Uses mathematical and computer models to explain how neurons and networks process information.
Models range from single neurons (integrate-and-fire) to networks and Bayesian brain theories. Artificial neural networks were inspired by neurons; deep networks are used to model visual cortex.
Models range from biophysical to abstract. They generate predictions and test ideas about coding and learning.
Example: neural networks model visual recognition.
Uses mathematical and computer models to explain how neurons and networks process information.
Computational Neuroscience is one of the 54 topics in Neuroscience. It is rated Advanced, so it suits learners who want specialist depth. Related topics in this area include Connectomics, Visual Cortex Processing, Cerebellum and Motor Learning.
Reinforcement learning models explain dopamine signals as prediction errors.
Work through the Beginner topics in Neuroscience first, such as Nervous System, Neuron, Central and Peripheral Nervous Systems, then return to Computational Neuroscience. Advanced topics assume the Intermediate vocabulary.
The closest topics to Computational Neuroscience are Connectomics, Visual Cortex Processing, Cerebellum and Motor Learning, Nervous System. Comparing them side by side is a good way to see how the ideas connect.
Read the summary and the in-depth section, then use the quick check on the interactive lesson for Computational Neuroscience. To practise the whole of Neuroscience, use the Neuroscience quiz.
Computational Neuroscience: Uses mathematical and computer models to explain how neurons and networks process information. Connectomics: Mapping the complete wiring diagram of neural connections, as achieved for the C. elegans nervous system. Read both side by side and note what each one explains.
First, read the summary and write the definition in your own words. Second, read the in-depth section and note any example. Third, compare it with Connectomics and explain the difference aloud. Finally, take the Neuroscience quiz and come back to this page for any question you miss.
Mapping the complete wiring diagram of neural connections, as achieved for the C. elegans nervous system.
🧠 NeuroscienceHierarchical neurons detect edges, motion and objects, as shown by Hubel and Wiesel.
🧠 NeuroscienceThe cerebellum fine-tunes movement and learns skills through error-based correction.
🧠 NeuroscienceThe brain, spinal cord and nerves that sense, process and respond to information.
🧠 Neuroscience