Post-Movement Beta Activity in Sensorimotor Cortex Indexes Confidence in the Estimations from Internal Models

Tan, Huiling; Wade, Cian; Brown, Peter

doi:10.1523/jneurosci.3204-15.2016

Cited by 213 publications

(242 citation statements)

References 55 publications

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“…A plausible and parsimonious way to reconcile seemingly disparate findings would be to posit that the internal state variable for timing in motor execution always contributes to the uncertainty in motor execution. This would be consistent with reports of β power in motor execution tasks (Tan et al, 2016), the more specific observations that β power fluctuates according to uncertainty and predictability in motor timing (Meijer et al, 2016;Tzagarakis, et al, 2010) and, more generally, in many explicit motor timing tasks (e.g. Fujioka et al, 2012).…”

Section: β Power As a Signature State Variable For Fojsupporting

confidence: 89%

“…However, it is important to add a few more observations, so as to not trivialize the importance of β power as passive motor rebound, notably in light of recent studies indicating active cognitive components encoded in the β rebound (Tan et al, 2016). First, we found no significant impact of simultaneous EMG in the β effect that was indicative of FOJ, providing no evidence for the implication of the strength or afferent feedback confounded with time estimation.…”

Section: β Power a Marker Of State Variable Coding For Timementioning

confidence: 61%

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Temporal metacognition as the decoding of self-generated brain dynamics

Kononowicz

Roger

Wassenhove

2017

Preprint

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(150 words)Metacognition, the ability to know about one's thought process, is self-referential. Here, we studied the brain mechanisms underlying metacognitive inferences in a self-generated behavior. Human participants generated a time interval, and evaluated the signed magnitude of their timing (first and second order behavioral judgments, respectively) while being recorded with time-resolved neuroimaging. We show that the first-and second-order judgments relied on the power of beta oscillations (β; 15-40 Hz), while error monitoring subsystems engaged alpha oscillations (α; 8-14 Hz). The spread of an individual's β power state-space trajectories during timing was indicative of the individual's metacognitive inference. Our results suggest that network inhibition (β power) instantiates a state variable determining future network trajectory; this naturally provides a code for duration and metacognitive inferences would consist in reading out this state variable. Altogether, our study describes oscillatory mechanisms for timing suggesting that temporal metacognition relies on inferential processes of self-generated dynamics.

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Section: β Power As a Signature State Variable For Fojsupporting

confidence: 89%

Section: β Power a Marker Of State Variable Coding For Timementioning

confidence: 61%

Temporal metacognition as the decoding of self-generated brain dynamics

Kononowicz

Roger

Wassenhove

2017

Preprint

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“…Following these erroneous responses, an optimal behavioural strategy would likely involve increasing the decision threshold for subsequent trials to avoid repeating the same mistake. We did not find a significant difference between correct and error trials when examining the post-response beta rebound in the STN, which has previously been implicated in across-trial adaptations (Tan et al, 2014, 2016). Instead, our data suggest that such adaptations may be mediated by other brain regions such as the mPFC, which then may lead to differences within the STN on subsequent trials.…”

Section: Discussioncontrasting

confidence: 77%

“…Finally, errors necessarily imply some uncertainty regarding what the predicted outcome of an action was, or will be. Recent evidence has demonstrated that both internally generated and externally induced errors during sensorimotor adaptation tasks result in attenuations of the post-response increases in mPFC beta power, thereby linking these changes in mPFC beta power to this aspect of cognitive control (Tan et al, 2016). …”

Section: Discussionmentioning

confidence: 99%

Cognitive control involves theta power within trials and beta power across trials in the prefrontal-subthalamic network

Zavala

Jang

Trotta

et al. 2018

Brain

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There is increasing evidence that the medial prefrontal cortex participates in conflict and feedback monitoring while the subthalamic nucleus adjusts actions. Yet how these two structures coordinate their activity during cognitive control remains poorly understood. We recorded from the human prefrontal cortex and the subthalamic nucleus simultaneously while participants (n = 22) performed a novel task involving high conflict trials, complete response inhibition trials, and trial-to-trial behavioural adaptations to conflict and errors. Overall, we found that within-trial adaptions to both conflict and complete response inhibition involved changes in the theta band while across-trial behavioural adaptations to both conflict and errors involved changes in the beta band (P < 0.05). Yet the role each region’s theta and beta oscillations played during the task differed significantly between the two sites. Trials that involved either within-trial conflict or complete response inhibition were associated with increased theta phase synchrony between the medial prefrontal cortex and the subthalamic nucleus (P < 0.05). Despite increased synchrony, however, increases in prefrontal theta power were associated with response inhibition, while increases in subthalamic theta power were associated with response execution (P < 0.05). In the beta band, post-response increases in prefrontal beta power were suppressed when the completed trial contained either conflict or an erroneous response (P < 0.05). Subthalamic beta power, on the other hand, was only modified during the subsequent trial that followed a conflict or error trial. Notably, these adaptation trials exhibited slower response times (P < 0.05), suggesting that both brain regions contribute to across-trial adaptations but do so at different stages of the adaptation process. Taken together, our data shed light on the mechanisms underlying within-trial and across-trial cognitive control and how disruption of this network can negatively impact cognition. More broadly, however, our data also demonstrate that the specific role of a brain region, rather than the frequency being utilized, governs the behavioural correlates of oscillatory activity.

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“…Conversely, exaggerated and overly consistent beta synchrony is antikinetic, whether achieved though Parkinson's pathology [Little et al, 2012] or direct stimulation [Pogosyan et al, 2009]. 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].…”

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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Post-Movement Beta Activity in Sensorimotor Cortex Indexes Confidence in the Estimations from Internal Models

Cited by 213 publications

References 55 publications

Temporal metacognition as the decoding of self-generated brain dynamics

Temporal metacognition as the decoding of self-generated brain dynamics

Cognitive control involves theta power within trials and beta power across trials in the prefrontal-subthalamic network

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

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