Localizing human visual gamma-band activity in frequency, time and space

Hoogenboom, Nienke; Schoffelen, Jan Mathijs; Oostenveld, Robert; Parkes, Laura M.; Fries, Pascal

doi:10.1016/j.neuroimage.2005.08.043

Cited by 450 publications

(529 citation statements)

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“…These locations are consistent with sources in the foveal confluence of the early visual areas V1, V2 and V3 (Dougherty et al, 2003). Taken together with the results of the present study, these observations support the proposition that the amplitude of the evoked EEG gamma-band response is positively related to stimulus size, and probably reflects the size-dependent activation of cortical areas in retinotopic visual cortices (Busch et al, 2004;Hoogenboom et al, 2006).…”

Section: Effects Of Increasing Stimulus Size On Evoked Gamma Power Ansupporting

confidence: 91%

“…Recent EEG and MEG studies located the sources for early gamma-band responses in occipital areas (Gruber et al, , 2008, especially in the posterior ends of the calcarine sulci of the two hemispheres (Hoogenboom et al, 2006). These locations are consistent with sources in the foveal confluence of the early visual areas V1, V2 and V3 (Dougherty et al, 2003).…”

Section: Effects Of Increasing Stimulus Size On Evoked Gamma Power Ansupporting

confidence: 61%

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EEG gamma-band synchronization in visual coding from childhood to old age: Evidence from evoked power and inter-trial phase locking

Werkle‐Bergner

Shing

Müller

et al. 2009

Clinical Neurophysiology

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a b s t r a c tObjective: To investigate lifespan age differences in neuronal mechanisms of visual coding in the context of perceptual discrimination. Methods: We recorded EEG from 17 children (10-12 years), 16 younger adults (20-26 years), and 17 older adults (70-76 years) during a simple choice-reaction task requiring discrimination of squares and circles of different sizes. We examined age-group differences in the effect of stimulus size on early ERP components, evoked gamma-band power, and inter-trial phase-stability in the gamma band as assessed by the phase-locking index (PLI). Results: In the absence of age differences in discrimination accuracy, we observed reliable age differences in patterns of ERP, evoked gamma power, and PLI. P1 and N1 peak amplitudes were larger and the peak latencies longer in children than in adults. Children also showed lower levels of evoked power and PLI than adults. Older adults showed smaller increments in evoked power with increasing stimulus size than younger adults, but similar amounts of phase locking for small-and medium-sized stimuli as younger adults. Conclusions: The relative importance of different coding mechanisms in early visual areas changes from childhood to old age. Due to synaptic overproduction and immature myelination, the visual system of children is less entrained by incoming information, resulting in less synchronized neuronal responses. Adults primarily rely on sparse representations formed through experience-dependent temporally synchronized neuronal interactions. In old age, senescent decline in neuronal density and neurotransmitter availability further increase the reliance on temporally synchronized processing. Significance: Findings from this study defy the notion that sensory aging consists in a reversal of sensory development in childhood, and point to a high degree of age specificity in mechanisms of visual coding.

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Section: Effects Of Increasing Stimulus Size On Evoked Gamma Power Ansupporting

confidence: 91%

Section: Effects Of Increasing Stimulus Size On Evoked Gamma Power Ansupporting

confidence: 61%

EEG gamma-band synchronization in visual coding from childhood to old age: Evidence from evoked power and inter-trial phase locking

Werkle‐Bergner

Shing

Müller

et al. 2009

Clinical Neurophysiology

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“…Through translational research [Hall et al, 2005], gamma oscillations have been implicated in human sensory and cognitive function, as well as in neuropsychiatric disease [see Bosman et al, 2014; Phillips and Uhlhaas, 2015; Sedley and Cunningham, 2013, for reviews]. In the magnetoencephalographic (MEG) signal, sustained narrow‐band gamma oscillations are generated in visual cortex in response to simple contrast pattern stimuli [Adjamian et al, 2004; Hoogenboom et al, 2006]. These responses arise from the interaction between local excitatory and inhibitory networks, which are believed to shape the amplitude, as well as the peak frequency of gamma oscillations [Bartos et al, 2007; Gonzalez‐Burgos and Lewis, 2012].…”

Section: Introductionmentioning

confidence: 99%

“…Despite the use of optimally designed experimental paradigms, gamma responses in certain participants can be barely detectable or scarcely quantifiable [Hoogenboom et al, 2006; Muthukumaraswamy et al, 2010]. Therefore, our ability to disentangle the relationship between gamma oscillation frequency and other parameters depends on the accurate and reliable estimation of peak frequency.…”

Section: Introductionmentioning

confidence: 99%

Significant reductions in human visual gamma frequency by the gaba reuptake inhibitor tiagabine revealed by robust peak frequency estimation

Magazzini

Muthukumaraswamy

Campbell

et al. 2016

Human Brain Mapping

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The frequency of visual gamma oscillations is determined by both the neuronal excitation–inhibition balance and the time constants of GABAergic processes. The gamma peak frequency has been linked to sensory processing, cognitive function, cortical structure, and may have a genetic contribution. To disentangle the intricate relationship among these factors, accurate and reliable estimates of peak frequency are required. Here, a bootstrapping approach that provides estimates of peak frequency reliability, thereby increasing the robustness of the inferences made on this parameter was developed. The method using both simulated data and real data from two previous pharmacological MEG studies of visual gamma with alcohol and tiagabine was validated. In particular, the study by Muthukumaraswamy et al. [2013a] (Neuropsychopharmacology 38(6):1105–1112), in which GABAergic enhancement by tiagabine had previously demonstrated a null effect on visual gamma oscillations, contrasting with strong evidence from both animal models and very recent human studies was re‐evaluated. After improved peak frequency estimation and additional exclusion of unreliably measured data, it was found that the GABA reuptake inhibitor tiagabine did produce, as predicted, a marked decrease in visual gamma oscillation frequency. This result demonstrates the potential impact of objective approaches to data quality control, and provides additional translational evidence for the mechanisms of GABAergic transmission generating gamma oscillations in humans. Hum Brain Mapp 37:3882–3896, 2016. © 2016 Wiley Periodicals, Inc.

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“…Researchers have recently begun to adopt multitapers (Thomson, 1982;Percival and Walden, 1993;Mitra and Pesaran, 1999) for EEG analysis Hoogenboom et al, 2006), also see Fig 1b,e. In the multitaper method, the data are multiplied with special windows before the frequency decomposition.…”

Section: Specifications Of Analysis Methodsmentioning

confidence: 99%

Comparison of spectral analysis methods for characterizing brain oscillations

Vugt

Sederberg

Kahana

2007

Journal of Neuroscience Methods

140

101

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Spectral analysis methods are now routinely used in electrophysiological studies of human and animal cognition. Although a wide variety of spectral methods has been used, the ways in which these methods differ are not generally understood. Here we use simulation methods to characterize the similarities and differences between three spectral analysis methods: wavelets, multitapers and P episode . P episode is a novel method that quantifies the fraction of time that oscillations exceed amplitude and duration thresholds. We show that wavelets and P episode used side-by-side helps to disentangle length and amplitude of a signal. P episode is especially sensitive to fluctuations around its thresholds, puts frequencies on a more equal footing, and is sensitive to long but low-amplitude signals. In contrast, multitaper methods are less sensitive to weak signals, but are very frequencyspecific. If frequency-specificity is not essential, then wavelets and P episode are recommended.

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Localizing human visual gamma-band activity in frequency, time and space

Cited by 450 publications

References 50 publications

EEG gamma-band synchronization in visual coding from childhood to old age: Evidence from evoked power and inter-trial phase locking

EEG gamma-band synchronization in visual coding from childhood to old age: Evidence from evoked power and inter-trial phase locking

Significant reductions in human visual gamma frequency by the gaba reuptake inhibitor tiagabine revealed by robust peak frequency estimation

Comparison of spectral analysis methods for characterizing brain oscillations

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