Psychophysical scaling

Question 1

Psychophysical scaling

Answer 1

refers to the process of quantifying mental
events. Distances in stimulus space are mapped onto distances in
psychological space.

Question 2

Psychophysical functions

Answer 2

refer to mathematical relations between

physical and psychological scales

Question 3

Psychophysical scaling

Answer 3

Weber’s law suggests that physical scales are not appropriate for
psychological experience

Fechner’s law: S = k log(I)

Psychophysical scale based on size estimations
(numbers/sizes attributed to experience)

Stevens’s law: S = k I^b

Question 4

Scaling in general

Answer 4

Evolved from attempts to measure ‘non-observable’, abstract concepts

In many cases there is no physical variable, so these are ‘psychological’ instead of ‘psychophysical’ scales.

Question 5

Why do we do scaling

Answer 5

hypothesis testing
explorative
scoring

Question 6

Different types of scales related to different levels of measurement

Answer 6

Nominal: Label switching
Ordinal: Rank ordering matters
Interval: Difference matters
Ratio: Ratio matters and zero point
Usually scaling aims to arrive at interval or ratio scales
Empirical procedures do not gaurantee arrival at a certain scale that was intended

Question 7

Scaling by discrimination methods

Answer 7

Rationale: “differences between sensations can be detected, but
their absolute magnitudes are less well apprehended” (Luce &
Krumhansl, 1988, p. 39).

Inferring sensation magnitudes from “proportion greater than“
judgments.

Question 8

Methods to come to psychological scales

Answer 8

Confusion scaleing: Pairwise comparisson
Partition scaling: 
-Category
-Equisection
Magnitude scaling ( search for ratio scale) compairing series of light flashes to a reference flash

Question 9

Fechnerian discrimination scales

Answer 9

Discriminatory ability increases as difference between psychological
magnitude increases.

Fechner himself relied on the JND to construct scales of sensation
magnitude (JNDs define pairs of stimuli that are equally discriminable)

Combination of assuming that one JND equals a unit increase in
sensation magnitude and Weber’s law gives the logarithmic law

Weber’s law does not hold across the entire physical scale, thus
Fechner’s assumptions are not completely valid.

JNDs can be used, by calculating them as a function of stimulus
intensity (rather than relying on Weber’s law)

Question 10

Are JNDs equal changes in sensation magnitude

Answer 10

Hellman 1987 not the case in hearing

Durup and Pieron 1933 not subjectively equal in visual modality.

consequence: JND can not be used as a basic unit for sensation magnitude

Question 11

Ekman propsed modification

Answer 11

Subjective size of the JND is not constant, but increases with sensation magnitude (weber’s kaw but in psychological space)
Δψ = bψ

Question 12

Thurstonian scaling

Answer 12

Law of comparative judgment: Theoretical model describing internal
processes that enable the observer to make paired comparison
judgments

Based on a series of pairwise judgments, it is possible to calculate
psychological scale values.

Thurstone assumes that stimulus presentation results in a discriminal
process that has a value on a psychological continuum.

The variability in this process, e.g. due to neural noise, is called discriminal dispersion

The psychological scale value is the mean of the distribution of discriminal processes.

Only indirect measurements can uncover this, by considering the proportions of comparative judgments between stimuli.

Discrimination of two stimuli results in a discriminal difference. The standard deviation of discriminal differences is given by Si-j

On each presentation of the stimulus pair, the observer chooses the
strongest one

Check ppt voor formules

Question 13

Thurstonian scaling: When assumption holds

Answer 13

The paird comparison method is consistent iwth fechner’s law if weber’s law holds

Thurstone’s model requires transitivity: If A > B and B > C, A > C must follow.

Sometimes transitivity fails because psychological experiences vary in
more than one dimension: Multidimensional scaling

Thurstonian scaling is applicable to dimensions that are not easily quantified

Question 14

Scaling with multiple dimensions

Answer 14

What are the underlying dimensions

how many dimensions

Technique to analyze multivariate data: Principal Component
Analysis (PCA)

Question 15

Principal Component

Analysis (PCA)

Answer 15

• Description of multivariate data in terms of a smaller set of uncorrelated (=non-redundant) variables (components or ‘eigenvectors’)
• Variables extracted in order of decreasing importance (percentage of
  explained variance)
  (=> with ICA variables are extracted that explain a unique portion of data)

Question 16

Multidimensional scaling (MDS)

Answer 16

Starting point is no longer the multivariate data matrix, but the similarity/difference among stimuli

Similarity can be given for each stimulus pair (e.g. correlations), or it can be computed from the multivariate data.

Purpose: Representation of the stimuli in a low dimensional space so that the proximity between stimuli approximates their similarity

Metric MDS assumes a particular distance metric (e.g. Euclidian,
city-block) : check ppt for formula

City-block distance frequently applies for dimensions that can be
intuitively added, Euclidian distance for so-called “integral” dimensions

Nonmetric MDS assumes that only the rank order of distances need to be modelled.

Number of dimensions is usually unknown. “Stress” is a measure to quantify the difference between the data and the predicted data obtained by the MDS solution

Often used as a useful data reduction technique.

Visualisations easy to grasp.

Question 17

Application of MDS in neuroscience

Answer 17

Use similarity analyses (often with MDS) to compare datasets from different measurements

Behavioral responses

Responses of single neurons in a nonhuman brain

fMRI responses in a human brain

Quantitative analyses of the stimuli

Computational models