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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Brain Topogr. Author manuscript; available in PMC 2010 November 22.
Published in final edited form as:
PMCID: PMC2989849

The Gamma Oscillation: Master or Slave?

While the involvement of gamma band (30–100 Hz) oscillations in perceptual “binding,” attentional amplification of representation and cross-areal communication, and several elaborate aspects of information encoding may be arguable, it does seem clear that gamma enhancement reflects a state of high neuronal excitability and synchrony, that is conducive or even critical for brain operations (Fries et al., 2007). This notion sets gamma up as a “master” or executor process that determines whether an input is effectively integrated and an effective output is generated. However, gamma amplitude (generally taken as synchrony) is often coupled to the phase of lower frequency delta or theta oscillations (Buzsaki and Draguhn, 2004;Canolty et al., 2006;Lakatos et al., 2005), which would make gamma a “slave” to lower frequency activity. This relationship is illustrated schematically in Figure 1a. Here, we discuss conditions in which gamma oscillations dynamically couple and de-couple with lower frequencies, in accord with task demands.

Fig. 1
A) Schematic of cross-frequency (phase-amplitude) coupling between delta, theta and gamma frequencies. The top (green) trace illustrates the typical observation: oscillations recorded in the brain are normally complex mixtures of components at different ...

Natural sensory stimulation has pervasive rhythms. The natural auditory environment has a 1/f spectrum and auditory cortical oscillatory activity appears tuned to this spectrum (Garcia-Lazaro et al., 2006), as does oscillatory activity throughout the brain (Buzsaki and Draguhn, 2004). Obviously, explicit rhythms are absent in static visual and somatosensory stimuli. However, task-relevant somatosensory and visual stimulation is usually “acquired” through the observer’s motor behavior (e.g., eye/hand movements), which imposes a rhythmic pattern on the input stream. In large part, this is because motor behavior is itself patterned by oscillatory mechanisms like the 10 Hz “µ” rhythm (Pfurtscheller et al., 2000;Pineda, 2005). Moreover, as best exemplified by human speech, motor outputs have complex rhythm structures in which higher frequencies are “nested” in lower frequencies, just as is seen in the hierarchical phase-amplitude coupling of the cortical electroencephalogram (EEG) (Schroeder et al., 2008). Thus, biologically-generated stimuli such as body movements and vocalizations, even if passively received, can impart a great deal of rhythm.

In order to enable the generation of adaptive behavior, the brain’s sensory operations are tied by selective attention to specific or “relevant” environmental objects and events. When task-relevant stimuli occur in rhythmic patterns, and/or are sampled by motor behavior as described above, the brain can operate in a rhythmic mode, simply entraining its low frequency rhythms to external event rhythms, and attention contributes by enforcing oscillatory entrainment to the task-relevant event stream. The reason that this is beneficial is that each oscillation cycle has high and low excitability phases lasting from 10’s of milliseconds for beta and alpha to 100’s of milliseconds for theta/delta (Fig. 1b), and entrainment aligns these transient windows of high excitability with the relevant stimuli (Fig. 1c-top), amplifying the neuronal representation and facilitating both sensory discrimination and response speed and accuracy (Lakatos et al., 2008;Schroeder and Lakatos, 2008). Stimuli occurring out-of-phase with the task-relevant event stream generate inputs that arrive in the brain during low excitability phases of the entrained oscillations, and are thus suppressed (Fig 1C-bottom). A key component of the high-excitability phase is enhancement of gamma amplitude/synchrony, and because gamma amplitude is coupled to lower frequency phase, there is effectively a burst of gamma occurring at the time an input from a task relevant event is expected. This is an efficient use of resources as gamma band activity appears to be more metabolically-demanding than low frequency oscillations (Mukamel et al., 2005;Niessing et al., 2005), and because of hierarchical coupling, gamma activity is “rationed,” or selectively enhanced at critical time points, when a high excitability state is most useful.

In contrast, when there is no task relevant rhythm that the system can entrain to, low frequency oscillations are actually detrimental to processing, as they entail long periods of low excitability during which detection of a subtle random stimulus is less likely. Under these conditions a continuous (vigilance) mode of operation is implemented, and attention maximizes the sensitivity of the system by suppressing lower frequency oscillations and exploiting the advantages of extended continuous gamma band oscillations (Borgers and Kopell, 2008). One might think that a system could optimize itself by just staying in a continuous vigilance mode, but it turns out that in line with the common subjective experience, the vigilance mode is difficult to maintain for extended periods. For a variety of reasons (Schroeder and Lakatos, 2008), the rhythmic seems to be the preferred mode of the system, in which it spends the most time. Thus, gamma may be more often slave than master.

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