Module 10: Hypothesis Testing and Circuit Function

🧐 What is a Hypothesis?

A hypothesis is a testable prediction about a biological process. In connectomics, hypotheses often relate to how specific circuits enable computation or behavior.

• Difference between descriptive questions and mechanistic hypotheses
• Operational definitions and falsifiability
• Examples from published neuroscience studies

🔢 Designing Experiments

Hypothesis-driven research requires careful planning. This includes defining variables, controls, and outcome measures that meaningfully reflect circuit function.

• Independent vs. dependent variables
• Experimental vs. observational studies
• Confounds and sources of bias

📈 Testing and Interpretation

We explore logic-based approaches, simple statistics, and model-based reasoning to interpret data and draw conclusions.

• Statistical power and sample size considerations
• Understanding p-values and confidence intervals
• Replicability and interpretation frameworks

🌍 COMPASS Integration

• Knowledge: Principles of experimental design
• Skills: Statistical reasoning, logic, conceptual clarity
• Character: Scientific humility, rigor, honesty
• Meta-Learning: Learning from failed hypotheses

📚 References & Resources

• Popper, K. (1959). The Logic of Scientific Discovery
• Ioannidis, J. (2005). Why Most Published Research Findings Are False. PLoS Medicine
• Curran-Everett, D. (2000). Statistics 101. Advances in Physiology Education

✅ Assessment

• Given a hypothesis, design a testable experiment and identify the key variables
• Evaluate a flawed experiment and suggest improvements
• Interpret mock experimental results in light of the hypothesis