Large-Scale Gamma-Band Phase Synchronization and Selective Attention

Doesburg, Sam M.; Roggeveen, Alexa B.; Kitajo, Keiichi; Ward, Lawrence M.

doi:10.1093/cercor/bhm073

Cited by 222 publications

(163 citation statements)

References 49 publications

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“…This result is supported by three sources of evidence: (i) tau expression is densely expressed in frontal regions (see Fig. 1C) as previously reported (Goerdert et al, 1989;Trojanowski et al, 1989;Santa-Maria et al, 2005;McMillan et al, 2008), (ii) anatomical studies have demonstrated the existence of a monosynaptic pathway from the hippocampus to the frontal cortex (Swanson, 1981;Ferino et al, 1987;Thierry et al, 2000), and (iii) gamma-band synchronization between distant brain regions, including the frontal lobe, has been involved in a variety of cognitive processes, such as perception, attentional selection, and memory (Desmedt and Tomberg, 1994;Von stein et al, 2000;Doesburg et al, 2008Doesburg et al, , 2009Sehatpour et al, 2008). Combining more specific cognitive tests with long-range gamma synchronization measurements could be a more adequate approach at providing novel insights into the role of tau in cognitive functions.…”

Section: Discussionsupporting

confidence: 78%

Role of tau protein on neocortical and hippocampal oscillatory patterns

et al. 2011

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ABSTRACT:Tau is a neuronal microtubule-associated protein implicated in microtubules stabilization, axonal establishment and elongation during neuronal morphogenesis. Because of its elevated expression in neocortical regions and hippocampus, tau might play a role in sculpting collective neural responses underlying slow and fast brain oscillations and/or long-range synchronization patterns between hippocampus and neocortex. To test this hypothesis, local field potentials were recorded in tau-deficient (tau 2/2 ) and wild-type mice from different neocortical regions and from the hippocampus during spontaneous motor exploratory behavior. We found that tau 2/2 mice showed hippocampal theta slowing and reduced levels of gamma long-range synchronization involving the frontal cortex. We hypothesize that the lack of normal phosphorylated tau during early stages of development might influence the maturation of parvalbumin interneurons affecting the spatiotemporal structure of long-range gamma synchronization. Also, the proper functioning of gap-junction channels might be compromised by the absence of tau in hippocampal networks. Altogether, these results provide novel insights into the functional role of tau protein in the formation of collective neural responses and emergence of neocortical-hippocampal interactions in the mammalian brain. V V C 2010 Wiley-Liss, Inc.

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Section: Discussionsupporting

confidence: 78%

Role of tau protein on neocortical and hippocampal oscillatory patterns

et al. 2011

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“…The key idea is that stimulus selection is achieved by establishing stable phase relationships of spiking activity among selected populations of neurons, enabling thereby effective communication across processing levels (Fries, 2005;Womelsdorf et al, 2007). In support of his hypothesis, there is now abundant evidence showing that gamma oscillations are modulated by attention both in monkeys Bichot et al, 2005;Taylor et al, 2005;Rotermund et al, 2009) and humans (Fell et al, 2002;Doesburg et al, 2008;Garcia-Garcia et al, 2010).…”

Section: Introductionmentioning

confidence: 97%

Gamma Responses Correlate with Temporal Expectation in Monkey Primary Visual Cortex

Lima¹,

Singer²,

Neuenschwander³

2011

J. Neurosci.

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Gamma oscillations have been linked to selective attention. Here, we investigate the effects of expecting a behaviorally relevant event (a change in the fixation point) on the oscillatory patterning of the local field potential and spiking responses in V1. Three protocols were used. In the first protocol, fixation point change occurred at a fixed time point, enabling predictions on task timing. In the second, fixation point change occurred in trial blocks either early or late in the trial, allowing us to compare responses during epochs of low and high expectation. Finally, we used a cue to indicate the upcoming fixation point change. All protocols led to an increase in gamma oscillations associated with alpha suppression when the monkeys expected an event in time. These effects were spatially widespread, since comparable results were observed for both central and peripheral visual representations in V1. Our findings indicate that expectations associated with perceptual decisions, motor responses, or upcoming reward may have a strong effect on the primary visual cortex, causing global, spatially nonselective modulation of gamma activity.

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“…These works were followed by efforts to develop better computational methods (see Gevins, 1988Gevins, , 1989Gevins et al, 1990;Perrin et al, 1989;Law et al, 1993a;Yao, 2002;Carvalhaes and Suppes, 2011) as well as attempts to combine the surface Laplacian with other methods (Kayser and Tenke, 2006b,a;Carvalhaes et al, 2009), making the technique increasingly popular among EEG researchers. For instance, modern applications include studies on generators of event-related potentials (Kayser and Tenke, 2006b,a), quantitative EEG (Tenke et al, 2011), spectral coherence , event-related synchronization/desynchronization (Del Percio et al, 2007), phase-lock synchronization (Doesburg et al, 2008), estimation of cortical connectivity (Astolfi et al, 2007), high-frequency EEG Fitzgibbon et al (2013), and brain-computer interface (Lu et al, 2013), just to mention a few.…”

Section: Introductionmentioning

confidence: 99%

The surface Laplacian technique in EEG: Theory and methods

Carvalhaes¹,

Barros

2015

International Journal of Psychophysiology

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This paper reviews the method of surface Laplacian differentiation to study EEG. We focus on topics that are helpful for a clear understanding of the underlying concepts and its efficient implementation, which is especially important for EEG researchers unfamiliar with the technique. The popular methods of finite difference and splines are reviewed in detail. The former has the advantage of simplicity and low computational cost, but its estimates are prone to a variety of errors due to discretization. The latter eliminates all issues related to discretization and incorporates a regularization mechanism to reduce spatial noise, but at the cost of increasing mathematical and computational complexity. These and several others issues deserving further development are highlighted, some of which we address to the extent possible. Here we develop a set of discrete approximations for Laplacian estimates at peripheral electrodes and a possible solution to the problem of multiple-frame regularization. We also provide the mathematical details of finite difference approximations that are missing in the literature, and discuss the problem of computational performance, which is particularly important in the context of EEG splines where data sets can be very large. Along this line, the matrix representation of the surface Laplacian operator is carefully discussed and some figures are given illustrating the advantages of this approach. In the final remarks, we briefly sketch a possible way to incorporate finite-size electrodes into Laplacian estimates that could guide further developments.

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Large-Scale Gamma-Band Phase Synchronization and Selective Attention

Cited by 222 publications

References 49 publications

Role of tau protein on neocortical and hippocampal oscillatory patterns

Role of tau protein on neocortical and hippocampal oscillatory patterns

Gamma Responses Correlate with Temporal Expectation in Monkey Primary Visual Cortex

The surface Laplacian technique in EEG: Theory and methods

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