Cortical Source Localization 1 Running Head: Infant Cortical Source Localization Cortical Source Localization of Infant Cognition

Neuroimaging techniques such as positron emission topography (PET) and functional magnetic resonance imaging (fMRI) have been utilized with older children and adults to identify cortical sources of perceptual and cognitive processes. However, due to practical and ethical concerns, these techniques cannot be routinely applied to infant participants. An alternative to such neuroimaging techniques appropriate for use with infant participants is high-density EEG recording and cortical source localization techniques. The current paper provides an overview of a method developed for such analyses. The method consists of four steps: 1) recording high-density (e.g., 128-channel) EEG. 2) Analysis of individual participant raw segmented data with independent component analysis (ICA). 3) Estimation of equivalent current dipoles (ECDs) that represent cortical sources for the observed ICA component clusters. 4) Calculation of component activations in relation to experimental factors. We discuss an example of research applying this technique to investigate the development of visual attention and recognition memory. We also describe the application of “realistic head modeling” to address some of the current limitations of infant cortical source localization. Cortical Source Localization 3 Cortical Source Localization of Infant Cognition Developmental cognitive neuroscience is concerned with the brain areas that serve as sources for cognitive processes during development. The field has been historically limited in tools available for examining cortical activity in young participants. This is particularly the case for those involved in infant research due to ethical and practical concerns regarding the use of PET and fMRI with infant participants. An alternative is to record electrical activity on the scalp that is generated by neural activity within the head, i.e., the electroencephalogram (EEG). This measure is currently one of the most informative and useful tools available for research on infant neurocognitive development and has been widely used to examine early cognitive development. One use of EEG is as a measure of cortical activity. The EEG measures electrical activity occurring on the scalp that is caused by changes in post-synaptic electrical potentials produced during cortical activity. However, measuring changes in the EEG at particular scalp locations does not provide solid evidence of the involvement of corresponding areas of the brain. The path an electrical current travels from origination at the source (or dipole) to observation on the scalp is not straightforward. Factors involved in determining the location and magnitude of the scalp potential recorded in the EEG include (but are not limited to) the depth, location, and orientation of the dipole, as well as the number of action potentials that sum together to form the dipole of interest. An additional factor is the type of tissue(s) that the potential passes through, with impedance (resistivity) values differing for white matter, gray matter, cerebrospinal fluid, skull matter, etc. The problem of inferring cortical sources from EEG recording thus has limited its use as a “functional neuroimaging” tool. Cortical Source Localization 4 This paper details an approach to localizing cortical sources of infant EEG using methods of cortical source localization and inferring the basis of cognitive activity in the brain. This approach is based on existing methods used with adult participants that we have modified for use with infant participants (DeLorme, Makeig , Fabre-Thorpe, & Sejnowski, 2002; Jung, Makeig, Fabre-Thorpe, & Sejnowski., 2001b; Makeig, Bell, Jung, & Sejnowski, 1996; Makeig, Jung, Bell, Ghahremani, & Sejnowski, 1997; Richards, 2004 a; Scherg, 1990, 1992; Scherg & Picton, 1991; Huizenga & Molenaar, 1994). The method consists of four steps: 1) recording EEG activity with a high-density (128 channel) EEG system, 2) analysis of individual participant raw segmented EEG data with ICA, 3) estimation of ECDs, i.e., cortical sources of the scalp current composing the ICA component clusters, and 4) calculation of ICA component temporal activations in relation to experimental factors. We present an example of this technique applied in an investigation of cortical sources of infant attention and recognition memory (Reynolds & Richards, 2005). Additionally, we discuss an advanced technique Richards (2006, 2007a, 2007b) is developing for use with human infants that utilizes “realistic source models” based on structural MRIs obtained from individual infant participants and addresses some of the current limitations of infant cortical source localization. (Footnote 1) High-Density EEG Recording The first step in the procedure involves recording infant EEG. Cortical source localization requires a recording system that contains a large number of electrodes distributed evenly on the scalp (Johnson, de Haan, Oliver, Smith, Hatzakis, Tucker, & Csibra, 2001). The traditional international 10-20 and 10-10 electrode configurations (Jasper, 1958; Michel, Murray, Lantz, Gonzalez, Spinelli & Grave de Peralta, Cortical Source Localization 5 2004; Pivik, Broughton, Coppola, Davidson, Fox, & Nuwer, 1993) do not meet these requirements. The "geodesic sensor net" developed by Don Tucker is an example of what has been called a high-density (or dense-array) configuration of electrodes (Electrical Geodesics Inc; Tucker, 1993; Tucker, Liotti, Potts, Russell, & Posner, 1994). The high-density Electrical Geodesics Inc. (EGI) nets have 64, 128, or 256 electrodes evenly distributed across the scalp, providing interelectrode distances of 35 to 40 mm for adults and 20 to 25 mm for infants (Tucker, 1993). The EEG scalp sites composed within the geodesic configuration differ from the electrode placement sites of the International 10-20 system (Jasper, 1958; Pivik, Broughton, Coppola, Davidson, Fox, & Nuwer, 1993), but a rough correspondence can be made between them (Luu & Ferree, 2000; Srinivasan, Tucker, & Murias, 1998). Figure 1 shows the layout of the International 10-20 and 10-10 systems, as well as the layout of the 64 and 128 channel EGI systems. Because the sensor nets contain much greater numbers of electrodes than traditional systems, one can examine multiple sites that correspond to or surround sites of interest in the 10-20 system or 10-10 systems (for examples, see Reynolds, Courage, & Richards, under review; Reynolds & Richards, 2005). For a more detailed overview of the use of the EGI system with infant participants, the interested reader is referred to Johnson and colleagues (2001). Insert Figure 1 about here The effect of the number of electrodes on the EEG recording also is shown in Figure 1. With the EGI system one can elect to only use or display data recorded from electrodes that coincide with the more traditional recording layouts. Figure 1 shows examples of topographical maps obtained from the four layouts of the same data recorded Cortical Source Localization 6 using the EGI 128 channel system. These data were recorded in an experiment that found presaccadic ERP activity over frontal electrodes (left panels) and occipital activities in response to a peripheral target (right panels; e.g., Richards, 2004b, 2005). In the example in the middle column, the EEG changes are occurring over the top of the head. All four recording configurations show this activity well. In the left and right columns, scalp potential activity is shown in which the anterior and posterior scalp leads near the boundary of the 10-20 system show significant activity. When the scalp potential covers anterior and posterior scalp regions or is widespread, the full distribution of the potential is not recorded by these traditional systems. These topographical maps demonstrate that recordings obtained from the International 10-20 and 10-10 systems sometimes do not provide an accurate representation of the distribution of the electrical scalp potential. With this in mind, the rationale behind the prerequisite of large numbers of evenly distributed electrodes prior to the application of cortical source localization is apparent. Although 64 channels may provide sufficient interelectrode distances, we suggest the use of the 128 channel EGI system for obtaining EEG data for the application of source localization techniques with infant participants. Once high-density EEG has been collected, the second step in the procedure involves component analysis of each individual participant’s raw EEG file. Component Analysis of High-Density EEG Data The EEG may be synchronized to specific environmental, internal, or physical events. Such potential changes related to a specific event are termed “event-related potentials (ERPs). ” The ERP is hypothesized to be a function of the cognitive or physiological activity surrounding the event. The event-related changes in EEG are small Cortical Source Localization 7 relative to the overall ongoing EEG activity. Thus, the ERP cannot be seen on a single trial because it is hidden by irrelevant EEG activity (signal-to-noise is low). However, the ERP activity is consistent across multiple events whereas irrelevant EEG activity is random. Thus, one way to identify the consistent activity is to average the EEG across a specifically defined time-window surrounding repeated presentations of the event of interest. ERP averaging increases the signal of the electrical potential related to the event over the noise inherent in EEG activity. An alternative approach is to use component analysis (principal component analysis; independent component analysis) to identify the event-related activity on single trials. Principal component analysis (PCA) and independent component analysis (ICA) are multivariate component analysis approaches for identifying components within the EEG for source localization. A common assumption to both approaches is that the scalp current observed in the EEG is a linear combina