Trends in Cognitive Sciences
OpinionBrain Networks and α-Oscillations: Structural and Functional Foundations of Cognitive Control
Section snippets
Challenging the Traditional View of α-Oscillations
Owing to their high amplitude relative to oscillatory neural activity in other frequency bands, ∼10 Hz oscillations (see Glossary) are easily detected. As such they were the first electrophysiological signal reported from human electroencephalography (EEG) and accordingly were named α-oscillations. For many decades, α-oscillations have largely been considered an epiphenomenal signature of an idling brain state [1]. According to this view, α-oscillations manifest when the brain is disengaged,
α-Band Oscillations
The many concurrent frequencies registered in human EEG cover a large range of speeds with a characteristic ‘power law’ spectral distribution: EEG log-power decreases roughly linearly with increasing log-frequency. Owing to its high amplitude, oscillatory activity near 10 Hz deviates from this power-law distribution by a characteristic protrusion. Most studies use a predefined α frequency range for all subjects, typically from 8 to 13 Hz. In some studies the α frequency band is defined
Cognitive Control Functions
The complex and multifaceted nature of cognitive control functions calls for a taxonomy to enable a neurobiological understanding. The cognitive architectures that have been proposed for such taxonomies commonly include a sustained and endogenously maintained type of top-down control process distinct from control processes that are phasic in nature. This sustained function is referred to as ‘vigilance’ [24], ‘vigilant attention’ [25], ‘sustained attention’ [26], or ‘tonic alertness’ [27]. In
Cognitive Control Networks
Large-scale networks refer to sets of distributed brain regions that span the spatially most expansive scale of functional interaction, commonly observed using functional magnetic resonance imaging (fMRI). Brain regions within each large-scale network usually increase activation in unison in response to task demands as well as during task-free resting states. This correlated activity is thought to reflect functional connectivity. In a task-free resting state, functional connectivity manifests
Cognitive Control Networks and Cognition
Neuroimaging findings suggest that the FP network supports phasic and adaptive aspects of cognitive control such as exogenously triggered initiation of control, adjusting control for instance after errors [28], and moment-to-moment executive control as in repeated rapid task-switching [29]. The DAT network is known to underlie top-down selective attention to specific stimulus features, for example as readily initiated by cues informing about content, spatial location, and timing of stimuli,
The α-Rhythm and Cognition
As described above, α-oscillations govern cortical excitability, and this effect is under top-down modulation. Evidence for an active role of these physiological mechanisms in cognitive control is emerging. During selective deployment of attention, spatially restricted reduction in α-oscillation power is observed over the cortical area processing the attended information in both invasive 18, 39 and non-invasive recordings 40, 41. For example, anticipation of a visual target at a cued location
The α-Rhythm and Cognitive Control Networks
The observations described above collectively suggest that α-oscillations impact on cognitive performance and play a role in top-down control functions such as selective attention and sustained alertness. Even so, which brain structures control the strength of α-band oscillations? Simultaneously recording α-oscillations by EEG, and localized brain activity by fMRI, can provide an answer. Although fMRI of course cannot trace activity modulations within the cycle length of the α-band, it is well
Proposed Model of the α-Rhythm as a Mechanism of Cognitive Control
Based on the role of α-oscillations in cognition described above, and the selective relation of these oscillations with the three core cognitive control networks, we suggest a comprehensive model of cognitive control mechanisms that is further illustrated in Figure 3. This model provides a neurobiological definition of the cognitive control functions as tonic alertness, selective attention, and adaptive control. In detail, the model includes the following features:
CO network activity and global
Functional Hierarchy
According to the model proposed here, the amplitude of widespread α-oscillations (under CO network control) affects the degree of impact from both focal de-synchronization (under DAT network control) and cross-region phase-locking (under FP network control). In other words, selective α-power reductions can only be effective relative to a background of high α power, and phase-locking of inhibitory cycles is only physiologically relevant if there are sufficiently strong α-oscillations. The
Concluding Remarks and Future Perspectives
In the suggested framework, α-band oscillations serve as mechanisms by which cognitive control networks exert top-down modulatory influences on local and distributed information processing. The framework thereby offers three advances–first, a detailed definition of the active role of α-band oscillations in cognition; second, a neurophysiologically anchored definition of psychological concepts as alertness, selective attention, and adaptive control; and third, a functional dissociation of
Acknowledgments
We thank Robert T. Knight, Mark D’Esposito, and Clio Coste for constructive discussions of the content. S.S is supported by the Carle Illinois Collaborative Research Seed Program. A.K. holds a Fondation Louis-Jeantet Professorship and has support from the Fonds National Suisse de la Recherche Scientifique (320030_149781).
Glossary
- Cognitive control
- an umbrella term for a group of regulatory functions that modulate information processing and information flow so as to map sensory inputs, internal states, and behavioral outputs according to goals.
- Electroencephalography (EEG)
- a (usually) noninvasive method to measure electrical brain signals most commonly from the scalp. These signals are thought to originate primarily from apical dendrites of radially oriented pyramidal neurons whose population activity is sufficiently strong
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