A statistical framework for neuroimaging data analysis based on mutual information estimated via a gaussian copula

We begin by reviewing the statistical framework of information theory as applicable to neuroimaging data analysis. A major factor hindering wider adoption of this framework in neuroimaging is the difficulty of estimating information theoretic quantities in practice. We present a novel estimation technique that combines the statistical theory of copulas with the closed form solution for the entropy of Gaussian variables. This results in a general, computationally efficient, flexible, and robust multivariate statistical framework that provides effect sizes on a common meaningful scale, allows for unified treatment of discrete, continuous, unidimensional and multidimensional variables, and enables direct comparisons of representations from behavioral and brain responses across any recording modality. We validate the use of this estimate as a statistical test within a neuroimaging context, considering both discrete stimulus classes and continuous stimulus features. We also present examples of analyses facilitated by these developments, including application of multivariate analyses to MEG planar magnetic field gradients, and pairwise temporal interactions in evoked EEG responses. We show the benefit of considering the instantaneous temporal derivative together with the raw values of M/EEG signals as a multivariate response, how we can separately quantify modulations of amplitude and direction for vector quantities, and how we can measure the emergence of novel information over time in evoked responses. Open-source Matlab and Python code implementing the new methods accompanies this article. Hum Brain Mapp 38:1541-1573, 2017. © 2016 Wiley Periodicals, Inc.

The role of brain oscillations in predicting self-generated sounds

Being able to predict self-generated sensory consequences is an important feature of normal brain functioning. In the auditory domain, self-generated sounds lead to smaller brain responses (e.g., auditory evoked responses) compared to externally generated sounds, which is usually referred to as the sensory attenuation effect. Here we investigated the role of brain oscillations underlying this effect. With magnetoencephalography, we show that self-generated sounds are associated with increased pre-stimulus alpha power and decreased post-stimulus gamma power and alpha/beta phase locking in auditory cortex. All these oscillatory changes are correlated with changes in evoked responses, suggesting a tight link between these oscillatory events and sensory attenuation. Furthermore, the pre- and post- oscillatory changes correlate with each other across participants, supporting the idea that they constitute a neural information processing sequence for self-generated sounds. In line with findings of alpha oscillations reflecting feedback and gamma oscillations feedforward processes and models of predictive coding, we suggest that pre-stimulus alpha power represent prediction and post-stimulus gamma power represent prediction error, which is further processed with post-stimulus alpha/beta phase resetting. The correlation between these oscillatory events is further validated with cross-trial analysis, which provides additional support for the proposed information processing sequence that might reflect a general mechanism for the prediction of self-generated sensory input.

Brain Rhythms of Pain

Pain is an integrative phenomenon that results from dynamic interactions between sensory and contextual (i.e., cognitive, emotional, and motivational) processes. In the brain the experience of pain is associated with neuronal oscillations and synchrony at different frequencies. However, an overarching framework for the significance of oscillations for pain remains lacking. Recent concepts relate oscillations at different frequencies to the routing of information flow in the brain and the signaling of predictions and prediction errors. The application of these concepts to pain promises insights into how flexible routing of information flow coordinates diverse processes that merge into the experience of pain. Such insights might have implications for the understanding and treatment of chronic pain.

The Youth Mental Health Risk and Resilience Study (YouR-Study)

BACKGROUND

The transition from adolescence to adulthood is associated with the emergence of psychosis and other mental health problems, highlighting the importance of this developmental period for the understanding of developing psychopathology and individual differences in risk and resilience. The Youth Mental Health Risk and Resilience Study (YouR-Study) aims to identify neurobiological mechanisms and predictors of psychosis-risk with a state-of-the-art neuroimaging approach (Magnetoencephalography, Magnetic Resonance Spectroscopy, Magnetic Resonance Imaging) in combination with core psychological processes, such as affect regulation and attachment, that have been implicated in the development and maintenance of severe mental health problems.

METHODS/DESIGN

One hundred participants meeting clinical high-risk criteria (CHR) for psychosis through the Comprehensive Assessment of At-Risk Mental State and Schizophrenia Proneness Instrument, Adult Version, in the age range from 16 to 35 years of age will be recruited. Mental-state monitoring up to a total of 2 years will be implemented to detect transition to psychosis. In addition, a sample of n = 40 help-seeking participants will be recruited who do not meet CHR-criteria, a group of n = 50 healthy control participants and a sample of n = 25 patients with first-episode psychosis. MEG-activity will be obtained during auditory and visual tasks to examine neural oscillations and event-related fields. In addition, we will obtain estimates of GABA and Glutamate levels through Magnetic Resonance Spectroscopy (MRS) to examine relationships between neural synchrony and excitatory-inhibition (E/I) balance parameters. Neuroimaging will be complemented by detailed neuropsychological assessments as well as psychological measures investigating the impact of childhood abuse, attachment experiences and affect regulation.

DISCUSSION

The YouR-study could potentially provide important insights into the neurobiological mechanisms that confer risk for psychosis as well as biomarkers for early diagnosis of severe mental health problems. Moreover, we expect novel data related to the contribution of affect regulation and attachment-processes in the development of mental health problems, leading to an integrative model of early stage psychosis and the factors underlying risk and resilience of emerging psychopathology.

Brain oscillations differentially encode noxious stimulus intensity and pain intensity

Noxious stimuli induce physiological processes which commonly translate into pain. However, under certain conditions, pain intensity can substantially dissociate from stimulus intensity, e.g. during longer-lasting pain in chronic pain syndromes. How stimulus intensity and pain intensity are differentially represented in the human brain is, however, not yet fully understood. We therefore used electroencephalography (EEG) to investigate the cerebral representation of noxious stimulus intensity and pain intensity during 10 min of painful heat stimulation in 39 healthy human participants. Time courses of objective stimulus intensity and subjective pain ratings indicated a dissociation of both measures. EEG data showed that stimulus intensity was encoded by decreases of neuronal oscillations at alpha and beta frequencies in sensorimotor areas. In contrast, pain intensity was encoded by gamma oscillations in the medial prefrontal cortex. Contrasting right versus left hand stimulation revealed that the encoding of stimulus intensity in contralateral sensorimotor areas depended on the stimulation side. In contrast, a conjunction analysis of right and left hand stimulation revealed that the encoding of pain in the medial prefrontal cortex was independent of the side of stimulation. Thus, the translation of noxious stimulus intensity into pain is associated with a change from a spatially specific representation of stimulus intensity by alpha and beta oscillations in sensorimotor areas to a spatially independent representation of pain by gamma oscillations in brain areas related to cognitive and affective-motivational processes. These findings extend the understanding of the brain mechanisms of nociception and pain and their dissociations during longer-lasting pain as a key symptom of chronic pain syndromes.

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Stimulus intensity is encoded by alpha/beta oscillations in sensorimotor areas.

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Pain intensity is encoded by gamma oscillations in the medial prefrontal cortex.

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The encoding of stimulus intensity depends on stimulation side.

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The encoding of pain is independent of stimulation side.

"Hearing faces and seeing voices": Amodal coding of person identity in the human brain

Recognizing familiar individuals is achieved by the brain by combining cues from several sensory modalities, including the face of a person and her voice. Here we used functional magnetic resonance (fMRI) and a whole-brain, searchlight multi-voxel pattern analysis (MVPA) to search for areas in which local fMRI patterns could result in identity classification as a function of sensory modality. We found several areas supporting face or voice stimulus classification based on fMRI responses, consistent with previous reports; the classification maps overlapped across modalities in a single area of right posterior superior temporal sulcus (pSTS). Remarkably, we also found several cortical areas, mostly located along the middle temporal gyrus, in which local fMRI patterns resulted in identity “cross-classification”: vocal identity could be classified based on fMRI responses to the faces, or the reverse, or both. These findings are suggestive of a series of cortical identity representations increasingly abstracted from the input modality.

The Deceptively Simple N170 Reflects Network Information Processing Mechanisms Involving Visual Feature Coding and Transfer Across Hemispheres

A key to understanding visual cognition is to determine “where”, “when”, and “how” brain responses reflect the processing of the specific visual features that modulate categorization behavior—the “what”. The N170 is the earliest Event-Related Potential (ERP) that preferentially responds to faces. Here, we demonstrate that a paradigmatic shift is necessary to interpret the N170 as the product of an information processing network that dynamically codes and transfers face features across hemispheres, rather than as a local stimulus-driven event. Reverse-correlation methods coupled with information-theoretic analyses revealed that visibility of the eyes influences face detection behavior. The N170 initially reflects coding of the behaviorally relevant eye contralateral to the sensor, followed by a causal communication of the other eye from the other hemisphere. These findings demonstrate that the deceptively simple N170 ERP hides a complex network information processing mechanism involving initial coding and subsequent cross-hemispheric transfer of visual features.

MEG sensor and source measures of visually induced gamma-band oscillations are highly reliable

High frequency brain oscillations are associated with numerous cognitive and behavioral processes. Non-invasive measurements using electro-/magnetoencephalography (EEG/MEG) have revealed that high frequency neural signals are heritable and manifest changes with age as well as in neuropsychiatric illnesses. Despite the extensive use of EEG/MEG-measured neural oscillations in basic and clinical research, studies demonstrating test-retest reliability of power and frequency measures of neural signals remain scarce. Here, we evaluated the test-retest reliability of visually induced gamma (30-100Hz) oscillations derived from sensor and source signals acquired over two MEG sessions. The study required participants (N=13) to detect the randomly occurring stimulus acceleration while viewing a moving concentric grating. Sensor and source MEG measures of gamma-band activity yielded comparably strong reliability (average intraclass correlation, ICC=0.861). Peak stimulus-induced gamma frequency (53-72Hz) yielded the highest measures of stability (ICCsensor=0.940; ICCsource=0.966) followed by spectral signal change (ICCsensor=0.890; ICCsource=0.893) and peak frequency bandwidth (ICCsensor=0.856; ICCsource=0.622). Furthermore, source-reconstruction significantly improved signal-to-noise for spectral amplitude of gamma activity compared to sensor estimates. Our assessments highlight that both sensor and source derived estimates of visually induced gamma-band oscillations from MEG signals are characterized by high test-retest reliability, with source derived oscillatory measures conferring an improvement in the stability of peak-frequency estimates. Importantly, our finding of high test-retest reliability supports the feasibility of pharma-MEG studies and longitudinal aging or clinical studies.

Let the Rhythm Guide You: Non-invasive Tracking of Cortical Communication Channels

In this issue of Neuron, a study by Michalareas et al. (2016) uses magnetoencephalography (MEG) to characterize the hierarchical organization of human visual areas based on their causal connectivity profiles.

Lip movements entrain the observers' low-frequency brain oscillations to facilitate speech intelligibility

During continuous speech, lip movements provide visual temporal signals that facilitate speech processing. Here, using MEG we directly investigated how these visual signals interact with rhythmic brain activity in participants listening to and seeing the speaker. First, we investigated coherence between oscillatory brain activity and speaker’s lip movements and demonstrated significant entrainment in visual cortex. We then used partial coherence to remove contributions of the coherent auditory speech signal from the lip-brain coherence. Comparing this synchronization between different attention conditions revealed that attending visual speech enhances the coherence between activity in visual cortex and the speaker’s lips. Further, we identified a significant partial coherence between left motor cortex and lip movements and this partial coherence directly predicted comprehension accuracy. Our results emphasize the importance of visually entrained and attention-modulated rhythmic brain activity for the enhancement of audiovisual speech processing.

DOI:http://dx.doi.org/10.7554/eLife.14521.001

People are able communicate effectively with each other even in very noisy places where it is difficult to actually hear what others are saying. In a face-to-face conversation, people detect and respond to many physical cues – including body posture, facial expressions, head and eye movements and gestures – alongside the sound cues. Lip movements are particularly important and contain enough information to allow trained observers to understand speech even if they cannot hear the speech itself.

It is known that brain waves in listeners are synchronized with the rhythms in a speech, especially the syllables. This is thought to establish a channel for communication – similar to tuning a radio to a certain frequency to listen to a certain radio station. Park et al. studied if listeners’ brain waves also align to the speaker’s lip movements during continuous speech and if this is important for understanding the speech.

The experiments reveal that a part of the brain that processes visual information – called the visual cortex – produces brain waves that are synchronized to the rhythm of syllables in continuous speech. This synchronization was more precise in a complex situation where lip movements would be more important to understand speech. Park et al. also found that the area of the observer’s brain that controls the lips (the motor cortex) also produced brain waves that were synchronized to lip movements. Volunteers whose motor cortex was more synchronized to the lip movements understood speech better. This supports the idea that brain areas that are used for producing speech are also important for understanding speech.

Future challenges include understanding how synchronization of brain waves with the rhythms of speech helps us to understand speech, and how the brain waves produced by the visual and motor areas interact.

DOI:http://dx.doi.org/10.7554/eLife.14521.002

Behavioural evidence for separate mechanisms of audiovisual temporal binding as a function of leading sensory modality

The ability to integrate auditory and visual information is critical for effective perception and interaction with the environment, and is thought to be abnormal in some clinical populations. Several studies have investigated the time window over which audiovisual events are integrated, also called the temporal binding window, and revealed asymmetries depending on the order of audiovisual input (i.e. the leading sense). When judging audiovisual simultaneity, the binding window appears narrower and non-malleable for auditory-leading stimulus pairs and wider and trainable for visual-leading pairs. Here we specifically examined the level of independence of binding mechanisms when auditory-before-visual vs. visual-before-auditory input is bound. Three groups of healthy participants practiced audiovisual simultaneity detection with feedback, selectively training on auditory-leading stimulus pairs (group 1), visual-leading stimulus pairs (group 2) or both (group 3). Subsequently, we tested for learning transfer (crossover) from trained stimulus pairs to non-trained pairs with opposite audiovisual input. Our data confirmed the known asymmetry in size and trainability for auditory-visual vs. visual-auditory binding windows. More importantly, practicing one type of audiovisual integration (e.g. auditory-visual) did not affect the other type (e.g. visual-auditory), even if trainable by within-condition practice. Together, these results provide crucial evidence that audiovisual temporal binding for auditory-leading vs. visual-leading stimulus pairs are independent, possibly tapping into different circuits for audiovisual integration due to engagement of different multisensory sampling mechanisms depending on leading sense. Our results have implications for informing the study of multisensory interactions in healthy participants and clinical populations with dysfunctional multisensory integration.

Lasting EEG/MEG Aftereffects of Rhythmic Transcranial Brain Stimulation: Level of Control Over Oscillatory Network Activity

A number of rhythmic protocols have emerged for non-invasive brain stimulation (NIBS) in humans, including transcranial alternating current stimulation (tACS), oscillatory transcranial direct current stimulation (otDCS), and repetitive (also called rhythmic) transcranial magnetic stimulation (rTMS). With these techniques, it is possible to match the frequency of the externally applied electromagnetic fields to the intrinsic frequency of oscillatory neural population activity (“frequency-tuning”). Mounting evidence suggests that by this means tACS, otDCS, and rTMS can entrain brain oscillations and promote associated functions in a frequency-specific manner, in particular during (i.e., online to) stimulation. Here, we focus instead on the changes in oscillatory brain activity that persist after the end of stimulation. Understanding such aftereffects in healthy participants is an important step for developing these techniques into potentially useful clinical tools for the treatment of specific patient groups. Reviewing the electrophysiological evidence in healthy participants, we find aftereffects on brain oscillations to be a common outcome following tACS/otDCS and rTMS. However, we did not find a consistent, predictable pattern of aftereffects across studies, which is in contrast to the relative homogeneity of reported online effects. This indicates that aftereffects are partially dissociated from online, frequency-specific (entrainment) effects during tACS/otDCS and rTMS. We outline possible accounts and future directions for a better understanding of the link between online entrainment and offline aftereffects, which will be key for developing more targeted interventions into oscillatory brain activity.

Cultural Differences in Perceiving Sounds Generated by Others: Self Matters

Sensory consequences resulting from own movements receive different neural processing compared to externally generated sensory consequences (e.g., by a computer), leading to sensory attenuation, i.e., a reduction in perceived intensity or brain evoked responses. However, discrepant findings exist from different cultural regions about whether sensory attenuation is also present for sensory consequences generated by others. In this study, we performed a cross culture (between Chinese and British) comparison on the processing of sensory consequences (perceived loudness) from self and others compared to an external source in the auditory domain. We found a cultural difference in processing sensory consequences generated by others, with only Chinese and not British showing the sensory attenuation effect. Sensory attenuation in this case was correlated with independent self-construal scores. The sensory attenuation effect for self-generated sensory consequences was not replicated. However, a correlation with delusional ideation was observed for British. These findings are discussed with respects to mechanisms of sensory attenuation.

Visual Benefits in Apparent Motion Displays: Automatically Driven Spatial and Temporal Anticipation Are Partially Dissociated

Many behaviourally relevant sensory events such as motion stimuli and speech have an intrinsic spatio-temporal structure. This will engage intentional and most likely unintentional (automatic) prediction mechanisms enhancing the perception of upcoming stimuli in the event stream. Here we sought to probe the anticipatory processes that are automatically driven by rhythmic input streams in terms of their spatial and temporal components. To this end, we employed an apparent visual motion paradigm testing the effects of pre-target motion on lateralized visual target discrimination. The motion stimuli either moved towards or away from peripheral target positions (valid vs. invalid spatial motion cueing) at a rhythmic or arrhythmic pace (valid vs. invalid temporal motion cueing). Crucially, we emphasized automatic motion-induced anticipatory processes by rendering the motion stimuli non-predictive of upcoming target position (by design) and task-irrelevant (by instruction), and by creating instead endogenous (orthogonal) expectations using symbolic cueing. Our data revealed that the apparent motion cues automatically engaged both spatial and temporal anticipatory processes, but that these processes were dissociated. We further found evidence for lateralisation of anticipatory temporal but not spatial processes. This indicates that distinct mechanisms may drive automatic spatial and temporal extrapolation of upcoming events from rhythmic event streams. This contrasts with previous findings that instead suggest an interaction between spatial and temporal attention processes when endogenously driven. Our results further highlight the need for isolating intentional from unintentional processes for better understanding the various anticipatory mechanisms engaged in processing behaviourally relevant stimuli with predictable spatio-temporal structure such as motion and speech.

Frontal top-down signals increase coupling of auditory low-frequency oscillations to continuous speech in human listeners

Humans show a remarkable ability to understand continuous speech even under adverse listening conditions. This ability critically relies on dynamically updated predictions of incoming sensory information, but exactly how top-down predictions improve speech processing is still unclear. Brain oscillations are a likely mechanism for these top-down predictions [1, 2]. Quasi-rhythmic components in speech are known to entrain low-frequency oscillations in auditory areas [3, 4], and this entrainment increases with intelligibility [5]. We hypothesize that top-down signals from frontal brain areas causally modulate the phase of brain oscillations in auditory cortex. We use magnetoencephalography (MEG) to monitor brain oscillations in 22 participants during continuous speech perception. We characterize prominent spectral components of speech-brain coupling in auditory cortex and use causal connectivity analysis (transfer entropy) to identify the top-down signals driving this coupling more strongly during intelligible speech than during unintelligible speech. We report three main findings. First, frontal and motor cortices significantly modulate the phase of speech-coupled low-frequency oscillations in auditory cortex, and this effect depends on intelligibility of speech. Second, top-down signals are significantly stronger for left auditory cortex than for right auditory cortex. Third, speech-auditory cortex coupling is enhanced as a function of stronger top-down signals. Together, our results suggest that low-frequency brain oscillations play a role in implementing predictive top-down control during continuous speech perception and that top-down control is largely directed at left auditory cortex. This suggests a close relationship between (left-lateralized) speech production areas and the implementation of top-down control in continuous speech perception.

Prefrontal Gamma Oscillations Encode Tonic Pain in Humans

Under physiological conditions, momentary pain serves vital protective functions. Ongoing pain in chronic pain states, on the other hand, is a pathological condition that causes widespread suffering and whose treatment remains unsatisfactory. The brain mechanisms of ongoing pain are largely unknown. In this study, we applied tonic painful heat stimuli of varying degree to healthy human subjects, obtained continuous pain ratings, and recorded electroencephalograms to relate ongoing pain to brain activity. Our results reveal that the subjective perception of tonic pain is selectively encoded by gamma oscillations in the medial prefrontal cortex. We further observed that the encoding of subjective pain intensity experienced by the participants differs fundamentally from that of objective stimulus intensity and from that of brief pain stimuli. These observations point to a role for gamma oscillations in the medial prefrontal cortex in ongoing, tonic pain and thereby extend current concepts of the brain mechanisms of pain to the clinically relevant state of ongoing pain. Furthermore, our approach might help to identify a brain marker of ongoing pain, which may prove useful for the diagnosis and therapy of chronic pain.

Making sense: Dopamine activates conscious self-monitoring through medial prefrontal cortex

When experiences become meaningful to the self, they are linked to synchronous activity in a paralimbic network of self-awareness and dopaminergic activity. This network includes medial prefrontal and medial parietal/posterior cingulate cortices, where transcranial magnetic stimulation may transiently impair self-awareness. Conversely, we hypothesize that dopaminergic stimulation may improve self-awareness and metacognition (i.e., the ability of the brain to consciously monitor its own cognitive processes). Here, we demonstrate improved noetic (conscious) metacognition by oral administration of 100 mg dopamine in minimal self-awareness. In a separate experiment with extended self-awareness dopamine improved the retrieval accuracy of memories of self-judgment (autonoetic, i.e., explicitly self-conscious) metacognition. Concomitantly, magnetoencephalography (MEG) showed increased amplitudes of oscillations (power) preferentially in the medial prefrontal cortex. Given that electromagnetic activity in this region is instrumental in self-awareness, this explains the specific effect of dopamine on explicit self-awareness and autonoetic metacognition.

Single-subject analyses of magnetoencephalographic evoked responses to the acoustic properties of affective non-verbal vocalizations

Magneto-encephalography (MEG) was used to examine the cerebral response to affective non-verbal vocalizations (ANVs) at the single-subject level. Stimuli consisted of non-verbal affect bursts from the Montreal Affective Voices morphed to parametrically vary acoustical structure and perceived emotional properties. Scalp magnetic fields were recorded in three participants while they performed a 3-alternative forced choice emotion categorization task (Anger, Fear, Pleasure). Each participant performed more than 6000 trials to allow single-subject level statistical analyses using a new toolbox which implements the general linear model (GLM) on stimulus-specific responses (LIMO-EEG). For each participant we estimated "simple" models [including just one affective regressor (Arousal or Valence)] as well as "combined" models (including acoustical regressors). Results from the "simple" models revealed in every participant the significant early effects (as early as ~100 ms after onset) of Valence and Arousal already reported at the group-level in previous work. However, the "combined" models showed that few effects of Arousal remained after removing the acoustically-explained variance, whereas significant effects of Valence remained especially at late stages. This study demonstrates (i) that single-subject analyses replicate the results observed at early stages by group-level studies and (ii) the feasibility of GLM-based analysis of MEG data. It also suggests that early modulation of MEG amplitude by affective stimuli partly reflects their acoustical properties.

Alpha Power Increase After Transcranial Alternating Current Stimulation at Alpha Frequency (α-tACS) Reflects Plastic Changes Rather Than Entrainment

Background

Periodic stimulation of occipital areas using transcranial alternating current stimulation (tACS) at alpha (α) frequency (8–12 Hz) enhances electroencephalographic (EEG) α-oscillation long after tACS-offset. Two mechanisms have been suggested to underlie these changes in oscillatory EEG activity: tACS-induced entrainment of brain oscillations and/or tACS-induced changes in oscillatory circuits by spike-timing dependent plasticity.

Objective

We tested to what extent plasticity can account for tACS-aftereffects when controlling for entrainment “echoes.” To this end, we used a novel, intermittent tACS protocol and investigated the strength of the aftereffect as a function of phase continuity between successive tACS episodes, as well as the match between stimulation frequency and endogenous α-frequency.

Methods

12 healthy participants were stimulated at around individual α-frequency for 11–15 min in four sessions using intermittent tACS or sham. Successive tACS events were either phase-continuous or phase-discontinuous, and either 3 or 8 s long. EEG α-phase and power changes were compared after and between episodes of α-tACS across conditions and against sham.

Results

α-aftereffects were successfully replicated after intermittent stimulation using 8-s but not 3-s trains. These aftereffects did not reveal any of the characteristics of entrainment echoes in that they were independent of tACS phase-continuity and showed neither prolonged phase alignment nor frequency synchronization to the exact stimulation frequency.

Conclusion

Our results indicate that plasticity mechanisms are sufficient to explain α-aftereffects in response to α-tACS, and inform models of tACS-induced plasticity in oscillatory circuits. Modifying brain oscillations with tACS holds promise for clinical applications in disorders involving abnormal neural synchrony.

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Intermittent periodic stimulation of occipital areas with alpha-tACS enhances offline EEG alpha power.

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Alpha-aftereffects cannot be explained by neuronal entrainment but are more likely due to plastic changes.

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We propose a physiological constraint to a recent model of tACS-induced spike-timing dependent plasticity.

Prefrontal control over motor cortex cycles at beta frequency during movement inhibition

A fully adapted behavior requires maximum efficiency to inhibit processes in the motor domain [1]. Although a number of cortical and subcortical brain regions have been implicated, converging evidence suggests that activation of right inferior frontal gyrus (r-IFG) and right presupplementary motor area (r-preSMA) is crucial for successful response inhibition [2, 3]. However, it is still unknown how these prefrontal areas convey the necessary signal to the primary motor cortex (M1), the cortical site where the final motor plan eventually has to be inhibited or executed. On the basis of the widely accepted view that brain oscillations are fundamental for communication between neuronal network elements [4–6], one would predict that the transmission of these inhibitory signals within the prefrontal-central networks (i.e., r-IFG/M1 and/or r-preSMA/M1) is realized in rapid, periodic bursts coinciding with oscillatory brain activity at a distinct frequency. However, the dynamics of corticocortical effective connectivity has never been directly tested on such timescales. By using double-coil transcranial magnetic stimulation (TMS) and electroencephalography (EEG) [7, 8], we assessed instantaneous prefrontal-to-motor cortex connectivity in a Go/NoGo paradigm as a function of delay from (Go/NoGo) cue onset. In NoGo trials only, the effects of a conditioning prefrontal TMS pulse on motor cortex excitability cycled at beta frequency, coinciding with a frontocentral beta signature in EEG. This establishes, for the first time, a tight link between effective cortical connectivity and related cortical oscillatory activity, leading to the conclusion that endogenous (top-down) inhibitory motor signals are transmitted in beta bursts in large-scale cortical networks for inhibitory motor control.

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r-IFG/l-M1 and r-preSMA/l-M1 connectivity increases during NoGo trials

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Motor inhibitory signals are transmitted cortically in beta bursts

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Effective connectivity is linked to beta oscillatory activity