This presentation showed work we have done on using Brain Computer Interfaces to detect scientific curiosity in images. The equipment used by the group from EPFL Lausanne was a full 32-node EEG while the CLARITY group from DCU used a home-built 4-channel EEG analyser with total cost less than €1,000.  Results indicate that the P300 ERP is a positive indicator of curiosity, especially in experts

Ampatzis, Christos

Dufaux, Frédéric

Ebrahimi, Touradj

Ha-Minh, Thien

Healy, Graham

Izzo, Dario

Ruciński, Marek

Smeaton, Alan F.

Wilkins, Peter

Yazdani, Ashkan

Irish Universities

Presentations and demos of the "Curiosity Cloning" project

Name not available

UNIVERSITY	  COLLEGE	  DUBLIN	  	  	  	  	  	  DUBLIN	  CITY	  UNIVERSITY	  	  	  	  	  	  TYNDALL	  NATIONAL	  INSTITUTEPresenta(ons	  &	  Demos	  of	  the	  “Curiosity	  Cloning”	  ProjectDario	  Izzo,	  Christos	  Ampatzis,	  Marek	  Ruciński,Touradj	  Ebrahimi,	  Ashkan	  Yazdani,	  Thien	  Ha-­‐Minh,	  Frédéric	  Dufaux,	  Alan	  F.	  Smeaton,	  PeterWilkins	  and	  Graham	  HealyEmail:	  alan.smeaton@dcu.iePresented	  at	  the	  Workshop	  on	  “Brain	  MachineInterfaces	  for	  Space	  Applica(ons:	  EnhancingAstronaut	  Capabili(es”,	  European	  Space	  Agency,Noordwijk	  (The	  Netherlands)UNIVERSITY	  COLLEGE	  DUBLIN	  	  	  	  	  	  DUBLIN	  CITY	  UNIVERSITY	  	  	  	  	  	  TYNDALL	  NATIONAL	  INSTITUTEIntroduc(on•	  BCI	  rapidly	  expanding	  area•	  U(lises	  specialist	  hardware•	  Consumer	  (	  <	  $1000	  USD)	  -­‐>	  Professional	  ($50k+)•	  DCU’s	  focus:What	  can	  be	  achieved	  with	  approx	  $1000	  USDhardware?UNIVERSITY	  COLLEGE	  DUBLIN	  	  	  	  	  	  DUBLIN	  CITY	  UNIVERSITY	  	  	  	  	  	  TYNDALL	  NATIONAL	  INSTITUTEOverview•	  Apparatus•	  Experimental	  Methodology•	  Experimental	  Outcomes•	  ConclusionsUNIVERSITY	  COLLEGE	  DUBLIN	  	  	  	  	  	  DUBLIN	  CITY	  UNIVERSITY	  	  	  	  	  	  TYNDALL	  NATIONAL	  INSTITUTEApparatus•	  EEG	  Equipment:•	  ‘Pendant	  EEG’	  -­‐	  hep://www.pocket-­‐neurobics.com/•	  2	  Channel	  device,	  254	  Samples	  Per	  Second,	  12-­‐bitresolu(on.	  	  Opera(on	  is	  wireless,	  with	  USB	  receiver.•	  ‘Daisy-­‐Chained’	  2	  devices	  together	  to	  create	  4-­‐nodedevice,	  with	  joint	  mastoid	  reference.•	  Custom	  wrieen	  device	  driver.UNIVERSITY	  COLLEGE	  DUBLIN	  	  	  	  	  	  DUBLIN	  CITY	  UNIVERSITY	  	  	  	  	  	  TYNDALL	  NATIONAL	  INSTITUTEApparatusUNIVERSITY	  COLLEGE	  DUBLIN	  	  	  	  	  	  DUBLIN	  CITY	  UNIVERSITY	  	  	  	  	  	  TYNDALL	  NATIONAL	  INSTITUTEExperimental	  Methodology•	  For	  Oddball	  style	  experiments,	  subjects	  required	  tocount	  number	  of	  oddballs	  observed.•	  Subjects	  asked	  to	  look	  at	  ﬁxa(on	  cross	  on	  screen,remain	  s(ll	  and	  to	  refrain	  from	  blinking	  wherecomfortable.•	  Expert	  advice:	  Node	  placements	  according	  to	  10-­‐20system,	  at	  sites	  Pz,	  Cz,	  P3	  and	  P4.	  	  Inten(on	  to	  capturemost	  data	  from	  P3	  ERP.UNIVERSITY	  COLLEGE	  DUBLIN	  	  	  	  	  	  DUBLIN	  CITY	  UNIVERSITY	  	  	  	  	  	  TYNDALL	  NATIONAL	  INSTITUTEExperimental	  MethodologyPzCzP3 P4UNIVERSITY	  COLLEGE	  DUBLIN	  	  	  	  	  	  DUBLIN	  CITY	  UNIVERSITY	  	  	  	  	  	  TYNDALL	  NATIONAL	  INSTITUTEExperimental	  Methodology•	  Signal	  Processing	  (per	  channel),	  generalized	  approach	  forcross-­‐subject	  applica(on:•	  Bandpassed	  0hz-­‐14hz,	  region	  220ms-­‐810ms,	  14	  samples.•	  FFT	  from	  region	  220ms-­‐620ms,	  5	  features	  extracted	  in	  range1hz-­‐15hz,	  3hz	  steps.•	  Low	  frequency	  sampling	  in	  range	  0hz-­‐5hz	  for	  region	  220ms	  –1000ms,	  5	  features	  extracted.•	  Total	  features	  per	  channel:	  24.	  	  Total	  features:	  96.•	  Time	  oﬀset	  is	  from	  s(mulus	  presenta(on	  (me.UNIVERSITY	  COLLEGE	  DUBLIN	  	  	  	  	  	  DUBLIN	  CITY	  UNIVERSITY	  	  	  	  	  	  TYNDALL	  NATIONAL	  INSTITUTEExperiments•	  ‘Reliability	  vs.	  Speed’–	  See	  how	  far	  we	  can	  push	  a	  4	  node	  setup.–	  SDmulus	  presentaDon	  rates	  500ms	  -­‐>	  50ms.–	  Dataset:	  ESTEC	  Rocks,	  Subjects:	  4•	  ‘Expert	  vs.	  Non-­‐Experts’–	  Determine	  if	  it	  was	  possible	  to	  detect	  3	  classes	  of	  image,	  oddball,	  non-­‐obvious	  oddball,	  non-­‐oddball.–	  Dataset:	  Nanomaterials	  Images	  (similar	  visually	  to	  heatmap).–	  Subjects:	  6	  (5	  ‘non-­‐expert’,	  1	  ‘expert’	  (ACT-­‐ESA)).•	  SenseCam–	  Similar	  to	  previous,	  determine	  diﬀerences	  in	  detecDon	  between	  ‘expert’	  &non-­‐expert,	  but	  on	  natural	  images.–	  Dataset:	  SenseCam	  images	  from	  one	  subject.–	  Subjects:	  5	  (4	  ‘non-­‐expert’,	  1	  ‘expert’	  (DCU)).UNIVERSITY	  COLLEGE	  DUBLIN	  	  	  	  	  	  DUBLIN	  CITY	  UNIVERSITY	  	  	  	  	  	  TYNDALL	  NATIONAL	  INSTITUTESenseCamSenseCam–	  SenseCam	  personal	  wearable	  camera,	  capturing	  up	  to	  3000	  personalimages	  per	  day.–	  Presents	  informaDon	  management	  research	  challenges,	  involvingevent	   segmentaDon,	  indexing	  and	  retrievalEventSegmentationSenseCam Images of a day (about2,000)Importance +SearchFunctionalityUNIVERSITY	  COLLEGE	  DUBLIN	  	  	  	  	  	  DUBLIN	  CITY	  UNIVERSITY	  	  	  	  	  	  TYNDALL	  NATIONAL	  INSTITUTEEvalua(onTwo	  fold	  evalua(on	  criteria:1. Crea(on	  of	  ‘Grand	  Average’	  ERP	  signatures,	  todetermine	  if	  we	  are	  capturing	  responses	  todiﬀerent	  s(mulus.2. Crea(on	  of	  discrimina(ve	  classiﬁers	  (SVM)	  todetermine	  if	  signals	  can	  be	  captured	  and	  classiﬁedon	  4	  node	  setup.	  	  Evalua(on	  metrics	  AUC	  &	  ROC.UNIVERSITY	  COLLEGE	  DUBLIN	  	  	  	  	  	  DUBLIN	  CITY	  UNIVERSITY	  	  	  	  	  	  TYNDALL	  NATIONAL	  INSTITUTEResultsReliability	  vs.	  Speed:Grand	  Averages	  –	  dashed	  line	  =	  oddball	  sDmulus.Subject ‘a’: 1000ms Subject ‘b’: 50msUNIVERSITY	  COLLEGE	  DUBLIN	  	  	  	  	  	  DUBLIN	  CITY	  UNIVERSITY	  	  	  	  	  	  TYNDALL	  NATIONAL	  INSTITUTEResultsReliability	  vs.	  Speed:–	  ClassiﬁcaDonUNIVERSITY	  COLLEGE	  DUBLIN	  	  	  	  	  	  DUBLIN	  CITY	  UNIVERSITY	  	  	  	  	  	  TYNDALL	  NATIONAL	  INSTITUTEResults‘Expert	  vs.	  Non-­‐Experts’•	  3	  Classes	  of	  s(mulus,	  oddball,	  non-­‐obvious	  oddball,non-­‐oddball.•	  Of	  6	  subjects,	  the	  expert	  &	  2	  non-­‐experts	  able	  todis(nguish	  3	  classes,	  based	  upon	  grand	  averages.•	  Classiﬁca(on	  accuracy	  for	  these	  3	  subjects	  around0.61-­‐0.64	  AUC	  –	  for	  remaining	  3	  performance	  close	  torandom.UNIVERSITY	  COLLEGE	  DUBLIN	  	  	  	  	  	  DUBLIN	  CITY	  UNIVERSITY	  	  	  	  	  	  TYNDALL	  NATIONAL	  INSTITUTEExpert Subject: Oddball vs. Non-OddballExpert Subject: Oddball vs. Non-Obvious OddballUNIVERSITY	  COLLEGE	  DUBLIN	  	  	  	  	  	  DUBLIN	  CITY	  UNIVERSITY	  	  	  	  	  	  TYNDALL	  NATIONAL	  INSTITUTEUNIVERSITY	  COLLEGE	  DUBLIN	  	  	  	  	  	  DUBLIN	  CITY	  UNIVERSITY	  	  	  	  	  	  TYNDALL	  NATIONAL	  INSTITUTEResultsSenseCam	  Experiments:•	  More	  diﬃcult	  than	  an(cipated.•	  Genera(on	  of	  mul(ple	  ERP’s	  such	  as	  N170generated	  in	  response	  to	  faces,	  hamperedclassiﬁca(on	  as	  could	  be	  detec(ng	  diﬀerent	  ERP’s.•	  More	  careful	  selec(on	  of	  dataset.•	  Resolu(on	  of	  more	  nodes	  would	  be	  useful.UNIVERSITY	  COLLEGE	  DUBLIN	  	  	  	  	  	  DUBLIN	  CITY	  UNIVERSITY	  	  	  	  	  	  TYNDALL	  NATIONAL	  INSTITUTEConclusions•	  4	  Node	  setup	  is	  capable	  of	  capturing	  ‘Oddball’s(mulus	  events,	  ideally	  around	  300ms.•	  Genera(on	  of	  data	  for	  classiﬁca(on	  requires	  carefulexperimental	  parameter	  selec(on.•	  Is	  theore(cally	  possible	  to	  capture	  the	  diﬀerencesbetween	  subjects	  as	  to	  what	  is	  of	  interest,	  aka‘curiosity	  cloning’,	  however	  is	  dependent	  on	  dataset.•	  Great	  variability	  between	  subject	  –	  long	  term	  goalto	  create	  generalized	  classiﬁer.

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http://doras.dcu.ie/15031/1/dcu_cc_exec_summary.pdf

Presentations and demos of the "Curiosity Cloning" project

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Irish Universities

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