Human gamma-band activity: A review on cognitive and behavioral correlates and network models

Herrmann, Christoph S.; Fründ, Ingo; Lenz, Daniel

doi:10.1016/j.neubiorev.2009.09.001

Cited by 267 publications

(226 citation statements)

References 130 publications

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“…27 There is clinical and experimental evidence that gamma oscillations play an important role in epilepsy. 14 -19,28 -32 The generation of gamma oscillations appears related to the balance between tonic excitation (increased by the activation of NMDA receptor 31 ) and tonic inhibition (GABA A receptormediated inhibition) of interneurons, 30,33 which is the cornerstone of seizure generation.…”

Section: Fast Oscillations and Interictal Epileptiform Dischargesmentioning

confidence: 99%

Interictal scalp fast oscillations as a marker of the seizure onset zone

Andrade-Valença

Dubeau²,

Mari³

et al. 2011

Neurology

255

252

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Objective: This study aims to identify if oscillations at frequencies higher than the traditional EEG can be recorded on the scalp EEG of patients with focal epilepsy and to analyze the association of these oscillations with interictal discharges and the seizure onset zone (SOZ). Methods:The scalp EEG of 15 patients with focal epilepsy was studied. We analyzed the rates of gamma (40-80 Hz) and ripple (Ͼ80 Hz) oscillations, their co-occurrence with spikes, the number of channels with fast oscillations inside and outside the SOZ, and the specificity, sensitivity, and accuracy of gamma, ripples, and spikes to determine the SOZ.Results: Gamma and ripples frequently co-occurred with spikes (77.5% and 63% of cases). For all events, the proportion of channels with events was consistently higher inside than outside the SOZ: spikes (100% vs 70%), gamma (82% vs 33%), and ripples (48% vs 11%); p Ͻ 0.0001. The mean rates (events/min) were higher inside than outside the SOZ: spikes (2.64 Ϯ 1.70 vs 0.69 Ϯ 0.26, p ϭ 0.02), gamma (0.77 Ϯ 0.71 vs 0.20 Ϯ 0.25, p ϭ 0.02), and ripples (0.08 Ϯ 0.12 vs 0.04 Ϯ 0.09, p ϭ 0.04). The sensitivity to identify the SOZ was spikes 100%, gamma 82%, and ripples 48%; the specificity was spikes 30%, gamma 68%, and ripples 89%; and the accuracy was spikes 43%, gamma 70%, and ripples 81%. Conclusion:The rates and the proportion of channels with gamma and ripple fast oscillations are higher inside the SOZ, indicating that they can be used as interictal scalp EEG markers for the SOZ. These fast oscillations are less sensitive but much more specific and accurate than spikes to delineate the SOZ. Neurology The conventional range of EEG analysis usually involves frequencies below 40 Hz. Studies over the last decade suggest, however, that high-frequency oscillations (HFOs) may have an essential role in normal and pathologic brain function. Reports using microelectrodes combined with depth EEG electrodes showed the presence of HFOs in epileptic patients.

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Section: Fast Oscillations and Interictal Epileptiform Dischargesmentioning

confidence: 99%

Interictal scalp fast oscillations as a marker of the seizure onset zone

Andrade-Valença

Dubeau²,

Mari³

et al. 2011

Neurology

255

252

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“…Alpha waves (8 -12 Hz) are typically associated with a state of relaxed awareness and reduced cognitive processing, while beta waves (13 -30 Hz) are often associated with a state of active cognitive processing. Gamma waves (30 -80 Hz) are thought to be associated with the complex integration and processing of sensory stimuli, among other behaviors related to perception and awareness, memory, problem solving, and motor skills (Herrmann, Fründ, and Lenz, 2010;Reider et al, 2011). 5 The cognitive processing interpretation of alpha and beta waves partly has its basis in an EEG study by Galin and Ornstein (1972), who found evidence to suggest that a greater amount of alpha activity present in one hemisphere (as compared to the other) during a cognitive task was negatively correlated with that hemisphere's level of active engagement in the task (i.e., more alpha, less active engagement of the hemisphere).…”

Section: Eeg Monitoring and Functionalmentioning

confidence: 99%

Extrasensory Perception and the Brain Hemispheres: Where Does the Issue Stand Now?

Williams¹

2012

Neuroquantology

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For over a century, evidence has been gathered to indicate that the two cerebral hemispheres of the human brain each tend to have their own behavioral specializations. An issue that has long been of interest to parapsychologists is whether the ostensibly anomalous behavioral phenomenon of "extrasensory perception" (ESP), in which a person seems to obtain veridical information about other people, objects, places, or events beyond the range of the body's sensory-motor system, may be a specialized function of either of the brain hemispheres. To address this issue, a review of parapsychological experiments designed to explore the potential relevance of cerebral lateralization to ESP performance was initially conducted by Broughton in 1983. He generally concluded that, although there was some possible indication of a contribution to ESP by the right hemisphere, the results were mixed and possibly confounded by issues of interpretation. In a more concise review conducted in 2002, Alexander found that a limited number of experiments continued to indicate a right hemispheric tendency, although certain others separately indicated left hemispheric involvement. Thus, the issue is still clearly unresolved. This paper seeks to build upon these two previous reviews by providing an updated and broader review of the various findings obtained in the experiments that have been conducted up to the present time. Although several experiments continue to offer modest support for a right hemispheric contribution, general interpretation of the current database remains hindered by a wide degree of variability in experimental methods and outcomes, potentially confounding factors, and the scarcity of additional clarifying data. Thus, while the issue remains unresolved, there appear to be at least some potential avenues for progress in future experiments.

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“…In recent years, the role of neuronal oscillations and crossfrequency phase coupling, particularly in the theta (3)(4)(5)(6)(7)(8) and gamma bands, has been demonstrated in a variety of cognitive and sensorimotor tasks in humans involving working memory (Herrmann et al 2010), spatial navigation (Burke et al 2013), perceptual grouping (Gray et al 1989), visuomotor integration (Roelfsema et al 1997) and adaptation (Perfetti et al 2011). Similar phase coupling has been shown for working memory tasks in monkeys (Lee et al 2005) and for associative learning in rats (Tort et al 2009).…”

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confidence: 99%

Redistribution of neural phase coherence reflects establishment of feedforward map in speech motor adaptation

Sengupta

Nasir

2015

Journal of Neurophysiology

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Sengupta R, Nasir SM. Redistribution of neural phase coherence reflects establishment of feedforward map in speech motor adaptation. J Neurophysiol 113: 2471-2479, 2015. First published January 28, 2015 doi:10.1152/jn.00731.2014.-Despite recent progress in our understanding of sensorimotor integration in speech learning, a comprehensive framework to investigate its neural basis is lacking at behaviorally relevant timescales. Structural and functional imaging studies in humans have helped us identify brain networks that support speech but fail to capture the precise spatiotemporal coordination within the networks that takes place during speech learning. Here we use neuronal oscillations to investigate interactions within speech motor networks in a paradigm of speech motor adaptation under altered feedback with continuous recording of EEG in which subjects adapted to the real-time auditory perturbation of a target vowel sound. As subjects adapted to the task, concurrent changes were observed in the theta-gamma phase coherence during speech planning at several distinct scalp regions that is consistent with the establishment of a feedforward map. In particular, there was an increase in coherence over the central region and a decrease over the fronto-temporal regions, revealing a redistribution of coherence over an interacting network of brain regions that could be a general feature of error-based motor learning in general. Our findings have implications for understanding the neural basis of speech motor learning and could elucidate how transient breakdown of neuronal communication within speech networks relates to speech disorders. speech motor learning; neural oscillations; feedforward map AS WE LEARN TO SPEAK, THE auditory, somatosensory and motor areas of our brain operate in parallel to perceive speech stimuli, detect feedback errors and generate the motor commands necessary to achieve speech goals (Guenther 2006;Perkell 2012;Tourville et al. 2008). While this process is believed to involve coordinated activity over several distributed brain areas (Guenther 2006;Hickok et al. 2011;Scott and Wise 2004), the neural mechanisms underlying their precise spatiotemporal coordination remain elusive. The oscillatory dynamics inherent in the brain's electrical activity provide a suitable means to study the neural communication within brain networks (Golfinopoulos et al. 2010;Varela et al. 2011) at timescales relevant for speech. In this study, we provide evidence that brain oscillation patterns change as a result of speech motor adaptation, enabling us to probe into the neural basis of learning at finer temporal resolutions.In recent years, the role of neuronal oscillations and crossfrequency phase coupling, particularly in the theta (3-8 Hz) and gamma (30 -55 Hz) bands, has been demonstrated in a variety of cognitive and sensorimotor tasks in humans involv- (Schack et al. 2002). Based on these results, it has been proposed that communication within brain networks during behavior is facilitated by synchronous neuronal o...

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Human gamma-band activity: A review on cognitive and behavioral correlates and network models

Cited by 267 publications

References 130 publications

Interictal scalp fast oscillations as a marker of the seizure onset zone

Interictal scalp fast oscillations as a marker of the seizure onset zone

Extrasensory Perception and the Brain Hemispheres: Where Does the Issue Stand Now?

Redistribution of neural phase coherence reflects establishment of feedforward map in speech motor adaptation

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