18 research outputs found

    Role of Basal Ganglia Circuits in Resisting Interference by Distracters: A swLORETA Study

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    BACKGROUND: The selection of task-relevant information requires both the focalization of attention on the task and resistance to interference from irrelevant stimuli. Both mechanisms rely on a dorsal frontoparietal network, while focalization additionally involves a ventral frontoparietal network. The role of subcortical structures in attention is less clear, despite the fact that the striatum interacts significantly with the frontal cortex via frontostriatal loops. One means of investigating the basal ganglia's contributions to attention is to examine the features of P300 components (i.e. amplitude, latency, and generators) in patients with basal ganglia damage (such as in Parkinson's disease (PD), in which attention is often impaired). Three-stimulus oddball paradigms can be used to study distracter-elicited and target-elicited P300 subcomponents. METHODOLOGY/PRINCIPAL FINDINGS: In order to compare distracter- and target-elicited P300 components, high-density (128-channel) electroencephalograms were recorded during a three-stimulus visual oddball paradigm in 15 patients with early PD and 15 matched healthy controls. For each subject, the P300 sources were localized using standardized weighted low-resolution electromagnetic tomography (swLORETA). Comparative analyses (one-sample and two-sample t-tests) were performed using SPM5® software. The swLORETA analyses showed that PD patients displayed fewer dorsolateral prefrontal (DLPF) distracter-P300 generators but no significant differences in target-elicited P300 sources; this suggests dysfunction of the DLPF cortex when the executive frontostriatal loop is disrupted by basal ganglia damage. CONCLUSIONS/SIGNIFICANCE: Our results suggest that the cortical attention frontoparietal networks (mainly the dorsal one) are modulated by the basal ganglia. Disruption of this network in PD impairs resistance to distracters, which results in attention disorders

    A psycho-physiological approach of attention disorders in parkinson's didsease

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    La Maladie de Parkinson (MP) est une maladie neuro-dégénérative fréquente, caractérisée par une déplétion dopaminergique striatale. Elle s'accompagne précocement de troubles cognitifs, notamment attentionnels, dont l’origine reste imprécise. Deux hypothèses sont évoquées : un déficit du contrôle volontaire de l'attention vers la tâche en cours (processus de type « top-down » (TD)) ou un défaut d’inhibition des informations non pertinentes pour la tâche (par défaillance de processus de type « bottom-up » (BU)). Les processus attentionnels, souvent explorés par la mesure de variables comportementales, peuvent également bénéficier de l'enregistrement des composantes N200 et P300 des potentiels évoqués cognitifs (PEC). La P300 comprend deux sous-composantes : (1) la P3a, survenant préférentiellement après un distracteur, reflétant un traitement BU ; (2) la P3b, associée à la détection de cibles et reflétant un traitement TD. La N200 se décompose en une « no-go-N2 » antérieure, impliquée dans la détection de la déviance et les mécanismes d’inhibition et une « go-N2 » postérieure, engagée dans les processus de catégorisation des cibles. Dans la MP, ces composantes ont le plus souvent une latence allongée et une amplitude réduite. La modification des générateurs des PEC dans la MP n’a, à notre connaissance, jamais été explorée. L’objectif de cette thèse est de préciser les mécanismes sous-jacents aux troubles attentionnels dans la MP. En cas de dysfonctionnement TD, les réseaux impliqués dans la genèse de la P3b et/ou de la N200 postérieure pourraient être altérés. Si une dysfonction BU en est à l’origine, les générateurs de la P3a et/ou de la N200 antérieure devraient être modifiés. Nous avons enregistré en haute résolution les PEC de 15 sujets sains jeunes, au cours d’un paradigme « oddball » visuel à trois stimulus afin d’étudier les générateurs des PEC chez le sujet sain. Le même enregistrement a ensuite été effectué chez 15 sujets atteints d’une MP comparés à 15 sujets appariés. Les latences et amplitudes des composantes des PEC ont été comparées au moyen d’analyses de variance. L’exploration des générateurs des PEC a été effectuée pour chaque sujet et dans chaque condition au moyen d’une méthode distribuée d’analyse de source, swLORETA (standardized weighted low resolution tomography). Les analyses statistiques de groupes des générateurs de la P300 ont été effectuées au moyen du logiciel SPM, celles de la N200 au moyen de méthodes de permutations. Chez les sujets jeunes, le réseau fronto-pariétal dorsal (FPD) apparaît impliqué dans la genèse des deux composantes de la P300, le réseau fronto-pariétal ventral étant spécifique du traitement de la cible. L’étude des générateurs de la N200 a mis en évidence le rôle prépondérant du cortex cingulaire antérieur (CCA) en interaction avec les réseaux fronto-pariétaux, le precuneus et le cortex cingulaire postérieur. Dans la MP, il existait une réduction des sources de la P300 générée par le distracteur au niveau du cortex dorsolatéral préfrontal (DLPF) appartenant au réseau FPD, en lien avec une augmentation des fausses alarmes aux distracteurs chez les patients, en faveur d'une défaillance des processus BU dans la MP. Une diminution des sources de la N200 a également été constatée au niveau du cortex DLPF et du CCA, dans toutes les conditions. Ceci suggère un dysfonctionnement de ces deux régions dès le stade précoce des processus attentionnels, seul le fonctionnement du cortex DLPF restant altéré spécifiquement dans le traitement des distracteurs lors des étapes ultérieures de traitement de l’information. Ces anomalies résultent probablement du dérèglement des boucles baso-corticales reliant le striatum associatif au cortex DLPF et CCA. Ceci entrainerait une altération du contrôle cognitif et des processus BU responsable d’anomalies de détection de la déviance et d'inhibition des stimulus non pertinents, sous-jacentes aux troubles de l’attention sélective dans la MP.Parkinson’s disease (PD) is a frequent neurodegenerative disease which is responsible for striatal dopaminergic depletion. PD patients present an early cognitive impairment, particularly attentional disorders. The origin of this impairment is still debated. It could result from a reduced allocation of attentional resources to the ongoing task (“top-down” process (TD)) or a defective inhibition of irrelevant events (failure of “bottom-up” filtering process (BU). Investigation of attentional processes mostly rely on behavioral analysis, but the study of the N200 and P300 components of the cognitive event-related potentials (ERPs) may be of interest. P300 can be divided into two subcomponents: (1) P3a, which occurs preferentially after distracter stimuli and is associated with BU processes; (2) P3b, related to target detection and associated with TD mechanisms. The N200 also comprises two main components: an anterior “no-go-N2", involved in mismatch detection and inhibition mechanisms, and a posterior “go-N2”, related to target categorization processes. Most of previous studies in PD have shown a longer latency and reduced amplitude of N200 and P300. To the best of our knowledge, modulation of their generators in PD has never been investigated. The main aim of this work was to improve our knowledge of the mechanisms of attention disorders in PD. If the attentional impairment in PD results from a failure of TD processes, this would result in modifications of the networks underlying the P3b and/or the posterior N2 during target detection. Alternatively, if this disorder is consecutive to a failure of BU processes, this would lead to difficulty in resisting interference from distracter stimuli and would change the characteristics of the P3a and/or anterior N200. ERPs were recorded in 15 young healthy subjects with high resolution electroencephalography during a three stimuli oddball paradigm in order to localize N200 and P300 generators in healthy subjects. Then, they were recorded with the same procedure in 15 patients with PD and 15 matched healthy controls. Group comparisons of the ERPs latency and amplitude were performed with analyses of variance. Generators of the ERPs components were identified for each subject and in each condition with a distributed source localization method, swLORETA (standardized weighted low resolution tomography). Group analyses of swLORETA solutions were performed with SPM® for the P300 subcomponents and with a permutation method for the N200. In young healthy controls, we showed an involvement of the dorsal frontoparietal (DFP) network in both P3a and P3b generation, while the ventral frontoparietal network was specific to target processing. The anterior cingulate cortex (ACC) that interacts with the frontoparietal networks, had a preponderant role in N200 generation. Other areas, namely the precuneus and the posterior cingulate cortex, which are connected to the ACC, are specific generators of some of the N200 subcomponents. In PD, a reduction of distracter-elicited P300 generators was found in the dorsolateral prefrontal cortex (DLPF), which is part of the DFP network, accordingly with an increased commission rate for distracter stimuli. These results suggest a failure of BU processes in PD. A reduced number of N200 generators was also displayed in both DLPF and ACC whatever the stimulus. This suggests a dysfunction of both the DLPF and the ACC at an early stage of attentional processes in PD, while only distracter processing was later impaired, in relation with a DLPF dysfunction. These abnormalities probably result from disturbances of the basocortical loops that link the associative striatum to the DLPF and ACC. This would then produce a sustainable alteration of cognitive control and BU processes, responsible for abnormal mismatch detection and inhibition of irrelevant stimuli, which would underlie the selective attention impairment in PD

    Effects of stimulus-driven and goal-directed attention on prepulse inhibition of brain oscillations

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    Objective: Prepulse inhibition (PPI) is an operational measure of sensory gating. PPI of cortical response to a startling pulse is known to be modulated by attention. With a time-frequency analysis, we sought to determine whether goal-directed and stimulus-driven attention differentially modulate inhibition of cortical oscillations elicited by a startling pulse. Methods: An electroencephalogram was recorded in 26 healthy controls performing an active acoustic PPI paradigm. Startling stimuli were presented alone or either 400 or 1000 ms after one of three types of visual prepulse: to-be-attended (goal-directed attention), unexpected (stimulus-driven attention) or to-be-ignored (non-focused attention). We calculated the percentage PPI for the auditory event-related spectral perturbation (ERSP) of theta (4-7 Hz), alpha (8-12 Hz), beta1 (13-20 Hz) and beta2 (20-30 Hz) oscillations and changes in inter-trial coherence (ITC), a measure of phase synchronization of electroencephalographic activity.Results: At 400 ms, (i) PPI of the ERSP of alpha, theta and beta1 oscillation was greater after an unexpected and a to-be-attended prepulse than after a to-be-ignored prepulse, and (ii) PPI of beta2 oscillations was greater after a to-be-attended than a to-be-ignored prepulse. At 1000 ms, (i) PPI of alpha oscillations was greater after an unexpected and a to-be-attended prepulse than after a to-be-ignored prepulse, and (ii) PPI of beta1 oscillations was greater after a to-be-attended than a to-be-ignored prepulse. The ITC values did not vary according to the type of prepulse.Conclusions: In an active PPI paradigm, stimulus-driven and goal-directed attention each have differential effects on the modulation of cortical oscillations

    Impaired Early Attentional Processes in Parkinson’s Disease: A High-Resolution Event-Related Potentials Study

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    <div><p>Introduction</p><p>The selection of task-relevant information requires both the focalization of attention on the task and resistance to interference from irrelevant stimuli. A previous study using the P3 component of the event-related potentials suggested that a reduced ability to resist interference could be responsible for attention disorders at early stages of Parkinson’s disease (PD), with a possible role of the dorsolateral prefrontal cortex (DLPFC).</p><p>Methods</p><p>Our objective was to better determine the origin of this impairment, by studying an earlier ERP component, the N2, and its subcomponents, as they reflect early inhibition processes and as they are known to have sources in the anterior cingulate cortex (ACC), which is involved together with the DLPFC in inhibition processes. Fifteen early-stage PD patients and 15 healthy controls (HCs) performed a three-stimulus visual oddball paradigm, consisting in detecting target inputs amongst standard stimuli, while resisting interference from distracter ones. A 128-channel electroencephalogram was recorded during this task and the generators of the N2 subcomponents were identified using standardized weighted low-resolution electromagnetic tomography (swLORETA).</p><p>Results</p><p>PD patients displayed fewer N2 generators than HCs in both the DLPFC and the ACC, for all types of stimuli. In contrast to controls, PD patients did not show any differences between their generators for different N2 subcomponents.</p><p>Conclusion</p><p>Our data suggest that impaired inhibition in PD results from dysfunction of the DLPFC and the ACC during the early stages of attentional processes.</p></div

    Clinical and demographic features of the Parkinson's disease (PD) patients and healthy controls.

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    <p>Mean (standard deviation). p values were determined in t-tests (except for the gender ratio, to which a χ<sup>2</sup> test was applied).</p><p>Clinical and demographic features of the Parkinson's disease (PD) patients and healthy controls.</p

    Statistical maps of the N2 components' grey matter current density obtained with swLORETA (Parkinson’s disease patients).

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    <p>Identification of N2 generators for standard-elicited (3A), distracter-elicited (3B) and target-elicited (3C) N2 components (p<0.001).</p

    Between-group statistical maps of the N200 components' grey matter current densities, with the permutation method (p<0.05).

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    <p>Top panel (4A-C): healthy controls vs. PD patients (4A: standard N200, 4B: distracter N200, 4C: target N200). Bottom panel (4D-F): PD patients vs. healthy controls (4D: standard N2, 4E: distracter N2, 4F: target N2).</p
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