LEVELS OF PROCESSING IN FACIAL MEMORY

Sarah Babcock, Rose Ann Calvieri, Lauren Cudney, Vedran Dzebic ,Silvia Eleftheriou, and Jeff

Mazurkewich,

TOPIC DEVELOPMENT Progression of ideas for possible studies:

Initial thought: Combine spatial memory with decision making task

Replaced spatial memory with word memory

Word memory is well studied, we wanted to approach memory from a different angle

Memory involving different levels of processing regarding objects

Decided to examine faces instead of objects

RATIONALE FOR THE STUDY

We encounter faces constantly, making facial memory a crucial skill for social interactions

Examining techniques of facial memory can potentially improve ease of everyday social interactions

LITERATURE: CRAIK & TULVING (1975)

Experiment Processing words at different levels

Subjects presented with words & asked questions to various levels Shallow = same font Medium = counting letters in word Deep = synonyms

Results Better memory recall for words processed at a

deeper level

LITERATURE: BRUCE & VALENTINE (1985)

Experiment Priming task: Subjects were shown the name or

photo of a celebrity Recognition task: Subjects were then shown a

series of photos of celebrities and asked to name them

The subject had seen either the name, same photo or a different photo of the same celebrity in the priming task

Results Better memory for faces which subject’s had seen

pictures of in the priming task (same or different)

Experiment Source memory for faces (internal or external) Questions were asked about faces in a

presentation of facial images The subject either generated the answer or the

answer was provided for them (accompanied the face)

Results Subjects were better at source memory for faces

which asked them to generate answers (internal), than for faces accompanied by the answers (external)

LITERATURE: GEGHMAN & MULTHAUP (2004)

PURPOSE OF THE EXPERIMENT

Purpose: To determine whether different questions can

elicit deeper levels of processing

To establish if deeper levels increase subsequent memory on a facial recognition task

LEVELS OF PROCESSING

Questions: 1) What is this person’s most attractive feature? 2) What job do you think this person has? 3) How old is this person? 4) What is this person’s gender?

Examine whether any of these questions will result in deeper level of processing, measured by accuracy of facial recognition

HYPOTHESIS

If different levels of facial processing can be achieved, deeper level processing will lead to better recognition of faces

Hypothesized to elicit shallower processing: Questions about gender and age

Hypothesized deeper processing: Questions about attractiveness and occupation

Kirkland, Reynolds and Pezdek (1992)

METHODS

Subjects

30 subjects 24 in experimental group 6 in control group All Mac undergrads Age range 18-24, Mean 20

METHODS

Stimulus/Materials

Study Task 32 faces

Experimental group Each Face paired with one question

Control group No questions presented

METHODS

Stimulus/Materials

Recognition Task 60 faces (28 novel)

Have you seen this face in the previous presentation? Yes/No responses

All subjects given same task

METHODS

Cover Story

Study Task – Subjects were told: There will be questions about the faces They need to answer as quickly as possible the questions We are looking at how much you can tell about a person

by their appearance

Recognition Task: Subjects were naïve of recognition task to follow the

study task

LEVELS OF PROCESSING

Questions: 1) What is this person’s most attractive feature? 2) What job do you think this person has? 3) How old is this person? 4) What is this person’s gender?

Examine whether any of these questions will result in deeper level of processing,

measured by accuracy of facial recognition

SLIDESHOW EXAMPLE: STUDY TASK

ATTRACTIVENESS?

AGE?

GENDER?

JOB?

SLIDESHOW EXAMPLE: RECOGNITION TASK

DATA COLLECTION

Study Task Recorded subject’s responses to questions

Recognition Task Recorded if the subject answered yes or no

STUDY TASK DATA SHEET

Subject #

Question Orders

Picture # Group NumberS’s response

1 2 3 4

1 a d b c  

2 b c a d  

3 c b d a  

4 d a c b  

5 a d b c  

6 b c a d  

RECOGNITION TASK DATA SHEET

Subject #

Recognition Task Ss Response Sheet

Recognition task slide #'s

Picture Number 1 2 3 4 S’s response

S’s Correct Responses

2 54 0 0 0 0    

4 21 a d b c    

6 27 c b d a    

8 45 0 0 0 0    

10 43 0 0 0 0    

12 14 b c a d    

14 41 0 0 0 0    

16 28 d a c b    

18 24 d a c b    

RESULTS

Group Results (Experimental & Control)

Independent t-test

Descriptives

One-way ANOVA

Post-hoc (Bonferroni)

GROUP STATISTICS

Group Statistics

Group N Mean Std. Deviation Std. Error Mean

Sstotal 124 49.4167 5.19964 1.06137

26 40.6667 6.37704 2.60342

INDEPENDENT T-TEST

Independent Samples Test

Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t dfSig.

(2-tailed)Mean

DifferenceStd. Error Difference

95% Confidence Interval of the

Difference

Lower Upper

Sstotal

Equal variances assumed

.033 .858 3.531 28 .001 8.75000 2.47783 3.67440 13.82560

Equal variances not assumed

3.112 6.760 .018 8.75000 2.81146 2.05373 15.44627

DESCRIPTIVES

Descriptives

Data

N Mean Std. Deviation Std. Error

95% Confidence Interval for Mean

Minimum MaximumLower

BoundUpper

Bound

124 6.7917 1.02062 .20833 6.3607 7.2226 5.00 8.00

224 6.0833 1.44212 .29437 5.4744 6.6923 3.00 8.00

324 5.2500 1.89393 .38660 4.4503 6.0497 1.00 8.00

424 5.7500 1.32698 .27087 5.1897 6.3103 3.00 8.00

Total96 5.9688 1.53865 .15704 5.6570 6.2805 1.00 8.00

ONE WAY ANOVA

ANOVA

Data

Sum of Squares df

Mean Square F Sig.

Between Groups

30.115 3 10.038 4.741 .004

Within Groups194.792 92 2.117

Total224.906 95

POST HOCMultiple Comparisons

DataBonferroni

(I) Questions

(J) Questions

Mean Difference (I-J) Std. Error Sig.

95% Confidence Interval

Lower Bound Upper Bound

1 2 .70833 .42005 .571 -.4243 1.8410

3 1.54167* .42005 .002 .4090 2.6743

4 1.04167 .42005 .090 -.0910 2.1743

2 1 -.70833 .42005 .571 -1.8410 .4243

3 .83333 .42005 .301 -.2993 1.9660

4 .33333 .42005 1.000 -.7993 1.4660

3 1 -1.54167* .42005 .002 -2.6743 -.4090

2 -.83333 .42005 .301 -1.9660 .2993

4 -.50000 .42005 1.000 -1.6327 .6327

4 1 -1.04167 .42005 .090 -2.1743 .0910

2 -.33333 .42005 1.000 -1.4660 .7993

3 .50000 .42005 1.000 -.6327 1.6327

*. The mean difference is significant at the 0.05 level.

LIMITATIONS OF CURRENT STUDY

1) Response time:

5 second time limit Subjects provided arbitrary responses May have focused more on the question than

actual face Further studies: allow slightly more time for

subjects’ responses

LIMITATIONS OF CURRENT STUDY

2) Occupation Question:

Was predicted to elicit deeper processing Answer didn’t require face processing Future studies: questions relying more on facial

features (I.e ethnicity, cosmetic surgery)

LIMITATIONS OF CURRENT STUDY

3) Facial Images:

Atypical facial images compared to participants and people within the participants’ environment

Non significant results maybe due to quality of faces

Faces presented in grey-scale : require deeper processing

Future studies: Use of coloured images is more realistic

Use more updated faces similar to those within participants’ social environment

LIMITATIONS OF CURRENT STUDY

4) Number of Images:

Study task: 32 faces Recognition task: 60 faces Future studies: More faces in study and recognition

tasks Increase power

LIMITATIONS OF CURRENT STUDY

5) Control Group:

Smaller than experimental group Future studies:

Larger number of subjects in control group size = increase power

Within-subjects control group: Have some pictures without any questions in

the slideshow

IMPLICATIONS

If significant:

Faces and words are processed similarly Improve peoples ability to remember new

acquaintances Eyewitness testimony

CONNECTIONS TO PREVIOUS RESEARCH

Verbalization and conceptualization of faces lead to better facial recognition Itoh, 2005; Bruce & Valentine, 1985

Improved memory when face is paired with question, and when the answers are generated Geghman & Multhaup, 2004

Levels of processing may have had an effect on facial recognition Craik, & Tulving, 1975

Word memory vs. Facial memory

Mechanisms by which words are processed may not be the same mechanisms employed in facial recognition

Similar processing may be involved

CONNECTIONS TO PREVIOUS RESEARCH

FUTURE RESEARCH

Intentional vs. Incidental Previous works show there is no difference in

memory if the learning is incidental or intentional Craik, & Tulving, 1975

Examine if intentional or incidental learning has an effect on facial recognition

FUTURE RESEARCH

Facial images Examine the recognition of faces more typically

seen in the subject’s environment

Investigating recognition of faces of varying ethnicities

Neuroimaging: fMRI Examine areas of activation between different

questions Compare word processing to facial processing