Detailed description of database contents

In the following, we describe the contents of all provided Matlab files and provide additional information on the data recorded for each subject.

Selected emotional stimuli

The following table lists describes the 13 emotional videos that have been selected from the FilmStim database [1] (http://nemo.psp.ucl.ac.be/FilmStim/ ). The descriptions of the scenes are reproduced from FilmStim.

 

Video ID

FilmStim  ID

Duration

Movie

Short description

1

5

1 min 17 s

American History X

A neo-nazi kills an African-American man, smashing his head on a curb

2

19

1 min 18 s

Schindler’s List

Dead bodies are being carried away in a concentration camp

3

55

3 min 57 s

The Blair Witch Project

Final scene in which the characters are apparently killed

4

16

6 min 33 s

Scream 1

A girl receives threats over the phone, is chased, and stabbed

5

First part of 27

4 min 39 s

Saving Private Ryan

Graphic war scene: fighting on the beaches

6

39

43 s

The Piano

One of the characters gets her hand cut off

7

12

1 min 40 s

The Dinner Game

Complex humoristic scene

8

42

1 min 47 s

“Le Pari”

Lunch to celebrate father’s birthday

9

1

2 min 9 s

The Visitors

Two men wearing medieval armor attack the postman’s car

10

67

2 min 13 s

“La cité de la peur”

Conversation between three characters at a dinner table

11

56

2 min 1 s

Benny and Joon

Benny plays the fool in a coffee shop

12

8

2 min 24 s

“Les trois frères”

One of the characters takes part in a TV game

13

61

2 min 54 s

Something about Mary

Ben Stiller fights with a dog

Summary and comments of subject data

The following table provides some information on the data provided for each subject. Note that the evaluation of the EEG quality is subjective. The suitability of the subject for inclusion in the EEG-based valence recognition analysis is rated on a scale from 1 (very good) to 6 (very bad) and is also subjective. The number of videos corresponds to the number of videos for which the subject reported to have felt positive or negative emotions. For the subjects for which marker signals for the beginning and ends of the videos were not present in the EEG, the synchronization was performed based on the time stamps of the EEG recordings and the E-Prime files. 

Subject ID

gender

age

EEG quality

number of videos (negative – positive)

comments

rating

considered in [2]

1

M

21

Very good

10 (5 - 5)

-

2

yes

2

M

20

Very good

12 (6 – 6)

no markers in EEG

2

yes

3

M

47

Very good

12 (6 – 6)

no markers in EEG

2

yes

4

M

40

Very good

9 (4 – 5)

no markers in EEG

4

yes

5

F

20

Very noisy

10 (5 – 5)

no markers in EEG, no GSR

6

no

6

F

20

Very noisy

11 (6 – 5)

no markers in EEG, no GSR

6

no

7

M

53

Very good

9 (3 – 6)

no markers in EEG, no GSR

5

no

8

F

25

Very good

8 (4 – 4)

-

4

yes

9

M

19

Slightly noisy

11 (5 – 6)

-

3

yes

10

F

45

Very good

11 (6 – 5)

-

2

yes

11

F

19

Good

11 (6 – 5)

-

3

yes

12

M

52

Very good

12 (6 – 6)

-

1

yes

13

M

25

Good

8 (6 – 2)

-

5

no

14

M

41

Very good

5 (4 – 1)

-

6

no

15

F

33

Slightly noisy

9 (5 – 4)

-

4

yes

16

M

22

Very good

12 (6 – 6)

-

1

yes

17

M

41

Very good

12 (6 – 6)

-

1

yes

18

M

37

Very good

10 (6 – 4)

-

4

yes

19

M

50

Very good

11 (6 – 5)

-

2

yes

20

M

58

Very good

11 (6 – 5)

-

2

yes

21

M

37

Very good

8 (4 – 4)

-

4

yes

22

M

25

Good

11 (5 – 6)

-

3

yes

23

M

25

Very good

10 (5 – 5)

-

2

yes

24

F

48

Very bad

6 (2 – 4)

-

6

no

25

M

68

Very good

2 (1 – 1)

-

6

no

26

M

41

Very good

12 (6 – 6)

-

1

yes

27

M

47

Very good

10 (6 – 4)

-

2

yes

28

M

23

Very good

6 (4 – 2)

-

5

no

29

M

62

Slightly noisy

8 (4 – 4)

-

4

yes

30

M

53

Very good

8 (5 – 3)

-

5

no

31

M

50

Noisy

6 (5 – 1)

bad contact of reference

6

no

32

M

31

Very good

10 (4 – 6)

-

4

yes

33

M

23

Good

9 (4 – 5)

-

4

yes

34

M

36

Very good

10 (4 – 6)

-

4

yes

35

F

19

Very good

10 (6 – 4)

-

4

yes

36

M

22

Good

8 (2 – 6)

-

5

no

37

M

29

Very good

7 (4 – 3)

-

5

no

38

F

50

Very good

8 (5 – 3)

-

5

no

39

M

46

Very good

9 (4 – 5)

-

4

yes

40

M

24

Very good

9 (5 – 4)

-

4

yes

Physiological recordings

For each subject, we provide the following data files:

Subject information:

age

age of the subject

gender

gender of the subject

 

Data:

X

cell array containing the EEG, ECG, respiration, blood oxygen level and pulse rate recordings for each of the 13 emotional videos

Xn

cell array containing the EEG, ECG, respiration, blood oxygen level and pulse rate recordings for each of the 13 neutral videos

Xb

cell array containing the EEG, ECG, respiration, blood oxygen level and pulse rate recordings for each of the 26 black screen periods

names

cell array containing the channel names

Fs

sampling rate of the EEG, ECG, respiration, blood oxygen level and pulse rate recordings

Xgsr

cell array containing the GSR recordings for each of the 13 emotional videos

Xgsr_n

cell array containing the GSR recordings for each of the 13 neutral videos

Xgsr_b

cell array containing the GSR recordings for each of the 26 black screen periods

Fs_gsr

sampling rate of the GSR recordings

Subject’s responses:

labels

vector containing the self-assessed emotion labels of the subject for each emotional video

Information about the experiment:

video_order_neutral

order in which the neutral videos were presented during the experiment

video_order_emo

order in which the emotional videos were presented during the experiment

Information relevant for the data analysis conducted in the associated journal paper:

idbad

vector containing the indices of bad channels that have been selected manually by visual inspection

int

matrix containing information about which data intervals of emotional videos have been considered in the analysis. The three columns correspond to the number of the video, valence label of the video, and time sample corresponding to the center of the selected interval

Files for source reconstruction

In order to enable other researchers to reproduce the results described in [2] based on the reconstruction of brain activity on the cortical surface, we provide the following files that essentially characterize the employed head model:

r

3 x N matrix characterizing the positions of the 257 EEG electrodes

meshscalp

structure characterizing the mesh which describes the surface of the scalp

mesh

structure characterizing the mesh which describes the source space, each vertex of the mesh corresponding to a grid dipole (8000 grid dipoles in total)

G

lead field matrix

idxtri

cell array describing the clustering of the 8000 grid dipoles into 549 brain regions

idmap

cell array describing the association of the 540 brain regions with the 68 areas of the Desikan-Killiany brain atlas

idsel

vector containing the indices of the 274 selected brain regions (out of 549) which are assumed to be involved in the processing of emotions

Matlab script

Along with the data, we provide two Matlab scripts, one for reading the data and the second one for extracting the features described in [2].

The script read_data includes the following functionalities:

  • load the data
  • display subject information
  • list information of analyzed data intervals
  • display the presentation order of neutral and emotional videos
  • list the indices of bad channels
  • visualize the GSR signals for each emotional video
  • filter EEG data
  • interpolate bad EEG channels from the 4 nearest sensors
  • extract physiological recordings from data array
  • combine EEG and all physiological recordings (including the GSR) in one matrix

The script feature_extraction permits to compute the following features for each EEG channel and for each emotional brain region (see [2] for more details):

  • powers in (4 – 8 Hz),  (8 – 13 Hz),  (13 – 30 Hz), low  (30 – 45 Hz), and high  (55 – 80 Hz) bands
  • connectivity in , low , and high bands
  • connectivity in the whole frequency range
  • higher order crossings for , low , and high bands up to derivative of order 20
  • higher order crossings for the whole frequency range up to derivative of order 50
  • fractal dimension
  • statistics (minimum, maximum, median, standard deviation, mean and maximum of the first two derivatives, skewness, kurtosis)
  • spectral moments
  • spectral crest factor in , low , and high bands

and to vary the following parameters:

  • number of sensors
  • length of the considered data interval
  • number of segments per interval
  • length of the analyzed segment
  • application of Independent Component Analysis (ICA) with Wavelet Denoising (WD) or not.

References

Schaefer, F. Nils, X. Sanchez, and P. Philippot, “Assessing the effectiveness of a large database of emotion-eliciting films: a new tool for emotion researchers,” Cognition & Emotion, vol. 24, no. 7, pp. 1153–1172, 2010

  • Becker, J. Fleureau, P. Guillotel, F. Wendling, I. Merlet, and L. Albera, “Emotion recognition based on high-resolution EEG recordings and reconstructed brain sources”, submitted to IEEE Transactions on Affective Computing, 2016