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Neural oscillations

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The concept of neural oscillations is close to the concept of brain waves. However, the latter usually refers to EEG recordings obtained from the skull, and the former refers to more invasive recording techniques such as single-unit recordings with extracellular electrodes, intracellular recordings of neuronal potentials and recordings of local field potentials (LFPs) using electrodes directly contacting the brain. Neuronal oscillations are quite typical for brain cells and neural ensembles. They occur at different frequency ranges, in different brain areas, and some type of oscillations have been related to particular behaviors.

Visual system

Neuronal oscillations became a hot topic in Neuroscience in the 1990s when the studies of the visual system of the brain by Gray, Singer and others appeared to support neural binding hypothesis. According to this idea, synchronous oscillations in neuronal ensembles bind neurons representing different features of an object. For example, when a person looks at a tree, visual cortex neurons representing the tree trunk and those representing the branches of the same tree would oscillate in synchrony to form a single representation of the tree (for the recent development see Fingelkurts An.A. and Fingelkurts Al.A., Operational architectonics of the human brain biopotential field: Towards solving the mind-brain problem. Brain and Mind. 2001. 2(3):261-296).

Olfactory System

In a series of elegant papers beginning in 1994, Gilles Laurent and his colleagues at the California Institute of Technology showed that oscillations exist in the brain of the locust, that different odors lead to different subsets of neurons firing on different sets of oscillatory cycles (Wehr and Laurent, 1996), that the oscillations can be disrupted by GABA blocker picrotoxin (MacLeod and Laurent, 1996), that disruption of the oscillatory synchronization leads to impairment of behavioral discrimination of chemically similar odorants in bees (Stopfer et al., 1997) and to more similar responses across odors in downstream β-lobe neurons (MacLeod et al., 1998).

Motor system

Oscillations have been also reported in the motor system. Murthy and Fetz (1992) described motor cortical oscillations in monkey cortex when the monkeys performed motor acts that required significant attention (retrieval of raisins from unseen locations). Similar oscillations were observed in motor cortex during periods of immobility by the groups of John Donoghue and Roger Lemon.

Oscillating neurons have been also reported in somatosensory cortex (Mikhail Lebedev and Randall Nelson) and in premotor cortex (Mikhail Lebedev and Steven Wise). In these cortical areas, 20-40 Hz oscillations are often observed during periods of attentive immobility, and they typically disappear during movements.

Large-scale oscillations

Oscillations recorded from multiple cortical areas can become synchonized and form a large-scale network, whose dynamics and functional connectivity can be studied by means of spectral analyses (Fingelkurts et al., [2003]), Granger causality (Andrea Brovelli, Steven L. Bressler and their colleagues, 2004), and operational synchrony (Fingelkurts and Fingelkurts, [2001]; [2005]) measures.

Brain-computer interface

Pesaran, Andersen and their colleagues suggested that neural oscillations can be used as a control signal for brain-computer interfaces because oscillatory pattern depends on the direction of movement that the monkey prepares to execute. Recent study of Rickert and colleagues (2005) supports this suggestion.

Oscillations and perception

Neural oscillations may have different functional roles in different brain areas, and their functional role continues to be a matter of debate.  Neural oscillations have been hypothesized to be involved  in the sense of time (Buhusi and Meck, 2005) and in somatosensory perception (Ahissar and Zacksenhouse, 2001) among other functions.

Neuronal mechanisms of oscillations

Neuronal mechanisms of oscillations are complex. Scientists suggest that both intrinsic neuronal properties (Rodolfo Llinas and colleagues, 1991) and neural network properties are involved.

References

 


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