Sequential Probability Ratio Test (SPRT) and Decision-Making

Decision-Making Models and Theories

• Sequential Probability Ratio Test (SPRT) is a mathematical method used to make decisions based on sequential observations.
• Signal Detection Theory (SDT) is a theoretical framework that explores how people make decisions under uncertainty, considering both true and false alarms.
• The concept of Integrating Likelihoods Over Time is based on the principle of combining evidence from multiple observations to make a decision.

Decision-Making Mechanisms

• The Drift-Diffusion Model suggests that decision-making is a gradual process, where evidence accumulates over time until a threshold is reached, leading to a decision.
• The Posterior Parietal Cortex plays a key role in decision-making, particularly in tasks that require the integration of sensory information.

Biases and Limitations

• Reward and History Biases are types of biases that influence decision-making by prioritizing past rewards and experiences.
• Attractor networks can exhibit oscillatory behavior in decision-making processes.
• The Speed-Accuracy Trade-Off suggests that faster decisions may come at the cost of accuracy.
• The concept of Multiple Samples Integration relates to decision-making, where evidence is integrated over time to make a decision.

Signal Detection Theory

• The four possible outcomes in Signal Detection Theory are Hits, Misses, False Alarms, and Correct Rejections.
• Performance limitations in Signal Detection Theory can be characterized by the receiver operating characteristic (ROC) curve.

Drift-Diffusion Model

• In the Drift-Diffusion Model, firing rates align with the decision variable, which accumulates evidence over time.
• The 'diffusion-to-bound' behavior in networks is driven by the integration of sensory evidence.

Reward and History Biases

• Reward and history biases in decision-making shifts can be influenced by the integration of past rewards and experiences into the decision-making process.