1. Introduction to the Human Brain

1. Introduction to the Human Brain

Retrospective Cortex (00:12:10)

  • A postdoc named Russell Epstein, specializing in computer vision, aimed to understand human vision by simulating brain algorithms.
  • Epstein was skeptical about the emerging brain imaging techniques and was persuaded to conduct an imaging experiment to aid his job prospects.
  • The experiment, which involved scanning people as they looked at images of scenes, unexpectedly identified a brain area highly responsive to scenes, not faces or objects.
  • This discovery of the parahippocampal place area spurred significant research in the field of vision and cognition.
  • A personal anecdote revealed the slow growth of a non-cancerous meningioma tumor found in a friend's brain, first observed in past research data.

Medical Incident and Neuropsychological Insights

  • The discovery that the tumor, initially unseen in earlier data, was growing slowly suggested it wasn't as aggressive as some brain tumors.
  • The friend's tumor was later identified as a non-cancerous meningioma.
  • During a hospital visit, a resident acknowledged the author's expertise in brain studies.
  • Urged by a neurosurgeon friend, the author used connections to find a top neurosurgeon for their friend's surgery.
  • A pre-surgery test revealed the friend had difficulties with spatial tasks, such as drawing a floor plan, but not with drawing objects like a bicycle or lobster, indicating a specific impairment in spatial reasoning related to places.

Surgical Outcome and Reflection [Not in the provided text]

  • Details concerning the surgical outcome and any further reflections were not included in the provided text.
  • Bob's navigational abilities did not recover following brain damage.
  • Relies on iPhone GPS for navigation, indicating technology's role in compensating for lost brain functions.
  • Recovery of such specific brain functions is less likely in adults, compared to children.
  • Left-right distinction and recognition of familiar places remain intact, but the ability to navigate or orient spatially to travel to those places is impaired.
  • Can follow memorized routes but cannot form new routes or alternate pathways.
  • Can estimate distances but struggles with creating mental maps of surroundings.
  • Difficulty with navigation persists even in familiar environments and within buildings.

The Organization of the Brain Echoes the Architecture of the Mind (00:29:46)

  • The organization of the brain reflects the architecture of the mind, indicating specific mental functions.
  • Brain structure corresponds to specific mental abilities; not all brain parts are equally specialized.

How Do Brains Change (00:30:54)

  • Changes in the brain due to normal development, learning, experience, and injury vary with age.
  • Children’s brains are more plastic and able to adjust after injury.
  • The study of how brains change can involve a variety of methods, from behavioral observations to anatomical and functional imaging.

Why How and What of Exploring the Brain (00:31:59)

  • Various methods are used to explore the brain's structure and functions, each providing different insights.

Why Should We Study the Brain (00:32:33)

  • Studying the brain is essential for understanding the essence of what makes us who we are.
  • The brain is a unique organ responsible for our identity, distinct from other vital organs.
  • Understanding the brain can help us grasp the limits of human knowledge.

Understand the Limits of Human Knowledge (00:33:49)

  • Recognizing the limits of human understanding can help gauge the quality of the knowledge we possess.
  • Ungraspable scientific theories might exist.
  • Studying the mind serves as empirical epistemology to understand the knower.
  • The development of AI has rapidly evolved, especially in vision, challenging the human visual system's superiority.
  • The landmark Krizhevsky paper in 2012 on deep nets drastically improved visual object recognition approaching human performance.
  • Despite advancements, deep nets still struggle with more variable and realistic sets of images compared to humans.

Image Understanding (00:41:06)

  • AI can label images but struggles with understanding the dynamic situations within them.
  • Image captioning algorithms can accurately describe some images but often fail with complex scenes.
  • Deep neural networks (deep nets) are proficient in pattern recognition but not in comprehending nuanced real-world scenarios.
  • AI lacks human capabilities like navigating new situations, understanding beliefs, communication, and creativity.
  • AI systems have dramatically advanced but still have much to learn from human brain functionality to fully replicate human cognition.

Fourth Reason To Study the Human Brain (00:46:03)

  • The human brain is considered the greatest intellectual quest of all time.
  • The brain has multiple levels of organization offering various approaches to its study.
  • This course will not focus on any single method but rather explore how the brain gives rise to the mind.

How Does the Brain Give Rise to the Mind (00:47:16)

  • Understanding the brain requires starting with the concept of the mind.
  • Identifying what the mind is and how it functions is critical.

Mental Functions (00:47:41)

  • The course will examine various mental functions, such as perception and cognition.
  • For each function, specialized neural machinery and brain region interactions will be explored.
  • Cognitive science methods such as psychophysics and studying perceptual illusions are fundamental to the course.
  • Functional MRI, neuropsychological studies, EEG, neurophysiology, and other methods will be used to understand the brain basis for mental functions.
  • The instructor addresses previous course feedback and clarifies that the focus is on cognitive science, not just the brain's biology.
  • Recent progress has greatly expanded knowledge about specific brain region functions related to mental processes.
  • The course will concentrate on functions with well-understood brain bases, like color, shape, motion perception, face recognition, language understanding, and others.
  • The discussions will include developmental aspects, species comparisons, and what is unique to the human brain.
  • Broader questions like knowledge acquisition, brain plasticity, and thinking without language will be considered.
  • The course will omit topics such as motor control due to time constraints.

Awareness (00:56:17)

  • The course will also touch upon the role of awareness in thinking, perceiving, and understanding.

Subcortical Function (00:56:48) and Related Sections

  • The course primarily focuses on the cerebral cortex, important for conscious thinking and cognition.
  • Comparative under-coverage of subcortical function and decision-making due to course's scope.
  • Understanding circuit-level mechanisms of high-level mental functions, such as comprehending sentences, is currently beyond our scientific grasp.
  • Detailed neuron-level understanding of less complex functions, like fear conditioning in mice, has been achieved.
  • Lack of focus on memory is due to the instructor's desire to avoid uninteresting lectures.
  • Reinforcement learning and reward systems, as well as attention, are mentioned but won't be major focuses.
  • The course is aimed at students who have taken prerequisites (900 or 901) but is accessible to others willing to put in extra effort.
  • Some overlap is inevitable with prerequisite courses due to the nature of the material.

The Goals of this Course (01:00:37)

  • The course aims to help students appreciate major questions and theoretical stakes in the field.
  • Understanding rather than memorization is emphasized.
  • Instruction on methods in human cognitive neuroscience, their strengths, and limitations.
  • Students will learn about domains of cognition with significant advancements at both the cognitive and brain level, such as face recognition and language understanding.
  • A major goal is to enable students to read and interpret current scientific papers in the field, with course readings advancing to recent publications.

Why no Textbook (01:02:15)

  • No textbook is used because the field progresses too rapidly for textbooks to keep up.
  • The course emphasizes reading current original research articles over outdated textbooks or review articles.
  • The approach is designed to empower students to engage directly with the most recent studies in the discipline.

Details on the Grading (01:02:47)

  • Grading is straightforward, with a midterm and final exam each constituting 25% of the grade.
  • The final exam is cumulative but focuses more on the latter part of the course material.

Reading and Writing Assignments (01:02:58)

  • Students will have reading and writing assignments, with two papers to read weekly and a short written assignment on one paper.
  • Understanding the paper is critical for answering questions.
  • Assignments and submissions will be managed via Stellar, with the first paper response due February 12 at 6 PM.
  • Assignments are due the night before the class to allow TAs to assess comprehension.

Scene Perception and Navigation (01:09:07)

  • The course will explore scene perception and navigation, using various methods to understand how these processes work.
  • Lectures will address development, how brains are wired, and the roles of genes and learning, focusing on navigation and face recognition systems.
  • Additional topics include the brains of blind people, number cognition, pleasure, pain, reward, neuroeconomics, uniquely human capabilities, and the differencse between human and animal cognition.

Brain Machine Interface (01:11:45) and Theory of Mind (01:12:11)

  • Guest lecturer Michael Cohen will cover brain-machine interfaces.
  • The course will also delve into language comprehension and production, and the concept of theory of mind, which involves interpreting others' mental states.

Brain Networks (01:12:39)

  • Brain function involves multiple regions working together.
  • Studies aim to identify which sets of regions collaborate.
  • The quest is to understand broader networks of brain regions.
  • The course will include a longer written assignment for students to design their own experiments.
  • Group sessions will refine experiment designs.
  • Katherina Dobbs will give a guest lecture on deep nets and their relation to cognition and brains.
  • Topics of attention and awareness will be discussed.
  • The final class might feature TAs presenting their research, pending confirmation.
  • The structure and content of the remaining classes were clarified to the students.

Reading and Understanding Academic Papers

  • This course isn't focused on statistics or MRI physics.
  • Students should understand basic concepts like P levels, T-tests, ANOVAs, and correlations.
  • Reading papers is not about mastering the statistics but understanding the study's substance.
    • When reading, identify the main question of the paper, ideally found in the abstract.
    • Ascertain the key findings from the paper.
    • Understand the interpretation of the findings, such as why they are significant.
  • The course will not cover the intricacies of statistical details in experiments due to time constraints.

Browse more from
MIT OpenCourseWare

Overwhelmed by Endless Content?