100 research outputs found

    Electrode Positioning and Montage in Transcranial Direct Current Stimulation

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    Transcranial direct current stimulation (tDCS) is a technique that has been intensively investigated in the past decade as this method offers a non-invasive and safe alternative to change cortical excitability2. The effects of one session of tDCS can last for several minutes, and its effects depend on polarity of stimulation, such as that cathodal stimulation induces a decrease in cortical excitability, and anodal stimulation induces an increase in cortical excitability that may last beyond the duration of stimulation6. These effects have been explored in cognitive neuroscience and also clinically in a variety of neuropsychiatric disorders – especially when applied over several consecutive sessions4. One area that has been attracting attention of neuroscientists and clinicians is the use of tDCS for modulation of pain-related neural networks3,5. Modulation of two main cortical areas in pain research has been explored: primary motor cortex and dorsolateral prefrontal cortex7. Due to the critical role of electrode montage, in this article, we show different alternatives for electrode placement for tDCS clinical trials on pain; discussing advantages and disadvantages of each method of stimulation

    Technique and Considerations in the Use of 4x1 Ring High-definition Transcranial Direct Current Stimulation (HD-tDCS)

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    High-definition transcranial direct current stimulation (HD-tDCS) has recently been developed as a noninvasive brain stimulation approach that increases the accuracy of current delivery to the brain by using arrays of smaller "high-definition" electrodes, instead of the larger pad-electrodes of conventional tDCS. Targeting is achieved by energizing electrodes placed in predetermined configurations. One of these is the 4x1-ring configuration. In this approach, a center ring electrode (anode or cathode) overlying the target cortical region is surrounded by four return electrodes, which help circumscribe the area of stimulation. Delivery of 4x1-ring HD-tDCS is capable of inducing significant neurophysiological and clinical effects in both healthy subjects and patients. Furthermore, its tolerability is supported by studies using intensities as high as 2.0 milliamperes for up to twenty minutes. Even though 4x1 HD-tDCS is simple to perform, correct electrode positioning is important in order to accurately stimulate target cortical regions and exert its neuromodulatory effects. The use of electrodes and hardware that have specifically been tested for HD-tDCS is critical for safety and tolerability. Given that most published studies on 4x1 HD-tDCS have targeted the primary motor cortex (M1), particularly for pain-related outcomes, the purpose of this article is to systematically describe its use for M1 stimulation, as well as the considerations to be taken for safe and effective stimulation. However, the methods outlined here can be adapted for other HD-tDCS configurations and cortical targets

    Reduced basal ganglia Ό-opioid receptor availability in trigeminal neuropathic pain: A pilot study

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    Abstract Background Although neuroimaging techniques have provided insights into the function of brain regions involved in Trigeminal Neuropathic Pain (TNP) in humans, there is little understanding of the molecular mechanisms affected during the course of this disorder. Understanding these processes is crucial to determine the systems involved in the development and persistence of TNP. Findings In this study, we examined the regional Ό-opioid receptor (ΌOR) availability in vivo (non-displaceable binding potential BPND) of TNP patients with positron emission tomography (PET) using the ΌOR selective radioligand [11C]carfentanil. Four TNP patients and eight gender and age-matched healthy controls were examined with PET. Patients with TNP showed reduced ΌOR BPND in the left nucleus accumbens (NAc), an area known to be involved in pain modulation and reward/aversive behaviors. In addition, the ΌOR BPND in the NAc was negatively correlated with the McGill sensory and total pain ratings in the TNP patients. Conclusions Our findings give preliminary evidence that the clinical pain in TNP patients can be related to alterations in the endogenous Ό-opioid system, rather than only to the peripheral pathology. The decreased availability of ΌORs found in TNP patients, and its inverse relationship to clinical pain levels, provide insights into the central mechanisms related to this condition. The results also expand our understanding about the impact of chronic pain on the limbic system.http://deepblue.lib.umich.edu/bitstream/2027.42/112555/1/12990_2012_Article_533.pd

    Classifying migraine using PET compressive big data analytics of brain’s ÎŒ-opioid and D2/D3 dopamine neurotransmission

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    Introduction: Migraine is a common and debilitating pain disorder associated with dysfunction of the central nervous system. Advanced magnetic resonance imaging (MRI) studies have reported relevant pathophysiologic states in migraine. However, its molecular mechanistic processes are still poorly understood in vivo. This study examined migraine patients with a novel machine learning (ML) method based on their central ÎŒ-opioid and dopamine D2/D3 profiles, the most critical neurotransmitters in the brain for pain perception and its cognitive-motivational interface.Methods: We employed compressive Big Data Analytics (CBDA) to identify migraineurs and healthy controls (HC) in a large positron emission tomography (PET) dataset. 198 PET volumes were obtained from 38 migraineurs and 23 HC during rest and thermal pain challenge. 61 subjects were scanned with the selective ÎŒ-opioid receptor (ÎŒOR) radiotracer [11C]Carfentanil, and 22 with the selective dopamine D2/D3 receptor (DOR) radiotracer [11C]Raclopride. PET scans were recast into a 1D array of 510,340 voxels with spatial and intensity filtering of non-displaceable binding potential (BPND), representing the receptor availability level. We then performed data reduction and CBDA to power rank the predictive brain voxels.Results: CBDA classified migraineurs from HC with accuracy, sensitivity, and specificity above 90% for whole-brain and region-of-interest (ROI) analyses. The most predictive ROIs for ÎŒOR were the insula (anterior), thalamus (pulvinar, medial-dorsal, and ventral lateral/posterior nuclei), and the putamen. The latter, putamen (anterior), was also the most predictive for migraine regarding DOR D2/D3 BPND levels.Discussion: CBDA of endogenous ÎŒ-opioid and D2/D3 dopamine dysfunctions in the brain can accurately identify a migraine patient based on their receptor availability across key sensory, motor, and motivational processing regions. Our ML-based findings in the migraineur’s brain neurotransmission partly explain the severe impact of migraine suffering and associated neuropsychiatric comorbidities

    Colocalized Structural and Functional Changes in the Cortex of Patients with Trigeminal Neuropathic Pain

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    Background: Recent data suggests that in chronic pain there are changes in gray matter consistent with decreased brain volume, indicating that the disease process may produce morphological changes in the brains of those affected. However, no study has evaluated cortical thickness in relation to specific functional changes in evoked pain. In this study we sought to investigate structural (gray matter thickness) and functional (blood oxygenation dependent level – BOLD) changes in cortical regions of precisely matched patients with chronic trigeminal neuropathic pain (TNP) affecting the right maxillary (V2) division of the trigeminal nerve. The model has a number of advantages including the evaluation of specific changes that can be mapped to known somatotopic anatomy. Methodology/Principal Findings: Cortical regions were chosen based on sensory (Somatosensory cortex (SI and SII), motor (MI) and posterior insula), or emotional (DLPFC, Frontal, Anterior Insula, Cingulate) processing of pain. Both structural and functional (to brush-induced allodynia) scans were obtained and averaged from two different imaging sessions separated by 2–6 months in all patients. Age and gender-matched healthy controls were also scanned twice for cortical thickness measurement. Changes in cortical thickness of TNP patients were frequently colocalized and correlated with functional allodynic activations, and included both cortical thickening and thinning in sensorimotor regions, and predominantly thinning in emotional regions. Conclusions: Overall, such patterns of cortical thickness suggest a dynamic functionally-driven plasticity of the brain. These structural changes, which correlated with the pain duration, age-at-onset, pain intensity and cortical activity, may be specific targets for evaluating therapeutic interventions

    Anatomical Alterations of the Visual Motion Processing Network in Migraine with and without Aura

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    BACKGROUND: Patients suffering from migraine with aura (MWA) and migraine without aura (MWoA) show abnormalities in visual motion perception during and between attacks. Whether this represents the consequences of structural changes in motion-processing networks in migraineurs is unknown. Moreover, the diagnosis of migraine relies on patient's history, and finding differences in the brain of migraineurs might help to contribute to basic research aimed at better understanding the pathophysiology of migraine. METHODS AND FINDINGS: To investigate a common potential anatomical basis for these disturbances, we used high-resolution cortical thickness measurement and diffusion tensor imaging (DTI) to examine the motion-processing network in 24 migraine patients (12 with MWA and 12 MWoA) and 15 age-matched healthy controls (HCs). We found increased cortical thickness of motion-processing visual areas MT+ and V3A in migraineurs compared to HCs. Cortical thickness increases were accompanied by abnormalities of the subjacent white matter. In addition, DTI revealed that migraineurs have alterations in superior colliculus and the lateral geniculate nucleus, which are also involved in visual processing. CONCLUSIONS: A structural abnormality in the network of motion-processing areas could account for, or be the result of, the cortical hyperexcitability observed in migraineurs. The finding in patients with both MWA and MWoA of thickness abnormalities in area V3A, previously described as a source in spreading changes involved in visual aura, raises the question as to whether a “silent” cortical spreading depression develops as well in MWoA. In addition, these experimental data may provide clinicians and researchers with a noninvasively acquirable migraine biomarker

    International study to evaluate PCR methods for detection of Trypanosoma cruzi DNA in blood samples from Chagas disease patients

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    A century after its discovery, Chagas disease, caused by the parasite Trypanosoma cruzi, still represents a major neglected tropical threat. Accurate diagnostics tools as well as surrogate markers of parasitological response to treatment are research priorities in the field. The polymerase chain reaction (PCR) has been proposed as a sensitive laboratory tool for detection of T. cruzi infection and monitoring of parasitological treatment outcome. However, high variation in accuracy and lack of international quality controls has precluded reliable applications in the clinical practice and comparisons of data among cohorts and geographical regions. In an effort towards harmonization of PCR strategies, 26 expert laboratories from 16 countries evaluated their current PCR procedures against sets of control samples, composed by serial dilutions of T.cruzi DNA from culture stocks belonging to different lineages, human blood spiked with parasite cells and blood samples from Chagas disease patients. A high variability in sensitivities and specificities was found among the 48 reported PCR tests. Out of them, four tests with best performance were selected and further evaluated. This study represents a crucial first step towards device of a standardized operative procedure for T. cruzi PCR.Fil: Schijman, Alejandro G. Instituto de Investigaciones en IngenierĂ­a GenĂ©tica y BiologĂ­a Molecular (INGEBI-CONICET). Laboratorio de BiologĂ­a Molecular de la Enfermedad de Chagas (LabMECh); Argentina.Fil: Bisio, Margarita. Instituto de Investigaciones en IngenierĂ­a GenĂ©tica y BiologĂ­a Molecular (INGEBI-CONICET). Laboratorio de BiologĂ­a Molecular de la Enfermedad de Chagas (LabMECh); Argentina.Fil: Orellana, Liliana. Universidad de Buenos Aires. Instituto de CĂĄlculo; Argentina.Fil: Sued, Mariela. Universidad de Buenos Aires. Instituto de CĂĄlculo; Argentina.Fil: Duffy, TomĂĄs. Instituto de Investigaciones en IngenierĂ­a GenĂ©tica y BiologĂ­a Molecular (INGEBI-CONICET). Laboratorio de BiologĂ­a Molecular de la Enfermedad de Chagas (LabMECh); Argentina.Fil: Mejia Jaramillo, Ana M. Universidad de Antioquia. Grupo Chagas; Colombia.Fil: Cura, Carolina. Instituto de Investigaciones en IngenierĂ­a GenĂ©tica y BiologĂ­a Molecular (INGEBI-CONICET). Laboratorio de BiologĂ­a Molecular de la Enfermedad de Chagas (LabMECh); Argentina.Fil: Auter, Frederic. French Blood Services; Francia.Fil: Veron, Vincent. Universidad de ParasitologĂ­a. Laboratorio Hospitalario; Guayana Francesa.Fil: Qvarnstrom, Yvonne. Centers for Disease Control. Department of Parasitic Diseases; Estados Unidos.Fil: Deborggraeve, Stijn. Institute of Tropical Medicine; BĂ©lgica.Fil: Hijar, Gisely. Instituto Nacional de Salud; PerĂș.Fil: Zulantay, InĂ©s. Facultad de Medicina; Chile.Fil: Lucero, RaĂșl Horacio. Universidad Nacional del Nordeste; Argentina.Fil: VelĂĄzquez, Elsa. ANLIS Dr.C.G.MalbrĂĄn. Instituto Nacional de ParasitologĂ­a Dr. Mario Fatala Chaben; Argentina.Fil: Tellez, Tatiana. Universidad Mayor de San Simon. Centro Universitario de Medicina Tropical; Bolivia.Fil: Sanchez Leon, Zunilda. Universidad Nacional de AsunciĂłn. Instituto de Investigaciones en Ciencias de la Salud; Paraguay.Fil: GalvĂŁo, Lucia. Faculdade de FarmĂĄcia; Brasil.Fil: Nolder, Debbie. Hospital for Tropical Diseases. London School of Tropical Medicine and Hygiene Department of Clinical Parasitology; Reino Unido.Fil: Monje Rumi, MarĂ­a. Universidad Nacional de Salta. Laboratorio de PatologĂ­a Experimental; Argentina.Fil: Levi, JosĂ© E. Hospital Sirio LibanĂȘs. Blood Bank; Brasil.Fil: Ramirez, Juan D. Universidad de los Andes. Centro de Investigaciones en MicrobiologĂ­a y ParasitologĂ­a Tropical; Colombia.Fil: Zorrilla, Pilar. Instituto Pasteur; Uruguay.Fil: Flores, MarĂ­a. Instituto de Salud Carlos III. Centro de Mahahonda; España.Fil: Jercic, Maria I. Instituto Nacional De Salud. SecciĂłn ParasitologĂ­a; Chile.Fil: Crisante, Gladys. Universidad de los Andes. Centro de Investigaciones ParasitolĂłgicas J.F. Torrealba; Venezuela.Fil: Añez, NĂ©stor. Universidad de los Andes. Centro de Investigaciones ParasitolĂłgicas J.F. Torrealba; Venezuela.Fil: De Castro, Ana M. Universidade Federal de GoiĂĄs. Instituto de Patologia Tropical e SaĂșde PĂșblica (IPTSP); Brasil.Fil: Gonzalez, Clara I. Universidad Industrial de Santander. Grupo de InmunologĂ­a y EpidemiologĂ­a Molecular (GIEM); Colombia.Fil: Acosta Viana, Karla. Universidad AutĂłnoma de YucatĂĄn. Departamento de Biomedicina de Enfermedades Infecciosas y Parasitarias Laboratorio de BiologĂ­a Celular; MĂ©xico.Fil: Yachelini, Pedro. Universidad CatĂłlica de Santiago del Estero. Instituto de Biomedicina; Argentina.Fil: Torrico, Faustino. Universidad Mayor de San Simon. Centro Universitario de Medicina Tropical; Bolivia.Fil: Robello, Carlos. Instituto Pasteur; Uruguay.Fil: Diosque, Patricio. Universidad Nacional de Salta. Laboratorio de PatologĂ­a Experimental; Argentina.Fil: Triana Chavez, Omar. Universidad de Antioquia. Grupo Chagas; Colombia.Fil: Aznar, Christine. Universidad de ParasitologĂ­a. Laboratorio Hospitalario; Guayana Francesa.Fil: Russomando, Graciela. Universidad Nacional de AsunciĂłn. Instituto de Investigaciones en Ciencias de la Salud; Paraguay.Fil: BĂŒscher, Philippe. Institute of Tropical Medicine; BĂ©lgica.Fil: Assal, Azzedine. French Blood Services; Francia.Fil: Guhl, Felipe. Universidad de los Andes. Centro de Investigaciones en MicrobiologĂ­a y ParasitologĂ­a Tropical; Colombia.Fil: Sosa Estani, Sergio. ANLIS Dr.C.G.MalbrĂĄn. Centro Nacional de DiagnĂłstico e InvestigaciĂłn en Endemo-Epidemias; Argentina.Fil: DaSilva, Alexandre. Centers for Disease Control. Department of Parasitic Diseases; Estados Unidos.Fil: Britto, Constança. Instituto Oswaldo Cruz/FIOCRUZ. LaboratĂłrio de Biologia Molecular e Doenças EndĂȘmicas; Brasil.Fil: Luquetti, Alejandro. LaboratĂłrio de Pesquisa de Doença de Chagas; Brasil.Fil: Ladzins, Janis. World Health Organization (WHO). Special Programme for Research and Training in Tropical Diseases (TDR); Suiza

    International Study to Evaluate PCR Methods for Detection of Trypanosoma cruzi DNA in Blood Samples from Chagas Disease Patients

    Get PDF
    A century after its discovery, Chagas disease, caused by the parasite Trypanosoma cruzi, still represents a major neglected tropical threat. Accurate diagnostics tools as well as surrogate markers of parasitological response to treatment are research priorities in the field. The polymerase chain reaction (PCR) has been proposed as a sensitive laboratory tool for detection of T. cruzi infection and monitoring of parasitological treatment outcome. However, high variation in accuracy and lack of international quality controls has precluded reliable applications in the clinical practice and comparisons of data among cohorts and geographical regions. In an effort towards harmonization of PCR strategies, 26 expert laboratories from 16 countries evaluated their current PCR procedures against sets of control samples, composed by serial dilutions of T.cruzi DNA from culture stocks belonging to different lineages, human blood spiked with parasite cells and blood samples from Chagas disease patients. A high variability in sensitivities and specificities was found among the 48 reported PCR tests. Out of them, four tests with best performance were selected and further evaluated. This study represents a crucial first step towards device of a standardized operative procedure for T. cruzi PCR

    Ordered patterning of the sensory system is susceptible to stochastic features of gene expression

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    Sensory neuron numbers and positions are precisely organized to accurately map environmental signals in the brain. This precision emerges from biochemical processes within and between cells that are inherently stochastic. We investigated impact of stochastic gene expression on pattern formation, focusing on senseless (sens), a key determinant of sensory fate in Drosophila. Perturbing microRNA regulation or genomic location of sens produced distinct noise signatures. Noise was greatly enhanced when both sens alleles were present in homologous loci such that each allele was regulated in trans by the other allele. This led to disordered patterning. In contrast, loss of microRNA repression of sens increased protein abundance but not sensory pattern disorder. This suggests that gene expression stochasticity is a critical feature that must be constrained during development to allow rapid yet accurate cell fate resolution
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