DISCRETE CHOICE MODELING USING NEURO-RESPONSE DATA

• US 20110237971A1
• Filed: 03/25/2010
• Published: 09/29/2011
• Est. Priority Date: 03/25/2010
• Status: Abandoned Application

• Current Assignee: Nielsen Company (US) LLC (RR Donnelley & Sons Company)
• Original Assignee: NeuroFocus Inc. (Nielsen Holdings plc)
• Inventors: Pradeep, Anantha, Knight, Robert T., Gurumoorthy, Ramachandran
• Application Number:
  US12/731,868
• Publication Number:
  US 20110237971A1
• Time in Patent Office: Days
• US Class Current: 600/544
• CPC Class Codes: A61B 5/163 by tracking eye movement, gaze, or pupil change
• CPC Class Codes: A61B 5/165 Evaluating the state of mind, e.g. depression, anxiety
• CPC Class Codes: A61B 5/378 Visual stimuli
• CPC Class Codes: A61B 5/398 Electrooculography [EOG], e.g. detecting nystagmus; Electroretinography [ERG]
• CPC Class Codes: A61B 5/4035 Evaluating the autonomic nervous system
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A system obtains neuro-response data as well as survey based data during discrete choice modeling to evaluate subject decision making processes. A discrete choice model evaluates a decision made by a subject as a function of multiple variables. Neuro-response data vectors and orthogonal survey based data vectors are weighted and combined to generate multi-dimensional vectors. The multi-dimensional vectors are used to estimate the effectiveness of changing particular variables in modifying subject behavior.

Claims

1. A method, comprising:

exposing a plurality of subjects to stimulus material associated with a discrete choice model;

obtaining neuro-response data from the plurality of subjects exposed to the stimulus material;

generating a plurality of neuro-response scores corresponding to a plurality of choices in the discrete choice model;

obtaining survey response data;

generating a plurality of survey response scores corresponding to the plurality of choices in the discrete choice model;

aggregating the neuro-response scores and the survey response scores using mult-dimensional vector combination.

2. The method of claim 1, wherein multi-dimensional vector combination comprises computing the square of the sum of squares for corresponding neuro-response scores and survey response scores.

3. The method of claim 1, wherein multi-dimensional vector combination comprises computing the combined magnatitude of neuro-response score vectors and corresponding survey response score vectors.

4. The method of claim 1, wherein a plurality of neuro-response score vectors are orthogonal to a plurality of survey response score vectors.

5. The method of claim 1, wherein choices correpsond to features of a products or service.

6. The method of claim 1, wherein neuro-response data is collected using a plurality of modalities including Electronencephalography (EEG) and Electrooculography (EOG).

7. The method of claim 1, wherein obtaining neuro-response data comprises obtaining target and distracter event related potential (ERP) measurements to determine differential measurements of ERP time domain components at multiple regions of the brain (DERP).

8. The method of claim 1, wherein obtaining neuro-response data further comprises obtaining event related time-frequency analysis of the differential response to assess the attention, emotion and memory retention (DERPSPs) across multiple frequency bands.

9. The method of claim 1, wherein survey response data is obtained from the plurality of subjects exposed to stimulus material.

10. The method of claim 1, wherein the survey response scores and the neuro-response scores are scaled prior to combination.

11. A system, comprising:

a data collection mechanisms operable to obtain neuro-response data from a plurality of subjects exposed to the stimulus material associated with a discrete choice model and operable to otain survey response data for the stimulus material;

a data analyzer operable to generate a plurality of neuro-response scores corresponding to a plurality of choices in the discrete choice model and a plurality of survey response scores corresponding to the plurality of choices in the discrete choice model;

wherein the neuro-response scores and the survey response scores are aggregated using mult-dimensional vector combination.

12. The system of claim 11, wherein multi-dimensional vector combination comprises computing the square of the sum of squares for corresponding neuro-response scores and survey response scores.

13. The system of claim 11, wherein multi-dimensional vector combination comprises computing the combined magnatitude of neuro-response score vectors and corresponding survey response score vectors.

14. The system of claim 11, wherein a plurality of neuro-response score vectors are orthogonal to a plurality of survey response score vectors.

15. The system of claim 11, wherein choices correpsond to features of a products or service.

16. The system of claim 11, wherein neuro-response data is collected using a plurality of modalities including Electronencephalography (EEG) and Electrooculography (EOG).

17. The system of claim 11, wherein obtaining neuro-response data comprises obtaining target and distracter event related potential (ERP) measurements to determine differential measurements of ERP time domain components at multiple regions of the brain (DERP).

18. The system of claim 11, wherein obtaining neuro-response data further comprises obtaining event related time-frequency analysis of the differential response to assess the attention, emotion and memory retention (DERPSPs) across multiple frequency bands.

19. The system of claim 11, wherein survey response data is obtained from the plurality of subjects exposed to stimulus material.

20. The system of claim 11, wherein the survey response scores and the neuro-response scores are scaled prior to combination.

21. An apparatus, comprising:

means for exposing a plurality of subjects to stimulus material associated with a discrete choice model;

means for obtaining neuro-response data from the plurality of subjects exposed to the stimulus material;

means for generating a plurality of neuro-response scores corresponding to a plurality of choices in the discrete choice model;

means for obtaining survey response data;

means for generating a plurality of survey response scores corresponding to the plurality of choices in the discrete choice model;

means for aggregating the neuro-response scores and the survey response scores using mult-dimensional vector combination.