x(t) |
State of the decision variable at time
t. |
Δt
|
Time step of the decision variable. |
z,
sz
|
Starting state of the decision variable (i.e.,
x(0) = z), and
decision-to-decision variability in starting state.
sz is the range of a uniform
distribution with mean (midpoint) z. |
vi,
sv
|
Rate at which the decision variable
accumulates decision-relevant information (drift rate,
v) in condition i, and
decision-to-decision variability in drift rate.
sv is the standard deviation of a normal
distribution with mean vi. |
γ(t) |
Urgency signal that dynamically modulates the
decision variable as a function of t. Can take
different functional forms in different models. |
aupper,
alower
|
Upper and lower response boundaries that
terminate the decision process. |
aupper(t),
alower(t) |
Upper and lower response boundaries that vary
as a function of t. |
Ter,
st
|
Time required for stimulus encoding and motor
preparation/execution (non-decision time), and decision-to-decision
variability in non-decision time. st is the
range of a uniform distribution with mean (midpoint)
Ter. |
s
|
Within-decision variability in the diffusion
process. Represents the standard deviation of a normal distribution. By
convention, set to a fixed value to satisfy a scaling property of the
model. |
E(t) |
Momentary sensory evidence at time
t. |
b,
sb
|
Intercept and variability of the intercept in
urgency based models with linear urgency signals. |
|
Normal distribution with zero mean and unit
variance. |
|
Uniform distribution over the interval
l1 and
l2. |