Beta-band oscillations — signalling the status quo?

Engel, Andreas K.; Fries, Pascal

doi:10.1016/j.conb.2010.02.015

Cited by 2,379 publications

(2,294 citation statements)

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“…The increase in beta phase-locking in the STS was seen conjointly with an increase in gamma activity locally and in lower-tier sensory areas. This supports the proposal that the beta range is involved in inter-areal coupling 17,[21][22][23] , and more specifically used in feedback projections 24,25 , and further suggests that the gamma range serves to propagate prediction error forward. …”

supporting

confidence: 81%

Transitions in neural oscillations reflect prediction errors generated in audiovisual speech

2011

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According to the predictive coding theory, top-down predictions are conveyed by backward connections and prediction errors are propagated forward across the cortical hierarchy. Using MEG in humans, we show that violating multisensory predictions causes a fundamental and qualitative change in both the frequency and spatial distribution of cortical activity. When visual speech input correctly predicted auditory speech signals, a slow delta regime (3-4 Hz) developed in higher-order speech areas. In contrast, when auditory signals invalidated predictions inferred from vision, a low-beta (14-15 Hz) / high-gamma (60-80 Hz) coupling regime appeared locally in a multisensory area (area STS). This frequency shift in oscillatory responses scaled with the degree of audio-visual congruence and was accompanied by increased gamma activity in lower sensory regions. These findings are consistent with the notion that bottom-up prediction errors are communicated in predominantly high (gamma) frequency ranges, whereas top-down predictions are mediated by slower (beta) frequencies.© 2011 Nature America, Inc. All rights reserved.7 9 8 VOLUME 14 | NUMBER 6 | JUNE 2011 nature neurOSCIenCe a r t I C l e S converge-that is, where multisensory predictions are generatedwhereas gamma activity was seen in lower sensory cortices where prediction errors emerge and are propagated forward. RESULTSWe presented 15 subjects with stimuli in one of three conditions: videos (audio-visual: AV condition) of a speaker pronouncing the syllables /pa/, / a/, /la/, /ta/, /ga/ and /fa/ (International Phonetic Alphabet notation); an auditory track of these videos combined with a still face (auditory: A condition); or a mute visual track (visual: V condition). The videos could be either natural or a random combination of auditory and visual tracks, creating conditions in which auditory and visual tracks were congruent (AVc condition) and ones in which they were incongruent (AVi condition; see Online Methods and Supplementary Fig. 1). Incongruent combinations yielding fusion illusory percepts-that is, McGurk stimuli-were excluded 8,11 . Subjects performed an unrelated target detection task on the syllable /fa/ that was presented in A, V or AVc form in 13% of the trials (97% correct detection). These trials were subsequently excluded from the analyses. The five other syllables were chosen because they yielded graded recognition accuracy when presented visually (Fig. 1a), resulting from an increasing predictiveness 10 . The phonological prediction conveyed by mouth movements (visemes) varies in specificity depending on the pronounced syllable. Typically, syllables beginning with a consonant that is formed at the front of the mouth (/p/, /m/) convey a more specific prediction than those formed at the back (/g/, /k/, /r/, /l/) 8 . Our second experimental factor pertained to the validity of the visual prediction with respect to the auditory input. Physically, the audio-visual stimuli could be either congruent (valid prediction) or incongruent (invalid prediction), w...

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confidence: 81%

Transitions in neural oscillations reflect prediction errors generated in audiovisual speech

2011

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“…Physiological beta synchrony is promoted in expectation of impending perturbation to a desired posture [Androulidakis et al, 2007] but is also sensitive to the uncertainty of motor outcome estimation [Tan et al, 2016]. Beta oscillations may also contribute to long‐range communication across cortical regions [Engel and Fries, 2010; Kopell et al, 2000] and can facilitate modulation of selective attention in support of action selection [Grent‐'t‐Jong et al, 2013, 2014; Tzagarakis et al, 2010], beyond simple correlation with reaction times [van Ede et al, 2012]. The abnormalities in this characteristic motor system rhythm displayed by ALS patients (amplified beta desychronization and attenuated beta rebound) may reflect or even contribute to an excitotoxic degeneration of neural microcircuitry, particularly given the apparent correlation with rate of disease progression.…”

Section: Discussionmentioning

confidence: 99%

Altered cortical beta‐band oscillations reflect motor system degeneration in amyotrophic lateral sclerosis

Proudfoot

Rohenkohl

Quinn

et al. 2016

Human Brain Mapping

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Continuous rhythmic neuronal oscillations underpin local and regional cortical communication. The impact of the motor system neurodegenerative syndrome amyotrophic lateral sclerosis (ALS) on the neuronal oscillations subserving movement might therefore serve as a sensitive marker of disease activity. Movement preparation and execution are consistently associated with modulations to neuronal oscillation beta (15–30 Hz) power. Cortical beta‐band oscillations were measured using magnetoencephalography (MEG) during preparation for, execution, and completion of a visually cued, lateralized motor task that included movement inhibition trials. Eleven “classical” ALS patients, 9 with the primary lateral sclerosis (PLS) phenotype, and 12 asymptomatic carriers of ALS‐associated gene mutations were compared with age‐similar healthy control groups. Augmented beta desynchronization was observed in both contra‐ and ipsilateral motor cortices of ALS patients during motor preparation. Movement execution coincided with excess beta desynchronization in asymptomatic mutation carriers. Movement completion was followed by a slowed rebound of beta power in all symptomatic patients, further reflected in delayed hemispheric lateralization for beta rebound in the PLS group. This may correspond to the particular involvement of interhemispheric fibers of the corpus callosum previously demonstrated in diffusion tensor imaging studies. We conclude that the ALS spectrum is characterized by intensified cortical beta desynchronization followed by delayed rebound, concordant with a broader concept of cortical hyperexcitability, possibly through loss of inhibitory interneuronal influences. MEG may potentially detect cortical dysfunction prior to the development of overt symptoms, and thus be able to contribute to the assessment of future neuroprotective strategies. Hum Brain Mapp 38:237–254, 2017. © 2016 Wiley Periodicals, Inc.

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“…Corticomuscular beta-band coherence is most prominent during tonic muscle contractions and disappears during movement (Baker et al, 1997;Riddle and Baker, 2006;Kilner et al, 2000;Baker et al, 1999) and beta-band activity is enhanced when higher precision is required Kristeva-Feige et al, 2002;Witte et al, 2007;Gilbertson et al, 2005). These findings suggest that the beta-band activity is related to a mechanism that maintains the current sensorimotor state (Baker, 2007;Engel and Fries, 2010;Van Wijk et al, 2012).…”

Section: Introductionmentioning

confidence: 90%

“…from sustained contractions to dynamic force output (Engel and Fries, 2010). Here we test this hypothesis by investigating corticomuscular coherence while participants make fast transitions between two distinct force levels.…”

Section: Introductionmentioning

confidence: 97%

The reorganization of corticomuscular coherence during a transition between sensorimotor states

2014

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Recent research suggests that neural oscillations in di↵erent frequency bands support distinct and sometimes parallel processing streams in neural circuits. Studies of the neural dynamics of human motor control have primarily focused on oscillations in the beta band (15 30 Hz). During sustained muscle contractions, corticomuscular coherence is mainly present in the beta band, while coherence in the alpha (8 12 Hz) and gamma (30 80 Hz) bands has not been consistently found. Here we test the hypothesis that the frequency of corticomuscular coherence changes during transitions between sensorimotor states. Corticomuscular coherence was investigated in twelve participants making rapid transitions in force output between two targets. Corticomuscular coherence was present in the beta band during sustained contractions but vanished before movement onset, being replaced by transient synchronization in the alpha and gamma bands during dynamic force output. Analysis of the phase spectra suggested a time delay from muscle to cortex for alpha-band coherence, by contrast to a time delay from cortex to muscle for gamma-band coherence, indicating a↵erent and e↵erent corticospinal interactions respectively. Moreover, alpha and gamma -band coherence revealed distinct spatial topologies, suggesting di↵erent generative mechanisms. Coherence in the alpha and gamma bands was almost exclusively confined to trials showing a movement overshoot, suggesting a functional role related to error correction. We interpret the dual-band synchronization in the alpha and gamma bands as parallel streams of corticospinal processing involved in parsing prediction errors and generating new motor predictions.

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Beta-band oscillations — signalling the status quo?

Cited by 2,379 publications

References 79 publications

Transitions in neural oscillations reflect prediction errors generated in audiovisual speech

Transitions in neural oscillations reflect prediction errors generated in audiovisual speech

Altered cortical beta‐band oscillations reflect motor system degeneration in amyotrophic lateral sclerosis

The reorganization of corticomuscular coherence during a transition between sensorimotor states

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