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Background: Many studies have shown effects of anodal transcranial direct current stimulation (a-tDCS) and high-frequency transcranial random noise stimulation (tRNS) on elevating cortical excitability. Moreover, tRNS with a direct current (DC)-offset is more likely to lead to increases in cortical excitability than solely tRNS. While a-tDCS over primary motor cortex (M1) has been shown to attenuate pain perception, tRNS + DC-offset may prove as an effective means for pain relief. Objective: This study aimed to examine effects of a-tDCS and high-frequency tRNS + DC-offset over M1 on pain expectation and perception, and assess whether these effects could be influenced by the certainty of pain expectation. Methods: Using a double-blinded and sham-controlled design, 150 healthy participants were recruited to receive a single-session a-tDCS, high-frequency tRNS + DC-offset, or sham stimulation over M1. The expectation and perception of electrical stimulation in certain and uncertain contexts were assessed at baseline, immediately after, and 30 min after stimulation. Results: Compared with sham stimulation, a-tDCS induced immediate analgesic effects that were greater when the stimulation outcome was expected with uncertainty; tRNS induced immediate and sustained analgesic effects that were mediated by decreasing pain expectation. Nevertheless, we found no strong evidence for tRNS being more effective for attenuating pain than a-tDCS. Conclusions: The analgesic effects of a-tDCS and tRNS showed different temporal courses, which could be related to the more sustained effectiveness of high-frequency tRNS + DC-offset in elevating cortical excitability. Moreover, expectations of pain intensity should be taken into consideration to maximize the benefits of neuromodulation.

Alterations of empathy for others’ pain among patients with chronic pain remained inconsistent. Here, applying a capsaicin-based ongoing pain model on healthy participants, this study investigated how ongoing first-hand pain influences empathic reactions to vicarious pain stimuli. Healthy participants were randomly treated with topical capsaicin cream (capsaicin group) or hand cream (control group) on the left forearm. Video clips showing limbs in painful and non-painful situations were used to induce empathic responses. The capsaicin group showed greater empathic neural responses in the right primary somatosensory cortex (S1) than the control group but smaller responses in the left anterior insula (AI) accompanied with smaller empathic pain-intensity ratings. Notably, the intensity of ongoing pain negatively correlated with empathy-related neural responses in the left AI. Inter-subject phase synchronization analysis was used to assess stimulus-dependent dynamic functional connectivity within or between brain regions engaged in pain empathy. The capsaicin group showed greater empathy-related neural synchronization within S1 and between S1 and AI, but less synchronization within AI and between AI and MCC. Behaviorally, the differential inter-subject pain-intensity rating alignment between painful and non-painful videos was more positive for the capsaicin group than for the control group, and this effect was partially mediated by the inter-subject neural synchronization between S1 and AI. These results suggest that ongoing first-hand pain facilitates neural activation and synchronization within brain regions associated with empathy-related somatosensory resonance at the cost of inhibiting activation and synchronization within brain regions engaged in empathy-related affective sharing.

Previous behavioral studies have shown that sharing painful experiences can strengthen social bonds and promote mutual prosociality, yet the neural mechanisms underlying this phenomenon remain unclear. We hypothesized that sharing a painful experience induces brain-to-brain synchronization and mutual empathy for each other's pain between pain-takers and pain-observers, which then leads to enhanced social bonding. To test this hypothesis, we adopted an electroencephalographic (EEG) hyper-scanning technique to assess neuronal and behavioral activity during a Pain-Sharing task in which high- or low-intensity pain stimulation was randomly delivered to one participant of a dyad on different experimental trials. Single-brain analysis showed that sensorimotor α-oscillation power was suppressed more when expecting high-intensity pain than when expecting low-intensity pain similarly for self-directed or partner-directed pain. Dual-brain analysis revealed that expecting high-intensity pain induced greater brain-to-brain synchronization of sensorimotor α-oscillation phases between pain-takers and pain-observers than did expecting low-intensity pain. Mediation analysis further revealed that brain-to-brain synchronization of sensorimotor α-oscillations mediated the effects of pain-stimulation intensity on mutual affective sharing for partner-directed pain. This mutual affective empathy during the task predicted the social bonding, as indexed by prosocial inclinations measured after the task. These results support the hypothesis that sharing a painful experience triggers emotional resonance between pairs of individuals through brain-to-brain synchronization of neuronal α-oscillations recorded over the sensorimotor cortex, and this emotional resonance further strengthens social bonds and motivates prosocial behavior within pairs of individuals.

Effort has been made to find biomarkers for vascular dementia (VaD). Nevertheless, the current findings are typically obtained through statistical tests of group level differences. In clinical practice, however, it is more common to perform individual level inferences, e.g., to determine if a subject is suffering from VaD, which cannot be resolved with statistical analysis. The goal of this study is to develop a method to effectively discriminate early VaD patients from normal controls by combining EEG features with machine learning methods. The EEG signals were recorded from a total of 15 VaD patients and 21 controls during a visual oddball task. Interregional directed connectivity was derived from directed transfer function (DTF) analysis and used as features in classification. Three machine learning methods, including linear discriminant analysis (LDA), error back-propagation (BP) neural network, and support vector machine (SVM) were used as classifiers, and their classification performance was compared. It was found that VaD patients can be effectively identified using the BP and SVM classifiers with high accuracy. In particular, when the SVM classifier was combined with feature selection by Fisher score, it reached an accuracy 86.11%, sensitivity 86.67%, and specificity 85.71%. The area under the curve (AUC, 0.854) indicates a good identification of VaD patients from the normal controls. Since the EEG is noninvasive, inexpensive, and widely available to use, the current study presents a novel clinical application of machine learning methods and could facilitate automatic screening and diagnosis of the VaD at an early stage in future.

Patients with somatoform pain disorder (SPD) suffer from somatic pain that cannot be fully explained by specific somatic pathology. While the pain experience requires the integration of sensory and contextual processes, the cortical oscillations have been suggested to play a crucial role in pain processing and integration. The present study is aimed at identifying the abnormalities of spontaneous cortical oscillations among patients with SPD, thus for a better understanding of the ongoing brain states in these patients. Spontaneous electroencephalography data during a resting state with eyes open were recorded from SPD patients and healthy controls, and their cortical oscillations as well as functional connectivity were compared using both electrode-level and source-level analysis. Compared with healthy controls, SPD patients exhibited greater resting-state alpha oscillations (8.5-12.5 Hz) at the parietal region, as reflected by both electrode-level spectral power density and exact low-resolution brain electromagnetic tomography (eLORETA) cortical current density. A significant correlation between parietal alpha oscillation and somatization severity was observed in SPD patients, after accounting for the influence of anxiety and depression. Functional connectivity analysis further revealed a greater frontoparietal connectivity of the resting-state alpha oscillations in SPD patients, which was indexed by the coherence between pairs of electrodes and the linear connectivity between pairs of eLORETA cortical sources. The enhanced resting-state alpha oscillation in SPD patients could be relevant with attenuated sensory information gating and excessive integration of pain-related information, while the enhanced frontoparietal connectivity could be reflecting their sustained attention to bodily sensations and hypervigilance to somatic sensations.

White matter hyperintensities (WMHs) have been reported to be correlated with functional brain changes, but the association of the specific WMHs distribution pattern with regional functional changes remains uncertain. The aim of this study is to explore the possible spatial correlation of WMH with changes in cerebral blood flow (CBF) and spontaneous brain activities in elderly using a novel approach. The WMHs, CBF, and spontaneous brain activities measured by intrinsic connectivity contrast (ICC), were quantified using multimodal magnetic resonance imaging for 69 elderly subjects. Such approach enables us to expand our search for newly identified correlated areas by drawing strengths of different modes and provides a means for triangulation as well as complementary insights. The results showed significant positive correlations between WMH volumes in the right superior corona radiata and CBF in the left supplementary motor area, as well as between WMH volumes in left anterior limb internal capsule and CBF in the right putamen. Significant correlations of regional WMH volumes and ICC were also detected between the right anterior corona radiata and the left cuneus, and the right superior occipital cortex, as well as between the right superior corona radiata and the left superior occipital cortex. These findings may suggest a regional compensatory functional enhancement accounting for the maintenance of cognitively normal status, which can be supported by the widely observed phenomenon that mild to moderate WMH load could have little effect on global cognitive performance.

Disruptions of the functional brain network and cerebral blood flow (CBF) have been revealed in patients with mild cognitive impairment (MCI). However, the neurophysiological mechanism of hypoperfusion as well as the reorganization of the intrinsic whole brain network due to the neuropathology of MCI are still unclear. In this study, we aimed to investigate the changes of CBF and the whole brain network organization in MCI by using a multimodal MRI approach. Resting state ASL MRI and BOLD MRI were used to evaluate disruptions of CBF and underlying functional connectivity in 27 patients with MCI and 35 cognitive normal controls (NC). The eigenvector centrality mapping (ECM) was used to assess the whole brain network reorganization in MCI, and a seed-based ECM approach was proposed to reveal the contributions of the whole brain network on the ECM alterations. Significantly decreased perfusion in the posterior parietal cortex as well as its connectivity within the default mode network and occipital cortex were found in the MCI group compared to the NC group. The ECM analysis revealed decreased EC in the middle cingulate cortex, parahippocampal gyrus, medial frontal gyrus, and increased EC in the right calcarine sulcus, superior temporal gyrus, and supplementary motor area in the MCI group. The results of this study indicate that there are deficits in cerebral blood flow and functional connectivity in the default mode network, and that sensory-processing networks might play a compensatory role to make up for the decreased connections in MCI. [ABSTRACT FROM AUTHOR]

Background: Previous studies employed demanding and complex hand tasks to study the brain activation in people with Parkinson's Disease (PD). There is inconsistent finding about the cerebellar activity during movement execution of this patient population. Objectives: This study aimed to examine the brain activation patterns of PD individuals in the on-state and healthy control subjects in a simple finger tapping task. Methods: Twenty-seven patients with PD and 22 age-matched healthy subjects were recruited for the study. Subjects were instructed to perform simple finger tapping tasks under self- and cue-initiated conditions in separate runs while their brain activations were captured using fMRI. Results: Healthy subjects had higher brain activity in contralateral precentral gyrus during the self-initiated task, and higher brain activity in the ipsilateral middle occipital gyrus during the cue-initiated task. PD patients had higher brain activity in the cerebellum Crus I (bilateral) and lobules VI (ipsilateral) during the self-initiated task and higher brain activity in the contralateral middle frontal gyrus during the cue-initiated task. When compared with healthy controls, PD patients had lower brain activity in the contralateral inferior parietal lobule during the self-initiated task, and lower brain activity in the ipsilateral cerebellum lobule VIII, lobule VIIB and vermis VIII, and thalamus during the cue-initiated task. Conjunction analysis indicated that both groups had activation in bilateral cerebellum and SMA and ipsilateral precentral gyrus and postcentral gyrus during both self- and cue-initiated movement. Individuals with PD exhibited higher brain activity in the executive zone (cerebellum Crus I and II) during self-initiated movement, and lower brain activity in the sensorimotor zone (i.e. lobule VIIb and VIII of the cerebellum) during cue-initiated movement. [ABSTRACT FROM AUTHOR]

Objective: The study was dedicated to investigating the change in information processing in brain networks of vascular dementia (VaD) patients during the process of decision making. Methods: EEG was recorded from 18 VaD patients and 19 healthy controls when subjects were performing a visual oddball task. The whole task was divided into several stages by using global field power analysis. In the stage related to the decision-making process, graph theoretical analysis was applied to the binary directed network derived from EEG signals at nine electrodes in the frontal, central, and parietal regions in δ (0.5-3.5 Hz), θ (4-7 Hz), α1 (8-10 Hz), α2 (11-13 Hz), and β (14-30 Hz) frequency bands based on directed transfer function. Results: A weakened outgoing information flow, a decrease in out-degree, and an increase in in-degree were found in the parietal region in VaD patients, compared to healthy controls. In VaD patients, the parietal region may also lose its hub status in brain networks. In addition, the clustering coefficient was significantly lower in VaD patients. Conclusions: Impairment might be present in the parietal region or its connections with other regions, and it may serve as one of the causes for cognitive decline in VaD patients. The brain networks of VaD patients were significantly altered toward random networks. Significance: The present study extended our understanding of VaD from the perspective of brain functional networks, and it provided possible interpretations for cognitive deficits in VaD patients. [ABSTRACT FROM AUTHOR]