1. Multimodal Neuroimaging Training Program NIRS module Anna Manelis Department of Psychology, CNBC Carnegie Mellon University Faculty Instructor: Theodore Huppert, PhD Technical Adviser: Nancy Beluk July 14, 2011

2. NIRS portable relatively non-invasive low cost has low sensitivity to subjects ’ motion able to measure both oxy- hemoglobin and deoxy- hemoglobin as a function of near- infrared wavelengths

3. CW6 system

4. Registration

5. Find a right spot detectors sources

6. 4 experiments Median nerve stimulation (2 subjects) Finger tapping (1 subject) Words encoding and recognition (1 subject) Working memory (2 subjects) the measurements were taken at two wavelengths (690nm and 830nm).

7. Finger tapping 15s on + 15s off 5 blocks Right hand Unilateral probe

8. Finger tapping sources detectors

9. Finger tapping Left motor cortex ΔOD – changes in optical Density at 830 nm Raw data Optical density = -log (I 1 /I 0 ) 0 50 100 150 200

10. Finger tapping Left motor cortex hp=70s, GF=2s 0 50 100 150 200

11. Finger tapping Left motor cortex hp=70s, GF=2s 0 50 100 150 200

12. Finger tapping Left motor cortex hp=70s, GF=2s 0 50 100 150 200

13. Memory Studies Right

14. Verbal memory 690nm 830nm encoding recognition 050100150200050100150200 time (sec)

15. Verbal memory encoding recognition HbR HbO HbT 0 10 20 30 40 50 60 70 800 10 20 30 40 50 60 70 time (sec)

16. N-back predictions fMRI results Owen et al., 2005 (HBM)

17. N-back load effect 1-back 2-back 3-back 0 10 20 30 40 50 60 70 time (sec)

18. Summary NIRS can detect changes in brain activity in various tasks that include simple sensory- motor and higher cognitive functions tasks

19. Three types of noise in NIRS data: instrument noise - sometimes difficult to detect - not much support from the companies - may have different distribution across channels and wavelengths physiological noise experiment error - cap motion (especially problematic for bilateral caps) - cap placement Limitations

20. 690 nm830 nm 690 nm vs. 830 nm

21. Noise in the data

22. Three types of noise in NIRS data: instrument noise - sometimes difficult to detect - not much support from the companies - may have different distribution across channels and wavelengths physiological noise experiment error - cap motion (especially problematic for bilateral caps) - cap placement Limitations

23. Methods for data analysis and registration are not well developed (i.e., work in progress) NIRS is sensitive to the changes in the scalp thickness over time between-subject variability within the brain stuctures Limitations

24. Acknowledgements 24 Seong-Gi Kim, PhD Bill Eddy, PhD Theodore Huppert, PhD Nancy Beluk Tomika Cohen MNTP Faculty, Staff, and Teaching Assistants University of Pittsburgh Medical Center Carnegie Mellon Center for Neural Basis of Cognition NIH R90DA02342 5T32-MH019983-12