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.

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.

Pain-related adaptations in movement require a network architecture that allows for integration across pain and motor circuits. Previous studies addressing this issue have focused on cortical areas such as the midcingulate cortex. Here, we focus on pain and motor processing in the human cerebellum. The goal of this study was to identify areas of activation in the cerebellum, which are common to pain and motor processing, and to determine whether the activation is limited to the superior and inferior cerebellar motor maps or extends into multimodal areas of the posterior cerebellum. Our observations identified overlapping activity in left and right lobules VI and VIIb during pain and motor processing. Activation in these multimodal regions persisted when pain and motor processes were combined within the same trial, and activation in contralateral left lobule VIIb persisted when stimulation was controlled for. Functional connectivity analyses revealed significant correlations in the BOLD time series between multimodal cerebellar regions and sensorimotor regions in the cerebrum including anterior midcingulate cortex, supplementary motor area, and thalamus. The current findings are the first to show multimodal processing in lobules VI and VIIb for motor control and pain processing and suggest that the posterior cerebellum may be important in understanding pain-related adaptations in motor control.

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.

Evidence indicates that voluntary and involuntary movements are altered by affective context as well as the characteristics of an initiating cue. The purpose of this study was to determine the contribution of central and peripheral mechanisms to this phenomenon. During the presentation of pleasant, unpleasant, neutral, and blank images, participants (N = 33) responded to auditory stimuli (startle, 107 dB startle or 80 dB tone) by initiating a bimanual isometric contraction of the wrist and finger extensor muscles. Analyses of electromyography and force measures supported the hypothesis that exposure to unpleasant images accelerates central processing times and increases the gradient of slope of peripheral movement execution. In addition, startle cues as compared with tone cues accelerated and magnified all temporal and amplitude indices. Collectively, these findings have noteworthy implications for (a) those seeking to facilitate the speed and force of voluntary movement (i.e., movement rehabilitation), (b) understanding the higher incidence of motor difficulty in individuals with affective disorders, and (c) those seeking to regulate emotional input so as to optimize the quality of intended movements.