Left Primary Somatosensory Research Articles

Welding techniques and manganese concentrations in blood and brain: Results from the WELDFUMES study

This study used whole-brain mapping to investigate the effect of different welding processes on manganese (Mn) accumulation in the brain. Exposure measurements were performed at the welders’ workplaces about 3 weeks before a magnetic resonance imaging (MRI) examination. The welders were categorized into three main groups based on welding method, and the T1-relaxation rate (R1) was measured using quantitative MRI (qMRI). Welders using shielded metal arc welding (SMAW) were found to have lower accumulations of total Mn in clusters encompassing white matter, thalamus, putamen, pallidum, and substantia nigra compared with welders using inert gas tungsten arc welding (GTAW) or continuous consumable electrode arc welding (CCEAW). A positive correlation was found between Mn in red blood cells (Mn-RBC) and R1 in a region encompassing pre-and post-central gyri. The results of this study show that the accumulation of free, bound, or compartmentalized Mn ions in the brain differed depending on the welding method used. These differences were predominately located in the basal ganglia but were also found in regions encompassing white matter. The level of Mn-RBC was correlated to the deposition of Mn in the left primary somatosensory and motor cortex and may therefore be linked to neurological and neurobehavioral symptoms.

The neural correlates of texture perception: A systematic review and activation likelihood estimation meta-analysis of functional magnetic resonance imaging studies.

Humans use discriminative touch to perceive texture through dynamic interactions with surfaces, activating low-threshold mechanoreceptors in the skin. It was largely assumed that texture was processed in primary somatosensory regions in the brain; however, imaging studies indicate heterogeneous patterns of brain activity associated with texture processing. To address this, we conducted a coordinate-based activation likelihood estimation meta-analysis of 13 functional magnetic resonance imaging studies (comprising 15 experiments contributing 228 participants and 275 foci) selected by a systematic review. Concordant activations for texture perception occurred in the left primary somatosensory and motor regions, with bilateral activations in the secondary somatosensory, posterior insula, and premotor and supplementary motor cortices. We also evaluated differences between studies that compared touch processing to non-haptic control (e.g., rest or visual control) or those that used haptic control (e.g., shape or orientation perception) to specifically investigate texture encoding. Studies employing a haptic control revealed concordance for texture processing only in the left secondary somatosensory cortex. Contrast analyses demonstrated greater concordance of activations in the left primary somatosensory regions and inferior parietal cortex for studies with a non-haptic control, compared to experiments accounting for other haptic aspects. These findings suggest that texture processing may recruit higher order integrative structures, and the secondary somatosensory cortex may play a key role in encoding textural properties. The present study provides unique insight into the neural correlates of texture-related processing by assessing the influence of non-textural haptic elements and identifies opportunities for a future research design to understand the neural processing of texture.

Novel Pulsed-Ultrahigh-Frequency Spinal Cord Stimulation Inhibits Mechanical Hypersensitivity and Brain Neuronal Activity in Rats after Nerve Injury.

Spinal cord stimulation (SCS) is an important pain treatment modality. We hypothesized that a novel pulsed-ultrahigh-frequency SCS (pUHF-SCS) could safely and effectively inhibit spared nerve injury-induced neuropathic pain in rats. Epidural pUHF-SCS (± 3V, 2Hz pulses comprising 500 kHz biphasic sinewaves) was implanted at the thoracic vertebrae (T9-T11). Local field brain potentials following hind paw stimulation were recorded. Analgesia was evaluated by von-Frey-evoked allodynia and acetone-induced cold allodynia. The mechanical withdrawal threshold of the injured paw was 0.91 ± 0.28 g lower than that of the sham surgery (24.9 ± 1.2 g). Applying 5-, 10-, or 20-minute pUHF-SCS five times every two days significantly increased the paw withdrawal threshold to 13.3 ± 6.5, 18.5 ± 3.6, and 21.0 ± 2.8 g at 5 hours post-SCS, respectively (p = 0.0002, < 0.0001, and < 0.0001; n = 6/group), and to 6.1 ± 2.5, 8.2 ± 2.7, and 14.3 ± 5.9 g on the second day, respectively (p = 0.123, 0.013, and < 0.0001). Acetone-induced paw response numbers decreased from pre-SCS (41 ± 12) to 24 ± 12 and 28 ± 10 (p = 0.006 and 0.027; n = 9) at 1 and 5 hours post-three rounds of 20-minute pUHF-SCS, respectively. The areas under the curve from the C component of the evoked potentials at the left primary somatosensory and anterior cingulate cortices were significantly decreased from pre-SCS (101.3 ± 58.3 and 86.9 ± 25.5, respectively) to 39.7 ± 40.3 and 36.3 ± 20.7 (p = 0.021, and 0.003; n = 5) at 60 minutes post-SCS, respectively. The intensity thresholds for pUHF-SCS to induce brain and sciatic nerve activations were much higher than the therapeutic intensities and thresholds of conventional low-frequency SCS. pUHF-SCS inhibited neuropathic pain-related behavior and paw stimulation evoked brain activation through mechanisms distinct from low-frequency SCS.

Dynamic causal modeling of sensorimotor networks elicited by saltatory pneumotactile velocity in the glabrous hand.

The effective connectivity of neuronal networks during passive saltatory pneumotactile velocity stimulation to the glabrous hand with different velocities is still unknown. The present study investigated the effectivity connectivity elicited by saltatory pneumotactile velocity arrays placed on the glabrous hand at three velocities (5, 25, and 65 cm/second). Dynamic causal modeling (DCM) was used on functional MRI data sampled from 20 neurotypical adults. Five brain regions, including the left primary somatosensory (SI) and motor (M1) cortices, bilateral secondary somatosensory (SII) cortices, and right cerebellar lobule VI, were used to build model space. Three velocities (5, 25, and 65 cm/second) of saltatory pneumotactile stimuli were processed in both serial and parallel modes within the sensorimotor networks. The medium velocity of 25 cm/second modulated forward interhemispheric connection from the contralateral SII to the ipsilateral SII. Pneumotactile stimulation at the medium velocity of 25 cm/second also influenced contralateral M1 through contralateral SI. Finally, the right cerebellar lobule VI was involved in the sensorimotor networks. Our DCM results suggest the coexistence of both serial and parallel processing for saltatory pneumotactile velocity stimulation. Significant contralateral M1 modulation promotes the prospect that the passive saltatory pneumotactile velocity arrays can be used to design sensorimotor rehabilitation protocols to activate M1. The effective connectivity from the right cerebellar lobule VI to other cortical regions demonstrates the cerebellum's role in the sensorimotor networks through feedforward and feedback neuronal pathways.

Structure-function abnormalities in cortical sensory projections in embouchure dystonia

BackgroundEmbouchure dystonia (ED) is a task-specific focal dystonia in professional brass players leading to abnormal orofacial muscle posturing/spasms during performance. Previous studies have outlined abnormal cortical sensorimotor function during sensory/motor tasks and in the resting state as well as abnormal cortical sensorimotor structure. Yet, potentially underlying white-matter tract abnormalities in this network disease are unknown. ObjectiveTo delineate structure-function abnormalities within cerebral sensorimotor trajectories in ED. MethodProbabilistic tractography and seed-based functional connectivity analysis were performed in 16/16 ED patients/healthy brass players within a simple literature-informed network model of cortical sensorimotor processing encompassing supplementary motor, superior parietal, primary somatosensory and motor cortex as well as the putamen. Post-hoc grey matter volumetry was performed within cortices of abnormal trajectories. ResultsED patients showed average axial diffusivity reduction within projections between the primary somatosensory cortex and putamen, with converse increases within projections between supplementary motor and superior parietal cortex in both hemispheres. Increase in the mode of anisotropy in patients was accompanying the latter left-hemispheric projection, as well as in the supplementary motor area’s projection to the left primary motor cortex. Patient’s left primary somatosensory functional connectivity with the putamen was abnormally reduced and significantly associated with the axial diffusivity reduction. Left primary somatosensory grey matter volume was increased in patients. ConclusionCorrelates of abnormal tract integrity within primary somatosensory cortico-subcortical projections and higher-order sensorimotor projections support the key role of dysfunctional sensory information propagation in ED pathophysiology. Differential directionality of cortico-cortical and cortico-subcortical abnormalities hints at non-uniform sensory system changes.

Motor imagery in chronic neglect: An fMRI pilot study

ABSTRACTAim. Previous studies indicate the effectiveness of motor imagery training in stroke patients. To determine whether patients showing chronic visuospatial neglect symptoms may profit from motor imagery training, it is important to assess how the brain implements motor imagery when cortical systems involved in attentional control are impaired.Method. Therefore, in this pilot study, nine chronic neglect patients with right-hemispheric stroke performed motor imagery of a finger opposition task during functional magnetic resonance imaging (fMRI).Results. Imagery of unaffected hand movements was related to activations in the left primary somatosensory and premotor cortices as well as in the left supplementary motor area. During the imagery of the affected hand, patients displayed activations in the left premotor cortex and supplementary motor area as well as left dorsolateral prefrontal cortex. Furthermore, time since onset and visual imagery capacity were negatively related to activation in the supplementary motor area during the imagery of the affected hand.Conclusions. These initial results demonstrate motor imagery capacity in patients with chronic neglect via compensatory neural processing during motor imagery of the affected hand in ipsilateral brain regions, since we found that the supplementary motor area appears to be specifically related to neglect severity. Although our results must be treated with caution due to the small sample size and missing control group, they indicate that neglect is not necessarily an exclusion criterion for motor imagery training per se.

Frontoparietal cortex and cerebellum contribution to the update of actual and mental motor performance during the day.

Actual and imagined movement speed increases from early morning until mid-afternoon. Here, we investigated the neural correlates of these daily changes. Fifteen subjects performed actual and imagined right finger opposition movement sequences at 8 am and 2 pm. Both actual and imagined movements were significantly faster at 2 pm than 8 am. In the morning, actual movements significantly activated the left primary somatosensory and motor areas, and bilaterally the cerebellum; in the afternoon activations were similar but reduced. Contrast analysis revealed greater activity in the cerebellum, the left primary sensorimotor cortex and parietal lobe in the morning than in the afternoon. Imagined movements in the morning significantly activated the parietal association cortices bilaterally, the left supplementary and premotor areas, and the right orbitofrontal cortex and cerebellum. In the afternoon, the frontal lobe was significantly activated with the right cerebellum. Contrast analysis revealed increased activity in the left parietal lobe in the morning than in the afternoon. For both tasks, speed in the morning was significantly related to the BOLD signal in the brain areas resulted more active. These findings suggest that motor performance is continuously updated on a daily basis with a predominant role of the frontoparietal cortex and cerebellum.

Musical expertise modulates functional connectivity of limbic regions during continuous music listening.

Music is known to be an important facet of all human cultures (Merriam, 1964). Listening to music in order to influence moods, evoke strong emotions, and derive pleasure is becoming increasingly common, especially in this day and age when access to music is easy and quick. In recent years, exploring the neural correlates of musical emotions has attracted the attention of neuroscientists (Brattico & Pearce, 2013; Koelsch, Fritz, v. Cramon, Muller, & Friederici, 2006). However, the majority of these studies have not accounted for the effect of musical expertise, despite increasing evidence of structural and functional differences between musicians and nonmusicians, particularly in the regions of the cerebrum associated with motor, auditory, and visuospatial processing (Amunts et al., 1997; Angulo-Perkins et al., 2014; Baumann et al., 2007; Fauvel et al., 2014; Gaser & Schlaug, 2003; Herdener et al., 2010; Hutchinson, Lee, Gaab, & Schlaug, 2003; Hyde et al., 2009; Lee, Chen, & Schlaug, 2003; Pantev & Herholz, 2011; Schlaug, Jancke, Huang, Staiger, & Steinmetz, 1995; Schlaug, Jancke, Huang, & Steinmetz, 1995; Sluming, Taylor, Keller, Cezayirli, & Roberts, 2003; Wong, Skoe, Russo, Dees, & Kraus, 2007). In addition, musicians were found to have greater amounts of white matter in the anterior corpus callosum than nonmusicians (for a review, see Moore, Schaefer, Bastin, Roberts, & Overy, 2014). Furthermore, higher cerebellar volume is associated with male musicians than nonmusicians (Hutchinson et al., 2003; Sluming et al., 2003), particularly concerning the regions involved in representing movement (Gaser & Schlaug, 2003). In addition, musicians have been found to have greater sensitivity in processing and discriminating sounds in the auditory cortex (Musacchia, Strait, & Kraus, 2008; Pantev et al., 1998; Strait et al., 2009; Tervaniemi et al., 2001; Wong et al., 2007). In sum, long-term musical practice causes structural and functional changes in the brain, with subsequent enhanced representation of sounds and music (see Kraus & Chandrasekaran, 2010; Reybrouck & Brattico, 2015 for an overview).The neuroscientific studies on musical emotions have predominantly utilized the classical controlled paradigm wherein the condition of interest is interspersed with other tasks or baseline, thereby not providing the entire picture of emotional networks in the brain. Recent times have seen an increase in fMRI studies that employ the continuous listening paradigm, in which participants listen to music continuously, typically lasting the entire span of the piece, and without any intermittent task, for investigating neural processing of music (Abrams et al., 2013; Alluri et al., 2012, 2013; Burunat, Alluri, Toiviainen, Numminen, & Brattico, 2014; Toiviainen, Alluri, Brattico, Wallentin, & Vuust, 2014; Trost, Ethofer, Zentner, & Vuilleumier, 2012). However, those studies examined whole brain regional activations, not focusing on limbic system structures or on the modulation of neural activity and connectivity by musical expertise. A single fMRI study (Koelsch et al., 2013) has used full pieces of music to investigate the dynamics of emotion processing in the limbic system, albeit with participants without musical training.On the contrary, resting-state-based fMRI studies have dealt with investigating functional networks that emerge during prolonged periods of rest without any stimulus (Lee, Smyser, & Shimony, 2013). There is abundant literature examining restingstate connectivity and connectivity in the visual domain, especially in terms of decoding. However, there has been a scarcity of studies investigating functional connectivity in the auditory domain as a function of musical expertise. The first resting-state study investigating connectivity differences between musicians and nonmusicians in resting state was conducted by Luo et al. (2012). Their functional connectivity analysis was limited to five seed regions representing the right primary motor, left primary auditory, left primary somatosensory cortices, and the left primary visual and left V2 areas. …

Distinguishable Brain Activation Networks for Short- and Long-Term Motor Skill Learning

The acquisition of a new motor skill is characterized first by a short-term, fast learning stage in which performance improves rapidly, and subsequently by a long-term, slower learning stage in which additional performance gains are incremental. Previous functional imaging studies have suggested that distinct brain networks mediate these two stages of learning, but direct comparisons using the same task have not been performed. Here we used a task in which subjects learn to track a continuous 8-s sequence demanding variable isometric force development between the fingers and thumb of the dominant, right hand. Learning-associated changes in brain activation were characterized using functional MRI (fMRI) during short-term learning of a novel sequence, during short-term learning after prior, brief exposure to the sequence, and over long-term (3 wk) training in the task. Short-term learning was associated with decreases in activity in the dorsolateral prefrontal, anterior cingulate, posterior parietal, primary motor, and cerebellar cortex, and with increased activation in the right cerebellar dentate nucleus, the left putamen, and left thalamus. Prefrontal, parietal, and cerebellar cortical changes were not apparent with short-term learning after prior exposure to the sequence. With long-term learning, increases in activity were found in the left primary somatosensory and motor cortex and in the right putamen. Our observations extend previous work suggesting that distinguishable networks are recruited during the different phases of motor learning. While short-term motor skill learning seems associated primarily with activation in a cortical network specific for the learned movements, long-term learning involves increased activation of a bihemispheric cortical-subcortical network in a pattern suggesting "plastic" development of new representations for both motor output and somatosensory afferent information.