Biology subjects

Richardson, M.

Publications and source records attributed to Richardson, M..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Theta-burst direct electrical stimulation remodels human brain networks

Patterned brain stimulation is a powerful therapeutic approach for treating a wide range of brain disorders. In particular, theta-burst stimulation (TBS), characterized by rhythmic bursts of 3-8 Hz mirroring endogenous brain rhythms, is delivered by transcranial magnetic stimulation to improve cognitive functions and relieve symptoms of depression. However, the mechanism by which TBS alters underlying neural activity remains poorly understood. In 10 pre-surgical epilepsy participants undergoing intracranial monitoring, we investigated the neural effects of TBS. Employing intracranial EEG (iEEG) during direct electrical stimulation across 29 stimulation cortical locations, we observed that individual bursts of electrical TBS consistently evoked strong neural responses spanning broad cortical regions. These responses exhibited dynamic changes over the course of stimulation presentations including either increasing or decreasing voltage responses, suggestive of short-term plasticity in the amplitude of the local field potential voltage response. Notably, stronger stimulation augmented the mean amplitude and distribution of TBS responses , leading to greater proportion of recording sites demonstrating short-term plasticity. TBS responses were stimulation site-specific and propagated according to the underlying functional brain architecture, as stronger responses were observed in regions with strong baseline effective (cortico-cortical evoked potentials) and functional (low frequency phase locking) connectivity. Further, our findings enabled the predictions of locations where both TBS responses and change in these responses (e.g. short-term plasticity) were observed. Future work may focus on using pre-treatment connectivity alongside other biophysical factors to personalize stimulation parameters, thereby optimizing induction of neuroplasticity within disease-relevant brain networks.

neuroscience↗

bioRxiv2023

Subthalamic nucleus neurons encode syllable sequence and phonetic characteristics during speech

Speech is a complex behavior that can be used to study unique contributions of the basal ganglia to motor control in the human brain. Computational models suggest that the basal ganglia encodes either the phonetic content or the sequence of speech elements. To explore this question, we investigated the relationship between phoneme and sequence features of a spoken syllable triplet and the firing rate of subthalamic nucleus (STN) neurons recorded during the implantation of deep brain stimulation (DBS) electrodes in individuals with Parkinsons disease. Patients repeated aloud a random sequence of three consonant-vowel (CV) syllables in response to audio cues. Single-unit extracellular potentials were sampled from the sensorimotor STN; a total of 227 unit recordings were obtained from the left STN of 25 subjects (4 female). Of these, 113 (50%) units showed significant task-related increased firing and 53 (23%) showed decreased firing (t-test relative to inter-trial period baseline, p<0.05). Linear regression analysis revealed that both populations of STN neurons encode phoneme and sequence features of produced speech. Maximal phoneme encoding occurred at the time of phoneme production, suggesting efference copyor sensory-related processing, rather than speech motor planning (-50ms and +175ms relative to CV transition for consonant and vowel encoding, respectively). These findings demonstrate that involvement of the basal ganglia in speaking includes separate single unit representations of speech sequencing and phoneme selection in the STN.

neuroscience↗

bioRxiv2023

Deep-Learning-Enabled Differentiation between Intraprostatic Gold Fiducial Markers and Calcification in Quantitative Susceptibility Mapping

PurposeInterest is growing in MR-only radiotherapy (RT) planning for prostate cancer (PCa) due to the potential reductions in cost and patient exposure to radiation, and a more streamlined work-flow and patient imaging pathway. However, in MRI, the gold fiducial markers (FMs) used for target localization appear as signal voids, complicating differentiation from other void sources such as calcifications and bleeds. This work investigates using Quantitative Susceptibility Mapping (QSM), an MRI phase post-processing technique, to aid in the differentiation task. It also presents deep learning models that capture nuanced information and automate the segmentation task, facilitating a streamlined approach to MR-only RT. MethodsCT and MRI, including GRE and T1-weighted imaging, were acquired from 26 PCa patients, each with three implanted gold FMs. GRE data were post-processed into QSM, T 2*, and R2* maps using QSMxTs body imaging pipeline. Statistical analyses were conducted to investigate the quantitative differentiation of FMs and calcification in each contrast. 3D U-Nets were developed using fastMONAI to automate the segmentation task using various combinations of MR-derived contrasts, with a model trained on CT used as a baseline. Models were evaluated using precision and recall calculated using a leave-one-out cross-validation scheme. ResultsSignificant differences were observed between FM and calcification regions in CT, QSM and T 2*, though overlap was observed in QSM and T 2*. The baseline CT U-Net achieved an FM-level precision of {approx} 98% and perfect recall. The best-performing QSM-based model achieved precision and recall of 80% and 90%, respectively, while conventional MRI had values below 70% and 80%, respectively. The QSM-based model produced segmentations with good agreement with the ground truth, including a challenging FM that coincided with a bleed. ConclusionThe model performance highlights the value of using QSM over indirect measures in MRI, such as signal voids in magnitude-based contrasts. The results also indicate that a U-Net can capture more information about the presentation of FMs and other sources than would be possible using susceptibility quantification alone, which may be less reliable due to the diverse presentation of sources across a patient population. In our study, QSM was a reliable discriminator of FMs and other sources in the prostate, facilitating an accurate and streamlined approach to MR-only RT.

pathology↗

bioRxiv2023

Decoding auditory working memory content from intracranial high frequency activity in humans

Working memory (WM), the human brains system for maintaining and manipulating information over short timescales, is critical for goal-directed behavior. Classic neurophysiological models, which emphasize persistent delay activity, are being challenged by an idea that WM is maintained through dynamic and activity-silent mechanisms, where the memory trace is preserved by transient changes in the connections between neurons. To date, human evidence for this alternative model has been limited to non-invasive studies. Here, leveraging high-resolution intracranial stereo-EEG with advanced machine learning decoding techniques, we investigate neuronal mechanisms of human auditory WM. Neuronal activity is quantified as broadband high frequency activity (70-190 Hz), a correlate of neuronal firing activity. Our multivariate pattern analyses, validated via robust non-parametric permutation testing, show that WM content is represented in multiple brain regions, exhibiting dynamic rather than persistent delay activity. Crucially, by using task-irrelevant sounds to probe latent mnemonic states, we provide the first human intracranial evidence of activity silent WM maintenance in a local sensory network.

neuroscience↗

bioRxiv2023

A supervised data-driven spatial filter denoising method for acoustic-induced artifacts in intracranial electrophysiological recordings

Neurosurgical procedures that enable direct brain recordings in awake patients offer unique opportunities to explore the neurophysiology of human speech. The scarcity of these opportunities and the altruism of participating patients compel us to apply the highest rigor to signal analysis. Intracranial electroencephalography (iEEG) signals recorded during overt speech can contain a speech artifact that tracks the fundamental frequency (F0) of the participants voice, involving the same high-gamma frequencies that are modulated during speech production and perception. To address this artifact, we developed a spatial-filtering approach to identify and remove acoustic-induced contaminations of the recorded signal. We found that traditional reference schemes jeopardized signal quality, whereas our data-driven method denoised the recordings while preserving underlying neural activity.

neuroscience↗

bioRxiv2023

Patch2MAP combines patch-clamp electrophysiology with super-resolution structural and protein imaging in identified single neurons without genetic modification

Recent developments in super-resolution microscopy have revolutionized the study of cell biology. However, dense tissues require exogenous protein expression for single cell morphological contrast. In the nervous system, many cell types and species of interest - particularly human - are not amenable to genetic modification and/or exhibit intricate anatomical specializations which make cellular delineation challenging. Here, we present a method for full morphological labeling of individual neurons from any species or cell type for subsequent cell-resolved protein analysis without genetic modification. Our method, which combines patch-clamp electrophysiology with epitope-preserving magnified analysis of proteome (eMAP), further allows for correlation of physiological properties with subcellular protein expression. We applied Patch2MAP to individual spiny synapses in human cortical pyramidal neurons and demonstrated that electrophysiological AMPA-to-NMDA receptor ratios correspond tightly to respective protein expression levels. Patch2MAP thus permits combined subcellular functional, anatomical, and proteomic analyses of any cell, opening new avenues for direct molecular investigation of the human brain in health and disease.

neuroscience↗

bioRxiv2023

Broadband aperiodic components of local field potentials reflect inherent differences between cortical and subcortical activity

Information flow in brain networks is reflected in intracerebral local field potential (LFP) measurements that have both periodic and aperiodic components. The 1/f{chi} broadband aperiodic component of the power spectra has been shown to track arousal level and to correlate with other physiological and pathophysiological states, with consistent patterns across cortical regions. Previous studies have focused almost exclusively on cortical neurophysiology. Here we explored the aperiodic activity of subcortical nuclei from the human thalamus and basal ganglia, in relation to simultaneously recorded cortical activity. We elaborated on the FOOOF (fitting of one over f) method by creating a new parameterization of the aperiodic component with independent and more easily interpretable parameters, which allows seamlessly fitting spectra with and without an aperiodic knee, a component of the signal that reflects the dominant timescale of aperiodic fluctuations. First, we found that the aperiodic exponent from sensorimotor cortex in Parkinsons disease (PD) patients correlated with disease severity. Second, although the aperiodic knee frequency changed across cortical regions as previously reported, no aperiodic knee was detected from subcortical regions across movement disorders patients, including the ventral thalamus (VIM), globus pallidus internus (GPi) and subthalamic nucleus (STN). All subcortical region studied exhibited a relatively low aperiodic exponent ({chi}STN=1.3{+/-}0.2, {chi}VIM=1.4{+/-}0.1, {chi}GPi=1.4{+/-}0.1) that differed markedly from cortical values ({chi}Cortex=3.2{+/-}0.4, fkCortex=17{+/-}5 Hz). These differences were replicated in a second dataset from epilepsy patients undergoing intracranial monitoring that included thalamic recordings. The consistently lower aperiodic exponent and lack of an aperiodic knee from all subcortical recordings may reflect cytoarchitectonic and/or functional differences between subcortical nuclei and the cortex. Significance StatementThe broadband aperiodic component of local field potentials is a useful and reproducible index of neural activity. Here we refined a widely used phenomenological model for extracting aperiodic parameters, with which we fit cortical, basal ganglia and thalamic intracranial local field potentials, recorded from unique cohorts of movement disorders and epilepsy patients. We found that the aperiodic exponent in motor cortex is higher in Parkinsons disease patients with more severe motor symptoms, suggesting that aperiodic features may have potential as electrophysiological biomarkers for movement disorders symptoms. Remarkably, we found conspicuous differences in the broadband aperiodic components of basal ganglia and thalamic signals compared to those from neocortex, suggesting that the aperiodic neural timescale of subcortical LFPs is slower than that in cortex.

neuroscience↗

bioRxiv2023

Charting the Heterogeneity of Colorectal Cancer Consensus Molecular Subtypes using Spatial Transcriptomics

The heterogeneity of colorectal cancer (CRC) contributes to substantial differences in patient response to standard therapies. The consensus molecular subtypes (CMS) of CRC is the most widely-used gene expression-based classification and has contributed to a better understanding of disease heterogeneity and prognosis. Nevertheless, CMS intratumoral heterogeneity restricts its clinical application, stressing the necessity of further characterizing the composition and architecture of CRC. Here, we used Spatial Transcriptomics (ST) in combination with single-cell RNA sequencing (scRNA-seq) to decipher the spatially resolved cellular and molecular composition of CRC. In addition to mapping the intratumoral heterogeneity of CMS and their microenvironment, we identified cell communication events in the tumor-stroma interface of CMS2 carcinomas. This includes tumor growth-inhibiting as well as -activating signatures, such as the potential regulation of the ETV4 transcriptional activity by DCN or the PLAU-PLAUR ligand-receptor interaction. Our data show the power of ST to bring the CMS-based classification of CRC to another level and thereby gain useful molecular insights for personalized therapy.

cancer biology↗

bioRxiv2022

Flexible, Scalable, High Channel Count Stereo-Electrode for Recording in the Human Brain

Over the past decade, stereotactically placed electrodes have become the gold standard for deep brain recording and stimulation for a wide variety of neurological and psychiatric diseases. Current electrodes, however, are limited in their spatial resolution and ability to record from small populations of neurons, let alone individual neurons. Here, we report on a novel, reconfigurable, monolithically integrated human-grade flexible depth electrode capable of recording from up to 128 channels and able to record at a depth of 10 cm in brain tissue. This thin, stylet-guided depth electrode is capable of recording local field potentials and single unit neuronal activity (action potentials), validated across species. This device represents a major new advance in manufacturing and design approaches which extends the capabilities of a mainstay technology in clinical neurology. One-Sentence SummaryA human-grade thin-film depth electrode offers new opportunities in spatial and temporal resolution for recording brain activity.

neuroscience↗

bioRxiv2022

Spatiotemporal dynamics during niche remodeling by super-colonizing microbiota in the mammalian gut

While fecal microbiota transplantation (FMT) has been shown to be effective in reversing gut dysbiosis, we lack an understanding for the fundamental processes underlying microbial engraftment in the mammalian gut. Here, we explored a murine gut colonization model leveraging natural inter-individual variations in gut microbiomes to elucidate the spatiotemporal dynamics of FMT. We identified a natural super-donor consortium that universally engrafts into diverse recipients and resists reciprocal colonization. Temporal profiling of the gut microbiome showed an ordered succession of rapid engraftment by early colonizers within 72 hours followed by a slower emergence of late colonizers over 15-30 days. Moreover, engraftment was localized to distinct compartments of the gastrointestinal tract in a species-specific manner. Spatial metagenomic characterization suggested engraftment was mediated by simultaneous transfer of spatially co-localizing species from the super-donor consortia. These results offer a mechanism of super-donor colonization by which nutritional niches are expanded in a spatiotemporally- dependent manner.

microbiology↗

bioRxiv2021

A Multimodal Approach to Investigate the Neural Mechanisms of Real World Social Vision

Eye tracking and other behavioral measurements collected from patient-participants in their hospital rooms afford a unique opportunity to study immersive natural behavior for basic and clinical translational research. We describe an immersive social and behavioral paradigm implemented in patients undergoing evaluation for surgical treatment of epilepsy, with electrodes implanted in the brain to determine the source of their seizures. Our studies entail collecting eye tracking with other behavioral and psychophysiological measurements from patient-participants during unscripted behavior, including social interactions with clinical staff, friends and family, in the hospital room. This approach affords a unique opportunity to study the neurobiology of natural social behavior, though it requires carefully addressing distinct logistical, technical, and ethical challenges. Collecting neurophysiological data synchronized to behavioral and psychophysiological measures helps us to study the relationship between behavior and physiology. Combining across these rich data sources while participants eat, read, converse with friends and family, etc., enables clinical-translational research aimed at understanding the participants disorders and clinician-patient interactions, as well as basic research into natural, real-world behavior. We discuss data acquisition, quality control, annotation, and analysis pipelines that are required for our studies. We also discuss the clinical, logistical, and ethical and privacy considerations critical to working in the hospital setting.

neuroscience↗

bioRxiv2021

Impact of stimulation location relative to grey and white matter on single pulse electrical stimulation responses in the human brain

BackgroundElectrical neuromodulation is an increasingly common therapy for a wide variety of neuropsychiatric diseases. Unfortunately, therapeutic efficacy is inconsistent, possibly a result of our limited understanding of the mechanisms and the massive stimulation parameter space. Objective/HypothesisTo better understand the role different parameters play in inducing a response, we systematically examined single pulse-induced cortico-cortico evoked potentials (CCEP) as a function of stimulation amplitude, duration and location in the brain and relative to grey and white matter. MethodsWe measured voltage peak amplitudes and area under the curve of intracranially recorded stimulation responses as a function of distance from the stimulation site, pulse width, current injected, location relative to grey and white matter, and brain region stimulated (N=52, n=719 stimulation sites). ResultsIncreasing stimulation pulse width increased response values near the stimulation location. Increasing stimulation amplitude (current) increased responses nonlinearly. Locally (<15 mm from the stimulation site), stimulation closer to the grey matter-white matter boundary induced larger responses. In contrast, for distant sites (>15 mm), white matter stimulation consistently produced larger responses than stimulation in or near grey matter. These relationships were different between cingulate, lateral prefrontal, and lateral temporal cortical stimulation. ConclusionThese results demonstrate the importance of location and stimulation parameters in inducing a specific output and indicate that a stronger local response may require stimulation in the grey-white boundary while stimulation in the white matter may be needed for network activation, suggesting that stimulation location can be tailored for a specific outcome, key to informed neuromodulatory therapy. HighlightsO_LIIntracranial single pulse electrical stimulation (SPES) response increases with increased pulse duration mostly near the stimulation site C_LIO_LISPES response varies nonlinearly with injected current with an effect of distance from the stimulation site. C_LIO_LISPES near the grey-white boundary and 90{degrees} to the nearest cortical axis induces larger local responses, but white matter stimulation produces larger distant responses. C_LIO_LIThe relationship between SPES location and responses depends on brain region stimulated C_LI

neuroscience↗

bioRxiv2021

Progression and Resolution of SARS-1 CoV-2 Infection in Golden Syrian Hamsters

To catalyze SARS-CoV-2 research including development of novel interventive and preventive strategies, we characterized progression of disease in depth in a robust COVID-19 animal model. In this model, male and female golden Syrian hamsters were inoculated intranasally with SARS-CoV-2 USA-WA1/2020. Groups of inoculated and mock-inoculated uninfected control animals were euthanized at day 2, 4, 7, 14, and 28 days post-inoculation to track multiple clinical, pathology, virology, and immunology outcomes. SARS-CoV-2-inoculated animals consistently lost body weight during the first week of infection, had higher lung weights at terminal timepoints, and developed lung consolidation per histopathology and quantitative image analysis measurements. High levels of infectious virus and viral RNA were reliably present in the respiratory tract at days 2 and 4 post-inoculation, corresponding with widespread necrosis and inflammation. At day 7, when infectious virus was rare, interstitial and alveolar macrophage infiltrates and marked reparative epithelial responses (type II hyperplasia) dominated in the lung. These lesions resolved over time, with only residual epithelial repair evident by day 28 post-inoculation. The use of quantitative approaches to measure cellular and morphologic alterations in the lung provides valuable outcome measures for developing therapeutic and preventive interventions for COVID-19 using the hamster COVID-19 model.

pathology↗

bioRxiv2021

Large-scale neural recordings with single-cell resolution in human cortex using high-density Neuropixels probes

Recent advances in multi-electrode array technology have made it possible to monitor large neuronal ensembles at cellular resolution. In humans, however, current approaches either restrict recordings to only a few neurons per penetrating electrode or combine the signals of thousands of neurons in local field potential (LFP) recordings. Here, we describe a new probe variant and set of techniques which enable simultaneous recording from over 200 well-isolated cortical single units in human participants during intraoperative neurosurgical procedures using silicon Neuropixels probes. We characterized a diversity of extracellular waveforms with eight separable single unit classes, with differing firing rates, positions along the length of the linear electrode array, spatial spread of the waveform, and modulation by LFP events such as inter-ictal discharges and burst suppression. While some additional challenges remain in creating a turn-key recording system, high-density silicon arrays provide a path for studying human-specific cognitive processes and their dysfunction at unprecedented spatiotemporal resolution.

neuroscience↗

bioRxiv2021

Durable antibody responses in staff at two long-term care facilities, during and post SARS-CoV-2 outbreaks

SARS-CoV-2 has had a disproportionate impact on non-hospital healthcare settings such as long-term care facilities (LTCFs). The communal nature of these facilities, paired with the high-risk profile of residents, has resulted in thousands of infections and deaths and a high case fatality rate. To detect pre-symptomatic infections and identify infected workers, we performed weekly surveillance testing of staff at two LTCFs which revealed a large outbreak at one of the sites. We collected serum from staff members throughout the study and evaluated it for binding and neutralization to measure seroprevalence, seroconversion, and type and functionality of antibodies. At the site with very few incident infections, we detected that over 40% of the staff had preexisting SARS-CoV-2 neutralizing antibodies, suggesting prior exposure. At the outbreak site, we saw rapid seroconversion following infection. Neutralizing antibody levels were stable for many weeks following infection, suggesting a durable, long-lived response. Receptor-binding domain antibodies and neutralizing antibodies were strongly correlated. The site with high seroprevalence among staff had two unique introductions of SARS-CoV-2 into the facility through seronegative infected staff during the period of study but these did not result in workplace spread or outbreaks. Together our results reveal that high seroprevalence rate among staff can contribute to herd immunity within a workplace and protect against subsequent infection and spread within a facility.

immunology↗

bioRxiv2021

Differentiation of speech-induced artifacts from physiological high gamma activity in intracranial recordings

There is great interest in identifying the neurophysiological underpinnings of speech production. Deep brain stimulation (DBS) surgery is unique in that it allows intracranial recordings from both cortical and subcortical regions in patients who are awake and speaking. The quality of these recordings, however, may be affected to various degrees by mechanical forces resulting from speech itself. Here we describe the presence of speech-induced artifacts in local-field potential (LFP) recordings obtained from mapping electrodes, DBS leads, and cortical electrodes. In addition to expected physiological increases in high gamma (60-200 Hz) activity during speech production, time-frequency analysis in many channels revealed a narrowband gamma component that exhibited a pattern similar to that observed in the speech audio spectrogram. This component was present to different degrees in multiple types of neural recordings. We show that this component tracks the fundamental frequency of the participants voice, correlates with the power spectrum of speech and has coherence with the produced speech audio. A vibration sensor attached to the stereotactic frame recorded speech-induced vibrations with the same pattern observed in the LFPs. No corresponding component was identified in any neural channel during the listening epoch of a syllable repetition task. These observations demonstrate how speech-induced vibrations can create artifacts in the primary frequency band of interest. Identifying and accounting for these artifacts is crucial for establishing the validity and reproducibility of speech-related data obtained from intracranial recordings during DBS surgery.

neuroscience↗

bioRxiv2021

Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson's disease

Brain signal decoding promises significant advances in the development of clinical brain computer interfaces (BCI). In Parkinsons disease (PD), first bidirectional BCI implants for adaptive deep brain stimulation (DBS) are now available. Brain signal decoding can extend the clinical utility of adaptive DBS but the impact of neural source, computational methods and PD pathophysiology on decoding performance are unknown. This represents an unmet need for the development of future neurotechnology. To address this, we developed an invasive brain-signal decoding approach based on intraoperative sensorimotor electrocorticography (ECoG) and subthalamic LFP to predict grip-force, a representative movement decoding application, in 11 PD patients undergoing DBS. We demonstrate that ECoG is superior to subthalamic LFP for accurate grip-force decoding. Gradient boosted decision trees (XGBOOST) outperformed other model architectures. ECoG based decoding performance negatively correlated with motor impairment, which could be attributed to subthalamic beta bursts in the motor preparation and movement period. This highlights the impact of PD pathophysiology on the neural capacity to encode movement kinematics. Finally, we developed a connectomic analysis that could predict grip-force decoding performance of individual ECoG channels across patients by using their connectomic fingerprints. Our study provides a neurophysiological and computational framework for invasive brain signal decoding to aid the development of an individualized precision-medicine approach to intelligent adaptive DBS. Significance StatementNeurotechnology will revolutionize the treatment of neurological and psychiatric patients, promising novel treatment avenues for previously intractable brain disorders. However, optimal surgical and computational approaches and their interactions with neurological disorders are unknown. How can recent advances in machine learning and connectomics aid the precision and performance of invasive brain signal decoding strategies? Do the brain disorders treated with such approaches have impact on decoding performance? We propose a real time compatible advanced machine learning pipeline for invasively recorded brain signals in Parkinsons disease (PD) patients. We report optimal movement decoding strategies with respect to signal source, model architecture and connectomic fingerprint and demonstrate that PD pathophysiology significantly and negatively impacts movement decoding. Our study has broad impacts for the development of smart brain implants for the treatment of PD and other brain disorders.

neuroscience↗

bioRxiv2021

Deep Brain Stimulation for Parkinson's Disease Induces Spontaneous Cortical Hypersynchrony In Extended Motor and Cognitive Networks

The mechanism of action of deep brain stimulation (DBS) for Parkinsons disease remains unclear. Studies have shown that DBS decreases pathological beta hypersynchrony between the basal ganglia and motor cortex. However, little is known about DBSs effects on long range corticocortical synchronization. Here, we use machine learning combined with spectral graph theory to compare resting-state cortical connectivity between the off and on-stimulation states and compare these differences to healthy controls. We found that turning DBS on increased high beta and gamma band coherence in a cortical circuit spanning the motor, occipitoparietal, middle temporal, and prefrontal cortices. We found no significant difference between DBS-off and controls in this network with multivariate pattern classification showing that the brain connectivity pattern in control subjects is more like those during DBS-off than DBS-on. These results show that therapeutic DBS increases spontaneous high beta-gamma synchrony in a network that couples motor areas to broader cognitive systems.

neuroscience↗