Cognitive Modelling ARTICLES

Question 1

What does the diffusion model aim to explain?

Answer 1

Two-choice decision-making by modeling evidence accumulation.

Question 2

What are the two main criteria in the diffusion model?

Answer 2

Evidence thresholds for decision alternatives.

Question 3

What determines the time to make a decision in the diffusion model?

Answer 3

The time to accumulate enough evidence to cross a threshold.

Question 4

What is ‘drift rate’ in the diffusion model?

Answer 4

The rate at which evidence accumulates toward a decision.

Question 5

How does stimulus difficulty affect drift rate?

Answer 5

More difficult stimuli lead to lower drift rates.

Question 6

What does between-trial variability in the model account for?

Answer 6

Differences in starting points and drift rates across trials.

Question 7

What does the term ‘non-decision time’ refer to?

Answer 7

Time spent on processes other than decision-making, such as encoding and response.

Question 8

How does the model explain the speed-accuracy tradeoff?

Answer 8

By adjusting the distance between decision thresholds.

Question 9

What is the significance of response time distributions in the model?

Answer 9

They provide a detailed fit to empirical data on decision speed and accuracy.

Question 10

How do the model’s parameters vary with stimulus discriminability?

Answer 10

Higher discriminability increases drift rate and reduces decision time.

Question 11

What role does noise play in the diffusion process?

Answer 11

It introduces variability in evidence accumulation.

Question 12

What is the function of setting different thresholds in the model?

Answer 12

To prioritize speed or accuracy depending on task demands.

Question 13

What experimental data supports the diffusion model?

Answer 13

Distributions of reaction times and error rates under varying conditions.

Question 14

How does starting point variability influence decision outcomes?

Answer 14

It biases decisions toward one threshold over the other.

Question 15

What is a key advantage of the diffusion model over simpler decision models?

Answer 15

Its ability to predict both choice accuracy and detailed response time patterns.

Question 16

What historical models influenced the development of the diffusion model?

Answer 16

Sequential sampling and random walk models.

Question 17

How are ‘fast errors’ explained by the model?

Answer 17

They occur when the starting point is closer to the incorrect threshold.

Question 18

What is a ‘first passage time’ in the context of the model?

Answer 18

The time at which the evidence first reaches a decision boundary.

Question 19

Why is the diffusion model particularly useful in cognitive neuroscience?

Answer 19

It links decision-making processes to neural mechanisms like firing rates.

Question 20

What types of tasks are best suited for diffusion model analysis?

Answer 20

Speeded, two-choice decision-making tasks.

Question 21

What is reinforcement learning?

Answer 21

A trial-and-error method to learn decision-making strategies that maximize rewards.

Question 22

What are prediction errors in reinforcement learning?

Answer 22

Differences between expected and received rewards.

Question 23

What role do dopamine neurons play in reinforcement learning?

Answer 23

They signal prediction errors.

Question 24

What is the Rescorla-Wagner model?

Answer 24

A mathematical model of learning based on prediction error updates.

Question 25

What is temporal difference learning?

Answer 25

An extension of reinforcement learning that predicts long-term rewards.

Question 26

How do dopamine neurons respond to unexpected rewards?

Answer 26

With phasic increases in firing rate.

Question 27

What is the significance of blocking in learning theory?

Answer 27

It shows that previously learned associations can prevent new learning.

Question 28

How do dopamine neurons react to predicted rewards?

Answer 28

They show no phasic activity.

Question 29

What is the role of the striatum in reinforcement learning?

Answer 29

It integrates reward signals from dopamine neurons.

Question 30

What is the main idea behind the Bellman Equation?

Answer 30

It represents value as the sum of immediate reward and future rewards.

Question 31

What is a major application of reinforcement learning in neuroscience?

Answer 31

Understanding decision-making and reward processing.

Question 32

How does the prediction error change with increased learning?

Answer 32

It decreases as predictions become more accurate.

Question 33

What is the learning rate in the Rescorla-Wagner model?

Answer 33

A parameter controlling the size of prediction updates.

Question 34

How do drugs of abuse affect the dopamine system?

Answer 34

They enhance dopamine activity, reinforcing addictive behaviors.

Question 35

What is second-order conditioning?

Answer 35

Learning associations between stimuli that predict other reward-predictive cues.

Question 36

How does variability in dopamine neuron responses reflect learning?

Answer 36

It tracks changes in prediction errors over time.

Question 37

What is the impact of stochastic rewards on learning?

Answer 37

They create variability in prediction error signals and slower learning curves.

Question 38

What does a negative prediction error indicate?

Answer 38

That a reward was less than expected or omitted.

Question 39

How are reinforcement learning theories tested experimentally?

Answer 39

Using tasks that vary reward probability and timing.

Question 40

What is the relationship between motivation and dopamine?

Answer 40

Dopamine signals influence motivation to perform rewarded actions.

Question 41

IN-CLASS MINI-QUIZ QUESTION 1: The linear ballistic accumulator (LBA) and the diffusion decision model (DDM) belong to the same class of decision-making models. Describe a key feature or assumption shared by these 2 models.

Question 42

IN-CLASS MINI-QUIZ QUESTION 2: Describe a benefit of combining behavioral and neural data with cognitive modelling, as is done in model-based cognitive neuroscience.