Recently, event-related neuroelectric oscillations have provided important tools with which to study information processing in the brain and with which to enrich our knowledge of brain maturation and cognitive develop- ment. The essential advantages of this approach are the ability to (1) ana- lyze neuroelectric responses reflecting mechanisms of stimulus information processing in comparison to electrical activity in a passive state reflecting the neurobiological maturation of the brain; (2) refine electrophysiological correlates of information processing by separating functionally different but simultaneously generated responses from different frequency ranges; and (3) reveal differential developmental dynamics of the power and synchronization of neuroelectric responses, thus providing information about independent neurophysiological mechanisms during biological and cognitive develop- ment.
In this chapter, the conceptual background of event-related oscillations will be presented with a major focus on their relevance for developmental research, followed by methods, analytic tools, and parameters for assessment of event-related oscillations. Finally, major findings on the development of the delta, theta, alpha, and gamma response systems in the brain will be described.
Event-Related Potentials
The electroencephalogram (EEG) is a time-varying signal reflecting the sum- mated neuroelectric activity from various neural sources in the brain during rest or functional activation. An EEG response that occurs in association with an eliciting event (sensory or cognitive stimulus) is defined as an event-related 15
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potential (ERP). However, the ERP may contain EEG activity not related to specific event processing, as well as electric activity from non-neural sources. To extract the EEG response elicited specifically by the event, an averaging procedure is applied with the assumption that the stimulus-locked event- related EEG activity is invariant while the electric activity not related to the event is random. In this way, the stimulus-locked EEG signal is emphasized while random components are attenuated by the averaging (Regan,1989; Ruchkin,1988).
The averaged ERP is typically analyzed in the time domain. It consists of consecutive positive and negative deflections called ERP components. Time- domain ERP components are characterized by their polarity, peak latency, distribution over the scalp, and specific sensitivity to experimental variables ( Picton et al.,2000; Picton & Stuss,1980; Regan,1989). As ERP components have been related to a variety of sensory and cognitive processes, they are commonly used in psychological and clinical research to study brain func- tioning (see e.g., Polich,1998; Regan,1989).
Event-Related EEG Oscillations
Based on the existence of oscillatory electric phenomena in the brain, ERP components have been proposed to originate from the spontaneous EEG rhythms and to reflect a superposition of oscillatory EEG responses in various frequency ranges (Basar,1980,1992,1998). It has been assumed that the EEG results from the activity of generators producing rhythmic oscillations in sev- eral frequency ranges. These oscillators are usually active in an uncorrelated manner. However, by application of sensory stimulation, these generators become coupled and act together coherently. The synchronization of EEG activity gives rise to evoked or induced responses in defined frequency ranges (Basar,1980). Experimental data have supported this model by demonstrat- ing that after external and/or internal stimulation, oscillatory EEG poten- tials in different frequency bands (delta ≈ 0.5–4 Hz, theta ≈ 4–7 Hz, alpha≈ 7–13 Hz, beta ≈ 15–30 Hz, gamma ≈ 30–70 Hz) can be recorded from cortical and subcortical structures in both humans and animals (Basar, 1980,1998; Basar et al., 1997a; Kahana et al., 2001; Makeig, 2002; Pantev et al.,1994). These oscillatory potentials associated with external or internal events are called frequency EEG responses, or event-related oscillations. They can be extracted from the ERP by appropriate analytic procedures (Basar, 1998; Samar et al.,1995).
ERP components can be regarded as originating from a transition from a disordered to an ordered state of bioelectric signals in the brain, i.e., as
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Event-Related Brain Oscillations in Normal Development 17
originating from the reorganization of the ongoing EEG after sensory- cognitive input (Basar,1980; Sayers et al.,1974). The simultaneous occur- rence and superposition of various EEG frequency responses are proposed to produce the time-domain ERP components (Basar,1992,1998). Recently, this concept has found strong support from neuronal (Arieli et al.,1995) and EEG/ERP recordings (Basar et al.,1997b; Makeig et al.,2004). Within this framework, the most important indices of event-related reorganization of the ongoing EEG in a given frequency channel are (1) power or amplitude changes (increase or decrease) in the post-stimulus period relative to pre- stimulus EEG, and (2) phase-reordering and phase-locking in relation to a stimulus (Yordanova & Kolev,1998a).
The Rule of Brain Response Susceptibility: Links to Developmental and Psychopathology Studies
If ERPs originate from the reorganization of the ongoing EEG activity upon application of a sensory-cognitive input (Basar, 1980), the ongoing EEG may modulate the brain’s reactions to sensory-cognitive stimulation (Basar et al.,1997b). Accordingly, as indicated in the principle of ‘brain response susceptibility’ or ‘excitability of brain tissue’, if a neural population shows spontaneous activity in a given frequency range, it can be excited in the same frequency range by sensory stimuli (Basar,1980,1992; Basar-Eroglu et al., 1994; Kolev et al.,1994a).
The spontaneous oscillatory activity of the brain depends on several fac- tors including the vigilance and/or cognitive state, the presence of pathology, and the participant’s age. Since the age of the participant is one of the most important factors for changes in amplitude and frequency of the EEG from childhood to late adulthood (Niedermeyer,1993,1997), the evoked oscilla- tory potentials can be expected to undergo some predictable changes with increasing age.
Developmental Changes in the Spontaneous EEG Activity
Developmental changes in the spontaneous EEG in children have been pre- viously described, with the consistent finding that age-related reduction of the spontaneous EEG activity in the slower (delta, theta) frequency bands is accompanied by an increase in the faster (alpha, beta) frequency bands (John et al.,1980; Matouˇsek & Peters´en,1973; Niedermeyer,1993,1997; Peters´en & Eeg-Olofsson, 1971). In regards to slow (theta) EEG activity, measure- ment of spontaneous EEG (using relative power spectra) has demonstrated
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that theta activity is present in each age group from 6 to 17 years, but its developmental reduction is accompanied by a complementary (substituting) increase in fast alpha activity (Gasser et al.,1988). Accordingly, the devel- opmental dynamics of the alpha activity in the spontaneous EEG include a shift of spectral alpha peak to higher frequencies from the alpha range (Niedermeyer,1997). Spontaneous gamma EEG in 3- to 12-year-old chil- dren manifests a power increase between 3 and 4 years at all leads, especially over the frontal region, and reaches a maximum at 4 to 5 years of age (Takano & Ogawa,1998). Thus, the power and frequency content of the spontaneous EEG undergo essential developmental alterations. According to the principle of brain response susceptibility, these alterations can be expected to affect the oscillations generated in relation with event processing.
Summary
Spontaneous EEG rhythms reflect the neurobiological background of the frequency-specific networks in the brain, whereas their reorganization is strongly modulated by the mode of event processing. Thus, analysis of both the spontaneous and event-related oscillations would indicate whether devel- opmental changes in cognitive stimulus processing may be associated with (1) basic alterations of the neurobiological substrate mediating the devel- opment of cognitive functions, (2) processes activated only upon specific processing demands, or (3) both.