Subject: Introduction to Computational Neuroscience (VU-CSC 323)
Computational neuroscience is the interdisciplinary field that uses mathematics, computer science, and modeling to understand how the brain and nervous system work or process information. It bridges biology and computation, offering insights into cognition, perception, and artificial intelligence.
Think of it like using a computer to study another computer; except the original computer (the brain) is made of billions of neurons, not metal and circuits.
Computational neuroscience asks “How does the brain process information?” and uses math, computer science, and experiments to explain how neurons and networks create behaviour.
Scope It covers things like:
- How neurons send messages (like MTN to Airtel calls)
- How the brain learns, remembers, and makes decisions
- How to simulate parts of the brain using code (mostly Python)
- How to build AI inspired by the brain
Why model the human brain?
1. Understand it
2. Fix or improve it (medicine, neuroprosthetics)
3. Get inspiration (AI, robotics, machine learning)
Think of it like studying how a generator works before you can repair or redesign it.
What Is the Brain Good At?
Computers beat humans in:
1. Chess
2. Go
3. Data processing
4. Calculations
But humans beat computers in:
1. Real-world interaction
2. Flexibility
3. Motor skills (e.g., Messi dribbling)
4. Perception (recognizing faces quickly)
This is why RoboCup robots still struggle compared to real footballers (2021, Michael Graupner).
What is Neuron
A neuron is the basic working unit of the brain, it is a special kind of cell designed to receive, process, and send information. A neuron is like a tiny electrical messenger in your brain and nervous system. It helps you think, move, feel, and react.
How a Neuron Works
Think of a neuron like a road network in Lagos:
1. Dendrites: the small streets receiving messages from many houses (other neurons)
2. Cell Body (Soma): the roundabout where decisions are made
3. Axon: the long expressway sending the message far away
4. Axon Terminals: the junctions where the message is passed to the next neuron
5. Synapse: the small gap between two neurons where the message is handed over
Messages travel like electrical signals (NEPA light) and get passed to the next neuron as chemical signals.
Relationship with Other Fields
Neuroscience
Neuroscience studies the brain biologically: nerves, neurons, chemicals.
Computational Neuroscience asks: Can we model this with equations, algorithms, or simulations?
Example: A neuroscientist studies memory cells, while a computational neuroscientist writes Python code that mimics how memory works.
Computer Science
Computer science gives us the tools:
- Algorithms
- Simulation techniques
- Data structures
- Machine learning
It’s like computer science provides the engine, while neuroscience provides the map.
Artificial Intelligence (AI)
AI is heavily inspired by the brain.
Things like:
- Neural networks
- Deep learning
- Reinforcement learning
All have roots in how biological neurons fire.
So computational neuroscience acts as the bridge between real brains and artificial brains.
Reference
Graupner, M. (2021). Introduction to computational neuroscience: From single neurons to network dynamics [Lecture notes]. Université de Paris. https://biomedicale.u-paris.fr/~mgraupe/teaching.php