1. Introduction to the Human Brain

MIT OpenCourseWare・2 minutes read

Nancy Kanwisher teaches a course on the human brain, sharing a personal story about a friend's medical emergency linked to brain abnormalities, leading to insights about brain functions and navigation issues. The course covers various mental functions understood by the brain, with a focus on perception, high-level vision, and audition, aiming to help students appreciate the field's big questions and gain knowledge about cognitive neuroscience methods through reading original research articles.

Insights

  • Nancy Kanwisher's class "Human Brain" delves into the importance of studying the human brain through real-life stories, highlighting how brain abnormalities can impact cognitive functions.
  • Deep neural networks like AlexNet have revolutionized object recognition tasks, approaching human-level accuracy but still falling short in atypical examples, showcasing the differences between human and AI cognitive capabilities.
  • The course emphasizes understanding the brain's organization and its role in mental functions like visual perception, cognition, and language, focusing on cognitive neuroscience methods to explore the brain's specialization and adaptability over time.

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Recent questions

  • What is the importance of studying the human brain?

    Understanding the human brain is crucial to comprehend human identity, evaluate knowledge limits, and advance artificial intelligence. By studying the brain, fundamental aspects of the mind can be revealed, showcasing the brain's specialization in distinct mental processes. Recent advancements in deep learning have revolutionized cognitive science and neuroscience, providing insights into human cognitive functions. The brain's organization mirrors the mind's architecture, emphasizing the significance of studying the brain to gain insights that artificial intelligence systems still lack.

  • How do deep neural networks like AlexNet perform in object recognition tasks?

    Deep neural networks like AlexNet have shown remarkable accuracy in object recognition tasks, approaching human-level performance. These networks have been transformative in the field, providing precise computational theories of human cognitive functions. While deep nets excel in recognizing patterns, they still struggle with object recognition compared to humans, especially in atypical examples. Despite their advancements, deep nets have limitations in understanding complex images and scenarios, showcasing the differences between human and artificial intelligence systems.

  • What methods are used to understand mental functions and their brain basis?

    Cognitive science methods like psychophysics and perceptual illusions are utilized to understand mental functions and their brain basis. These methods help researchers delve into the brain's organization and functions, revealing the roles of various brain regions in mental processes. Functional MRI has significantly contributed to understanding brain organization, showcasing the functions of numerous brain regions compared to limited knowledge in the past. By employing these methods, researchers can gain insights into how the brain gives rise to the mind and comprehend the brain's adaptability and change over time.

  • What topics are covered in the course on human cognitive neuroscience?

    The course on human cognitive neuroscience covers various mental functions understood by the brain, such as visual perception, recognition of faces, places, bodies, scenes, understanding numbers, speech, music, language, and more. Emphasis is placed on perception, high-level vision, and audition due to significant progress in these areas and the involvement of the cortex. The course aims to explore questions related to the brain's specialization in mental functions, system development, homologues in other species, uniqueness to humans, and the brain's adaptability over time. Students will engage with current research papers to enhance their understanding of cognition domains and human cognitive neuroscience methods.

  • How are assignments and assessments structured in the course?

    Assignments and assessments in the course include reading and writing assignments based on research papers to enhance understanding of the material. Grading consists of a midterm and final exam, with additional quizzes to assess understanding and knowledge retention. Students are required to submit assignments on Stellar, with the first written response due on a specific date. Quizzes are conducted using Google Forms to keep students updated on the material, with a longer written assignment involving designing an experiment. The course also includes a brain dissection session and lectures on various topics in human cognitive neuroscience, aiming to provide a comprehensive understanding of the subject matter.

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Summary

00:00

"Human Brain: A Professor's Personal Story"

  • The class is titled "Human Brain" and is taught by Nancy Kanwisher at 11:05.
  • Nancy Kanwisher introduces herself as the professor and shows a brain image with colored bits.
  • She plans to tell a brief story, discuss the importance of studying the human brain, and course details.
  • The story involves a friend named Bob who experiences a medical emergency at Nancy's house.
  • Bob is taken to the hospital after collapsing, where tests reveal no immediate issues.
  • Nancy recalls Bob's previous navigation difficulties and worries about his brain health.
  • Despite Bob's high-functioning abilities, signs of brain issues were evident.
  • Nancy's research on brain functions should have alerted her to Bob's navigation problems.
  • Bob is eventually found to have a lime-sized abnormality in his brain near a navigation-related region.
  • Nancy reflects on her past work with a postdoc named Russell Epstein, who studied visual recognition algorithms in the brain.

13:24

Brain scan leads to discovery of tumor.

  • Experiment conducted by Russell and the speaker involved scanning people's brains while looking at scenes and other pictures.
  • The experiment was not well-planned but led to the discovery of a brain region that responds selectively to scenes.
  • This region was named the parahippocampal place area and sparked further research in many labs.
  • A scan of the speaker's friend, Bob, revealed a slow-growing brain tumor near the parahippocampal place area.
  • The tumor was identified as a meningioma, not cancer, but still required surgery.
  • The speaker sought out the best neurosurgeon for Bob's surgery, emphasizing its importance.
  • Bob underwent an 11-hour surgery to remove the tumor near the vein of Galen, a major vein in the brain.
  • Due to the expertise of the neurosurgeon, Bob recovered quickly and was back to work within days.
  • Despite the successful surgery, Bob's navigational abilities did not return, relying heavily on GPS for directions.
  • Bob's ability to recognize familiar places remained intact, but he struggled with spatial navigation and route planning.

26:23

Brain organization and cognition in human identity

  • The individual discussed has difficulty creating new routes in familiar places but can recall established routes easily.
  • The person lacks conscious access to past knowledge when trying to navigate and struggles to construct a mental image of nearby places.
  • The brain's structure and organization play a crucial role in mental abilities, as seen in a case where a specific mental function was lost due to brain damage.
  • Specific parts of the brain are responsible for distinct mental processes, highlighting the brain's specialization.
  • The brain's organization mirrors the mind's architecture, indicating that understanding the brain can reveal fundamental aspects of the mind.
  • Studying the brain is essential to comprehend human identity, evaluate the limits of knowledge, and advance artificial intelligence.
  • Recent advancements in deep learning, particularly in object recognition, have revolutionized the field and provided insights into human cognitive processes.
  • Deep nets, like AlexNet, have shown remarkable accuracy in object recognition tasks, approaching human-level performance.
  • The use of deep nets in cognitive science and neuroscience has led to precise computational theories of human cognitive functions.
  • Testing deep nets on images outside standard datasets like ImageNet can reveal the generalizability of their performance and their potential in understanding human visual processing.

39:23

Challenges in Object Recognition for AI Systems

  • Researchers are working on a new, more challenging object recognition task to test deep neural networks like AlexNet, using a dataset of images created by Mechanical Turk workers.
  • The dataset includes hundreds of thousands of images with varying object locations and orientations, revealing that human performance surpasses that of deep nets like ResNet.
  • While deep nets are transformative, they still struggle with object recognition compared to humans, especially in atypical examples.
  • Image captioning algorithms have improved, with examples like identifying a dinosaur on a surfboard or people playing football accurately.
  • Humans and deep nets excel at pattern recognition but differ in their ability to understand complex images and situations.
  • AI systems have limitations in navigating new scenarios, understanding beliefs, using language, creating art, or developing solutions like bridges and medicines.
  • Studying the human brain is a significant intellectual pursuit, offering insights that AI systems still lack.
  • Various levels of brain organization can be studied, with a focus on understanding how the brain gives rise to the mind.
  • Cognitive science methods like psychophysics and perceptual illusions are used to understand mental functions and their brain basis.
  • Significant progress has been made in understanding brain organization, with functional MRI revealing the functions of numerous brain regions compared to the limited knowledge in 1990.

52:59

Exploring Human Cognitive Neuroscience: Big Questions

  • The course focuses on mental functions understood by the brain, such as visual perception of color, shape, and motion, recognition of faces, places, bodies, and words, scenes, perceiving scenes, navigating, understanding numbers, speech, music, language, and other people's minds.
  • Emphasis is placed on perception, high-level vision, and audition due to significant progress and the involvement of the cortex in these functions.
  • Questions to be explored include the brain's specialization in mental functions, the division of labor among brain regions, system development, homologues in other species, uniqueness to humans, and the brain's adaptability and change over time.
  • The course will not cover motor control, subcortical function, decision-making, circuit-level mechanisms, memory, reinforcement learning, reward systems, and attention extensively.
  • Designed as a tier two course for those who have taken previous related courses, additional work may be required for those who haven't.
  • The course aims to help students appreciate big questions in the field, understand human cognitive neuroscience methods, gain knowledge about cognition domains, and read current research papers.
  • No textbook is used due to the fast-paced nature of the field, with a focus on reading original research articles to stay updated.
  • Grading includes a midterm and final exam, with reading and writing assignments based on research papers to enhance understanding of the material.
  • Assignments will be submitted on Stellar, with the first written response due on February 12 at 6:00 PM.
  • Quizzes will be introduced, occurring in class using Google Forms, to assess understanding and knowledge retention.

01:05:33

Neuroscience Course: Quizzes, Experiments, and Lectures

  • Quizzes are meant to keep students updated and ensure they understand the material, with the first quiz scheduled for February 20.
  • A longer written assignment involves designing an experiment, expected to be three to five pages, with specific requirements like stating hypotheses and experimental designs.
  • The class will cover neuroanatomy briefly before a brain dissection by renowned neuroscientist Ann Graybiel, focusing on subcortical regions.
  • Lectures will delve into high-level vision, including motion, color, shape, faces, scenes, and bodies, teaching content and methods in the field.
  • Debates on the organization of visual cortex in humans will be explored, presenting different views and considering functional specificity in cortex regions.
  • The class will progress to scene perception, navigation, and development, focusing on wiring the brain, genes, and learning in navigation and face systems.
  • Lectures will cover brains in blind individuals, number cognition, neuroeconomics, pleasure, pain, and reward processing, with a guest lecture on brain-machine interfaces.
  • Language production and understanding, brain regions involved, cognition insights, and the language-thought relationship will be discussed.
  • Theory of mind, understanding others' emotions and thoughts, will be explored, followed by brain network discussions and a focus on broader brain regions working together.
  • The course will conclude with student-designed experiments, a guest lecture on deep nets, attention and awareness, and possibly short talks by TAs on their work.

01:17:26

Key Elements in Reading Scientific Papers

  • The process of reading a scientific paper involves identifying key elements such as the specific actions taken, the design and logic behind the study, and how the data was analyzed, with a focus on answering questions for oneself.
  • When reading a paper, it is essential to look for details like MRI responses to upright and inverted faces, the design and logic of the study, and how data was analyzed, while disregarding technical jargon that may not be relevant to the understanding of the paper.
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