Brain Waves

Electroencephalography

Neural oscillation is rhythmic or repetitive neural activity in the central nervous system. In individual neurons, oscillations can appear either as oscillations in membrane potential or as rhythmic patterns of action potentials, which then produce oscillatory activation of post-synaptic neurons. At the level of neural ensembles, synchronized activity of large numbers of neurons can give rise to macroscopic oscillations, which can be observed in the electroencephalogram (EEG).

Oscillatory activity in groups of neurons generally arise from feedback connections between the neurons that result in the synchronization of their firing patterns. The interaction between neurons can give rise to oscillations at a different frequency than the firing frequency of individual neurons. A well-known example of macroscopic neural oscillations is alpha activity, neural oscillations in the frequency range of 8–12 Hz arising from electrical activity of thalamic pacemaker. In lay terms, they are brain waves associated with feelings of relaxation.

Neural oscillations were observed by researchers as early as Hans Berger (the first to record human electroencephalograms in 1924), but their functional role is still not fully understood. The possible roles of neural oscillations include feature binding (linking different features of neuronal representations together), information transfer mechanisms (neural coding), and the generation of rhythmic motor output (central pattern generators are neural networks that produce rhythmic patterned outputs without sensory feedback). Over the last decades more insight has been gained, especially with advances in brain imaging. A major area of research in neuroscience involves determining how oscillations are generated and what their roles are. Oscillatory activity in the brain is widely observed at different levels of observation and is thought to play a key role in processing neural information. Numerous experimental studies indeed support a functional role of neural oscillations; a unified interpretation, however, is still lacking.

In general, oscillations can be characterized by their frequency, amplitude and phase. In large-scale oscillations, amplitude changes are considered to result from changes in synchronization within a neural ensemble, also referred to as local synchronization. In addition to local synchronization, oscillatory activity of distant neural structures (single neurons or neural ensembles) can synchronize. Neural oscillations and synchronization have been linked to many cognitive functions such as information transfer, perception, motor control, and memory.

Neural oscillations have been most widely studied in neural activity generated by large groups of neurons. Large-scale activity can measured by techniques such as electroencephalography (EEG). In general, EEG signals have a broad spectral content similar to pink noise (similar to white noise), but also reveal oscillatory activity in specific frequency bands. The first discovered and best-known frequency band is alpha activity (8–12 Hz) that can be detected from the occipital lobe during relaxed wakefulness and increases when the eyes are closed. Other frequency bands are: delta (1–4 Hz), theta (4–8 Hz), beta (13–30 Hz), and gamma (30–70 Hz) frequency band. Faster rhythms, such as gamma activity, have been linked to cognitive processing. Indeed, EEG signals change dramatically during sleep and show a transition from faster frequencies such as alpha waves to increasingly slower frequencies. Different sleep stages are commonly characterized by their spectral content. Consequently, neural oscillations have been linked to cognitive states, such as awareness and consciousness.

Neural oscillations are commonly studied from a mathematical framework and belong to the field of ‘neurodynamics,’ an area of research in the cognitive sciences that places a strong focus upon the dynamic character of neural activity in describing brain function. It considers the brain a dynamical system and uses differential equations to describe how neural activity evolves over time. In particular, it aims to relate dynamic patterns of brain activity to cognitive functions such as perception and memory.

The functions of neural oscillations are wide ranging and vary for different types of oscillatory activity. Examples are the generation of rhythmic activity such as a heartbeat and the neural binding of sensory features in perception, such as the shape and color of an object. Neural oscillations also play an important role in many neurological disorders, such as excessive synchronization during seizure activity in epilepsy or tremor in patients with Parkinson’s disease. Oscillatory activity can also be used to control external devises in brain-computer interfaces, in which subjects can control an external device by changing the amplitude of particular brain rhythmics.

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