17 Lab 17: Bridging Biological and Artificial Intelligence
17.1 Learning Objectives
- Understand core concepts from Chapter 17
- Implement key algorithms and techniques
- Apply methods to practical problems
- Analyze results and draw insights
- Connect to broader NeuroAI themes
17.2 Prerequisites
- Reading: Chapter 17: Bridging Biology and AI
- Libraries: NumPy, Matplotlib, relevant frameworks
- Concepts: NeuroAI principles
17.3 Setup
import numpy as np
import matplotlib.pyplot as plt
np.random.seed(42)
plt.rcParams['figure.figsize'] = (12, 8)17.4 Part 1: Fundamentals
Core concepts and theory from Bridging Biology and AI.
## Example implementation
def example_function():
'''Placeholder for main implementation.'''
pass17.5 Part 2: Hands-On Implementation
Practical exercises exploring NeuroAI principles.
17.6 Part 3: Analysis
Analyze and visualize results.
17.7 Exercises
17.7.1 Exercise 1
Implement the basic algorithm.
17.7.2 Exercise 2
Explore parameter variations.
17.7.3 Exercise 3
Apply to real or simulated data.
17.7.4 Exercise 4
Compare different approaches.
17.7.5 Exercise 5
Discuss NeuroAI connections.
17.8 Challenge Problems
17.8.1 Challenge 1
Advanced implementation.
17.8.2 Challenge 2
Reproduce research findings.
17.8.3 Challenge 3
Novel application.
17.9 Discussion Questions
17.9.1 Question 1
How does this relate to neuroscience?
17.9.2 Question 2
What are the AI implications?
17.9.3 Question 3
Future research directions?
17.10 Summary
Explored NeuroAI principles through theory and practice.
Key Takeaways: - Core concepts mastered - Practical implementation skills developed - NeuroAI connections understood