1. LEVELS OF PROCESSING IN FACIAL MEMORY
Sarah Babcock, Rose Ann Calvieri, Lauren Cudney, Vedran Dzebic ,Silvia Eleftheriou, and Jeff Mazurkewich,

2. 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
HONING

3. 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

4. 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
Concept of memory, levels of processing…10 experiments response latency
Describe what levels of processing are
The main methods of the study and major findings of the studies which relate to LOP

5. 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)
Famous people, name or face

6. LITERATURE: GEGHMAN & MULTHAUP (2004)
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)

7. PURPOSE OF THE EXPERIMENT
To determine whether different questions can elicit deeper levels of processing
To establish if deeper levels increase subsequent memory on a facial recognition task

8. 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

9. 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)

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

11. Methods Stimulus/Materials Study Task 32 faces Experimental group
Each Face paired with one question
Control group
No questions presented

12. 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

13. Methods Cover Story Study Task – Subjects were told: Recognition Task:
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

14. 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

15. SLIDESHOW EXAMPLE: STUDY TASK

16. Attractiveness?

17. Age?

18. Gender?

19. Job?

20. Slideshow Example: Recognition Task

28. DATA COLLECTION Study Task Recognition Task
Recorded subject’s responses to questions
Recognition Task
Recorded if the subject answered yes or no

29. STUDY TASK DATA SHEET Subject # Question Orders Group Number Picture #
S’s response 1 2 3 4 a d b c 5 6

30. 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 54 21 a d b c 6 27 8 45 10 43 12 14 41 16 28 18 24

31. RESULTS Group Results (Experimental & Control) Independent t-test
Descriptives
One-way ANOVA
Post-hoc (Bonferroni)

32. GROUP STATISTICS Group Statistics Group N Mean Std. Deviation
Std. Error Mean
Sstotal 1 24 2 6

33. Independent Samples Test
INDEPENDENT T-TEST
Independent Samples Test
Levene's
Test for
Equality of
Variances
t-test for Equality of Means F
Sig. t df
(2-tailed)
Mean
Difference
Std. Error
95% Confidence
Interval of the
Lower
Upper Ss
total
Equal variances assumed
.033
.858
3.531 28
.001
Equal variances not assumed
3.112
6.760
.018
-The mean number of faces correctly identified in the recognition task (possible total of 60) for the control subjects (M=40.67, SD=6.38) was less than the mean number identified by the experimental group (M=49.42, SD=5.20).
-subjects who had answered questions during the study task remembered significantly more faces than the control group

35. 95% Confidence Interval for Mean
DESCRIPTIVES
Descriptives
Data N
Mean
Std. Deviation
Std. Error
95% Confidence Interval for Mean
Minimum
Maximum
Lower Bound
Upper Bound 1 24
6.7917
.20833
6.3607
7.2226
5.00
8.00 2
6.0833
.29437
5.4744
6.6923
3.00 3
5.2500
.38660
4.4503
6.0497
1.00 4
5.7500
.27087
5.1897
6.3103
Total 96
5.9688
.15704
5.6570
6.2805
-mean number of faces recognized correctly by the subjects was greatest for faces which had been paired with the question about attractiveness (M=6.7917, SD=1.0206).
-occupation (M=6.0833, SD=1.4421) was higher than the mean number of age (M=5.7500, SD=1.3270)
-remembered the least with the question about gender (M=5.25, SD=1.8939).

36. ONE WAY ANOVA ANOVA Data Sum of Squares df Mean Square F Sig.
Between Groups
30.115 3
10.038
4.741
.004
Within Groups 92
2.117
Total 95

37. POST HOC Multiple Comparisons Data Bonferroni (I) Questions (J)
Mean Difference (I-J)
Std. Error
Sig.
95% Confidence Interval
Lower Bound
Upper Bound 1 2
.70833
.42005
.571
-.4243
1.8410 3 *
.002
.4090
2.6743 4
.090
-.0910
2.1743
.4243
.83333
.301
-.2993
1.9660
.33333
1.000
-.7993
1.4660 *
-.4090
.2993
.6327
.0910
.7993
.50000
-.6327
1.6327
*. The mean difference is significant at the 0.05 level.
-Sig. diff b/w Q1(attractiveness) and Q3(gender)
-thinking about a face in terms of attractive features required the subject to process the face on a deeper level compared to the question regarding gender, consequently leading to a better memory of that face

39. 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

40. 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)

41. 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

42. 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

43. 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

44. Implications If significant: Faces and words are processed similarly
Improve peoples ability to remember new acquaintances
Eyewitness testimony

45. 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

46. CONNECTIONS TO PREVIOUS RESEARCH
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

47. 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

48. FUTURE RESEARCH Facial images Neuroimaging: fMRI
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