Question

What is the process of DDM (drift diffusion model)?

1) Observe magnitude in time period #1 and compare it to a threshold
2) Compare magnitude to a criterion based on firing rate
3) Stop and commit to a decision if magnitude is larger than threshold
4) Compare magnitude in time period #2 to criterion, compare magnitude to previous measure, and return to step #2

Answer 1

The Drift Diffusion Model (DDM) is a computational model that describes the cognitive process of decision-making involving the observation of a decision variable over time, which is compared against a threshold to commit to a choice. This model is connected to broader decision-making processes in ecological contexts as described by the Stochastic Dynamic Methodology, and illustrates how a negative feedback loop functions like a driver approaching a wall and slowing down to avoid a crash.

Step-by-step explanation:

The process of the Drift Diffusion Model (DDM) is a computational model used to study decision-making, specifically how decisions are made under uncertain conditions. This cognitive process involves multiple steps where a decision variable, or 'magnitude', is observed over time and compared against a certain threshold to make a commitment to a choice. Initially, an individual observes the magnitude in a given time period and compares it to a pre-established threshold. If at any point the magnitude exceeds this threshold, the process stops, and a decision is made.

The steps can be detailed as follows:

1. Observe the magnitude in time period #1 and compare it to a threshold.
2. Compare magnitude to a criterion based on firing rate.
3. Stop and commit to a decision if the magnitude is larger than the threshold.
4. Compare magnitude in time period #2 to the criterion, then compare the magnitude to the previous measure and return to step #2 if necessary.

The Drift Diffusion Model provides insight into the mental processes that lead to decision-making in a variety of contexts, including ecological decision-making as suggested by the stochastic dynamic methodology (StDM). The car and brick wall analogy illustrates how negative feedback loops are integral in slowing down a process to prevent unwanted consequences, such as population overshoot. A similar approach is used in the DDM to guide decision-making processes by contrasting observed magnitudes against defined thresholds.