Fundamentals of Neuroscience Part 2: Neurons and Networks - Harvard University

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Online

Free

Important information

  • Course
  • Online
  • When:
    Flexible
Description

Discover what makes your brain tick in this second part of a four-part introductory series in Neuroscience.
With this course you earn while you learn, you gain recognized qualifications, job specific skills and knowledge and this helps you stand out in the job market.

Important information

Requirements: There are no formal requirements for MCB80x, though prior background in biology, chemistry and/or physics is helpful. There is no required textbook to buy. We link to related text in open-source Neuroscience textbooks online.

Venues

Where and when

Starts Location
Flexible
Online

What you'll learn on the course

Networks
Biology
Neuroscience
Neurons
Fundamentals of Neuroscience

Course programme

In this second module we will explore how neurons communicate with each other.  We will investigate the collective behavior of neurons in small circuits and ways in which signals between neurons are modulated.

Each lesson will be media and content rich and will challenge you to master material with interactive segments that depend on your feedback to move forward in the lesson. You will be able to use virtual labs simulating neurons and circuitry to test your understanding of the course material. Lessons will also be filled with beautiful animations, exploring the richness and complexity of the brain. Documentaries focusing on cutting-edge topics in neuroscience will take you inside labs, hospitals and research institutions around Harvard, MIT and Boston, and quiz banks will allow you to test your knowledge on your own time.

What you'll learn

  • Fundamental concepts of neuroscience, including the synapse, excitation and inhibition, small circuits, neuromodulation, and potentiation and depression.

Additional information

David Cox David Cox is an Assistant Professor of Molecular and Cellular Biology and of Computer Science, and is a member of the Center for Brain Science at Harvard University. He completed his Ph.D. in the Department of Brain and Cognitive Sciences at MIT with a specialization in computational neuroscience.
 
His laboratory seeks to understand the computational underpinnings of visual processing through concerted efforts in both reverse- and forward-engineering. To this end, his group employs a wide range of experimental techniques (ranging from microelectrode recordings in living brains to visual psychophysics in humans) to probe natural systems, while at the same time actively developing practical computer vision systems based on what is learned about the brain.