How does intelligence emerge from the activity of neural circuits in the brain? In this unit, you will learn about empirical methods used to probe neural activity and what these methods reveal about the neural processes underlying important tasks such as visual recognition in humans and primates, and spatial navigation in lower mammals.
From Nancy Kanwisher, you will learn that the brain contains areas of functional specialization for the processing of faces, language, speech, and the Theory of Mind.
Neural signals flow from the sensory systems of vision, hearing, and touch, to higher cortical areas of cognitive function, and there is an even greater flow of information from higher to lower levels of the hierarchy of cortical areas. From Gabriel Kreiman, you will learn how the feedback of information from higher to lower levels of the visual system enables us to perform challenging tasks of object recognition and search.
Humans can recognize object categories in a brief glance of only 100 milliseconds. James DiCarlo takes an in-depth look at the neural circuits underlying rapid object recognition, examining how neurons encode properties of the visual scene and how these neural signals can be decoded into the object categories they represent.
From Winrich Freiwald, you will first learn about the important connection between sociality and intelligence, and the key role of face analysis in social behaviour. You will then explore the function of a specialized network of face processing regions in the brain.
Work by Winrich Freiwald and colleagues reveals a network of “face patches” in the primate brain containing neurons whose activity represents increasingly complex stages of face recognition. (Image courtesy of Winrich Friewald, used with permission.)
The hippocampus plays a central role in the formation of memories that connect locations and events in space and time. From Matt Wilson, you will learn how temporal sequences are encoded in neural signals, and the role of sleep in memory consolidation.
A fly may not seem very intelligent, but the simplicity of its neural circuitry provides the opportunity for a complete understanding of a biological function, from neurons to behavior. The guest lecture by Larry Abbott explores the computations performed by neural circuits of the fly’s olfactory system and how the fly learns to distinguish scents.
Unit Activities
Useful Background
- Introduction to neuroscience, including the structure and function of neurons, functional organization of the brain, and common empirical methods such as single cell recording and fMRI. View the video tutorial on neuroscience by Leyla Isik.
- Introduction to machine learning, including simple linear classification methods. View Part 1 of the video tutorial on machine learning by Lorenzo Rosasco.
- Nancy’s Brain Talks includes short talks on fMRI and other brain imaging methods, and how these methods are used to study problems such as face perception.