Dina Lelic

Pain-associated adaptive cortical reorganisation in chronic pancreatitis.

Background/Aims: In various chronic pain conditions cortical reorganisation seems to play a role in the symptomatology. The aims of this study were to investigate cortical reorganisation in patients with pain caused by chronic pancreatitis (CP) and to correlate putative cortical reorganisation to clinical pain scores. Methods: 24 patients suffering from CP and 14 healthy volunteers were included. Patients’ daily experience of pain was recorded in a pain diary. The sigmoid was stimulated electrically with simultaneous recording of evoked brain potentials (EPs). The brain source localisations reflecting direct neuronal activity were fitted by a five-dipole model projected to magnetic resonance imaging of the individual brains. Results: Patients showed prolonged latencies of the EPs confined to the frontal region of the brain (p < 0.01). The corresponding brain sources were located in the bilateral insula, cingulate gyrus and bilateral secondary somatosensory area. The insular dipoles were localised more posterior in the patients than in healthy subjects (p < 0.01). The shift in insular dipole localisation was negatively correlated with the patients’ clinical pain scores (p < 0.05). Conclusions: The findings indicate that sustained pain in CP leads to functional reorganisation of the insular cortex. We suggest its physiological correlate to be an adaptive response to chronic pain.

Pathophysiology of chronic pancreatitis

Chronic pancreatitis (CP) is an inflammatory disease of the pancreas characterized by progressive fibrotic destruction of the pancreatic secretory parenchyma. Despite the heterogeneity in pathogenesis and involved risk factors, processes such as necrosis/apoptosis, inflammation or duct obstruction are involved. This fibrosing process ultimately leads to progressive loss of the lobular morphology and structure of the pancreas, deformation of the large ducts and severe changes in the arrangement and composition of the islets. These conditions lead to irreversible morphological and structural changes resulting in impairment of both exocrine and endocrine functions. The prevalence of the disease is largely dependent on culture and geography. The etiological risk-factors associated with CP are multiple and involve both genetic and environmental factors. Throughout this review the M-ANNHEIM classification system will be used, comprising a detailed description of risk factors such as: alcohol-consumption, nicotine-consumption, nutritional factors, hereditary factors, efferent duct factors, immunological factors and miscellaneous and rare metabolic factors. Increased knowledge of the different etiological factors may encourage the use of further advanced diagnostic tools, which potentially will help clinicians to diagnose CP at an earlier stage. However, in view of the multi factorial disease and the complex clinical picture, it is not surprising that treatment of patients with CP is challenging and often unsuccessful.

Inverse modeling on decomposed electroencephalographic data: a way forward?

Inverse modeling is typically applied to instantaneous electroencephalogram signals. However, this approach has several shortcomings including its instability to model multiple and deep located dipole sources and the interference of background noise may hamper the sensitivity, stability, and precision of the estimated dipoles. This article validates different dipole estimation techniques to find the most optimal combination of different analysis principles using both simulations and recordings. Electroencephalogram data were simulated with six known source locations. First, a dataset was simulated with sources chosen to mimic somatosensory-evoked potentials to electrical stimuli. Additionally, 20 further datasets were simulated each containing six randomly located and oriented sources. The simulated sources included superficial, deep, and simultaneously active sources. Furthermore, somatosensory-evoked potentials to median nerve stimuli were recorded from one subject. On both simulated and recorded evoked potential data, three different methods of signal decomposition were compared: independent component analysis (ICA), second-order blind identification (SOBI), and multichannel matching pursuit (MMP). For inverse modeling of the brain sources, the DIPFIT function of the EEGLAB software was used on raw and decomposed data. MMP was able to separate all simulated components that corresponded to superficial, deep, and simultaneously active sources. ICA and SOBI were only able to find components that corresponded to superficial sources. For the 20 randomized simulations, the results from the evoked potential simulation were reproduced. Inverse modeling on MMP components (atoms) was better than on ICA or SOBI components (P < 0.001). DIPFIT on MMP atoms localized 99.2% of the simulated dipoles in correct areas with their correct time/frequency distribution. DIPFIT on ICA and SOBI components localized 35% and 39.6%, respectively of the simulated dipoles in correct areas. As for the real-evoked potentials recorded in one subject, DIPFIT on MMP atoms allowed us to build a dipole model closer to the current physiological knowledge than dipole modeling of ICA and SOBI components. The results show that using MMP before inverse modeling is a reliable way to noninvasively estimate cortical activation.

Diabetic Autonomic Neuropathy Affects Symptom Generation and Brain-Gut Axis

OBJECTIVE Long-term diabetes leads to severe peripheral, autonomous, and central neuropathy in combination with clinical gastrointestinal symptoms. The brain-gut axis thus expresses a neurophysiological profile, and heart rate variability (HRV) can be correlated with clinical gastrointestinal symptoms. RESEARCH DESIGN AND METHODS Fifteen healthy volunteers and 15 diabetic patients (12 with type 1 diabetes) with severe gastrointestinal symptoms and clinical suspicion of autonomic neuropathy were included. Psychophysics and evoked brain potentials were assessed after painful rectosigmoid electrostimulations, and brain activity was modeled by brain electrical source analysis. Self-reported gastrointestinal symptoms (per the Patient Assessment of Upper Gastrointestinal Disorder Severity Symptom Index) and quality of life (SF-36 Short Form Survey) were collected. RESULTS Diabetic patients had autonomous neuropathy, evidenced by decreased electrocardiographic R-R interval (P = 0.03) and lower HRV (P = 0.008). Patients were less sensitive to painful stimulation (P = 0.007), had prolonged latencies of evoked potentials (P ≤ 0.001), and showed diminished amplitude of the N2–P2 component in evoked potentials (P = 0.01). There was a caudoanterior shift of the insular brain source (P = 0.01) and an anterior shift of the cingulate generator (P = 0.01). Insular source location was associated with HRV assessments (all P < 0.02), and the shift (expressed in mm) correlated negatively with physical health (P < 0.001) and positively with nausea (P = 0.03) and postprandial fullness (P = 0.03). Cingulate source shift was correlated negatively with physical health (P = 0.005) and positively with postprandial fullness (P ≤ 0.001). CONCLUSIONS This study provides evidence for interaction between autonomic neuropathy and peripheral nervous degeneration, as well as changes in dipole sources in diabetic patients with gastrointestinal symptoms. The findings may lead to improved treatment modalities targeting pharmacological neuroprotection or neuromodulation.

Brain source connectivity reveals the visceral pain network

INTRODUCTION Several brain structures have been consistently found to be involved in visceral pain processing. However, recent research questions the specificity of these regions and it has been suggested that it is not singular activations of brain areas, but their cross-communication that results in perception of pain. Moreover, frequency at which neurons are firing could be what separates pain from other sensory modalities which otherwise involve the same anatomical locations. In this test/retest study, we identified the network of sources and their frequencies following visceral pain. METHODS 62-channel evoked potentials following electrical stimulation in oesophagus were recorded in twelve healthy volunteers on two separate days. Multichannel matching pursuit (MMP) and dipolar source localisation were used. Multiple sources responsible for one MMP component were considered to act synchronously as each MMP component is mono-frequency and has a single topography. We first identified components that were reproducible within subjects over recording sessions. These components were then analysed across subjects. RESULTS MMP and source localisation showed three main brain networks; an early network at ~8.3 Hz and ~3.5 Hz involving brainstem, operculum, and pre-frontal cortex peaking at ~77 ms. This was followed by an operculum, amygdale, mid-cingulate, and anterior-cingulate network at ~4.5 Hz. Finally, there was an operculum and mid-cingulate network that persisted over the entire time interval, peaking at 245.5±51.4 ms at ~2.1 Hz. CONCLUSION This study gives evidence of operculums central integrative role for perception of pain and shows that MMP is a reliable method to study upstream brain activity.

Biomechanical functional and sensory modelling of the gastrointestinal tract

The aim of this review is to describe the biomechanical, functional and sensory modelling work that can be used to integrate the physiological, anatomical and medical knowledge of the gastrointestinal (GI) system. The computational modelling in the GI tract was designed, implemented and evaluated using a series of information and communication technologies-based tools. These tools modelled the morphometry, biomechanics, functions and sensory aspects of the human GI tract. The research presented in this review is based on the virtual physiological human concept that pursues a holistic approach to representation of the human body. Such computational modelling combines imaging data, GI physiology, the gut–brain axis, geometrical and biomechanical reconstruction, and computer graphics for mechanical, electronic and pain analysis. The developed modelling will aid research and ensure that medical professionals benefit through the provision of relevant and precise information about a patients condition. It will also improve the accuracy and efficiency of the medical procedures that could result in reduced cost for diagnosis and treatment.

The brain networks encoding visceral sensation in patients with gastrointestinal symptoms due to diabetic neuropathy

Increasing evidence points to association between long‐term diabetes mellitus and abnormal brain processing. The aim of this study was to investigate central changes due to electrical stimulation in esophagus in patients with upper gastrointestinal (GI) symptoms due to diabetic neuropathy.

Brain networks encoding rectal sensation in type 1 diabetes.

INTRODUCTION It has been shown that patients with type 1 diabetes mellitus and gastrointestinal (GI) symptoms have abnormal processing of sensory information following stimulation in the oesophagus. In order to find less invasive stimuli to study visceral afferent processing and to further elaborate the gut-brain network in diabetes, we studied brain networks following rectal electrical stimulations. METHODS Twelve type 1 diabetes patients with GI symptoms and twelve healthy controls were included. A standard ambulatory 24-h electrocardiography was performed. 122-channel-evoked brain potentials to electrical stimulation in the rectum were recorded. Brain source-connectivity analysis was done. GI symptoms were assessed with the gastroparesis cardinal symptom index and quality of life (QOL) with SF-36. Any changes in brain source connectivity were correlated to duration of the disease, heart beat-to-beat intervals (RRs), clinical symptoms, and QOL of the patients. RESULTS Diabetic patients with GI symptoms showed changes relative to controls in the operculum-cingulate network with the operculum source localized deeper and more anterior (P≤0.001) and the cingulate source localized more anterior (P=0.03). The shift of operculum source was correlated with the duration of the disease, severity of GI symptoms, and decreased RR (P<0.05). The shift of the cingulate source was correlated with the mental QOL (P=0.04). In healthy controls, the contribution of the cingulate source to the network was higher than the contribution of the operculum source (P≤0.001), whereas in patients the contribution of the two sources was comparable. CONCLUSION This study gives further evidence for CNS involvement in diabetes. Since network reorganizations were correlated to GI symptoms, irregularities of rectal-evoked potentials can be viewed as a proxy for abnormal bottom-up visceral afferent processing. The network changes might serve as a biomarker for disturbed sensory visceral processing of GI symptoms in diabetes patients.

Multichannel matching pursuit validation and clustering: A simulation and empirical study

INTRODUCTION Multichannel matching pursuit (MMP) is a relatively new method that can be applied to electroencephalogram (EEG) signals in combination with inverse modelling. However, limitations of MMP have not been adequately tested. The aims of this study were to investigate how the accuracy of MMP algorithm is altered due to increased number of brain sources and increased noise level, and to implement and test a modified K-means clustering algorithm in order to group similar MMP atoms in time-frequency and space between subjects together. METHODS Four groups of 20 EEG signals were simulated. The groups consisted of simulations with 5, 10, 15, and 20 brain sources. The accuracy of MMP algorithm was first tested on increasing number of sources. Then, different levels of noise were added to the simulations and accuracy of the algorithm was tested on increasing noise level. K-means clustering algorithm was tested on 4 datasets (5, 10, 15, and 20 sources) of 10 similar phantom subjects. Finally, the clustering algorithm was tested on empirical somatosensory evoked potential and brainstem evoked potential data. RESULTS The MMP accuracy decreased as the number of sources increased and MMP accuracy was robust to noise. Furthermore, we found that when applying the clustering method to a subject groups MMP data, the clustering method grouped the similar atoms between subjects correctly. CONCLUSION The MMP and clustering method proved to be an efficient way to group similar brain activity and thus study differences in brain activation sequence to sensory stimulation between groups of subjects.

Manipulation of dysfunctional spinal joints affects sensorimotor integration in the prefrontal cortex: a brain source localization study

Objectives. Studies have shown decreases in N30 somatosensory evoked potential (SEP) peak amplitudes following spinal manipulation (SM) of dysfunctional segments in subclinical pain (SCP) populations. This study sought to verify these findings and to investigate underlying brain sources that may be responsible for such changes. Methods. Nineteen SCP volunteers attended two experimental sessions, SM and control in random order. SEPs from 62-channel EEG cap were recorded following median nerve stimulation (1000 stimuli at 2.3 Hz) before and after either intervention. Peak-to-peak amplitude and latency analysis was completed for different SEPs peak. Dipolar models of underlying brain sources were built by using the brain electrical source analysis. Two-way repeated measures ANOVA was used to assessed differences in N30 amplitudes, dipole locations, and dipole strengths. Results. SM decreased the N30 amplitude by 16.9 ± 31.3% (P = 0.02), while no differences were seen following the control intervention (P = 0.4). Brain source modeling revealed a 4-source model but only the prefrontal source showed reduced activity by 20.2 ± 12.2% (P = 0.03) following SM. Conclusion. A single session of spinal manipulation of dysfunctional segments in subclinical pain patients alters somatosensory processing at the cortical level, particularly within the prefrontal cortex.