The Scalp Time-Varying Networks of N170: Reference, Latency, and Information Flow

Using the scalp time-varying network method, the present study is the first to investigate the temporal influence of the reference on N170, a negative event-related potential component (ERP) appeared about 170 ms that is elicited by facial recognition, in the network levels. Two kinds of scalp electroencephalogram (EEG) references, namely, AR (average of all recording channels) and reference electrode standardization technique (REST), were comparatively investigated via the time-varying processing of N170. Results showed that the latency and amplitude of N170 were significantly different between REST and AR, with the former being earlier and smaller. In particular, the information flow from right temporal-parietal P8 to left P7 in the time-varying network was earlier in REST than that in AR, and this phenomenon was reproduced by simulation, in which the performance of REST was closer to the true case at source level. These findings indicate that reference plays a crucial role in ERP data interpretation, and importantly, the newly developed approximate zero-reference REST would be a superior choice for precise evaluation of the scalp spatio-temporal changes relating to various cognitive events.

[1]  M. Fuchs,et al.  An improved boundary element method for realistic volume-conductor modeling , 1998, IEEE Transactions on Biomedical Engineering.

[2]  C. Degueldre,et al.  Here I am: The cortical correlates of visual self-recognition , 2007, Brain Research.

[3]  Jennifer J. Richler,et al.  Effect size estimates: current use, calculations, and interpretation. , 2012, Journal of experimental psychology. General.

[4]  Bin He,et al.  Estimation of Time-Varying Connectivity Patterns Through the Use of an Adaptive Directed Transfer Function , 2008, IEEE Transactions on Biomedical Engineering.

[5]  Scott M. Hayes,et al.  Neural Mechanisms of Context Effects on Face Recognition: Automatic Binding and Context Shift Decrements , 2010, Journal of Cognitive Neuroscience.

[6]  Guido Nolte,et al.  The use of standardized infinity reference in EEG coherency studies , 2007, NeuroImage.

[7]  Andrew J. Edmonds,et al.  EVIDENCE FOR DIFFERENT REPRESENTATIONS OF FAMILIAR AND UNFAMILIAR FACES , 2009 .

[8]  N. Sagiv,et al.  Structural Encoding of Human and Schematic Faces: Holistic and Part-Based Processes , 2001, Journal of Cognitive Neuroscience.

[9]  Esa Mervaala,et al.  Forehead EEG electrode set versus full-head scalp EEG in 100 patients with altered mental state , 2015, Epilepsy & Behavior.

[10]  Giuseppe Iaria,et al.  The anatomic basis of the right face-selective N170 IN acquired prosopagnosia: A combined ERP/fMRI study , 2011, Neuropsychologia.

[11]  Michael Murias,et al.  Response to familiar faces, newly familiar faces, and novel faces as assessed by ERPs is intact in adults with autism spectrum disorders. , 2010, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[12]  Olaf Sporns,et al.  Complex network measures of brain connectivity: Uses and interpretations , 2010, NeuroImage.

[13]  Robert Oostenveld,et al.  A comparative study of different references for EEG spectral mapping: the issue of the neutral reference and the use of the infinity reference , 2005, Physiological measurement.

[14]  Jürgen Kayser,et al.  In search of the Rosetta Stone for scalp EEG: Converging on reference-free techniques , 2010, Clinical Neurophysiology.

[15]  T. Allison,et al.  Electrophysiological Studies of Face Perception in Humans , 1996, Journal of Cognitive Neuroscience.

[16]  Peng Xu,et al.  Efficient resting-state EEG network facilitates motor imagery performance , 2015, Journal of neural engineering.

[17]  Theodor Landis,et al.  Submillisecond unmasked subliminal visual stimuli evoke electrical brain responses , 2015, Human brain mapping.

[18]  Doris Y. Tsao,et al.  Patches with Links: A Unified System for Processing Faces in the Macaque Temporal Lobe , 2008, Science.

[19]  Dan Liu,et al.  The time-frequency representation of the ERPs of face processing , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[20]  Li Wang,et al.  The effect of reference choices on the spatio-temporal analysis of brain evoked potentials: The use of infinite reference , 2007, Comput. Biol. Medicine.

[21]  Dezhong Yao,et al.  A study on the reference electrode standardization technique for a realistic head model , 2004, Comput. Methods Programs Biomed..

[22]  Tao Zhang,et al.  The Time-Varying Networks in P300: A Task-Evoked EEG Study , 2016, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[23]  Paul L. Nunez,et al.  REST: A good idea but not the gold standard , 2010, Clinical Neurophysiology.

[24]  Nicholas B. Turk-Browne,et al.  Representations of Facial Identity in the Left Hemisphere Require Right Hemisphere Processing , 2012, Journal of Cognitive Neuroscience.

[25]  Margot J. Taylor,et al.  N170 or N1? Spatiotemporal differences between object and face processing using ERPs. , 2004, Cerebral cortex.

[26]  Margot J. Taylor,et al.  Early processing of the six basic facial emotional expressions. , 2003, Brain research. Cognitive brain research.

[27]  Robert W Thatcher,et al.  Coherence, Phase Differences, Phase Shift, and Phase Lock in EEG/ERP Analyses , 2012, Developmental neuropsychology.

[28]  Peng Xu,et al.  A comparative study of different references for EEG default mode network: The use of the infinity reference , 2010, Clinical Neurophysiology.

[29]  Federico Chella,et al.  Non-linear Analysis of Scalp EEG by Using Bispectra: The Effect of the Reference Choice , 2017, Front. Neurosci..

[30]  Dezhong Yao,et al.  Why do we need to use a zero reference? Reference influences on the ERPs of audiovisual effects. , 2013, Psychophysiology.

[31]  Isha Dewan,et al.  Wilcoxon-signed rank test for associated sequences , 2005 .

[32]  J. Hinojosa,et al.  N170 sensitivity to facial expression: A meta-analysis , 2015, Neuroscience & Biobehavioral Reviews.

[33]  G. Schwarz Estimating the Dimension of a Model , 1978 .

[34]  D.B. Geselowitz,et al.  The zero of potential , 1998, IEEE Engineering in Medicine and Biology Magazine.

[35]  W. Sommer,et al.  Emotion Effects on the N170: A Question of Reference? , 2012, Brain Topography.

[36]  Bruno Rossion,et al.  At a Single Glance: Fast Periodic Visual Stimulation Uncovers the Spatio-Temporal Dynamics of Brief Facial Expression Changes in the Human Brain , 2016, Cerebral cortex.

[37]  Dezhong Yao,et al.  Is the Surface Potential Integral of a Dipole in a Volume Conductor Always Zero? A Cloud Over the Average Reference of EEG and ERP , 2017, Brain Topography.

[38]  D. Yao,et al.  A method to standardize a reference of scalp EEG recordings to a point at infinity , 2001, Physiological measurement.

[39]  Yu Ping Wang,et al.  Recognizing mild cognitive impairment based on network connectivity analysis of resting EEG with zero reference , 2014, Physiological measurement.