Neurocognitive Psychometrics of Individual Differences in
Working Memory Processes

​Kolloqium WS 23/24

Jan Göttmann

Project

Neurocognitive Psychometrics of interindividual differences in working memory

  • Development of tasks which enable the estimation of the Memory Measurement Model (M3; Oberauer & Lewandowsky, 2019) and are suitable for EEG measurements
     
  • Mutual validation of model parameters of the M3 model and neurocognitive correlates of working memory processes

Experiments:

Memory Measurement Model
Implementation Ressource

(MEMOIR)

MEMOIR

Memoir Toolbox

  • Flexible toolbox of experiments tailored for the Memory Measurement Model (M3)
     
  • Features Verbal, Visual and Numerical domain
     
  • Customizable for different research enviroments (behavioral and electrophysiological)
     
  • Customizable for different samples (e.g. general population vs. student sample)
     
  • Extensive Tuning on several student samples 

MEMOIR

Memoir Toolbox

  • Random vs. Sequential recall possible
     
  • 25 % filler trials with varying Set Size to discourage participants to predict the number of remaining Items
     
  • Different Cue Types possible (pre- & post-cue)
     
  • Different Set Sizes possible (3 to 6)
     
  • Planned: Different Recall Types (Continoues Reproduction of colors)

Experiment: Verbal Cued Complex Span Task

?

Target Item

Distractor Item

Secondary Task: Jugde color hue (more blueish or redish?)

200 ms

1200 ms

650 ms

200 ms

Fixation + for 1000 ms before each Cue onset

Experiment: Verbal Cued Complex Span Tasks

Haus

Socke

Schlüssel

Nuss

Maus

Brettspiel

Auto

Flasche

Stuhl

Elefant

Nudel

Bonbon

Münze

Tasse

2. 

The Memory Measurement Model (M3)

Memory Measurement Model (M3)

Measurement models for simple, complex, and updating working memory tasks.

Main Idea:

The probability of choosing the correct item from a set of retrieval candidates mainly depends on the strength of binding between the item and its context, such as its serial position.

Colour

Position

1

2

3

4

A(correct) = b + a + c \\ A(otheritem) = b + a \\ A(distractor.in.position) = b + f \cdot (a + c) \\ A(distractor.in.other.position) = b + f \cdot a \\ A(not.presented.lure) = b.\\

Memory Measurement Model

Different M3 parameters contribute to this activation, which drives retrieval
 

  • The ability to form bindings of memory items to context information (c)
     
  • The ability to filter task irrelevant information like distractors (f)
     
  • The general feature activation of a memory item (a)

Experiment: Verbal Cued Complex Span Tasks

Current Study

  • Synchronized alpha-activity after cue-onset is related to the filter parameter f of the M3 model
     
  • Binding parameter c (or filter f) could be related to CRN (preparation of cognitive Ressources) or P300, or other ERP-components related to attention allocation and preparatory processes

Experiment: Verbal Cued Complex Span Tasks

Current Study

  • n = 36 (planned 60 subjects for visual and verbal domain)
     
  • 80 Trials (360 retrievals) for each Task (25 % Filler Trials)
     
  • Set Size 6 for Verbal Task, Set Size 4 for Visual Task
     
  • 2 x Sessions for Verbal and Visual Cued Complex Span Task with EEG - Recording
     
  • HMT (longform), Operation Span, and Posner Task
    as secondary measures

Experiment: Verbal Cued Complex Span Tasks

EEG Recording

  • 32 Electrodes 10 / 20 System
     
  • 1000 Hz Sampling Rate

EEG PreProcessing

  • automatic cleaning procedure
  • high-pass filter at 1 Hz; 30 Hz low-pass filter
  • noisy channel removal
  • (line noise removal)
  • re-reference to average reference
  • artefactual IC removal
  • interpolation of channels
  • epoching around cue onset (-200 – 2300 ms)
  • excluding trials (incorrect secondary repsonses, filler trials, EEG artifacts

Experiment: Verbal Cued Complex Span Tasks

Behavioral Results

  • \(\mu_{ACC-Verbal} = .73\)

  • \(\mu_{ACC-Visual} = .59\)

  • Strong relationship between HMT Score and percentage correct of r = .66

  • Strong Correlation of binding parameter c with HMT Score of r = .64

  • Strong Correlation of filter parameter f with HMT Score of r = -.56

Experiment: Verbal Cued Complex Span Tasks

ERP Results

  • Exploartive first analysis of ERP with different baselines:
    • Trial Baseline: 500 - 800 ms for first after initial fixation cross
    • Cue baseline: 200 ms before cue onset
    • 30 Hz low pass filter 
    • grand avarage ERPs 
    • (1 Hz high pass)

Experiments: Cued Complex Span Tasks

Cue Baseline

Trial Baseline

Grand Avarage über P3, Pz & P4

Experiments: Cued Complex Span Tasks

Grand Avarage over P3, Pz, P4

315 - 410 ms

1360 - 1660 ms

1670 - 2100 ms

d = - 1.24,

p  < .001

d = - .33

p  < .001

d = - .56

p  < .001

Experiments: Cued Complex Span Tasks

Grand Avarage over Fz

d = - .51

p  < .001

508 - 765 ms

Experiments: Cued Complex Span Tasks

Parameter Correlations

CRN

  • Filter parameter f is related to frontal CRN of Memory Cue Condition Activation,
    r = .38 p < .05 and to Distractor Cue Condition Activation r = .42 p < .05 !
     
  • No significant correlations of f with the effect (between conditions)
     
  • Binding strenght c is is related to frontal
    CRN of     Memory Cue Condition Activation,
    r =  - .30 p = .08 and to Distractor Cue Condition Activation r = - .30 p = .07 !

Experiments: Cued Complex Span Tasks

Parameter Correlations

CRN

  • Filter parameter f is related to frontal CRN of Memory Cue Condition Activation,
    r = .38 p < .05 and to Distractor Cue Condition Activation r = .42 p < .05 !
     
  • No significant correlations of f with the effect (between conditions)
     
  • Binding strenght c is is related to frontal CRN of Memory Cue Condition Activation,
    r =  - .30 p = .08 and to Distractor Cue Condition Activation r = - .30 p = .07 !

Experiments: Cued Complex Span Tasks

Parameter Correlations

P300 (early)

  • General activiation parameter a is related to P300 time window effect,
    r = .31, p = .06 
     
  • No significant correlations of c and f for this time window

Experiments: Cued Complex Span Tasks

Parameter Correlations

P300 (Late)

  • Binding strength parameter is realted to Memory Cue Condition Activation, r = - .28, p = .10
    and to Distractor Cue Condition Activation r = - .33  p < .05 !
     
  • No significant correlations for other parameters

Experiments: Cued Complex Span Tasks

Parameter Correlations

Late negativity

  • Filter parameter f is realted to Memory Cue Condition Activation,
    r = - .48, p < .05
    and to Distractor Cue Condition Activation r = - .41  p < .05 !
     
  • No significant correlations for other parameters

Fragen

Discussion

  • Welche Baseline wäre bei relativ langen Trials (12 Stimuli) für Zeitfrequenz-Analysen sinnvoll
     
  • Welche EKP-Komponenten wären interessant im Hinblick auf Cueing-Effekte
     
  • Unterschiede im EKP / Zeitfrequenzverlauf für veerschiedene Fehlerkategorien (Distraktorfehler, Transpositionerrors)

Thank you for Your Attention!

github.com/jgman86

jan.goettmann@uni-mainz.de

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