This preview shows page 1. Sign up to view the full content.
Unformatted text preview: and McClelland, 2001;
od, Howposterior probabilities. In this case, for a given weight
er. 1979).
Vickers, 1979).
df the co“natural
of evidence (e.g., is analogous to in Banburismus):
This problem the stopping point onedimensional
ponses and Turing’s Weight of Evidence
ted quanlar responses from a pair of sensory neurons when h a pairtrue, barriers (Link, 1992; Ratcliff
Brownian motion to or h is of as indicated. For
of tradePr(h1mmotion. The lower curve would
)
obabilities
es of a directionselective neuron that prefers upward The weight of evidence
articular
and Rouder, 1998).
means of the normal B
distribu(3)
log
ron” that prefers downward motion. Here wePr(h the simplifying assumption that the
make m)
surprisal”
r can be equal variances ( represent the drift rates, i (where the subscript i
tions ). Note that other0 forms of the distribution, including
f
and
and
bans but
old and Shadlen, 2001). The panelthe particular Turing’s weight of evidenceThe psychometon the
f reward
reflects B is a right shows motion strength).the barrier height
where
constant that represents
of their difference; note the linear relationship.
m of base
ric function describing the probability of correctly reachexclusive hypotheses
in favor of h1. For two mutually accumulate/integrate over
Decision Model
tiontime Figure 2. ing eitherh the is“up” r(h difference between equivalently, given) antineuron is:
or “down” barrier on a Pr(h trial
The weight (Pr(h favor of
evidence in m) over h
the accumulated m) or, responses of a neuron that prefers h and an
1depicted P computed under thetcondition) thatyh( is)true. The thin, wavy line depicts a simulated
1
0
0
ntlities has that prefers weight of7).evidence atare
motion
(
d (7)
total h (see Equation The curves
time1t k
ihich the trajectory that represents how the weight of evidence might grow on a single trial as a function of time. The dashed line depicts the expectation
0
Pr(h1)), and assuming the weight of evidence is exn motion
(mean value) of this trajectory at each time point. Note that changing the constant of proportionality used to rel...
View
Full
Document
This note was uploaded on 09/15/2011 for the course COGS 1 taught by Professor Lewis during the Spring '08 term at UCSD.
 Spring '08
 LEWIS

Click to edit the document details