SPM Course slides

1
Experimental Design
Christian Ruff With thanks to Rik
Henson Daniel Glaser
2
Statistical parametric map (SPM)
Design matrix
Image time-series
Kernel
Realignment
Smoothing
General linear model
Gaussian field theory
Statistical inference
Normalisation
p lt0.05
Template
Parameter estimates
3
Overview

• Categorical designs
• Subtraction - Pure insertion, evoked /
  differential responses
• Conjunction - Testing multiple hypotheses
• Parametric designs
• Linear - Adaptation, cognitive dimensions
• Nonlinear - Polynomial expansions, neurometric
  functions
• Factorial designs
• Categorical - Interactions and pure insertion
• Parametric - Linear and nonlinear interactions
• - Psychophysiological Interactions

4
Cognitive Subtraction

• Aim
• Brain structures underlying process P?
• Procedure
• Contrast Task with P control task without
  P P
• the critical assumption of pure insertion

5
Cognitive Subtraction Baseline-problems

• Distant stimuli

- ? Several components differ !

6
Differential event-related fMRI
Evoked responses Rest baseline
Inferotemporal response to faces
SPMF testing for evoked responses

• Baseline here corresponds to session mean
  (and thus processing during rest)
• Null events or long SOAs essential for
  estimation
• Cognitive interpretation hardly possible,
  but useful to define regions generally involved
  in the task

7
A categorical analysis
Experimental design Word generation G Word
repetition R R G R G R G R G R G R G
G - R Intrinsic word generation under
assumption of pure insertion
8
Overview

• Categorical designs
• Subtraction - Pure insertion, evoked /
  differential responses
• Conjunction - Testing multiple hypotheses
• Parametric designs
• Linear - Adaptation, cognitive dimensions
• Nonlinear - Polynomial expansions, neurometric
  functions
• Factorial designs
• Categorical - Interactions and pure insertion
• Parametric - Linear and nonlinear interactions
• - Psychophysiological Interactions

9
Conjunctions

• One way to minimise the baseline/pure insertion
  problem is to isolate the same process by two or
  more separate comparisons, and inspect the
  resulting simple effects for commonalities
• A test for such activation common to several
  independent contrasts is called Conjunction
• Conjunctions can be conducted across a whole
  variety of different contexts
• tasks
• stimuli
• senses (vision, audition)
• etc.
• But the contrasts entering a conjunction have to
  be truly independent!

10
Conjunctions
Example Which neural structures support object
recognition, independent of task (naming vs
viewing)?
Visual Processing V Object Recognition
R Phonological Retrieval P (Object - Colour
viewing) (Object - Colour naming) ? 1 -1 0
0 0 0 1 -1 ? R,V - V P,R,V -
P,V R R R (assuming no
interaction RxP see later)
11
Conjunctions
12
Two flavours of inference about conjunctions

• SPM8 offers two general ways to test the
  significance of conjunctions
• Test of global null hypothesis Significant set
  of consistent effects
• ? which voxels show effects of similar
  direction (but not necessarily individual
  significance) across contrasts?
• Test of conjunction null hypothesis Set of
  consistently significant effects
• ? which voxels show, for each specified
  contrast, effects gt threshold?
• Choice of test depends on hypothesis and
  congruence of contrasts the global null test is
  more sensitive (i.e., when direction of effects
  hypothesised)

Friston et al. (2005). Neuroimage,
25661-7. Nichols et al. (2005). Neuroimage,
25653-60.
13
Overview

• Categorical designs
• Subtraction - Pure insertion, evoked /
  differential responses
• Conjunction - Testing multiple hypotheses
• Parametric designs
• Linear - Adaptation, cognitive dimensions
• Nonlinear - Polynomial expansions, neurometric
  functions
• Factorial designs
• Categorical - Interactions and pure insertion
• Parametric - Linear and nonlinear interactions
• - Psychophysiological Interactions

14
Parametric Designs General Approach

• Parametric designs approach the baseline problem
  by
• Varying a stimulus-parameter of interest on a
  continuum, in multiple (ngt2) steps...
• ... and relating blood-flow to this parameter
• Flexible choice of tests for such relations
• Linear
• Nonlinear Quadratic/cubic/etc.
• Data-driven (e.g., neurometric functions)
• Model-based

15
A linear parametric contrast
Adaptation Linear effects of time?
16
A nonlinear parametric contrast
Adaptation Nonlinear effects of time?
17
Nonlinear parametric design matrix
Polynomial expansion f(x) b1 x b2 x2
... up to (N-1)th order for N levels
Mean response
Linear change
Quadratic change
(SPM8 GUI offers polynomial expansion as option
during creation of parametric modulation
regressors)
E.g, F-contrast 0 1 0 on Quadratic Parameter gt
Inverted U response to increasing word
presentation rate in the DLPFC
18
Parametric Designs Neurometric functions
versus
Rees, G., et al. (1997). Neuroimage, 6 27-78
Inverted U response to increasing word
presentation rate in the DLPFC
Rees, G., et al. (1997). Neuroimage, 6 27-78
19
Parametric Designs Neurometric functions

• Coding of tactile stimuli in Anterior Cingulate
  Cortex
• Stimulus (a) presence, (b) intensity, and (c)
  pain intensity
• Variation of intensity of a heat stimulus applied
  to the right hand
• (300, 400, 500, and 600 mJ)

Büchel et al. (2002). The Journal of
Neuroscience, 22 970-6
20
Parametric Designs Neurometric functions
Büchel et al. (2002). The Journal of
Neuroscience, 22 970-6
21
Parametric Designs Model-based regressors
Seymour, ODoherty, et al. (2004). Nature.
22
Overview

• Categorical designs
• Subtraction - Pure insertion, evoked /
  differential responses
• Conjunction - Testing multiple hypotheses
• Parametric designs
• Linear - Adaptation, cognitive dimensions
• Nonlinear - Polynomial expansions, neurometric
  functions
• Factorial designs
• Categorical - Interactions and pure insertion
• Parametric - Linear and nonlinear interactions
• - Psychophysiological Interactions

23
Factorial designs Main effects and Interactions

• Main effect of task (A1 B1) (A2 B2)
• Main effect of stimuli (A1 A2) (B1 B2)
• Interaction of task and stimuli Can show a
  failure of pure insertion
• (A1 B1) (A2 B2)

interaction effect (Task x Stimuli)
Colours Objects
Colours Objects
Viewing
Naming
24
Interactions and pure insertion
Components Visual processing V Object
recognition R Phonological retrieval P Interactio
n RxP Interaction (name object - colour) -
(view object - colour) ? 1 -1 0 0 - 0 0 1
-1 P,R,V RxP - P,V - R,V - V
RxP

Object-naming-specific activations
adjusted rCBF
Context no naming naming
25
Interactions and pure insertion
Interactions simple and cross-over We
can selectively inspect our data for one or the
other by masking during inference
A1 A2 B1 B2
A1 A2 B1 B2
26
Overview

• Categorical designs
• Subtraction - Pure insertion, evoked /
  differential responses
• Conjunction - Testing multiple hypotheses
• Parametric designs
• Linear - Adaptation, cognitive dimensions
• Nonlinear - Polynomial expansions, neurometric
  functions
• Factorial designs
• Categorical - Interactions and pure insertion
• Parametric - Linear and nonlinear interactions
• - Psychophysiological Interactions

27
Linear Parametric Interaction
A linear Time-by-Condition Interaction (differen
ce in adaptation for repeating vs generating)
Contrast 5 3 1 -1 -3 -5 ? -1 1 -5 5 -3 3
-1 1 1 -1 3 -3 5 -5
28
Nonlinear Parametric Interaction

• Factorial Design with 2 factors
• Gen/Rep (Categorical, 2 levels)
• Time (Parametric, 6 levels)
• Time effects modelled with both linear and
  quadratic components

29
Overview

• Categorical designs
• Subtraction - Pure insertion, evoked /
  differential responses
• Conjunction - Testing multiple hypotheses
• Parametric designs
• Linear - Adaptation, cognitive dimensions
• Nonlinear - Polynomial expansions, neurometric
  functions
• Factorial designs
• Categorical - Interactions and pure insertion
• Parametric - Linear and nonlinear interactions
• - Psychophysiological Interactions

30
Psycho-physiological Interaction (PPI)
Parametric, factorial design, in which one factor
is a psychological context ...and the other is
a physiological source (activity extracted from
a brain region of interest)
31
Psycho-physiological Interaction (PPI)
Parametric, factorial design, in which one factor
is a psychological context ...and the other is
a physiological source (activity extracted from
a brain region of interest)
32
Psycho-physiological Interaction (PPI)
0 0 1
Attentional modulation of V1 - V5 contribution
33
Psycho-physiological Interaction (PPI)
V1 activity
time
attention
V5 activity
no attention
Attentional modulation of V1 - V5 contribution
V1 activity
34
Psycho-physiological Interaction (PPI)
0 0 1
Stimuli Faces or objects
PPC
IT
35
Psycho-physiological Interaction (PPI)
SPMZ
Stimuli Faces or objects
Faces
PPC
IT
adjusted rCBF
Objects
medial parietal activity
36
Psycho-physiological Interaction (PPI)

• PPIs tested by a GLM with form
• y (V1?A).b1 V1.b2 A.b3 e c 1 0 0
• However, the interaction term of interest, V1?A,
  is the product of V1 activity and Attention block
  AFTER convolution with HRF
• We are really interested in interaction at neural
  level, but
• (HRF ? V1) ? (HRF ? A) ? HRF ? (V1 ? A)
• (unless A low frequency, e.g., blocked mainly
  problem for event-related PPIs)
• SPM8 can effect a deconvolution of physiological
  regressors (V1), before calculating interaction
  term and reconvolving with the HRF the PPI
  button

37
Overview

• Categorical designs
• Subtraction - Pure insertion, evoked /
  differential responses
• Conjunction - Testing multiple hypotheses
• Parametric designs
• Linear - Adaptation, cognitive dimensions
• Nonlinear - Polynomial expansions, neurometric
  functions
• Factorial designs
• Categorical - Interactions and pure insertion
• Parametric - Linear and nonlinear interactions
• - Psychophysiological Interactions