Voluntary Motor Command Release Coincides with Restricted Sensorimotor Beta Rhythm Phases.

Sensory perception and memory are enhanced during restricted phases of ongoing brain rhythms, but whether voluntary movement is constrained by brain rhythm phase is not known. Voluntary movement requires motor commands to be released from motor cortex (M1) and transmitted to spinal motoneurons and effector muscles. Here, we tested the hypothesis that motor commands are preferentially released from M1 during circumscribed phases of ongoing sensorimotor rhythms. Healthy humans of both sexes performed a self-paced finger movement task during electroencephalography (EEG) and electromyography (EMG) recordings. We first estimated the time of motor command release preceding each finger movement by subtracting individually measured corticomuscular transmission latencies from EMG-determined movement onset times. Then, we determined the phase of ipsilateral and contralateral sensorimotor mu (8-12 Hz) and beta (13-35 Hz) rhythms during release of each motor command. We report that motor commands were most often released between 120 and 140° along the contralateral beta cycle but were released uniformly along the contralateral mu cycle. Motor commands were also released uniformly along ipsilateral mu and beta cycles. Results demonstrate that motor command release coincides with restricted phases of the contralateral sensorimotor beta rhythm, suggesting that sensorimotor beta rhythm phase may sculpt the timing of voluntary human movement.SIGNIFICANCE STATEMENT Perceptual and cognitive function is optimal during specific brain rhythm phases. Although brain rhythm phase influences motor cortical neuronal activity and communication between the motor cortex and spinal cord, its role in voluntary movement is poorly understood. Here, we show that the motor commands needed to produce voluntary movements are preferentially released from the motor cortex during contralateral sensorimotor beta rhythm phases. Our findings are consistent with the notion that sensorimotor rhythm phase influences the timing of voluntary human movement.

Differential Brain Mechanisms of Selection and Maintenance of Information during Working Memory.

Working memory is our ability to select and temporarily hold information as needed for complex cognitive operations. The temporal dynamics of sustained and transient neural activity supporting the selection and holding of memory content is not known. To address this problem, we recorded magnetoencephalography in healthy participants performing a retro-cue working memory task in which the selection rule and the memory content varied independently. Multivariate decoding and source analyses showed that selecting the memory content relies on prefrontal and parieto-occipital persistent oscillatory neural activity. By contrast, the memory content was reactivated in a distributed occipitotemporal posterior network, preceding the working memory decision and in a different format than during the visual encoding. These results identify a neural signature of content selection and characterize differentiated spatiotemporal constraints for subprocesses of working memory.SIGNIFICANCE STATEMENT Our brain selects and maintains information during short time windows in a way that is essential to reasoning and learning. Recent advances in multivariate analysis of brain activity allowed the characterization of brain regions that stores the memory. We applied multivariate analysis to time-resolved brain signals to characterize the spatiotemporal signature underlying these subprocesses. The selection of information relies on sustained oscillatory activity in a network that includes the ventrolateral prefrontal cortex while memory content is transiently replayed in an occipitotemporal network that differs from encoding. Our results characterized differentiated spatiotemporal activity underlying encoding, selection, and maintenance of information during working memory.

Cortico-thalamic disconnection in a patient with supernumerary phantom limb.

Supernumerary phantom limb (SPL) designates the experience of an illusory additional limb occurring after brain damage. Functional neuroimaging during SPL movements documented increased response in the ipsilesional supplementary motor area (SMA), premotor cortex (PMC), thalamus and caudate. This suggested that motor circuits are important for bodily related cognition, but anatomical evidence is sparse. Here, we tested this hypothesis by studying an extremely rare patient with chronic SPL, still present 3 years after a vascular stroke affecting cortical and subcortical right-hemisphere structures. Anatomical analysis included an advanced in vivo reconstruction of white matter tracts using diffusion-based spherical deconvolution. This reconstruction demonstrated a massive and relatively selective disconnection between anatomically preserved SMA/PMC and the thalamus. Our results provide strong anatomical support for the hypothesis that cortico-thalamic loops involving motor-related circuits are crucial to integrate sensorimotor processing with bodily self-awareness.

Visual Contrast Sensitivity Improvement by Right Frontal High-Beta Activity Is Mediated by Contrast Gain Mechanisms and Influenced by Fronto-Parietal White Matter Microstructure.

Behavioral and electrophysiological studies in humans and non-human primates have correlated frontal high-beta activity with the orienting of endogenous attention and shown the ability of the latter function to modulate visual performance. We here combined rhythmic transcranial magnetic stimulation (TMS) and diffusion imaging to study the relation between frontal oscillatory activity and visual performance, and we associated these phenomena to a specific set of white matter pathways that in humans subtend attentional processes. High-beta rhythmic activity on the right frontal eye field (FEF) was induced with TMS and its causal effects on a contrast sensitivity function were recorded to explore its ability to improve visual detection performance across different stimulus contrast levels. Our results show that frequency-specific activity patterns engaged in the right FEF have the ability to induce a leftward shift of the psychometric function. This increase in visual performance across different levels of stimulus contrast is likely mediated by a contrast gain mechanism. Interestingly, microstructural measures of white matter connectivity suggest a strong implication of right fronto-parietal connectivity linking the FEF and the intraparietal sulcus in propagating high-beta rhythmic signals across brain networks and subtending top-down frontal influences on visual performance.

Fronto-Parietal Anatomical Connections Influence the Modulation of Conscious Visual Perception by High-Beta Frontal Oscillatory Activity.

May white matter connectivity influence rhythmic brain activity underlying visual cognition? We here employed diffusion imaging to reconstruct the fronto-parietal white matter pathways in a group of healthy participants who displayed frequency-specific ameliorations of visual sensitivity during the entrainment of high-beta oscillatory activity by rhythmic transcranial magnetic stimulation over their right frontal eye field. Our analyses reveal a strong tract-specific association between the volume of the first branch of the superior longitudinal fasciculus and improvements of conscious visual detection driven by frontal beta oscillation patterns. These data indicate that the architecture of specific white matter pathways has the ability to influence the distributed effects of rhythmic spatio-temporal activity, and suggest a potentially relevant role for long-range connectivity in the synchronization of oscillatory patterns across fronto-parietal networks subtending the modulation of conscious visual perception.

Causal frequency-specific contributions of frontal spatiotemporal patterns induced by non-invasive neurostimulation to human visual performance.

Neural oscillatory activity is known to play a crucial role in brain function. In the particular domain of visual perception, specific frequency bands in different brain regions and networks, from sensory areas to large-scale frontoparietal systems, have been associated with distinct aspects of visual behavior. Nonetheless, their contributions to human visual cognition remain to be causally demonstrated. We hereby used non-uniform (and thus non-frequency-specific) and uniform (frequency-specific) high-beta and gamma patterns of noninvasive neurostimulation over the right frontal eye field (FEF) to isolate the behavioral effects of oscillation frequency and provide causal evidence that distinct visual behavioral outcomes could be modulated by frequency-specific activity emerging from a single cortical region. In a visual detection task using near-threshold targets, high-beta frequency enhanced perceptual sensitivity (d') without changing response criterion (beta), whereas gamma frequency shifted response criterion but showed no effects on perceptual sensitivity. The lack of behavioral modulations by non-frequency-specific patterns demonstrates that these behavioral effects were specifically driven by burst frequency. We hypothesize that such frequency-coded behavioral impact of oscillatory activity may reflect a general brain mechanism to multiplex functions within the same neural substrate. Furthermore, pathological conditions involving impaired cerebral oscillations could potentially benefit in the near future from the use of neurostimulation to restore the characteristic oscillatory patterns of healthy systems.

Fronto-tectal white matter connectivity mediates facilitatory effects of non-invasive neurostimulation on visual detection.

The causal ability of pre-target FEF activity to modulate visual detection for perithreshold stimuli has been recently demonstrated in humans by means of non-invasive neurostimulation. Yet in spite of the network-distributed effects of these type of techniques, the white matter (WM) tracts and distant visual nodes contributing to such behavioral impact remain unknown. We hereby used individual data from a group of healthy human subjects, who received time-locked pulses of active or sham Transcranial Magnetic Stimulation (TMS) to the right Frontal Eye Field (FEF) region, and experienced increases in visual detection sensitivity. We then studied the extent to which interindividual differences in visual modulation might be dependent on the WM patterns linking the targeted area to other regions relevant for visuo-attentional behaviors. We report a statistically significant correlation between the probability of connection in a right fronto-tectal pathway (FEF-Superior Colliculus) and the modulation of visual sensitivity during a detection task. Our findings support the potential contribution of this pathway and the superior colliculus in the mediation of visual performance from frontal regions in humans. Furthermore, we also show the ability of a TMS/DTI correlational approach to contribute to the disambiguation of the specific long-range pathways driving network-wide neurostimulatory effects on behavior, anticipating their future role in guiding a more efficient use of focal neurostimulation.

Manipulating the Rapid Consolidation Periods in a Learning Task Affects General Skills More than Statistical Learning and Changes the Dynamics of Learning.

Memory consolidation processes have traditionally been investigated from the perspective of hours or days. However, recent developments in memory research have shown that memory consolidation processes could occur even within seconds, possibly because of the neural replay of just practiced memory traces during short breaks. Here, we investigate this rapid form of consolidation during statistical learning. We aim to answer (1) whether this rapid consolidation occurs in implicit statistical learning and general skill learning, and (2) whether the duration of rest periods affects these two learning types differently. Human participants performed a widely used statistical learning task-the alternating serial reaction time (ASRT) task-that enables us to measure implicit statistical and general skill learning separately. The ASRT task consisted of 25 learning blocks with a rest period between the blocks. In a between-subjects design, the length of the rest periods was fixed at 15 or 30 s, or the participants could control the length themselves. We found that the duration of rest periods does not affect the amount of statistical knowledge acquired but does change the dynamics of learning. Shorter rest periods led to better learning during the learning blocks, whereas longer rest periods promoted learning also in the between-block rest periods, possibly because of the higher amount of replay. Moreover, we found weaker general skill learning in the self-paced group than in the fixed rest period groups. These results suggest that distinct learning processes are differently affected by the duration of short rest periods.

Decoding personalized motor cortical excitability states from human electroencephalography.

Brain state-dependent transcranial magnetic stimulation (TMS) requires real-time identification of cortical excitability states. Current approaches deliver TMS during brain states that correlate with motor cortex (M1) excitability at the group level. Here, we hypothesized that machine learning classifiers could successfully discriminate between high and low M1 excitability states in individual participants using information obtained from low-density electroencephalography (EEG) signals. To test this, we analyzed a publicly available dataset that delivered 600 single TMS pulses to the right M1 during EEG and electromyography (EMG) recordings in 20 healthy adults. Multivariate pattern classification was used to discriminate between brain states during which TMS evoked small and large motor-evoked potentials (MEPs). Results show that personalized classifiers successfully discriminated between low and high M1 excitability states in 80% of tested participants. MEPs elicited during classifier-predicted high excitability states were significantly larger than those elicited during classifier-predicted low excitability states in 90% of tested participants. Personalized classifiers did not generalize across participants. Overall, results show that individual participants exhibit unique brain activity patterns which predict low and high M1 excitability states and that these patterns can be efficiently captured using low-density EEG signals. Our findings suggest that deploying individualized classifiers during brain state-dependent TMS may enable fully personalized neuromodulation in the future.

Consolidation of human skill linked to waking hippocampo-neocortical replay.

The introduction of rest intervals interspersed with practice strengthens wakeful consolidation of skill. The mechanisms by which the brain binds discrete action representations into consolidated, highly temporally resolved skill sequences during waking rest are not known. To address this question, we recorded magnetoencephalography (MEG) during acquisition and rapid consolidation of a sequential motor skill. We report the presence of prominent, fast waking neural replay during the same rest periods in which rapid consolidation occurs. The observed replay is temporally compressed by approximately 20-fold relative to the acquired skill, is selective for the trained sequence, and predicts the magnitude of skill consolidation. Replay representations extend beyond the hippocampus and entorhinal cortex to the contralateral sensorimotor cortex. These results document the presence of robust hippocampo-neocortical replay supporting rapid wakeful consolidation of skill.

Statistical learning occurs during practice while high-order rule learning during rest period.

Knowing when the brain learns is crucial for both the comprehension of memory formation and consolidation and for developing new training and neurorehabilitation strategies in healthy and patient populations. Recently, a rapid form of offline learning developing during short rest periods has been shown to account for most of procedural learning, leading to the hypothesis that the brain mainly learns during rest between practice periods. Nonetheless, procedural learning has several subcomponents not disentangled in previous studies investigating learning dynamics, such as acquiring the statistical regularities of the task, or else the high-order rules that regulate its organization. Here we analyzed 506 behavioral sessions of implicit visuomotor deterministic and probabilistic sequence learning tasks, allowing the distinction between general skill learning, statistical learning, and high-order rule learning. Our results show that the temporal dynamics of apparently simultaneous learning processes differ. While high-order rule learning is acquired offline, statistical learning is evidenced online. These findings open new avenues on the short-scale temporal dynamics of learning and memory consolidation and reveal a fundamental distinction between statistical and high-order rule learning, the former benefiting from online evidence accumulation and the latter requiring short rest periods for rapid consolidation.

Plasticity and recovery of function.

The frontal lobe plays a crucial role in human motor behavior. It is one of the last areas of the brain to mature, especially the prefrontal regions. After a brief historical perspective on the perceived dichotomy between the view of the brain as a static organ and that of a plastic, constantly changing structure, we discuss the stability/plasticity dilemma including examples of documented cortical reorganization taking place at multiple spatial and temporal scales. We pose that while plasticity is needed for motor learning, stability of the system is necessary for storage and maintenance of memorized skills. We discuss how this plasticity/stability dilemma is resolved along the life span and after a brain injury. We then examine the main challenges that clinicians have to overcome to promote recovery of function in patients with brain lesions, including attempts to use neurostimulation techniques as adjuvant to training-based customary neurorehabilitation.

Entrainment of local synchrony reveals a causal role for high-beta right frontal oscillations in human visual consciousness.

Prior evidence supports a critical role of oscillatory activity in visual cognition, but are cerebral oscillations simply correlated or causally linked to our ability to consciously acknowledge the presence of a target in our visual field? Here, EEG signals were recorded on humans performing a visual detection task, while they received brief patterns of rhythmic or random transcranial magnetic stimulation (TMS) delivered to the right Frontal Eye Field (FEF) prior to the onset of a lateralized target. TMS entrained oscillations, i.e., increased high-beta power and phase alignment (the latter to a higher extent for rhythmic high-beta patterns than random patterns) while also boosting visual detection sensitivity. Considering post-hoc only those participants in which rhythmic stimulation enhanced visual detection, the magnitude of high-beta entrainment correlated with left visual performance increases. Our study provides evidence in favor of a causal link between high-beta oscillatory activity in the Frontal Eye Field and visual detection. Furthermore, it supports future applications of brain stimulation to manipulate local synchrony and improve or restore impaired visual behaviors.

MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis.

The development of the Brain Imaging Data Structure (BIDS; Gorgolewski et al., 2016) gave the neuroscientific community a standard to organize and share data. BIDS prescribes file naming conventions and a folder structure to store data in a set of already existing file formats. Next to rules about organization of the data itself, BIDS provides standardized templates to store associated metadata in the form of Javascript Object Notation (JSON) and tab separated value (TSV) files. It thus facilitates data sharing, eases metadata querying, and enables automatic data analysis pipelines. BIDS is a rich system to curate, aggregate, and annotate neuroimaging databases.

Arrhythmic activity in the left frontal eye field facilitates conscious visual perception in humans.

The frontal eye field (FEF) is a brain region involved in several processes relevant for visual performance, including visuo-spatial attention, conscious access and decision-making. Prior research has causally demonstrated that high-beta FEF activity in the right hemisphere enhances conscious visual perception, an outcome that is in agreement with evidence of neural synchronization along a right dorsal fronto-parietal network during attentional orienting and a right-hemisphere dominance for visuospatial processing. Nonetheless, frontal regions in the left hemisphere have also been shown to modulate perceptual performance. To causally explore the neural basis of these modulations, we delivered high-beta frequency-specific bursts of transcranial magnetic stimulation (TMS) to the left FEF and report that, in this region, these patterns failed to modulate conscious perception. In contrast, non-frequency-specific TMS patterns yielded visual performance improvements similar to those formerly causally associated to the induction of high-beta activity on its right-hemisphere homotopic area. This noise-induced facilitation of conscious vision suggests a relevant role of the left frontal cortex in visual perception. Furthermore, taken together with prior causal right-FEF evidence, our study indicates that frontal regions of each hemisphere employ different coding strategies to modulate conscious perception.

Frontal eye field, where art thou? Anatomy, function, and non-invasive manipulation of frontal regions involved in eye movements and associated cognitive operations.

The planning, control and execution of eye movements in 3D space relies on a distributed system of cortical and subcortical brain regions. Within this network, the Eye Fields have been described in animals as cortical regions in which electrical stimulation is able to trigger eye movements and influence their latency or accuracy. This review focuses on the Frontal Eye Field (FEF) a "hub" region located in Humans in the vicinity of the pre-central sulcus and the dorsal-most portion of the superior frontal sulcus. The straightforward localization of the FEF through electrical stimulation in animals is difficult to translate to the healthy human brain, particularly with non-invasive neuroimaging techniques. Hence, in the first part of this review, we describe attempts made to characterize the anatomical localization of this area in the human brain. The outcome of functional Magnetic Resonance Imaging (fMRI), Magneto-encephalography (MEG) and particularly, non-invasive mapping methods such a Transcranial Magnetic Stimulation (TMS) are described and the variability of FEF localization across individuals and mapping techniques are discussed. In the second part of this review, we will address the role of the FEF. We explore its involvement both in the physiology of fixation, saccade, pursuit, and vergence movements and in associated cognitive processes such as attentional orienting, visual awareness and perceptual modulation. Finally in the third part, we review recent evidence suggesting the high level of malleability and plasticity of these regions and associated networks to non-invasive stimulation. The exploratory, diagnostic, and therapeutic interest of such interventions for the modulation and improvement of perception in 3D space are discussed.

Manipulation of pre-target activity on the right frontal eye field enhances conscious visual perception in humans.

The right Frontal Eye Field (FEF) is a region of the human brain, which has been consistently involved in visuo-spatial attention and access to consciousness. Nonetheless, the extent of this cortical site's ability to influence specific aspects of visual performance remains debated. We hereby manipulated pre-target activity on the right FEF and explored its influence on the detection and categorization of low-contrast near-threshold visual stimuli. Our data show that pre-target frontal neurostimulation has the potential when used alone to induce enhancements of conscious visual detection. More interestingly, when FEF stimulation was combined with visuo-spatial cues, improvements remained present only for trials in which the cue correctly predicted the location of the subsequent target. Our data provide evidence for the causal role of the right FEF pre-target activity in the modulation of human conscious vision and reveal the dependence of such neurostimulatory effects on the state of activity set up by cue validity in the dorsal attentional orienting network.