Sickle cell disease (SCD) is a red blood cell disorder that causes many complications including life-long pain. Treatment of pain remains challenging due to a poor understanding of the mechanisms and limitations to characterize and quantify pain. In the present study, we examined simultaneously recording functional MRI (fMRI) and electroencephalogram (EEG) to better understand neural connectivity as a consequence of chronic pain in SCD patients. We performed independent component analysis and seed-based connectivity on fMRI data. Spontaneous power and microstate analysis was performed on EEG-fMRI data. ICA analysis showed that patients lacked activity in the default mode network (DMN) and executive control network compared to controls. EEG-fMRI data revealed that the insula cortex's role in salience increases with age in patients. EEG microstate analysis showed patients had increased activity in pain processing regions. The cerebellum in patients showed a stronger connection to the periaqueductal gray matter (involved in pain inhibition), and negative connections to pain processing areas. These results suggest that patients have reduced activity of DMN and increased activity in pain processing regions during rest. The present findings suggest resting state connectivity differences between patients and controls can be used as novel biomarkers of SCD pain.

Unlike focal or partial epilepsy, which has a confined range of influence, idiopathic generalized epilepsy (IGE) often affects the whole or a larger portion of the brain without obvious, known cause. It is important to understand the underlying network which generates epileptic activity and through which epileptic activity propagates. The aim of the present study was to investigate the thalamocortical relationship using non-invasive imaging modalities in a group of IGE patients. We specifically investigated the roles of the mediodorsal nuclei in the thalami and the medial frontal cortex in generating and spreading IGE activities. We hypothesized that the connectivity between these two structures is key in understanding the generation and propagation of epileptic activity in brains affected by IGE. Using three imaging techniques of EEG, fMRI and EEG-informed fMRI, we identified important players in generation and propagation of generalized spike-and-wave discharges (GSWDs). EEG-informed fMRI suggested multiple regions including the medial frontal area near to the anterior cingulate cortex, mediodorsal nuclei of the thalamus, caudate nucleus among others that related to the GSWDs. The subsequent seed-based fMRI analysis revealed a reciprocal cortical and bi-thalamic functional connection. Through EEG-based Granger Causality analysis using (DTF) and adaptive DTF, within the reciprocal thalamocortical circuitry, thalamus seems to serve as a stronger source in driving cortical activity from initiation to the propagation of a GSWD. Such connectivity change starts before the GSWDs and continues till the end of the slow wave discharge. Thalamus, especially the mediodorsal nuclei, may serve as potential targets for deep brain stimulation to provide more effective treatment options for patients with drug-resistant generalized epilepsy.

Motor imagery-based (MI based) brain-computer interface (BCI) using electroencephalography (EEG) allows users to directly control a computer or external device by modulating and decoding the brain waves. A variety of factors could potentially affect the performance of BCI such as the health status of subjects or the environment. In this study, we investigated the effects of soft drinks and regular coffee on EEG signals under resting state and on the performance of MI based BCI. Twenty-six healthy human subjects participated in three or four BCI sessions with a resting period in each session. During each session, the subjects drank an unlabeled soft drink with either sugar (Caffeine Free Coca-Cola), caffeine (Diet Coke), neither ingredient (Caffeine Free Diet Coke), or a regular coffee if there was a fourth session. The resting state spectral power in each condition was compared; the analysis showed that power in alpha and beta band after caffeine consumption were decreased substantially compared to control and sugar condition. Although the attenuation of powers in the frequency range used for the online BCI control signal was shown, group averaged BCI online performance after consuming caffeine was similar to those of other conditions. This work, for the first time, shows the effect of caffeine, sugar intake on the online BCI performance and resting state brain signal.

Introduction One major challenge in the treatment of pain from sickle cell disease (SCD) is the current lack of an objective measure of pain. Therefore, we used functional magnetic imaging (fMRI) to compare a specific brain network in SCD patients with healthy subjects to develop objective methods to assess pain. We hypothesize that in SCD patients, the default-mode-network (DMN) is less active in comparison to healthy subjects. DMN is a prevalent network dynamic that appears in the absence of overt behavior and is thought to be responsible for a host of visceral mental activities. This DMN difference may be due to prolonged SCD-related pain. Methods Ten healthy subjects (6 males and 4 females; age: mean=23.3, SD= 3.3 years) and ten SCD patients (5 males, 5 females; age: mean= 28.5, SD=7.1 years) participated in the study following informed consent to the procedures approved by the IRB of the University of Minnesota. Patients were recruited by hematologists at the University of Minnesota Medical Center. None of the patients were experiencing acute crisis during the experiments. FMRI data was acquired with a 3T Siemens Trio whole-body scanner with echo-planar imaging (EPI) sequence. Each fMRI recording lasted about 6minutes. The experiment procedures were well tolerated by all subjects. Both independent component analysis (ICA) and seed-based region of interest (ROI) analysis were applied to the fMRI data, and the analysis was performed using the BrainVoyager QX software. Results Experimental and analyticalprocedures were applied to both groups under similar conditions and the recorded data in the two groups have comparable quality. Using the data driven ICA-based analysis, each fMRI data set was decomposed into thirty independent components. The DMN component waseasilyidentified in all of the ten healthy subjects. In contrast, none of the ten SCD patients had any identifiable DMN component in the ICA-based analysis. Seed-based ROI analysis was also performed to find correlational networks. The ROIs were predetermined to be in medial prefrontal cortex (mPFC), posterior cingulate cortex (PCC), left and right lateral parietal cortex (LP). Using the time course extracted from the ROIs, DMN was revealed in all ten healthy subjects. However, DMN can only be found in three SCD patients.The identified DMN in patients showed incomplete clusters and had smaller cluster size comparing with the DMNin healthy subjects. By examining different possible ROI locations, DMN identified in patients consistently showed smaller number of voxels compared to controls. Conclusions Our findings suggest that the neurological signature of SCD patients may be altered by the chronic painful condition caused by the disease. Diminished activity in the DMN during rest has been previously reported by studies on both cognitive impairments and other types of chronic pain. It is currently unclear whether synchrony among the nodes in the default mode network can be reestablished once the pain condition is alleviated. Knowledge of the neurological characteristics of SCD patients may shed light in understanding in disease and the role of pain in SCD. Changes in DMN activity may also serve as a potential biomarker to quantify pain severity in the future.(This work was supported in part by NIH U01 HL117664 and NSF DGE-1069104.) References Baliki, M.N. (2008), ‘Beyond feeling: chronic pain hurts the brain, disrupting the default-mode network dynamics’, The Journal of Neuroscience, vol. 28, no. 6, pp. 1398-1403. Fox, M.D. (2005), ‘The human brain is intrinsically organized into dynamic, anticorrelated functional networks’,ProcNatlAcadSci USA, vol. 102, pp. 9673–9678. Disclosures No relevant conflicts of interest to declare.

Brain-computer interface (BCI) systems allow users to directly control computers and other machines by modulating their brain waves. In the present study, we investigated the effect of soft drinks on resting state (RS) EEG signals and BCI control. Eight healthy human volunteers each participated in three sessions of BCI cursor tasks and resting state EEG. During each session, the subjects drank an unlabeled soft drink with either sugar, caffeine, or neither ingredient. A comparison of resting state spectral power shows a substantial decrease in alpha and beta power after caffeine consumption relative to control. Despite attenuation of the frequency range used for the control signal, caffeine average BCI performance was the same as control. Our work provides a useful characterization of caffeine, the world's most popular stimulant, on brain signal frequencies and their effect on BCI performance.

Sickle cell disease (SCD) is associated with impaired cognitive function, pain, cerebral stroke and other neural dysfunctions suggestive of altered brain function. The most common reason for hospitalization of SCD patients is pain. Sickle pain is unique compared to other clinical pain conditions because it includes chronic pain as well as acute pain due to vasoocclusive crisis. The neuropathic and nociceptive aspects of pain in SCD make pain treatment challenging. Opioids, the most common analgesics, are associated with liabilities, such as addiction and tolerance. As a result, patients are often under-treated because of a lack of an objective pain measurement system. We therefore sought to develop an unbiased pain quantification method using non-invasive imaging techniques to recognize the biomarkers of pain and altered brain function. We examined the brain network connectivity in SCD patients (N=14) and healthy controls (N=13) to identify altered activity between the two groups that can be used as biomarkers for chronic pain. All experimental procedures were approved by the IRB of the University of Minnesota, and all subjects gave written informed consent before participating in the study. Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) were simultaneously recorded while the subjects were in a wakeful resting state. A 3T Siemens Trio whole-body scanner and a 16 channel head coil with an echo-planar imaging (EPI) sequence were used to acquire fMRI data. EEG data was recorded using a 64-channel EEG cap and MR-compatible amplifiers. Seed-based region of interest (ROI) analysis was performed on the fMRI data using Brain Voyager QX software. EEG informed fMRI (EEG-fMRI) was performed for power and microstate analysis using Matlab and SPM8 software. Statistical activation maps (p<0.001, uncorrected) were generated from general linear models (GLM) based on the time courses found from power and microstate analysis. Seeds were placed in the insula regions, and the functional connectivity between the left and right insula appeared to be stronger in SCD patients than in healthy controls. This result was verified in EEG-fMRI analysis. Activation of the insula and striatum regions positively correlated with the beta band in SCD patients, where healthy controls showed less activation in the insula in the same frequency band. Microstates corresponding to insula activation were observed in both healthy controls and SCD patients; however, activation seems stronger in SCD patients. Activation in the striatum regions was also observed in microstates for SCD patients, but not for healthy controls. These results show that the insula and striatum regions have greater activation in SCD patients compared to controls, and that patients have altered brain connectivity during resting state. Insula activation could be related to the salience network, a resting state network that is responsible for processing external input, or to pain processing. The insula and striatum are some of the common brain regions that have been shown to be active during painful stimuli. This altered activation could be caused by sickle pain and could be a potential biomarker of pain intensity. Due to the non-invasive nature of these quantitative data, this method can have applications in the unbiased objective quantification of pain and treatment outcomes. Altered connectivity observed in SCD patients can also be used to help better understand the neural pathophysiology of sickle pain and can lead to better management strategies for these patients. This work was supported in part by NIH grant U01-HL117664 and NSF IGERT grant DGE-1069104. Disclosures No relevant conflicts of interest to declare.

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