The effect of age on alpha rhythms in the human brain derived from source localized resting-state electroencephalography.

With increasing age, peak alpha frequency (PAF) is slowed, and alpha power is reduced during resting-states with eyes closed. These age-related changes are evident across the whole scalp but remained unclear at the source level. The purpose of this study was to determine whether age impacts the power and frequency of the dominant alpha rhythm equally across source generators or whether the impact of age varies across sources. A total of 28 young adults and 26 elderly adults were recruited. High-density EEG was recorded for 10 mins with eyes closed. Single dipoles for each independent component were localized and clustered based on their anatomical label, resulting in 36 clusters. Meta-analyses were then conducted to assess effect sizes for PAF and power at PAF for all 36 clusters. Subgroup analyses were then implemented for frontal, sensorimotor, parietal, temporal, and occipital regions. The results of the meta-analyses showed that the elderly group exhibited slower PAF and less power at PAF compared to the young group. Subgroup analyses revealed age effects on PAF in parietal (g = 0.38), temporal (g = 0.65), and occipital regions (g = 1.04), with the largest effects observed in occipital regions. For power at PAF, age effects were observed in sensorimotor (g = 0.84) and parietal regions (g = 0.80), with the sensorimotor region showing the largest effect. Our findings show that age-related slowing and attenuation of the alpha rhythm manifests differentially across cortical regions, with sensorimotor and occipital regions most susceptible to age effects.

Diffusion MRI relates to plasma Aß42/40 in PET negative participants without dementia.

INTRODUCTION: Magnetic resonance imaging (MRI) biomarkers are needed for indexing early biological stages of Alzheimer's disease (AD), such as plasma amyloid-ß (Aß42/40) positivity in Aß positron emission tomography (PET) negative individuals. METHODS: Diffusion free-water (FW) MRI was acquired in individuals with normal cognition (NC) and mild cognitive impairment (MCI) with Aß plasma-/PET- (NC = 22, MCI = 60), plasma+/PET- (NC = 5, MCI = 20), and plasma+/PET+ (AD dementia = 21) biomarker status. Gray and white matter FW and fractional anisotropy (FAt) were compared cross-sectionally and the relationships between imaging, plasma and PET biomarkers were assessed. RESULTS: Plasma+/PET- demonstrated increased FW (24 regions) and decreased FAt (66 regions) compared to plasma-/PET-. FW (16 regions) and FAt (51 regions) were increased in plasma+/PET+ compared to plasma+/PET-. Composite brain FW correlated with plasma Aß42/40 and p-tau181. DISCUSSION: FW imaging changes distinguish plasma Aß42/40 positive and negative groups, independent of group differences in cognitive status, Aß PET status, and other plasma biomarkers (i.e., t-tau, p-tau181, glial fibrillary acidic protein, neurofilament light). HIGHLIGHTS: Plasma Aß42/40 positivity is associated with brain microstructure decline. Plasma+/PET- demonstrated increased FW in 24 total GM and WM regions. Plasma+/PET- demonstrated decreased FAt in 66 total GM and WM regions. Whole-brain FW correlated with plasma Aß42/40 and p-tau181 measures. Plasma+/PET- demonstrated decreased cortical volume and thickness.

Visuomotor brain network activation and functional connectivity among individuals with autism spectrum disorder.

Sensorimotor abnormalities are common in autism spectrum disorder (ASD) and predictive of functional outcomes, though their neural underpinnings remain poorly understood. Using functional magnetic resonance imaging, we examined both brain activation and functional connectivity during visuomotor behavior in 27 individuals with ASD and 30 typically developing (TD) controls (ages 9-35 years). Participants maintained a constant grip force while receiving visual feedback at three different visual gain levels. Relative to controls, ASD participants showed increased force variability, especially at high gain, and reduced entropy. Brain activation was greater in individuals with ASD than controls in supplementary motor area, bilateral superior parietal lobules, and contralateral middle frontal gyrus at high gain. During motor action, functional connectivity was reduced between parietal-premotor and parietal-putamen in individuals with ASD compared to controls. Individuals with ASD also showed greater age-associated increases in functional connectivity between cerebellum and visual, motor, and prefrontal cortical areas relative to controls. These results indicate that visuomotor deficits in ASD are associated with atypical activation and functional connectivity of posterior parietal, premotor, and striatal circuits involved in translating sensory feedback information into precision motor behaviors, and that functional connectivity of cerebellar-cortical sensorimotor and nonsensorimotor networks show delayed maturation.

Cortical dynamics of movement-evoked pain in chronic low back pain.

KEY POINTS: Cortical activity underlying movement-evoked pain is not well understood, despite being a key symptom of chronic musculoskeletal pain. We combined high-density electroencephalography with a full-body reaching protocol in a virtual reality environment to assess cortical activity during movement-evoked pain in chronic low back pain. Movement-evoked pain in individuals with chronic low back pain was associated with longer reaction times, delayed peak velocity and greater movement variability. Movement-evoked pain was associated with attenuated disinhibition in prefrontal motor areas, as evidenced by an attenuated reduction in beta power in the premotor cortex and supplementary motor area. ABSTRACT: Although experimental pain alters neural activity in the cortex, evidence of changes in neural activity in individuals with chronic low back pain (cLBP) remains scarce and results are inconsistent. One of the challenges in studying cLBP is that the clinical pain fluctuates over time and often changes during movement. The goal of the present study was to address this challenge by recording high-density electroencephalography (HD-EEG) data during a full-body reaching task to understand neural activity during movement-evoked pain. HD-EEG data were analysed using independent component analyses, source localization and measure projection analyses to compare neural oscillations between individuals with cLBP who experienced movement-evoked pain and pain-free controls. We report two novel findings. First, movement-evoked pain in individuals with cLBP was associated with longer reaction times, delayed peak velocity and greater movement variability. Second, movement-evoked pain was associated with an attenuated reduction in beta power in the premotor cortex and supplementary motor area. Our observations move the field forward by revealing attenuated disinhibition in prefrontal motor areas during movement-evoked pain in cLBP.

Unraveling somatotopic organization in the human brain using machine learning and adaptive supervoxel-based parcellations.

In addition to the well-established somatotopy in the pre- and post-central gyrus, there is now strong evidence that somatotopic organization is evident across other regions in the sensorimotor network. This raises several experimental questions: To what extent is activity in the sensorimotor network effector-dependent and effector-independent? How important is the sensorimotor cortex when predicting the motor effector? Is there redundancy in the distributed somatotopically organized network such that removing one region has little impact on classification accuracy? To answer these questions, we developed a novel experimental approach. fMRI data were collected while human subjects performed a precisely controlled force generation task separately with their hand, foot, and mouth. We used a simple linear iterative clustering (SLIC) algorithm to segment whole-brain beta coefficient maps to build an adaptive brain parcellation and then classified effectors using extreme gradient boosting (XGBoost) based on parcellations at various spatial resolutions. This allowed us to understand how data-driven adaptive brain parcellation granularity altered classification accuracy. Results revealed effector-dependent activity in regions of the post-central gyrus, precentral gyrus, and paracentral lobule. SMA, regions of the inferior and superior parietal lobule, and cerebellum each contained effector-dependent and effector-independent representations. Machine learning analyses showed that increasing the spatial resolution of the data-driven model increased classification accuracy, which reached 94% with 1755 supervoxels. Our SLIC-based supervoxel parcellation outperformed classification analyses using established brain templates and random simulations. Occlusion experiments further demonstrated redundancy across the sensorimotor network when classifying effectors. Our observations extend our understanding of effector-dependent and effector-independent organization within the human brain and provide new insight into the functional neuroanatomy required to predict the motor effector used in a motor control task.

Functional imaging of the brainstem during visually-guided motor control reveals visuomotor regions in the pons and midbrain.

Integrating visual information for motor output is an essential process of visually-guided motor control. The brainstem is known to be a major center involved in the integration of sensory information for motor output, however, limitations of functional imaging in humans have impaired our knowledge about the individual roles of sub-nuclei within the brainstem. Thus, the bulk of our knowledge surrounding the function of the brainstem is based on anatomical and behavioral studies in non-human primates, cats, and rodents, despite studies demonstrating differences in the organization of visuomotor processing between mammals. fMRI studies in humans have examined activity related to visually-guided motor tasks, however, few have done so while controlling for both force without visual feedback activity and visual stimuli without force activity. Of the studies that have controlled for both conditions, none have reported brainstem activity. Here, we employed a novel fMRI paradigm focused on the brainstem and cerebellum to systematically investigate the hypothesis that the pons and midbrain are critical for the integration of visual information for motor control. Visuomotor activity during visually-guided pinch-grip force was measured while controlling for force without visual feedback activity and visual stimuli without force activity in healthy adults. Using physiological noise correction and multiple task repetitions, we demonstrated that visuomotor activity occurs in the inferior portion of the basilar pons and the midbrain. These findings provide direct evidence in humans that the pons and midbrain support the integration of visual information for motor control. We also determined the effect of physiological noise and task repetitions on the visuomotor signal that will be useful in future studies of neurodegenerative diseases affecting the brainstem.

Development of a transcallosal tractography template and its application to dementia.

Understanding the architecture of transcallosal connections would allow for more specific assessments of neurodegeneration across many fields of neuroscience, neurology, and psychiatry. To map these connections, we conducted probabilistic tractography in 100 Human Connectome Project subjects in 32 cortical areas using novel post-processing algorithms to create a spatially precise Trancallosal Tract Template (TCATT). We found robust transcallosal tracts in all 32 regions, and a topographical analysis in the corpus callosum largely agreed with well-established subdivisions of the corpus callosum. We then obtained diffusion MRI data from a cohort of patients with Alzheimer's disease (AD) and another with progressive supranuclear palsy (PSP) and used a two-compartment model to calculate free-water corrected fractional anisotropy (FAT) and free-water (FW) within the TCATT. These metrics were used to determine between-group differences and to determine which subset of tracts was best associated with cognitive function (Montreal Cognitive Assessment (MoCA)). In AD, we found robust between-group differences in FW (31/32 TCATT tracts) in the absence of between-group differences in FAT. FW in the inferior temporal gyrus TCATT tract was most associated with MoCA scores in AD. In PSP, there were widespread differences in both FAT and FW, and MoCA was predicted by FAT in the inferior frontal pars triangularis, preSMA, and medial frontal gyrus TCATT tracts as well as FW in the inferior frontal pars opercularis TCATT tract. The TCATT improves spatial localization of corpus callosum measurements to enhance the evaluation of treatment effects, as well as the monitoring of brain microstructure in relation to cognitive dysfunction and disease progression. Here, we have shown its direct relevance in capturing between-group differences and associating it with the MoCA in AD and PSP.

Neurite orientation dispersion and density imaging (NODDI) and free-water imaging in Parkinsonism.

Neurite orientation dispersion and density imaging (NODDI) uses a three-compartment model to probe brain tissue microstructure, whereas free-water (FW) imaging models two-compartments. It is unknown if NODDI detects more disease-specific effects related to neurodegeneration in Parkinson's disease (PD) and atypical Parkinsonism. We acquired multi- and single-shell diffusion imaging at 3 Tesla across two sites. NODDI (using multi-shell; isotropic volume [Viso]; intracellular volume [Vic]; orientation dispersion [ODI]) and FW imaging (using single-shell; FW; free-water corrected fractional anisotropy [FAt]) were compared with 44 PD, 21 multiple system atrophy Parkinsonian variant (MSAp), 26 progressive supranuclear palsy (PSP), and 24 healthy control subjects in the basal ganglia, midbrain/thalamus, cerebellum, and corpus callosum. There was elevated Viso in posterior substantia nigra across Parkinsonisms, and Viso, Vic, and ODI were altered in MSAp and PSP in the striatum, globus pallidus, midbrain, thalamus, cerebellum, and corpus callosum relative to controls. The mean effect size across regions for Viso was 0.163, ODI 0.131, Vic 0.122, FW 0.359, and FAt 0.125, with extracellular compartments having the greatest effect size. A key question addressed was if these techniques discriminate PD and atypical Parkinsonism. Both NODDI (AUC: 0.945) and FW imaging (AUC: 0.969) had high accuracy, with no significant difference between models. This study provides new evidence that NODDI and FW imaging offer similar discriminability between PD and atypical Parkinsonism, and FW had higher effect sizes for detecting Parkinsonism within regions across the basal ganglia and cerebellum.

Cortical dynamics within and between parietal and motor cortex in essential tremor.

BACKGROUND: Evidence from functional imaging in essential tremor suggests that activity within parietal and motor cortices may be associated with worsening of tremor at increased visual feedback. OBJECTIVES: Examine how cortical oscillations within these regions and the connectivity between these regions is associated with worsening of tremor in essential tremor in response to high visual feedback. METHOD: The study included 24 essential tremor participants and 17 controls. We measured cortical activity and tremor magnitude at low and high feedback conditions. Cortical activity was measured using high-density electroencephalogram and isolated using source localization. RESULTS: Changes in power across feedback in the 4-12 Hz and 12-30 Hz bands were reduced within the contralateral motor cortex of essential tremor patients compared to controls. The 12-30 Hz bidirectional connectivity between the parietal and contralateral motor cortex was decreased in essential tremor patients. Worsening of tremor from low to high visual feedback was associated with 4-12 Hz activity in contralateral motor cortex. The greatest separation between groups was found when using the difference of the contralateral motor cortex activity at high and low feedback, rather than either feedback condition alone. CONCLUSION: Our findings provide new evidence that tremor in essential tremor is associated with reduced power across feedback in the motor cortex and reduced connectivity between the parietal and motor cortices. Combined with previous work on the cerebellar-thalamo-cortical motor circuit, our findings suggest that the network level disturbances associated with essential tremor extend to the cortico-cortical pathway between the parietal cortex and motor cortex. © 2018 International Parkinson and Movement Disorder Society.

A widespread visually-sensitive functional network relates to symptoms in essential tremor.

Essential tremor is a neurological syndrome of heterogeneous pathology and aetiology that is characterized by tremor primarily in the upper extremities. This tremor is commonly hypothesized to be driven by a single or multiple neural oscillator(s) within the cerebello-thalamo-cortical pathway. Several studies have found an association of blood-oxygen level-dependent (BOLD) signal in the cerebello-thalamo-cortical pathway with essential tremor, but there is behavioural evidence that also points to the possibility that the severity of tremor could be influenced by visual feedback. Here, we directly manipulated visual feedback during a functional MRI grip force task in patients with essential tremor and control participants, and hypothesized that an increase in visual feedback would exacerbate tremor in the 4-12 Hz range in essential tremor patients. Further, we hypothesized that this exacerbation of tremor would be associated with dysfunctional changes in BOLD signal and entropy within, and beyond, the cerebello-thalamo-cortical pathway. We found that increases in visual feedback increased tremor in the 4-12 Hz range in essential tremor patients, and this increase in tremor was associated with abnormal changes in BOLD amplitude and entropy in regions within the cerebello-thalamo-motor cortical pathway, and extended to visual and parietal areas. To determine if the tremor severity was associated with single or multiple brain region(s), we conducted a birectional stepwise multiple regression analysis, and found that a widespread functional network extending beyond the cerebello-thalamo-motor cortical pathway was associated with changes in tremor severity measured during the imaging protocol. Further, this same network was associated with clinical tremor severity measured with the Fahn, Tolosa, Marin Tremor Rating Scale, suggesting this network is clinically relevant. Since increased visual feedback also reduced force error, this network was evaluated in relation to force error but the model was not significant, indicating it is associated with force tremor but not force error. This study therefore provides new evidence that a widespread functional network is associated with the severity of tremor in patients with essential tremor measured simultaneously at the hand during functional imaging, and is also associated with the clinical severity of tremor. These findings support the idea that the severity of tremor is exacerbated by increased visual feedback, suggesting that designers of new computing technologies should consider using lower visual feedback levels to reduce tremor in essential tremor.

A Template and Probabilistic Atlas of the Human Sensorimotor Tracts using Diffusion MRI.

The purpose of this study was to develop a high-resolution sensorimotor area tract template (SMATT) which segments corticofugal tracts based on 6 cortical regions in primary motor cortex, dorsal premotor cortex, ventral premotor cortex, supplementary motor area (SMA), pre-supplementary motor area (preSMA), and primary somatosensory cortex using diffusion tensor imaging. Individual probabilistic tractography analyses were conducted in 100 subjects using the highest resolution data currently available. Tractography results were refined using a novel algorithm to objectively determine slice level thresholds that best minimized overlap between tracts while preserving tract volume. Consistent with tracing studies in monkey and rodent, our observations show that cortical topography is generally preserved through the internal capsule, with the preSMA tract remaining most anterior and the primary somatosensory tract remaining most posterior. We combine our results into a freely available white matter template named the SMATT. We also provide a probabilistic SMATT that quantifies the extent of overlap between tracts. Finally, we assess how the SMATT operates at the individual subject level in another independent data set, and in an individual after stroke. The SMATT and probabilistic SMATT provide new tools that segment and label sensorimotor tracts at a spatial resolution not previously available.

Pain-Related Suppression of Beta Oscillations Facilitates Voluntary Movement.

Increased beta oscillations over sensorimotor cortex are antikinetic. Motor- and pain-related processes separately suppress beta oscillations over sensorimotor cortex leading to the prediction that ongoing pain should facilitate movement. In the current study, we used a paradigm in which voluntary movements were executed during an ongoing pain-eliciting stimulus to test the hypothesis that a pain-related suppression of beta oscillations would facilitate the initiation of a subsequent voluntary movement. Using kinematic measures, electromyography, and high-density electroencephalography, we demonstrate that ongoing pain leads to shorter reaction times without affecting the kinematics or accuracy of movement. Reaction time was positively correlated with beta power prior to movement in contralateral premotor areas. Our findings corroborate the view that beta-band oscillations are antikinetic and provide new evidence that pain primes the motor system for action. Our observations provide the first evidence that a pain-related suppression of beta oscillations over contralateral premotor areas leads to shorter reaction times for voluntary movement.

Automated classification of pain perception using high-density electroencephalography data.

The translation of brief, millisecond-long pain-eliciting stimuli to the subjective perception of pain is associated with changes in theta, alpha, beta, and gamma oscillations over sensorimotor cortex. However, when a pain-eliciting stimulus continues for minutes, regions beyond the sensorimotor cortex, such as the prefrontal cortex, are also engaged. Abnormalities in prefrontal cortex have been associated with chronic pain states, but conventional, millisecond-long EEG paradigms do not engage prefrontal regions. In the current study, we collected high-density EEG data during an experimental paradigm in which subjects experienced a 4-s, low- or high-intensity pain-eliciting stimulus. EEG data were analyzed using independent component analyses, EEG source localization analyses, and measure projection analyses. We report three novel findings. First, an increase in pain perception was associated with an increase in gamma and theta power in a cortical region that included medial prefrontal cortex. Second, a decrease in lower beta power was associated with an increase in pain perception in a cortical region that included the contralateral sensorimotor cortex. Third, we used machine learning for automated classification of EEG data into low- and high-pain classes. Theta and gamma power in the medial prefrontal region and lower beta power in the contralateral sensorimotor region served as features for classification. We found a leave-one-out cross-validation accuracy of 89.58%. The development of biological markers for pain states continues to gain traction in the literature, and our findings provide new information that advances this body of work.NEW & NOTEWORTHY The development of a biological marker for pain continues to gain traction in literature. Our findings show that high- and low-pain perception in human subjects can be classified with 89% accuracy using high-density EEG data from prefrontal cortex and contralateral sensorimotor cortex. Our approach represents a novel neurophysiological paradigm that advances the literature on biological markers for pain.

Free-water and free-water corrected fractional anisotropy in primary and premotor corticospinal tracts in chronic stroke.

Measures from diffusion MRI have been used to characterize the corticospinal tract in chronic stroke. However, diffusivity can be influenced by partial volume effects from free-water, region of interest placement, and lesion masking. We collected diffusion MRI from a cohort of chronic stroke patients and controls and used a bitensor model to calculate free-water corrected fractional anisotropy (FAT ) and free water (FW) in the primary motor corticospinal tract (M1-CST) and the dorsal premotor corticospinal tract (PMd-CST). Region of interest analyses and whole-tract slice-by-slice analyses were used to assess between-group differences in FAT and FW in each tract. Correlations between FAT and FW and grip strength were also examined. Following lesion masking and correction for multiple comparisons, relative increases in FW were found for the stroke group in large portions of the M1-CST and PMd-CST in the lesioned hemisphere. FW in cortical regions was the strongest predictor of grip strength in the stroke group. Our findings also demonstrated that FAT is sensitive to the direct effects of the lesion itself, thus after controlling for the lesion, differences in FAT in nonlesioned tissue were small and generally similar between hemispheres and groups. Our observations suggest that FW may be a robust biological measurement that can be used to assess microstructure in residual white matter after stroke. Hum Brain Mapp 38:4546-4562, 2017. © 2017 Wiley Periodicals, Inc.

Functional activity of the sensorimotor cortex and cerebellum relates to cervical dystonia symptoms.

Cervical dystonia (CD) is the most common type of focal dystonia, causing abnormal movements of the neck and head. In this study, we used noninvasive imaging to investigate the motor system of patients with CD and uncover the neural correlates of dystonic symptoms. Furthermore, we examined whether a commonly prescribed anticholinergic medication in CD has an effect on the dystonia-related brain abnormalities. Participants included 16 patients with CD and 16 healthy age-matched controls. We collected functional MRI scans during a force task previously shown to extensively engage the motor system, and diffusion and T1-weighted MRI scans from which we calculated free-water and brain tissue densities. The dystonia group was also scanned ca. 2 h after a 2-mg dose of trihexyphenidyl. Severity of dystonia was assessed pre- and post-drug using the Burke-Fahn-Marsden Dystonia Rating Scale. Motor-related activity in CD was altered relative to controls in the primary somatosensory cortex, cerebellum, dorsal premotor and posterior parietal cortices, and occipital cortex. Most importantly, a regression model showed that increased severity of symptoms was associated with decreased functional activity of the somatosensory cortex and increased activity of the cerebellum. Structural imaging measures did not differ between CD and controls. The single dose of trihexyphenidyl altered the fMRI signal in the somatosensory cortex but not in the cerebellum. Symptom severity was not significantly reduced post-treatment. Findings show widespread changes in functional brain activity in CD and most importantly that dystonic symptoms relate to disrupted activity in the somatosensory cortex and cerebellum. Hum Brain Mapp 38:4563-4573, 2017. © 2017 Wiley Periodicals, Inc.

Microstructural properties of premotor pathways predict visuomotor performance in chronic stroke.

Microstructural properties of the corticospinal tract (CST) descending from the motor cortex predict strength and motor skill in the chronic phase after stroke. Much less is known about the relation between brain microstructure and visuomotor processing after stroke. In this study, individual's poststroke and age-matched controls performed a unimanual force task separately with each hand at three levels of visual gain. We collected diffusion MRI data and used probabilistic tractography algorithms to identify the primary and premotor CSTs. Fractional anisotropy (FA) within each tract was used to predict changes in force variability across different levels of visual gain. Our observations revealed that individuals poststroke reduced force variability with an increase in visual gain, performed the force task with greater variability as compared with controls across all gain levels, and had lower FA in the primary motor and premotor CSTs. Our results also demonstrated that the CST descending from the premotor cortex, rather than the primary motor cortex, best predicted force variability. Together, these findings demonstrate that the microstructural properties of the premotor CST predict visual gain-related changes in force variability in individuals poststroke. Hum Brain Mapp 37:2039-2054, 2016. © 2016 Wiley Periodicals, Inc.

Neuroimaging Evidence of Motor Control and Pain Processing in the Human Midcingulate Cortex.

Human neuroimaging and virus-tracing studies in monkey predict that motor control and pain processes should overlap in anterior midcingulate cortex (aMCC), but there is currently no direct evidence that this is the case. We used a novel functional magnetic resonance imaging paradigm to examine brain activity while subjects performed a motor control task, experienced a pain-eliciting stimulus on their hand, and performed the motor control task while also experiencing the pain-eliciting stimulus. Our experiment produced 3 novel results. First, group-level analyses showed that when separate trials of motor control and pain processing were performed, overlapping functional activity was found in the same regions of aMCC, supplementary motor area (SMA), anterior insula, and putamen. Secondly, increased activity was found in the aMCC and SMA when motor control and pain processing occurred simultaneously. Thirdly, individual-level analyses showed that 93% of subjects engaged the same region of aMCC during separate trials of motor control and pain processing irrespective of differences in the sulcal/gyral morphology of the cingulate cortex across individuals. These observations provide direct evidence in humans that the same region of aMCC is engaged for motor control and pain processing.

3D Cortical electrophysiology of ballistic upper limb movement in humans.

Precise motor control requires the ability to scale the parameters of movement. Theta oscillations across the cortex have been associated with changes in memory, attention, and sensorimotor processing. What has proven more elusive is pinpointing the region-specific frequency band oscillations that are associated with specific parameters of movement during the acceleration and deceleration phases. We report a study using 3D analytic techniques for high density electroencephalography that examines electrocortical dynamics while participants produce upper limb movements to different distances at varying rates. During fast ballistic movements, we observed increased theta band activity in the left motor area contralateral to the moving limb during the acceleration phase of the movement, and theta power correlated with the acceleration of movement. In contrast, beta band activity scaled with the type of movement during the deceleration phase near the end of the movement and correlated with movement time. In the ipsilateral motor and somatosensory area, alpha band activity decreased with the type of movement near the end of the movement, and gamma band activity in visual cortex increased with the type of movement near the end of the movement. Our results suggest that humans use distinct lateralized cortical activity for distance and speed dependent arm movements. We provide new evidence that a temporary increase in theta band power relates to movement acceleration and is important during movement execution. Further, the theta power increase is coupled with desychronization of beta band power and alpha band power which are modulated by the task near the end of movement.

Smile without euphoria induced by deep brain stimulation: a case report.

Poststroke central pain (PSCP) can be a debilitating medication-refractory disorder. We report a single case where right unilateral ventral capsule/ventral striatum (VC/VS) deep brain stimulation was used to treat PSCP and inadvertently induced a smile without euphoria. The patient was a 69 year-old woman who had a stroke with resultant dysesthesia and allodynia in her left hemibody and also a painful left hemibody dystonia. In her case, VC/VS stimulation induced a smile phenomenon, but without a euphoric sensation. This phenomenon was different from the typical smile responses we have observed in obsessive-compulsive disorder cases. This difference was considered to be possibly attributable to impairment in the emotional smile pathway.