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Human immunodeficiency virus-associated distal sensory polyneuropathy (HIV-DSP) affects up to 50% of people with HIV and is associated with depression, unemployment, and generally worsened quality of life. Previous work on the cortical mechanism of HIV neuropathy found decreased gray matter volume in the bilateral midbrain, thalamus, and posterior cingulate cortex, but structural connectivity in this context remains under-studied. Here we examine alterations in white matter microstructure using diffusion imaging, hypothesizing that cortical white matter degeneration would be observed in continuation of the peripheral white matter atrophy previously observed in HIV-DSP. Male HIV seropositive patients (n = 57) experiencing varying degrees of HIV neuropathy underwent single-shell diffusion tensor imaging with 51 sampling directions. The scans were pooled using tractography and connectometry to create a quantitative map of white matter tract integrity, measured in generalized fractional anisotropy (GFA). The relationship between GFA and neuropathy severity was evaluated with linear regression. Correction for multiple comparisons was done using false discovery rate (FDR), a statistical method commonly used in genomics and imaging to minimize false positives when thousands of individual comparisons are made. Neuropathy severity was associated with decreased GFA along thalamocortical radiations leading along the lateral thalamus to sensorimotor cortex, with r = -0.405 (p

The ability of humans to coordinate stereotyped, alternating movements between the two legs during bipedal walking is a complex motor behavior that requires precisely timed activities across multiple nodes of the supraspinal network. Understanding of the neural network dynamics that underlie natural walking in humans is limited. We investigated cortical and subthalamic neural activities during overground walking and evaluated spectral biomarkers to decode the gait cycle in three patients with Parkinson's disease without gait disturbances. Patients were implanted with chronic bilateral deep brain stimulation (DBS) leads in the subthalamic nucleus (STN) and electrocorticography paddles overlaying the primary motor and somatosensory cortices. Local field potentials were recorded from these areas while the participants performed overground walking and synchronized to external gait kinematic sensors. We found that the STN displays increased low-frequency (4-12 Hz) spectral power during the period before contralateral leg swing. Furthermore, STN shows increased theta frequency (4-8 Hz) coherence with the primary motor through the initiation and early phase of contralateral leg swing. Additional analysis revealed that each patient had specific frequency bands that could detect a significant difference between left and right initial leg swing. Our findings indicate that there are alternating spectral changes between the two hemispheres in accordance with the gait cycle. In addition, we identified patient-specific, gait-related biomarkers in both the STN and cortical areas at discrete frequency bands that may be used to drive adaptive DBS to improve gait dysfunction in patients with Parkinson's disease.

Resting state (RS) fMRI is now widely used for gaining insight into the organization of brain networks. Functional connectivity (FC) inferred from RS-fMRI is typically at macroscale, which is too coarse for much of the detail in cortical architecture. Here, we examined whether imaging RS at higher contrast and resolution could reveal cortical connectivity with columnar granularity. In longitudinal experiments (~1.5 years) in squirrel monkeys, we partitioned sensorimotor cortex using dense microelectrode mapping and then recorded RS with intrinsic signal optical imaging (RS-ISOI, 20 µm/pixel). FC maps were benchmarked against microstimulation-evoked activation and traced anatomical connections. These direct comparisons showed high correspondence in connectivity patterns across methods. The fidelity of FC maps to cortical connections indicates that granular details of network organization are embedded in RS. Thus, for recording RS, the field-of-view and effective resolution achieved with ISOI fills a wide gap between fMRI and invasive approaches (2-photon imaging, electrophysiology). RS-ISOI opens exciting opportunities for high resolution mapping of cortical networks in living animals.

Magnetoencephalography (MEG) is a robust method for non-invasive functional brain mapping of sensory cortices due to its exceptional spatial and temporal resolution. The clinical standard for MEG source localization of functional landmarks from sensory evoked responses is the equivalent current dipole (ECD) localization algorithm, known to be sensitive to initialization, noise, and manual choice of the number of dipoles. Recently many automated and robust algorithms have been developed, including the Champagne algorithm, an empirical Bayesian algorithm, with powerful abilities for MEG source reconstruction and time course estimation (Wipf et al. 2010; Owen et al. 2012). Here, we evaluate automated Champagne performance in a clinical population of tumor patients where there was minimal failure in localizing sensory evoked responses using the clinical standard, ECD localization algorithm. MEG data of auditory evoked potentials and somatosensory evoked potentials from 21 brain tumor patients were analyzed using Champagne, and these results were compared with equivalent current dipole (ECD) fit. Across both somatosensory and auditory evoked field localization, we found there was a strong agreement between Champagne and ECD localizations in all cases. Given resolution of 8mm voxel size, peak source localizations from Champagne were below 10mm of ECD peak source localization. The Champagne algorithm provides a robust and automated alternative to manual ECD fits for clinical localization of sensory evoked potentials and can contribute to improved clinical MEG data processing workflows.

BackgroundTechnology to restore the ability to communicate in paralyzed persons who cannot speak has the potential to improve autonomy and quality of life. An approach that decodes words and sentences directly from the cerebral cortical activity of such patients may represent an advancement over existing methods for assisted communication.MethodsWe implanted a subdural, high-density, multielectrode array over the area of the sensorimotor cortex that controls speech in a person with anarthria (the loss of the ability to articulate speech) and spastic quadriparesis caused by a brain-stem stroke. Over the course of 48 sessions, we recorded 22 hours of cortical activity while the participant attempted to say individual words from a vocabulary set of 50 words. We used deep-learning algorithms to create computational models for the detection and classification of words from patterns in the recorded cortical activity. We applied these computational models, as well as a natural-language model that yielded next-word probabilities given the preceding words in a sequence, to decode full sentences as the participant attempted to say them.ResultsWe decoded sentences from the participant's cortical activity in real time at a median rate of 15.2 words per minute, with a median word error rate of 25.6%. In post hoc analyses, we detected 98% of the attempts by the participant to produce individual words, and we classified words with 47.1% accuracy using cortical signals that were stable throughout the 81-week study period.ConclusionsIn a person with anarthria and spastic quadriparesis caused by a brain-stem stroke, words and sentences were decoded directly from cortical activity during attempted speech with the use of deep-learning models and a natural-language model. (Funded by Facebook and others; ClinicalTrials.gov number, NCT03698149.).

The ability to perceive and produce movements in the real world with precise timing is critical for survival in animals, including humans. However, research on sensorimotor timing has rarely considered the tight interrelation between perception, action, and cognition. In this review, we present new evidence from behavioral, computational, and neural studies in humans and nonhuman primates, suggesting a pivotal link between sensorimotor control and temporal processing, as well as describing new theoretical frameworks regarding timing in perception and action. We first discuss the link between movement coordination and interval-based timing by addressing how motor training develops accurate spatiotemporal patterns in behavior and influences the perception of temporal intervals. We then discuss how motor expertise results from establishing task-relevant neural manifolds in sensorimotor cortical areas and how the geometry and dynamics of these manifolds help reduce timing variability. We also highlight how neural dynamics in sensorimotor areas are involved in beat-based timing. These lines of research aim to extend our understanding of how timing arises from and contributes to perceptual-motor behaviors in complex environments to seamlessly interact with other cognitive processes.

The motor system demonstrates an exquisite ability to adapt to changes in the environment and to quickly reset when these changes prove transient. If similar environmental changes are encountered in the future, learning may be faster, a phenomenon known as savings. In studies of sensorimotor learning, a central component of savings is attributed to the explicit recall of the task structure and appropriate compensatory strategies. Whether implicit adaptation also contributes to savings remains subject to debate. We tackled this question by measuring, in parallel, explicit and implicit adaptive responses in a visuomotor rotation task, employing a protocol that typically elicits savings. While the initial rate of learning was faster in the second exposure to the perturbation, an analysis decomposing the 2 processes showed the benefit to be solely associated with explicit re-aiming. Surprisingly, we found a significant decrease after relearning in aftereffect magnitudes during no-feedback trials, a direct measure of implicit adaptation. In a second experiment, we isolated implicit adaptation using clamped visual feedback, a method known to eliminate the contribution of explicit learning processes. Consistent with the results of the first experiment, participants exhibited a marked reduction in the adaptation function, as well as an attenuated aftereffect when relearning from the clamped feedback. Motivated by these results, we reanalyzed data from prior studies and observed a consistent, yet unappreciated pattern of attenuation of implicit adaptation during relearning. These results indicate that explicit and implicit sensorimotor processes exhibit opposite effects upon relearning: Explicit learning shows savings, while implicit adaptation becomes attenuated.

The fluent production of a signed language requires exquisite coordination of sensory, motor, and cognitive processes. Similar to speech production, language produced with the hands by fluent signers appears effortless but reflects the precise coordination of both large-scale and local cortical networks. The organization and representational structure of sensorimotor features underlying sign language phonology in these networks remains unknown. Here, we present a unique case study of high-density electrocorticography (ECoG) recordings from the cortical surface of profoundly deaf signer during awake craniotomy. While neural activity was recorded from sensorimotor cortex, the participant produced a large variety of movements in linguistic and transitional movement contexts. We found that at both single electrode and neural population levels, high-gamma activity reflected tuning for particular hand, arm, and face movements, which were organized along dimensions that are relevant for phonology in sign language. Decoding of manual articulatory features revealed a clear functional organization and population dynamics for these highly practiced movements. Furthermore, neural activity clearly differentiated linguistic and transitional movements, demonstrating encoding of language-relevant articulatory features. These results provide a novel and unique view of the fine-scale dynamics of complex and meaningful sensorimotor actions.

Approximately half of individuals with Social Anxiety Disorder (SAD) treated with psychological intervention do not achieve clinically significant improvement or retain long-term gains. Neurobiological models of SAD propose that disruptions in functioning of amygdala-prefrontal circuitry is implicated in short-term treatment response. However, whether treatment-related changes in functional connectivity predict long-term well-being after psychotherapy is unknown. Patients with SAD completed an incidental emotion regulation task during fMRI before and after treatment with cognitive behavioral therapy or acceptance and commitment therapy (n = 23, collapsed across groups). Psychophysiological interaction analyses using amygdala seed regions were conducted to assess changes in functional connectivity from pre-to post-treatment that predicted symptom change from 6 to 12-month follow-up. Negative change (i.e., greater inverse/weaker positive) in amygdala connectivity with the dorsomedial prefrontal cortex (dmPFC) and dorsal anterior cingulate cortex (dACC) predicted greater symptom reduction during follow-up. Positive change in amygdala connectivity with the cerebellum, fusiform gyrus, and pre-central and post-central gyri predicted less symptom reduction (e.g., no change or worsening). Results suggest that strengthened amygdala connectivity with regulatory regions may promote better long-term outcomes, whereas changes with visual and sensorimotor regions may represent sensitization to emotion-related cues, conferring poorer outcomes. Clinical implications for treatment personalization are discussed, should effects replicate in larger samples.

Speaking is a sensorimotor behavior whose neural basis is difficult to study with single neuron resolution due to the scarcity of human intracortical measurements. We used electrode arrays to record from the motor cortex 'hand knob' in two people with tetraplegia, an area not previously implicated in speech. Neurons modulated during speaking and during non-speaking movements of the tongue, lips, and jaw. This challenges whether the conventional model of a 'motor homunculus' division by major body regions extends to the single-neuron scale. Spoken words and syllables could be decoded from single trials, demonstrating the potential of intracortical recordings for brain-computer interfaces to restore speech. Two neural population dynamics features previously reported for arm movements were also present during speaking: a component that was mostly invariant across initiating different words, followed by rotatory dynamics during speaking. This suggests that common neural dynamical motifs may underlie movement of arm and speech articulators.

Background and aimsEvidence from preclinical and clinical studies suggests that interactions among the brain, gut, and microbiota may affect the pathophysiology of irritable bowel syndrome (IBS). As disruptions in central and peripheral serotonergic signaling pathways have been found in patients with IBS, we explored the hypothesis that the abundance of serotonin-modulating microbes of the order Clostridiales is associated with functional connectivity of somatosensory brain regions and gastrointestinal (GI) sensorimotor function.MethodsWe performed a prospective study of 65 patients with IBS and 21 healthy individuals (controls) recruited from 2011 through 2013 at a secondary/tertiary care outpatient clinic in Sweden. Study participants underwent functional brain imaging, rectal balloon distension, a nutrient and lactulose challenge test, and assessment of oroanal transit time within a month. They also submitted stool samples, which were analyzed by 16S ribosomal RNA gene sequencing. A tripartite network analysis based on graph theory was used to investigate the interactions among bacteria in the order Clostridiales, connectivity of brain regions in the somatosensory network, and GI sensorimotor function.ResultsWe found associations between GI sensorimotor function and gut microbes in stool samples from controls, but not in samples from IBS patients. The largest differences between controls and patients with IBS were observed in the Lachnospiraceae incertae sedis, Clostridium XIVa, and Coprococcus subnetworks. We found connectivity of subcortical (thalamus, caudate, and putamen) and cortical (primary and secondary somatosensory cortices) regions to be involved in mediating interactions among these networks.ConclusionsIn a comparison of patients with IBS and controls, we observed disruptions in the interactions between the brain, gut, and gut microbial metabolites in patients with IBS-these involve mainly subcortical but also cortical regions of brain. These disruptions may contribute to altered perception of pain in patients with IBS and may be mediated by microbial modulation of the gut serotonergic system.

Beta oscillations (∼13 to 30 Hz) have been observed during many perceptual, cognitive, and motor processes in a plethora of brain recording studies. Although the function of beta oscillations (hereafter "beta" for short) is unlikely to be explained by any single monolithic description, we here discuss several convergent findings. In prefrontal cortex (PFC), increased beta appears at the end of a trial when working memory information needs to be erased. A similar "clear-out" function might apply during the stopping of action and the stopping of long-term memory retrieval (stopping thoughts), where increased prefrontal beta is also observed. A different apparent role for beta in PFC occurs during the delay period of working memory tasks: it might serve to maintain the current contents and/or to prevent interference from distraction. We confront the challenge of relating these observations to the large literature on beta recorded from sensorimotor cortex. Potentially, the clear-out of working memory in PFC has its counterpart in the postmovement clear-out of the motor plan in sensorimotor cortex. However, recent studies support alternative interpretations. In addition, we flag emerging research on different frequencies of beta and the relationship between beta and single-neuron spiking. We also discuss where beta might be generated: basal ganglia, cortex, or both. We end by considering the clinical implications for adaptive deep-brain stimulation.

A fundamental challenge in neuroscience is to understand what structure in the world is represented in spatially distributed patterns of neural activity from multiple single-trial measurements. This is often accomplished by learning a simple, linear transformations between neural features and features of the sensory stimuli or motor task. While successful in some early sensory processing areas, linear mappings are unlikely to be ideal tools for elucidating nonlinear, hierarchical representations of higher-order brain areas during complex tasks, such as the production of speech by humans. Here, we apply deep networks to predict produced speech syllables from a dataset of high gamma cortical surface electric potentials recorded from human sensorimotor cortex. We find that deep networks had higher decoding prediction accuracy compared to baseline models. Having established that deep networks extract more task relevant information from neural data sets relative to linear models (i.e., higher predictive accuracy), we next sought to demonstrate their utility as a data analysis tool for neuroscience. We first show that deep network's confusions revealed hierarchical latent structure in the neural data, which recapitulated the underlying articulatory nature of speech motor control. We next broadened the frequency features beyond high-gamma and identified a novel high-gamma-to-beta coupling during speech production. Finally, we used deep networks to compare task-relevant information in different neural frequency bands, and found that the high-gamma band contains the vast majority of information relevant for the speech prediction task, with little-to-no additional contribution from lower-frequency amplitudes. Together, these results demonstrate the utility of deep networks as a data analysis tool for basic and applied neuroscience.

Sensorimotor deficits are prevalent in many neurodevelopmental disorders like autism, including one of its common genetic etiologies, a 600 kb reciprocal deletion/duplication at 16p11.2. We have previously shown that copy number variations of 16p11.2 impact regional brain volume, white matter integrity, and early sensory responses in auditory cortex. Here, we test the hypothesis that abnormal cortical neurophysiology is present when genes in the 16p11.2 region are haploinsufficient, and in humans that this in turn may account for behavioral deficits specific to deletion carriers. We examine sensorimotor cortical network activity in males and females with 16p11.2 deletions compared with both typically developing individuals, and those with duplications of 16p11.2, using magnetoencephalographic imaging during preparation of overt speech or hand movements in tasks designed to be easy for all participants. In deletion carriers, modulation of beta oscillations (12-30 Hz) were increased during both movement types over effector-specific regions of motor cortices compared with typically developing individuals or duplication carriers, with no task-related performance differences between cohorts, even when corrected for their own cognitive and sensorimotor deficits. Reduced left hemispheric language specialization was observed in deletion carriers but not in duplication carriers. Neural activity over sensorimotor cortices in deletion carriers was linearly related to clinical measures of speech and motor impairment. These findings link insufficient copy number repeats at 16p11.2 to excessive neural activity (e.g., increased beta oscillations) in motor cortical networks for speech and hand motor control. These results have significant implications for understanding the neural basis of autism and related neurodevelopmental disorders.SIGNIFICANCE STATEMENT The recurrent ∼600 kb deletion at 16p11.2 (BP4-BP5) is one of the most common genetic etiologies of ASD and, more generally, of neurodevelopmental disorders. Here, we use high-resolution magnetoencephalographic imaging (MEG-I) to define with millisecond precision the underlying neurophysiological signature of motor impairments for individuals with 16p11.2 deletions. We identify significant increases in beta (12-30 Hz) suppression in sensorimotor cortices related to performance during speech and hand movement tasks. These findings not only provide a neurophysiological phenotype for the clinical presentation of this genetic deletion, but also guide our understanding of how genetic variation encodes for neural oscillatory dynamics.

We present a new computational model of speech motor control: the Feedback-Aware Control of Tasks in Speech or FACTS model. FACTS employs a hierarchical state feedback control architecture to control simulated vocal tract and produce intelligible speech. The model includes higher-level control of speech tasks and lower-level control of speech articulators. The task controller is modeled as a dynamical system governing the creation of desired constrictions in the vocal tract, after Task Dynamics. Both the task and articulatory controllers rely on an internal estimate of the current state of the vocal tract to generate motor commands. This estimate is derived, based on efference copy of applied controls, from a forward model that predicts both the next vocal tract state as well as expected auditory and somatosensory feedback. A comparison between predicted feedback and actual feedback is then used to update the internal state prediction. FACTS is able to qualitatively replicate many characteristics of the human speech system: the model is robust to noise in both the sensory and motor pathways, is relatively unaffected by a loss of auditory feedback but is more significantly impacted by the loss of somatosensory feedback, and responds appropriately to externally-imposed alterations of auditory and somatosensory feedback. The model also replicates previously hypothesized trade-offs between reliance on auditory and somatosensory feedback and shows for the first time how this relationship may be mediated by acuity in each sensory domain. These results have important implications for our understanding of the speech motor control system in humans.

The 22q11.2 deletion syndrome (22q11DS) is a recurrent copy number variant with high penetrance for developmental neuropsychiatric disorders. Study of individuals with 22q11DS therefore may offer key insights into neural mechanisms underlying such complex illnesses. Resting-state functional connectivity MRI studies in idiopathic schizophrenia have consistently revealed disruption of thalamic and hippocampal circuitry. Here, we sought to test whether this circuitry is similarly disrupted in the context of this genetic high-risk condition. To this end, resting-state functional connectivity patterns were assessed in a sample of human youth with 22q11DS (n = 42; 59.5% female) and demographically matched healthy controls (n = 39; 53.8% female). Neuroimaging data were acquired via single-band protocols and analyzed in line with methods provided by the Human Connectome Project. We computed functional relationships between individual-specific anatomically defined thalamic and hippocampal seeds and all gray matter voxels in the brain. Whole-brain Type I error protection was achieved through nonparametric permutation-based methods. The 22q11DS patients displayed dissociable disruptions in thalamic and hippocampal functional connectivity relative to control subjects. Thalamocortical coupling was increased in somatomotor regions and reduced across associative networks. The opposite effect was observed for the hippocampus in regards to somatomotor and associative network connectivity. The thalamic and hippocampal dysconnectivity observed in 22q11DS suggests that high genetic risk for psychiatric illness is linked with disruptions in large-scale corticosubcortical networks underlying higher-order cognitive functions. These effects highlight the translational importance of large-effect copy number variants for informing mechanisms underlying neural disruptions observed in idiopathic developmental neuropsychiatric disorders.SIGNIFICANCE STATEMENT Investigation of neuroimaging biomarkers in highly penetrant genetic syndromes represents a more biologically tractable approach to identify neural circuit disruptions underlying developmental neuropsychiatric conditions. The 22q11.2 deletion syndrome confers particularly high risk for psychotic disorders and is thus an important translational model in which to investigate systems-level mechanisms implicated in idiopathic illness. Here, we show resting-state fMRI evidence of large-scale sensory and executive network disruptions in youth with 22q11DS. In particular, this study provides the first evidence that these networks are disrupted in a dissociable fashion with regard to the functional connectivity of the thalamus and hippocampus, suggesting circuit-level dysfunction.

Localizing neurologic function within the brain remains a significant challenge in clinical neurosurgery. Invasive mapping with direct electrocortical stimulation currently is the clinical gold standard but is impractical in young or cognitively delayed patients who are unable to reliably perform tasks. Resting state functional magnetic resonance imaging non-invasively identifies resting state networks without the need for task performance, hence, is well suited to pediatric patients. We compared sensorimotor network localization by resting state fMRI to cortical stimulation sensory and motor mapping in 16 pediatric patients aged 3.1 to 18.6 years. All had medically refractory epilepsy that required invasive electrographic monitoring and stimulation mapping. The resting state fMRI data were analyzed using a previously trained machine learning classifier that has previously been evaluated in adults. We report comparable functional localization by resting state fMRI compared to stimulation mapping. These results provide strong evidence for the utility of resting state functional imaging in the localization of sensorimotor cortex across a wide range of pediatric patients.

That experience shapes sensory tuning in primary sensory cortex is well understood. But effective neural population codes depend on more than just sensory tuning. Recent population imaging and recording studies have characterized population codes in sensory cortex, and tracked how they change with sensory manipulations and training on perceptual learning tasks. These studies confirm sensory tuning changes, but also reveal other features of plasticity, including sensory gain modulation, restructuring of firing correlations, and differential routing of information to output pathways. Unexpectedly strong day-to-day variation exists in single-neuron sensory tuning, which stabilizes during learning. These are novel dimensions of plasticity in sensory cortex, which refine population codes during learning, but whose mechanisms are unknown.

ObjectiveTo determine the relationship between functional connectivity (FC) using resting-state functional magnetic resonance imaging (MRI) and neurological impairment in patients with cervical spondylosis and healthy controls.MethodsA total of 24 patients with cervical spondylosis with or without myelopathy and 17 neurologically intact, healthy volunteer subjects were prospectively enrolled in a cross-sectional study involving observational MRI and evaluation of neurological function using the modified Japanese Orthopedic Association (mJOA) score. Seed-to-seed connectivity and seed-to-voxel connectivity on functional MRI data were performed using a general linear model of connectivity with respect to age and mJOA score.ResultsIncreased FC was observed with increasing neurological impairment in patients with cervical stenosis within sensorimotor areas, including precentral gyrus, postcentral gyrus, and supplemental motor regions, using both seed-to-seed and seed-to-voxel analyses. The anterior cingulate showed increasing connectivity with the supplemental motor area, thalamus, and cerebellum with increasing neurological function. Similarly, the thalamus, cerebellum, and putamen presented with increasing connectivity to both the bilateral precuneus and the posterior cingulate with an increasing mJOA score.ConclusionsPatients with cervical spondylosis exhibiting neurological impairment experience changes in brain connectivity similar to that of patients with chronic traumatic spinal cord injury. These results suggest an increase in FC within sensorimotor regions with increasing neurological impairment and decreased connectivity between the cerebellum, putamen, and thalamus to the anterior and posterior cingulate and frontal lobe regions.

Recent work has highlighted the importance of transient low-frequency oscillatory (LFO;

When speaking, we dynamically coordinate movements of our jaw, tongue, lips, and larynx. To investigate the neural mechanisms underlying articulation, we used direct cortical recordings from human sensorimotor cortex while participants spoke natural sentences that included sounds spanning the entire English phonetic inventory. We used deep neural networks to infer speakers' articulator movements from produced speech acoustics. Individual electrodes encoded a diversity of articulatory kinematic trajectories (AKTs), each revealing coordinated articulator movements toward specific vocal tract shapes. AKTs captured a wide range of movement types, yet they could be differentiated by the place of vocal tract constriction. Additionally, AKTs manifested out-and-back trajectories with harmonic oscillator dynamics. While AKTs were functionally stereotyped across different sentences, context-dependent encoding of preceding and following movements during production of the same phoneme demonstrated the cortical representation of coarticulation. Articulatory movements encoded in sensorimotor cortex give rise to the complex kinematics underlying continuous speech production. VIDEO ABSTRACT.

During speech production, we make vocal tract movements with remarkable precision and speed. Our understanding of how the human brain achieves such proficient control is limited, in part due to the challenge of simultaneously acquiring high-resolution neural recordings and detailed vocal tract measurements. To overcome this challenge, we combined ultrasound and video monitoring of the supralaryngeal articulators (lips, jaw, and tongue) with electrocorticographic recordings from the cortical surface of 4 subjects (3 female, 1 male) to investigate how neural activity in the ventral sensory-motor cortex (vSMC) relates to measured articulator movement kinematics (position, speed, velocity, acceleration) during the production of English vowels. We found that high-gamma activity at many individual vSMC electrodes strongly encoded the kinematics of one or more articulators, but less so for vowel formants and vowel identity. Neural population decoding methods further revealed the structure of kinematic features that distinguish vowels. Encoding of articulator kinematics was sparsely distributed across time and primarily occurred during the time of vowel onset and offset. In contrast, encoding was low during the steady-state portion of the vowel, despite sustained neural activity at some electrodes. Significant representations were found for all kinematic parameters, but speed was the most robust. These findings enabled by direct vocal tract monitoring demonstrate novel insights into the representation of articulatory kinematic parameters encoded in the vSMC during speech production.SIGNIFICANCE STATEMENT Speaking requires precise control and coordination of the vocal tract articulators (lips, jaw, and tongue). Despite the impressive proficiency with which humans move these articulators during speech production, our understanding of how the brain achieves such control is rudimentary, in part because the movements themselves are difficult to observe. By simultaneously measuring speech movements and the neural activity that gives rise to them, we demonstrate how neural activity in sensorimotor cortex produces complex, coordinated movements of the vocal tract.

Autism has been characterized by atypical task-related brain activation and functional connections, coinciding with deficits in sociocommunicative abilities. However, evidence of the brain's experience-dependent plasticity suggests that abnormal activity patterns may be reversed with treatment. In particular, neurofeedback training (NFT), an intervention based on operant conditioning resulting in self-regulation of brain electrical oscillations, has shown increasing promise in addressing abnormalities in brain function and behavior. We examined the effects of ≥ 20 h of sensorimotor mu-rhythm-based NFT in children with high-functioning autism spectrum disorders (ASD) and a matched control group of typically developing children (ages 8-17). During a functional magnetic resonance imaging imitation and observation task, the ASD group showed increased activation in regions of the human mirror neuron system following the NFT, as part of a significant interaction between group (ASD vs. controls) and training (pre- vs. post-training). These changes were positively correlated with behavioral improvements in the ASD participants, indicating that mu-rhythm NFT may be beneficial to individuals with ASD.

BackgroundAnesthetics are believed to alter functional connectivity across brain regions. However, network-level analyses of anesthesia, particularly in humans, are sparse. The authors hypothesized that propofol-induced loss of consciousness results in functional disconnection of human sensorimotor cortices underlying the loss of volitional motor responses.MethodsThe authors recorded local field potentials from sensorimotor cortices in patients with Parkinson disease (N = 12) and essential tremor (N = 7) undergoing deep brain stimulation surgery, before and after propofol-induced loss of consciousness. Local spectral power and interregional connectivity (coherence and imaginary coherence) were evaluated separately across conditions for the two populations.ResultsPropofol anesthesia caused power increases for frequencies between 2 and 100 Hz across the sensorimotor cortices and a shift of the dominant spectral peak in α and β frequencies toward lower frequencies (median ± SD peak frequency: 24.5 ± 2.6 Hz to 12.8 ± 2.3 Hz in Parkinson disease; 13.8 ± 2.1 Hz to 12.1 ± 1.0 Hz in essential tremor). Despite local increases in power, sensorimotor cortical coherence was suppressed with propofol in both cohorts, specifically in β frequencies (18 to 29 Hz) for Parkinson disease and α and β (10 to 48 Hz) in essential tremor.ConclusionsThe decrease in functional connectivity between sensory and motor cortices, despite an increase in local spectral power, suggests that propofol causes a functional disconnection of cortices with increases in autonomous activity within cortical regions. This pattern occurs across diseases evaluated, suggesting that these may be generalizable effects of propofol in patients with movement disorders and beyond. Sensorimotor network disruption may underlie anesthetic-induced loss of volitional control.

Distinct anatomical and spectral channels are thought to play specialized roles in the communication within cortical networks. While activity in the alpha and beta frequency range (7 - 40 Hz) is thought to predominantly originate from infragranular cortical layers conveying feedback-related information, activity in the gamma range (>40 Hz) dominates in supragranular layers communicating feedforward signals. We leveraged high precision MEG to test this proposal, directly and non-invasively, in human participants performing visually cued actions. We found that visual alpha mapped onto deep cortical laminae, whereas visual gamma predominantly occurred more superficially. This lamina-specificity was echoed in movement-related sensorimotor beta and gamma activity. These lamina-specific pre- and post- movement changes in sensorimotor beta and gamma activity suggest a more complex functional role than the proposed feedback and feedforward communication in sensory cortex. Distinct frequency channels thus operate in a lamina-specific manner across cortex, but may fulfill distinct functional roles in sensory and motor processes.

The Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Research Network has yielded neuroimaging and urinary biomarker findings that highlight unique alterations in brain structure and in urinary proteins related to tissue remodeling and vascular structure in patients with Urological Chronic Pelvic Pain Syndrome (UCPPS). We hypothesized that localized changes in diffusion tensor imaging (DTI) measurements might be associated with corresponding changes in urinary protein levels in UCPPS. To test this hypothesis, we created statistical parameter maps depicting the linear correlation between DTI measurements (fractional anisotropy (FA) and apparent diffusion coefficient (ADC)) and urinary protein quantification (MMP2, MMP9, NGAL, MMP9/NGAL complex, and VEGF) in 30 UCPPS patients from the MAPP Research Network, after accounting for clinical covariates. Results identified a brainstem region that showed a strong correlation between both ADC (R2 = 0.49, P

Resting state functional connectivity is defined in terms of temporal correlations between physiologic signals, most commonly studied using functional magnetic resonance imaging. Major features of functional connectivity correspond to structural (axonal) connectivity. However, this relation is not one-to-one. Interhemispheric functional connectivity in relation to the corpus callosum presents a case in point. Specifically, several reports have documented nearly intact interhemispheric functional connectivity in individuals in whom the corpus callosum (the major commissure between the hemispheres) never develops. To investigate this question, we assessed functional connectivity before and after surgical section of the corpus callosum in 22 patients with medically refractory epilepsy. Section of the corpus callosum markedly reduced interhemispheric functional connectivity. This effect was more profound in multimodal associative areas in the frontal and parietal lobe than primary regions of sensorimotor and visual function. Moreover, no evidence of recovery was observed in a limited sample in which multiyear, longitudinal follow-up was obtained. Comparison of partial vs. complete callosotomy revealed several effects implying the existence of polysynaptic functional connectivity between remote brain regions. Thus, our results demonstrate that callosal as well as extracallosal anatomical connections play a role in the maintenance of interhemispheric functional connectivity.

Parkinson's disease (PD) is characterized by motor symptoms such as rigidity and bradykinesia that prevent normal movement. Beta band oscillations (13-30 Hz) in neural local field potentials (LFPs) have been associated with these motor symptoms. Here, three PD patients implanted with a therapeutic deep brain neural stimulator that can also record and wirelessly stream neural data played a neurofeedback game where they modulated their beta band power from sensorimotor cortical areas. Patients' beta band power was streamed in real-time to update the position of a cursor that they tried to drive into a cued target. After playing the game for 1-2 hours each, all three patients exhibited above chance-level performance regardless of subcortical stimulation levels. This study, for the first time, demonstrates using an invasive neural recording system for at-home neurofeedback training. Future work will investigate chronic neurofeedback training as a potentially therapeutic tool for patients with neurological disorders.

Sensorimotor adaptation tasks have been used to characterize processes responsible for calibrating the mapping between desired outcomes and motor commands. Research has focused on how this form of error-based learning takes place in an implicit and automatic manner. However, recent work has revealed the operation of multiple learning processes, even in this simple form of learning. This review focuses on the contribution of cognitive strategies and heuristics to sensorimotor learning, and how these processes enable humans to rapidly explore and evaluate novel solutions to enable flexible, goal-oriented behavior. This new work points to limitations in current computational models, and how these must be updated to describe the conjoint impact of multiple processes in sensorimotor learning.

Study objectivesObstructive sleep apnea (OSA) is accompanied by tissue injury to the insular cortices, areas that regulate autonomic pain, dyspnea, and mood, all of which are affected in the syndrome. Presumably, the dysregulation of insular-related functions are mediated by aberrant functional connections with other brain regions; however, the integrity of the functional connectivity (FC) to other sites is undescribed. Our aim was to examine resting-state FC of the insular cortices to other brain areas in OSA, relative to control subjects.MethodsWe collected resting-state functional magnetic resonance imaging (MRI) data from 67 newly diagnosed, treatment-naïve OSA and 75 control subjects using a 3.0-Tesla MRI scanner. After standard processing, data were analyzed for the left and right insular FC.ResultsOSA subjects showed complex aberrant insular FC to several brain regions, including frontal, parietal, cingulate, temporal, limbic, basal ganglia, thalamus, occipital, cerebellar, and brainstem regions. Areas of altered FC in OSA showed linear relationships with magnitudes of sleep related and neuropsychologic-related variables, whereas control subjects showed no such relationships with those measures.ConclusionsBrain functional connections from insular sites to other brain regions in OSA subjects represent abnormal autonomic, affective, sensorimotor, and cognitive control networks that may affect both impaired parasympathetic and sympathetic interactions, as well as abnormal sensorimotor integration, affected in the condition. The functional changes likely result from the previously reported structural changes in OSA subjects, as demonstrated by diverse neuroimaging studies.

Study objectivesTo examine nonrapid eye movement (NREM) sleep in insomnia using high-density electroencephalography (EEG).MethodsAll-night sleep recordings with 256 channel high-density EEG were analyzed for 8 insomnia subjects (5 females) and 8 sex and age-matched controls without sleep complaints. Spectral analyses were conducted using unpaired t-tests and topographical differences between groups were assessed using statistical non-parametric mapping. Five minute segments of deep NREM sleep were further analyzed using sLORETA cortical source imaging.ResultsThe initial topographic analysis of all-night NREM sleep EEG revealed that insomnia subjects had more high-frequency EEG activity (> 16 Hz) compared to good sleeping controls and that the difference between groups was widespread across the scalp. In addition, the analysis also showed that there was a more circumscribed difference in theta (4-8 Hz) and alpha (8-12 Hz) power bands between groups. When deep NREM sleep (N3) was examined separately, the high-frequency difference between groups diminished, whereas the higher regional alpha activity in insomnia subjects persisted. Source imaging analysis demonstrated that sensory and sensorimotor cortical areas consistently exhibited elevated levels of alpha activity during deep NREM sleep in insomnia subjects relative to good sleeping controls.ConclusionsThese results suggest that even during the deepest stage of sleep, sensory and sensorimotor areas in insomnia subjects may still be relatively active compared to control subjects and to the rest of the sleeping brain.

Modulation of vocal pitch is a key speech feature that conveys important linguistic and affective information. Auditory feedback is used to monitor and maintain pitch. We examined induced neural high gamma power (HGP) (65-150 Hz) using magnetoencephalography during pitch feedback control. Participants phonated into a microphone while hearing their auditory feedback through headphones. During each phonation, a single real-time 400 ms pitch shift was applied to the auditory feedback. Participants compensated by rapidly changing their pitch to oppose the pitch shifts. This behavioral change required coordination of the neural speech motor control network, including integration of auditory and somatosensory feedback to initiate change in motor plans. We found increases in HGP across both hemispheres within 200 ms of pitch shifts, covering left sensory and right premotor, parietal, temporal, and frontal regions, involved in sensory detection and processing of the pitch shift. Later responses to pitch shifts (200-300 ms) were right dominant, in parietal, frontal, and temporal regions. Timing of activity in these regions indicates their role in coordinating motor change and detecting and processing of the sensory consequences of this change. Subtracting out cortical responses during passive listening to recordings of the phonations isolated HGP increases specific to speech production, highlighting right parietal and premotor cortex, and left posterior temporal cortex involvement in the motor response. Correlation of HGP with behavioral compensation demonstrated right frontal region involvement in modulating participant's compensatory response. This study highlights the bihemispheric sensorimotor cortical network involvement in auditory feedback-based control of vocal pitch.

IntroductionObstructive sleep apnea (OSA) subjects show impaired autonomic, affective, executive, sensorimotor, and cognitive functions. Brain injury in OSA subjects appears in multiple sites regulating these functions, but the integrity of functional networks within the regulatory sites remains unclear. Our aim was to examine the functional interactions and the complex network organization of these interactions across the whole brain in OSA, using regional functional connectivity (FC) and brain network topological properties.MethodsWe collected resting-state functional magnetic resonance imaging (MRI) data, using a 3.0-Tesla MRI scanner, from 69 newly diagnosed, treatment-naïve, moderate-to-severe OSA (age, 48.3 ± 9.2 years; body mass index, 31 ± 6.2 kg/m(2); apnea-hypopnea index (AHI), 35.6 ± 23.3 events/h) and 82 control subjects (47.6 ± 9.1 years; body mass index, 25.1 ± 3.5 kg/m(2)). Data were analyzed to examine FC in OSA over controls as interregional correlations and brain network topological properties.ResultsObstructive sleep apnea subjects showed significantly altered FC in the cerebellar, frontal, parietal, temporal, occipital, limbic, and basal ganglia regions (FDR, P < 0.05). Entire functional brain networks in OSA subjects showed significantly less efficient integration, and their regional topological properties of functional integration and specialization characteristics also showed declined trends in areas showing altered FC, an outcome which would interfere with brain network organization (P < 0.05; 10,000 permutations). Brain sites with abnormal topological properties in OSA showed significant relationships with AHI scores.ConclusionsOur findings suggest that the dysfunction extends to resting conditions, and the altered FC and impaired network organization may underlie the impaired responses in autonomic, cognitive, and sensorimotor functions. The outcomes likely result from the prominent structural changes in both axons and nuclear structures, which occur in the condition.

Dysregulation of the Mirror Neuron System (MNS) in schizophrenia (SCZ) may underlie the cognitive and behavioral manifestations of social dysfunction associated with that disorder. In healthy subjects intranasal (IN) oxytocin (OT) improves neural processing in the MNS and is associated with improved social cognition. OT's brain effects can be measured through its modulation of the MNS by suppressing EEG mu-band electrical activity (8-13Hz) in response to motion perception. Although IN OT's effects on social cognition have been tested in SCZ, OT's impact on the MNS has not been evaluated to date. Therefore, we designed a study to investigate the effects of two different OT doses on biological motion-induced mu suppression in SCZ and healthy subjects. EEG recordings were taken after each subject received a single IN administration of placebo, OT-24IU and OT-48IU in randomized order in a double-blind crossover design. The results provide support for OT's regulation of the MNS in both healthy and SCZ subjects, with the optimal dose dependent on diagnostic group and sex of subject. A statistically significant response was seen in SCZ males only, indicating a heightened sensitivity to those effects, although sex hormone related effects cannot be ruled out. In general, OT appears to have positive effects on neural circuitry that supports social cognition and socially adaptive behaviors.

BackgroundfMRI graph theory reveals resting-state brain networks, but has never been used in pediatric OCD.MethodsWhole-brain resting-state fMRI was acquired at 3T from 21 children with OCD and 20 age-matched healthy controls. BOLD connectivity was analyzed yielding global and local graph-theory metrics across 100 child-based functional nodes. We also compared local metrics between groups in frontopolar, supplementary motor, and sensorimotor cortices, regions implicated in recent neuroimaging and/or brain stimulation treatment studies in OCD.ResultsAs in adults, the global metric small-worldness was significantly (P

The pathophysiology of rest tremor in Parkinson's disease (PD) is not well understood, and its severity does not correlate with the severity of other cardinal signs of PD. We hypothesized that tremor-related oscillatory activity in the basal-ganglia-thalamocortical loop might serve as a compensatory mechanism for the excessive beta band synchronization associated with the parkinsonian state. We recorded electrocorticography (ECoG) from the sensorimotor cortex and local field potentials (LFP) from the subthalamic nucleus (STN) in patients undergoing lead implantation for deep brain stimulation (DBS). We analyzed differences in measures of network synchronization during epochs of spontaneous rest tremor, versus epochs without rest tremor, occurring in the same subjects. The presence of tremor was associated with reduced beta power in the cortex and STN. Cortico-cortical coherence and phase-amplitude coupling (PAC) decreased during rest tremor, as did basal ganglia-cortical coherence in the same frequency band. Cortical broadband gamma power was not increased by tremor onset, in contrast to the movement-related gamma increase typically observed at the onset of voluntary movement. These findings suggest that the cortical representation of rest tremor is distinct from that of voluntary movement, and support a model in which tremor acts to decrease beta band synchronization within the basal ganglia-cortical loop.

Heart failure (HF) patients show brain injury in autonomic, affective, and cognitive sites, which can change resting-state functional connectivity (FC), potentially altering overall functional brain network organization. However, the status of such connectivity or functional organization is unknown in HF. Determination of that status was the aim here, and we examined region-to-region FC and brain network topological properties across the whole-brain in 27 HF patients compared to 53 controls with resting-state functional MRI procedures. Decreased FC in HF appeared between the caudate and cerebellar regions, olfactory and cerebellar sites, vermis and medial frontal regions, and precentral gyri and cerebellar areas. However, increased FC emerged between the middle frontal gyrus and sensorimotor areas, superior parietal gyrus and orbito/medial frontal regions, inferior temporal gyrus and lingual gyrus/cerebellar lobe/pallidum, fusiform gyrus and superior orbitofrontal gyrus and cerebellar sites, and within vermis and cerebellar areas; these connections were largely in the right hemisphere (p

ObjectiveParkinson disease (PD) can be difficult to diagnose and treat. Development of a biomarker for PD would reduce these challenges by providing an objective measure of disease. Emerging theories suggest PD is characterized by excessive synchronization in the beta frequency band (∼20Hz) throughout basal ganglia-thalamocortical loops. Recently we showed with invasive electrocorticography that one robust measure of this synchronization is the coupling of beta phase to broadband gamma amplitude (ie, phase-amplitude coupling [PAC]). Other recent work suggests that high-frequency activity is detectable at the scalp using electroencephalography (EEG). Motivated by these findings, we tested whether beta-gamma PAC over sensorimotor cortex, recorded noninvasively with EEG, differs between PD patients off and on medications, and healthy control subjects.MethodsResting EEG was compared from 15 PD patients and 16 healthy control subjects. PD patients were tested on and off medications on different days, in a counterbalanced order. For each data set we calculated PAC and compared results across groups.ResultsPAC was elevated in the patients off medications compared to on medications (p = 0.008) and for patients off medications compared to controls (p = 0.009).InterpretationElevated PAC is detectable using scalp EEG in PD patients off medications compared to on medications, and compared to healthy controls. This suggests that EEG PAC may provide a noninvasive biomarker of the parkinsonian state. This biomarker could be used as a control signal for closed-loop control of deep brain stimulation devices, for adjustment of dopaminergic treatment, and also has the potential to aid in diagnosis.

Speech production requires the precise control of vocal tract movements to generate individual speech sounds (phonemes) which, in turn, are rapidly organized into complex sequences. Multiple productions of the same phoneme can exhibit substantial variability, some of which is inherent to control of the vocal tract and its biomechanics, and some of which reflects the contextual effects of surrounding phonemes ("coarticulation"). The role of the CNS in these aspects of speech motor control is not well understood. To address these issues, we recorded multielectrode cortical activity directly from human ventral sensory-motor cortex (vSMC) during the production of consonant-vowel syllables. We analyzed the relationship between the acoustic parameters of vowels (pitch and formants) and cortical activity on a single-trial level. We found that vSMC activity robustly predicted acoustic parameters across vowel categories (up to 80% of variance), as well as different renditions of the same vowel (up to 25% of variance). Furthermore, we observed significant contextual effects on vSMC representations of produced phonemes that suggest active control of coarticulation: vSMC representations for vowels were biased toward the representations of the preceding consonant, and conversely, representations for consonants were biased toward upcoming vowels. These results reveal that vSMC activity for phonemes are not invariant and provide insight into the cortical mechanisms of coarticulation.

ObjectiveEssential tremor (ET) is characterized by an action tremor believed to be due to excessive theta-alpha activity in the cerebello-thalamo-cortical system. This study aimed to test the hypothesis that therapeutic thalamic stimulation in patients with ET decreases theta-alpha oscillatory activity in primary motor (M1) and sensory (S1) cortices.MethodsDuring surgical treatment of ET in 10 patients, an electrocorticography (ECoG) strip electrode was placed temporarily over the arm region of M1 and S1. Local field potentials (LFP) were recorded at rest, during a tremor-inducing posture, during acute therapeutic thalamic stimulation, and following therapeutic thalamotomy (three patients). Power spectral density (PSD) was calculated using the Fast Fourier Transform.ResultsAt rest, alpha activity (8-13Hz) in M1 was significantly decreased during high-frequency stimulation, while theta activity (4-8Hz) decreased in S1. Following thalamotomy, theta and beta (13-30Hz) was increased in M1. Induction of postural tremor reduced M1 theta, alpha and beta activity compared to the resting state.ConclusionsHigh-frequency thalamic deep brain stimulation (DBS) significantly reduces alpha oscillatory activity in the primary motor cortex of patients with ET, though this change is probably not critical for therapeutic efficacy.SignificanceWe demonstrate that ECoG can be effectively used to study the effect of subcortical stimulation on cortical oscillations.