional imaging, patient studies).
Kanwisher presents four reasons: 1) Know thyself (the brain defines identity), 2) Understand the limits of human knowledge (empirical epistemology), 3) Advance AI (despite recent deep-net progress, human-level understanding and generalization remain unmatched), and 4) It is the greatest intellectual quest of all time.
She discusses the transformative impact of deep learning, particularly AlexNet's success in visual object recognition. However, she highlights its limitations compared to human vision, especially with atypical images, and its profound failure in image understanding (e.g., humor, context, and structural models of the world).
Studying the brain involves multiple levels of organization (molecules, neurons, circuits, regions). The course focuses on how the brain gives rise to the mind, starting with mental functions and then examining their brain bases. Methods include psychophysics, neuropsychology (patients with brain damage), fMRI, neurophysiology, EEG, MEG, and connectivity measures.
Addressing student feedback from previous years, Kanwisher clarifies that the course integrates cognitive science with brain science, arguing that understanding the brain's biological properties without considering the mental functions it implements is incomplete. The goal is to identify which mental processes have specialized machinery, what information is represented, and how.
She presents a historical overview, showing the significant increase in knowledge about brain function since 1990, largely due to fMRI. The course will focus on mental functions whose brain bases are best understood, such as visual perception, face/place/body recognition, navigation, number understanding, speech perception, language, and social cognition.
The course will explore questions about brain specialization, development, species homologues, human uniqueness, the origin of knowledge, brain plasticity, and thought without language. Topics NOT covered include motor control, subcortical mechanisms (beyond basic anatomy), decision-making, circuit-level explanations (due to current limitations in the field), memory, reinforcement learning, and detailed attention.
The course is designed for students with prior neuroscience background but is accessible to others with extra effort. Emphasis is on understanding rather than memorization. Grading includes midterm (25%), final (25%), weekly reading assignments with short written responses (30%), a final longer written assignment (10%), and brief in-class quizzes (10%).
The schedule includes an initial neuroanatomy lecture, a live brain dissection by Ann Graybiel, lectures on high-level vision, debates on visual cortex organization, scene perception and navigation, brain development, brains in blind people, number cognition, neuroeconomics (pleasure, pain, reward), language, social cognition (theory of mind), brain networks, a guest lecture on brain-machine interfaces, and a lecture on deep nets and their implications for brain science.
Kanwisher provides guidance on how to read scientific papers effectively: identify the research question, findings, and interpretation (why it matters) first, then delve into experimental design and analysis. She advises against getting bogged down in technical jargon (like MRI physics or complex statistics) that isn't central to the course's learning objectives, and emphasizes active reading with specific questions in mind.