Brain Topography

, Volume 11, Issue 4, pp 291–303 | Cite as

Single Trial Analysis of Neurophysiological Correlates of the Recognition of Complex Objects and Facial Expressions of Emotion

  • Lichan Liu
  • Andreas A. Ioannides
  • Marcus Streit


In an earlier experiment, we have used the BTi twin MAGNES system (2 × 37 channels) to record the evoked magnetic field from five healthy right-handed male volunteers using two tasks: visual recognition of complex objects including faces and facial expressions of emotion. We have repeated the experiment with one of the five subjects using the BTi whole head system (148 channels). Magnetic field tomography (MFT) was used to extract 3D estimates of brain activity millisecond by millisecond from the recorded magnetoencephalographic (MEG) signals. Results from the MFT analysis of the average signals of the five subjects have been reported elsewhere (Streit et al. 1997; Streit et al. 1999). In this paper, we present results of the detailed single trial analysis for the subject recorded from the whole head system. We found activations in areas extending from the occipital pole to anterior areas. Regions of interest (ROIs) were defined entirely on functional criteria and confirmed independently by the location of the maximum activity on the MRI. Activation curves for each ROI were computed and objective statistical measures (Kolmogorov-Smirnov test) were then used to identify time segments for which the ROI activity showed significant differences both within the same and across different object/emotion categories. Emphasis is placed on the quantification of the activity from two ROIs, fusiform gyrus (FG) and amygdala (AM), which have been best studied in the context of processing of faces and facial expressions of emotion, respectively. We found no face-specific area as such, but instead areas like the FG was activated by all complex objects at roughly similar latencies and varying strengths. The amygdala activity was significantly different between 150 and 180 ms for fearful expression, and even earlier for happy expression.

Visual object recognition Face recognition Facial emotion recognition Magnetoencephalography (MEG) Single trial analysis Statistical measures 


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  1. Adolphs, A., Damasio, H., Tranel, D. and Damasio, A. Cortical systems for the recognition of emotion in facial expressions. The Journal of Neuroscience, 1996, 16(23): 7678-7687.Google Scholar
  2. Allison, T., Ginter, H., McCarthy, G., Nobre, A.C., Puce, A., Luby, M. and Spencer, D.D. Face recognition in human extrastriate cortex. J. Neurophysiol., 1994, 71(2): 821-825.Google Scholar
  3. Bowers, D., Blonder, L., Feinberg, T. and Heilman, K.M. Differential impact of right and left hemisphere lesions on facial emotion and object imagery. Brain, 1991, 114: 2593-2609.Google Scholar
  4. Cahill, L., Haier, R., Fallon, J., Alkire, M., Tang, C., Keator, D., Wu, J. and McGaugh, J. Amygdala activity at encoding correlated with long-term, free recall of emotional information. Proc. Natl. Acad. Sci., 1996, 93: 8016-8021.Google Scholar
  5. Clark, V.P., Keil, K., Ma, J., Maisog, J., Courtney, S., Ungerleider, L.G. and Haxby, J.V. Functional magnetic resonance imaging of human visual cortex during face matching: a comparison with positron emission tomography. Neuroimage, 1996, 4: 1-15.Google Scholar
  6. Gauthier, I., Anderson, A.W., Tarr, M.J., Skudlarski, P. and Gore, J.C. Levels of categorization in visual recognition studied using functional magnetic resonance imaging. Current Biology, 1997, 7: 645-651.Google Scholar
  7. George, N., Jemel, B., Fiori, N. and Renault, B. Face and shape repetition effects in humans: a spatio-temporal ERP study. Neuroreport, 1997, 8(6): 1417-1423.Google Scholar
  8. Halgren, E., Baudena, P., Heit, G., Clarke, J.M. and Marinkovic, K. Spatio-temporal stages in face and word processing. 1. Depth-recorded potentials in the human occipital, temporal and parietal lobes. J. Physiol. Paris, 1994, 88(1): 1-50.Google Scholar
  9. Ioannides, A.A., Bolton, J.P.R. and Clarke, C.J.S. Continuous probabilistic solutions to the biomagnetic inverse problem. Inverse Problem, 1990, 6: 523-542.Google Scholar
  10. Ioannides, A.A., Muratore, R., Balish, M. and Sato, S. In vivo validation of distributed source solutions for the biomagnetic inverse problem. Brain Topography, 1993a, 5: 263-273.Google Scholar
  11. Ioannides, A.A., Singh, K.D., Hasson, R., Baumann, S.B., Rogers, R.L., Guinto, F.C. and Papanicolaou, A.C. Comparison of current dipole and magnetic field tomography analyses of the cortical response to auditory stimuli. Brain Topography, 1993b, 6: 27-34.Google Scholar
  12. Ioannides, A.A. Estimates of 3D brain activity ms by ms from Biomagnetic signals: method (MFT), results and their significance. In: E. Eiselt, U. Zwiener and H. Witte (Eds), Quantitative and Topological EEG and MEG Analysis. Universitätsverlag Druckhaus-Maayer GmbH, Jena, 1995a: 59-68.Google Scholar
  13. Ioannides, A.A., Liu, M.J., Liu, L.C., Bamidis, P.D., Hellstrand, E. and Stephan, K.M. Magnetic field tomography of cortical and deep processes: examples of "real-time mapping" of averaged and single trial MEG signals. International Journal of Psychophysiology, 1995b, 20: 161-175.Google Scholar
  14. Kanwisher, N., McDermott, J. and Chun, M. The fusiform face area: a module in human extrastriate cortex specialized for face perception. The Journal of Neuroscience, 1997, 17(11): 4302-4311.Google Scholar
  15. Kling, A., Steklis, H.D. and Deutsch, S. Radiotelemetered activity from the amygdala during social interactions in the monkey. Exp. Neurol., 1979, 66(1): 88-96.Google Scholar
  16. Liu, L.C. and Ioannides, A.A. A correlation study of averaged and single trial MEG signals: the average describes multiple histories each in a different set of single trials. Brain Topography, 1996, 8(4): 385-396.Google Scholar
  17. Liu, L.C., Ioannides, A.A. and Müller-Gärtner, H.W. Bi-hemispheric study of single trial MEG signals of the human auditory cortex. Electroenceph. clin. Neurophysiol., 1998, 106: 64-78.Google Scholar
  18. Liu, M.J., Fenwick, P.B., Lumsden, J., Lever, C., Stephan, K.M. and Ioannides, A.A. Averaged and single-trial analysis of cortical activation sequences in movement preparation, initiation and inhibition. Human Brain Mapping, 1996, 4: 254-264.Google Scholar
  19. McCarthy, G., Puce, A., Gore, J.C. and Allison, T. Face-specific processing in the human fusiform gyrus. Journal of Cognitive Neuroscience, 1997, 9(5): 605-610.Google Scholar
  20. Morris, J.S., Frith, C.D., Perrett, D.I., Rowland, D., Young, A.W., Calder, A.J. and Dolan, R.J. A differential neural response in the human amygdala to fearful and happy facial expressions. Nature, 1996, 383: 812-815.Google Scholar
  21. Moscovitch, M., Winocur, G. and Behrmann, M. What is special about face recognition? Nineteen experiments on a person with visual object agonsia and dyslexia but normal face recognition. Journal of Cognitive Neuroscience, 1997, 9(5): 555-604.Google Scholar
  22. Puce, A., Allison, T., Gore, J.C. and McCarthy, G. Face-sensitive regions in human extrastriate cortex studied by functional MRI. Journal of Neurophysiology, 1998, 74(3): 1192-1199.Google Scholar
  23. Rogan, M.T., Stäubli, U.V. and LeDoux, J.E. Fear conditioning induces associative long-term potentiation in the amygdala. Nature, 1997, 390: 604-607.Google Scholar
  24. Sam, M., Hietanen, J.K., Hari, R., Ilmoniemi, R.J. and Lounasmaa, O.V. Face-specific responses from the human inferior occipito-temporal cortex. Neuroscience, 1997, 77(1): 49-55.Google Scholar
  25. Sergent, J., Ohta, S. and MacDonald, B. Functional neuroanatomy of face and object processing: a positron emission tomography study. Brain, 1992, 115: 15-36.Google Scholar
  26. Stephens, M.A. Use of Kolmogorov-Smirnof, Cramer-von-Mises and related statistics without extensive tables. Journal of the Royal Statistical Society, ser. B, 1970, 32: 115-122.Google Scholar
  27. Streit, M., Ioannides, A.A., Wölwer, W., Dammers, J., Gaebel, W. and Müller-Gärtner, H.W. Correlates of facial affect recognition and visual object recognition. In: H. Witte, U. Zwiener, Bärbel Schack et al. (Eds), Druckhaus Mayer Verlag GmbH Jena/Erlangen, Germany, 1997: 117-119.Google Scholar
  28. Streit, M., Ioannides, A.A., Liu, L.C., Wölwer, W., Dammers, J., Gross, J., Gaebel, W. and Müller-Gärtner, H.W. Neurophysiological correlates of the recognition of facial expressions of emotion as revealed by magnetoencephalography. Cognitive Brain Research, 1999, 7(4): 481-491.Google Scholar
  29. Swithenby, S.J., Bailey, A.J., Bräutigam, S., Josephs, O.E., Jousmäki, V. and Tesche, C.D. Neural processing of human faces: a magnetoencephalographic study. Exp. Brain Res., 1998, 118: 501-510.Google Scholar
  30. Taylor, J.G., Ioannides, A.A. and Müller-Gärtner H.W. Mathematical analysis of lead field expansions. IEEE Trans. Med. Imag. (accepted for publication).Google Scholar

Copyright information

© Human Sciences Press, Inc. 1999

Authors and Affiliations

  • Lichan Liu
    • 1
  • Andreas A. Ioannides
    • 2
  • Marcus Streit
    • 3
  1. 1.Institute of Medicine, Research Centre JülichJülichGermany
  2. 2.Laboratory for Human Brain DynamicsBrain Science Institute (BSI)Wako-shi, SaitamaJapan
  3. 3.Department of PsychiatryUniversity of DüsseldorfDusseldorfGermany

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