Very Slow EEG Fluctuations Predict the Dynamics of Stimulus Detection and Oscillation Amplitudes in Humans

Monto, Simo; Palva, Satu; Voipio, Juha

doi:10.1523/jneurosci.1910-08.2008

Cited by 420 publications

(476 citation statements)

References 31 publications

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“…Our findings complement recent findings showing that accurate phase encoding of temporal event structure affords predictability (Schroeder and Lakatos, 2009;Stefanics et al, 2010) and enhances task performance (Busch et al, 2009;Monto et al, 2008;Neuling et al, 2012;Romei et al, 2012;Varela et al, 1981). Our results further suggest that mechanisms analogous to phase precession in the hippocampus may be used in cortex for the encoding of event timing.…”

Section: Resultssupporting

confidence: 91%

“…It is well known that distinct phases of low-frequency neural oscillations are associated with periods of high and low neural excitability (Buzsáki, 2010;Lakatos et al, 2008). These fluctuations have been shown to impose temporal constraints on the "what" of perception by modulating the perceptual detection threshold of various stimuli (Busch et al, 2009;Fiebelkorn et al, 2013;Henry and Obleser, 2012;Monto et al, 2008;Neuling et al, 2012). They have also been proposed to serve parsing and informational chunking of sensory information over time (VanRullen and Koch, 2003) notably for complex temporal structures such as speech (Giraud and Poeppel, 2012).…”

Section: Introductionmentioning

confidence: 99%

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Encoding of event timing in the phase of neural oscillations

2014

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a b s t r a c t a r t i c l e i n f oTime perception is a critical component of conscious experience. To be in synchrony with the environment, the brain must deal not only with differences in the speed of light and sound but also with its computational and neural transmission delays. Here, we asked whether the brain could actively compensate for temporal delays by changing its processing time. Specifically, can changes in neural timing or in the phase of neural oscillation index perceived timing? For this, a lag-adaptation paradigm was used to manipulate participants' perceived audiovisual (AV) simultaneity of events while they were recorded with magnetoencephalography (MEG). Desynchronized AV stimuli were presented rhythmically to elicit a robust 1 Hz frequency-tagging of auditory and visual cortical responses. As participants' perception of AV simultaneity shifted, systematic changes in the phase of entrained neural oscillations were observed. This suggests that neural entrainment is not a passive response and that the entrained neural oscillation shifts in time. Crucially, our results indicate that shifts in neural timing in auditory cortices linearly map participants' perceived AV simultaneity. To our knowledge, these results provide the first mechanistic evidence for active neural compensation in the encoding of sensory event timing in support of the emergence of time awareness.

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Section: Resultssupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Encoding of event timing in the phase of neural oscillations

2014

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“…Furthermore, we were not limited to only sensorimotor ROIs in our approach. The interconnected nature of the activity structure of infraslow and slow activity is consistent with a cross-frequency phase-amplitude coupling relationship that has previously been indicated for infraslow fluctuations in EEG and MEG recordings in human subjects [13][14][15]60 .…”

Section: Discussionsupporting

confidence: 87%

“…In the developing brain, electrophysiological infraslow activity in the form of neuronal activity transients or bursting activity has been linked with the development of neuronal networks 11,12 , whereas in the adult brain, infraslow activity has been demonstrated to synchronize with higher-frequency brain activity 13,14 and to correlate to variability in behavioural performance 15,16 . Renewed focus on the nature of spontaneous resting-state infraslow activity has been precipitated due to an immense proliferation of functional neuroimaging studies that have revealed much about the brain's functional organization and have identified what has been described as the brain's Default Mode Network (DMN) 17 , a network of brain structures that are coherently, highly active at rest and reduced during active task performance 18 .…”

mentioning

confidence: 99%

Mesoscale infraslow spontaneous membrane potential fluctuations recapitulate high-frequency activity cortical motifs

et al. 2015

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Neuroimaging of spontaneous, resting-state infraslow (o0.1 Hz) brain activity has been used to reveal the regional functional organization of the brain and may lead to the identification of novel biomarkers of neurological disease. However, these imaging studies generally rely on indirect measures of neuronal activity and the nature of the neuronal activity correlate remains unclear. Here we show, using wide-field, voltage-sensitive dye imaging, the mesoscale spatiotemporal structure and pharmacological dependence of spontaneous, infraslow cortical activity in anaesthetized and awake mice. Spontaneous infraslow activity is regionally distinct, correlates with electroencephalography and local field potential recordings, and shows bilateral symmetry between cortical hemispheres. Infraslow activity is attenuated and its functional structure abolished after treatment with voltage-gated sodium channel and glutamate receptor antagonists. Correlation analysis reveals patterns of infraslow regional connectivity that are analogous to cortical motifs observed from higher-frequency spontaneous activity and reflect the underlying framework of intracortical axonal projections.

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“…Moreover, VLFOs are thought to contribute to inter-trial variability in evoked responses and behaviour Monto et al, 2008;Demanuele et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Neuronal oscillations in the EEG under varying cognitive load: A comparative study between slow waves and faster oscillations

Demanuele

Broyd

Sonuga‐Barke

et al. 2013

Clinical Neurophysiology

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the support of our participants, Suzannah Helps (Developmental Brain-Behaviour Laboratory, School of Psychology, University of Southampton, UK) for her contributions to the task design, and Daniel Durstewitz (Central Institute of Mental Health, Mannheim, Germany) for useful comments on the manuscript. We also thank all three anonymous reviewers for their constructive comments. AbstractObjective: This study has been specifically designed to investigate very low frequency neuronal oscillations (VLFO, <0.5 Hz) during resting states and during goal-directed tasks of graded difficulty levels, quantify the changes that the slow waves undergo in these conditions and compare them with those for higher frequency bands (namely delta, theta and alpha).Methods: To this end we developed a multistage signal processing methodology comprising blind source separation coupled with a neural network based feature extraction and classification method.Results: Changes in the amplitude and phase of brain sources estimates in the VLF band between rest and task were enhanced with increased task difficulty, but remained lower than those experienced in higher frequency bands. The slow wave variations were also significantly correlated with task performance measures, and hence with the level of task-directed attention.Conclusions: These findings suggest that besides their prominent sensitivity to external stimulation, VLFOs also contribute to the cortical ongoing background activity which may not be specifically related to task-specific attention and performance.Significance: Our work provides important insight into the association between VLF brain activity and conventional EEG frequency bands, and presents a novel framework for assessing neural activity during various mental conditions and psychiatric states. Highlights• We present a novel approach for exploring the functional relationship between very low frequency EEG oscillations (VLFO, <0.5 Hz) recorded at rest and those following the transition to goaldirected tasks of graded difficulty levels.• We show that slow waves (i) are attenuated but not extinguished following a rest to task transition, and (ii) are sensitive to variations in cognitive load; (iii) the rest-to-task changes in the slow wave band correlate with performance measures and (iv) the changes are lower than those in higher frequency bands, tentatively suggesting the VLFOs' contribution to the cortical ongoing background activity.• We present a new signal processing methodology for quantifying changes in band-limited EEG activity -this method, developed to gain insight into the neurophysiological role of the slow waves, could be explored with respect to altered functioning of brain oscillators in psychiatric and neurobehavioural disorders such as schizophrenia and ADHD. C. Demanuele et al., 20123

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Very Slow EEG Fluctuations Predict the Dynamics of Stimulus Detection and Oscillation Amplitudes in Humans

Cited by 420 publications

References 31 publications

Encoding of event timing in the phase of neural oscillations

Encoding of event timing in the phase of neural oscillations

Mesoscale infraslow spontaneous membrane potential fluctuations recapitulate high-frequency activity cortical motifs

Neuronal oscillations in the EEG under varying cognitive load: A comparative study between slow waves and faster oscillations

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