973 resultados para Brain Activation Pattern


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Objectives. Emotional dysregulation in bipolar disorder is thought to arise from dysfunction within prefrontal cortical regions involved in cognitive control coupled with increased or aberrant activation within regions engaged in emotional processing. The aim of this study was to determine the common and distinct patterns of functional brain abnormalities during reward and working memory processing in patients with bipolar disorder. Methods. Participants were 36 euthymic bipolar disorder patients and 37 healthy comparison subjects matched for age, sex and IQ. Functional magnetic resonance imaging (fMRI) was conducted during the Iowa Gambling Task (IGT) and the n-back working memory task. Results. During both tasks, patients with bipolar disorder demonstrated a pattern of inefficient engagement within the ventral frontopolar prefrontal cortex with evidence of segregation along the medial-lateral dimension for reward and working memory processing, respectively. Moreover, patients also showed greater activation in the anterior cingulate cortex during the Iowa Gambling Task and in the insula during the n-back task. Conclusions. Our data implicate ventral frontopolar dysfunction as a core abnormality underpinning bipolar disorder and confirm that overactivation in regions involved in emotional arousal is present even in tasks that do not typically engage emotional systems. © 2012 Informa Healthcare.

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Background - When a moving stimulus and a briefly flashed static stimulus are physically aligned in space the static stimulus is perceived as lagging behind the moving stimulus. This vastly replicated phenomenon is known as the Flash-Lag Effect (FLE). For the first time we employed biological motion as the moving stimulus, which is important for two reasons. Firstly, biological motion is processed by visual as well as somatosensory brain areas, which makes it a prime candidate for elucidating the interplay between the two systems with respect to the FLE. Secondly, discussions about the mechanisms of the FLE tend to recur to evolutionary arguments, while most studies employ highly artificial stimuli with constant velocities. Methodology/Principal Finding - Since biological motion is ecologically valid it follows complex patterns with changing velocity. We therefore compared biological to symbolic motion with the same acceleration profile. Our results with 16 observers revealed a qualitatively different pattern for biological compared to symbolic motion and this pattern was predicted by the characteristics of motor resonance: The amount of anticipatory processing of perceived actions based on the induced perspective and agency modulated the FLE. Conclusions/Significance - Our study provides first evidence for an FLE with non-linear motion in general and with biological motion in particular. Our results suggest that predictive coding within the sensorimotor system alone cannot explain the FLE. Our findings are compatible with visual prediction (Nijhawan, 2008) which assumes that extrapolated motion representations within the visual system generate the FLE. These representations are modulated by sudden visual input (e.g. offset signals) or by input from other systems (e.g. sensorimotor) that can boost or attenuate overshooting representations in accordance with biased neural competition (Desimone & Duncan, 1995).

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Much of the research on visual hallucinations (VHs) has been conducted in the context of eye disease and neurodegenerative conditions, but little is known about these phenomena in psychiatric and nonclinical populations. The purpose of this article is to bring together current knowledge regarding VHs in the psychosis phenotype and contrast this data with the literature drawn from neurodegenerative disorders and eye disease. The evidence challenges the traditional views that VHs are atypical or uncommon in psychosis. The weighted mean for VHs is 27% in schizophrenia, 15% in affective psychosis, and 7.3% in the general community. VHs are linked to a more severe psychopathological profile and less favorable outcome in psychosis and neurodegenerative conditions. VHs typically co-occur with auditory hallucinations, suggesting a common etiological cause. VHs in psychosis are also remarkably complex, negative in content, and are interpreted to have personal relevance. The cognitive mechanisms of VHs in psychosis have rarely been investigated, but existing studies point to source-monitoring deficits and distortions in top-down mechanisms, although evidence for visual processing deficits, which feature strongly in the organic literature, is lacking. Brain imaging studies point to the activation of visual cortex during hallucinations on a background of structural and connectivity changes within wider brain networks. The relationship between VHs in psychosis, eye disease, and neurodegeneration remains unclear, although the pattern of similarities and differences described in this review suggests that comparative studies may have potentially important clinical and theoretical implications. © 2014 The Author.

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The gamma-aminobutyric acid (GABA) metabolite gamma-hydroxybutyric acid (GHB) shows a variety of behavioural effects when administered to animals and humans, including reward/addiction properties and absence seizures. At the cellular level, these actions of GHB are mediated by activation of neuronal GABAB receptors (GABABRs) where it acts as a weak agonist. Because astrocytes respond to endogenous and exogenously applied GABA by activation of both GABAA and GABABRs, here we investigated the action of GHB on astrocytes on the ventral tegmental area (VTA) and the ventrobasal (VB) thalamic nucleus, two brain areas involved in the reward and proepileptic action of GHB, respectively, and compared it with that of the potent GABABR agonist baclofen. We found that GHB and baclofen elicited dose-dependent (ED50: 1.6 mM and 1.3 µM, respectively) transient increases in intracellular Ca2+ in VTA and VB astrocytes of young mice and rats, which were accounted for by activation of their GABABRs and mediated by Ca2+ release from intracellular store release. In contrast, prolonged GHB and baclofen exposure caused a reduction in spontaneous astrocyte activity and glutamate release from VTA astrocytes. These findings have key (patho)physiological implications for our understanding of the addictive and proepileptic actions of GHB.

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We describe the case of a dysgraphic aphasic individual-S.G.W.-who, in writing to dictation, produced high rates of formally related errors consisting of both lexical substitutions and what we call morphological-compound errors involving legal or illegal combinations of morphemes. These errors were produced in the context of a minimal number of semantic errors. We could exclude problems with phonological discrimination and phonological short-term memory. We also excluded rapid decay of lexical information and/or weak activation of word forms and letter representations since S.G.W.'s spelling showed no effect of delay and no consistent length effects, but, instead, paradoxical complexity effects with segmental, lexical, and morphological errors that were more complex than the target. The case of S.G.W. strongly resembles that of another dysgraphic individual reported in the literature-D.W.-suggesting that this pattern of errors can be replicated across patients. In particular, both patients show unusual errors resulting in the production of neologistic compounds (e.g., "bed button" in response to "bed"). These patterns can be explained if we accept two claims: (a) Brain damage can produce both a reduction and an increase in lexical activation; and (b) there are direct connections between phonological and orthographic lexical representations (a third spelling route). We suggest that both patients are suffering from a difficulty of lexical selection resulting from excessive activation of formally related lexical representations. This hypothesis is strongly supported by S.G.W.'s worse performance in spelling to dictation than in written naming, which shows that a phonological input, activating a cohort of formally related lexical representations, increases selection difficulties. © 2014 Taylor & Francis.

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Interaction engineering is fundamental for agent based systems. In this paper we will present a design pattern for the core of a multi-agent platform - the message communication and behavior activation mechanisms - using language features of C#. An agent platform is developed based on the pattern structure, which is legiti- mated through experiences of using JADE in real applications. Results of the communication model are compared against the popular JADE platform.

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Many studies have assessed the neural underpinnings of creativity, failing to find a clear anatomical localization. We aimed to provide evidence for a multi-componential neural system for creativity. We applied a general activation likelihood estimation (ALE) meta-analysis to 45 fMRI studies. Three individual ALE analyses were performed to assess creativity in different cognitive domains (Musical, Verbal, and Visuo-spatial). The general ALE revealed that creativity relies on clusters of activations in the bilateral occipital, parietal, frontal, and temporal lobes. The individual ALE revealed different maximal activation in different domains. Musical creativity yields activations in the bilateral medial frontal gyrus, in the left cingulate gyrus, middle frontal gyrus, and inferior parietal lobule and in the right postcentral and fusiform gyri. Verbal creativity yields activations mainly located in the left hemisphere, in the prefrontal cortex, middle and superior temporal gyri, inferior parietal lobule, postcentral and supramarginal gyri, middle occipital gyrus, and insula. The right inferior frontal gyrus and the lingual gyrus were also activated. Visuo-spatial creativity activates the right middle and inferior frontal gyri, the bilateral thalamus and the left precentral gyrus. This evidence suggests that creativity relies on multi-componential neural networks and that different creativity domains depend on different brain regions.

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Auditory sensory gating (ASG) is the ability in individuals to suppress incoming irrelevant sensory input, indexed by evoked response to paired auditory stimuli. ASG is impaired in psychopathology such as schizophrenia, in which it has been proposed as putative endophenotype. This study aims to characterise electrophysiological properties of the phenomenon using MEG in time and frequency domains as well as to localise putative networks involved in the process at both sensor and source level. We also investigated the relationship between ASG measures and personality profiles in healthy participants in the light of its candidate endophenotype role in psychiatric disorders. Auditory evoked magnetic fields were recorded in twenty seven healthy participants by P50 ‘paired-click’ paradigm presented in pairs (conditioning stimulus S1- testing stimulus S2) at 80dB, separated by 250msec with inter trial interval of 7-10 seconds. Gating ratio in healthy adults ranged from 0.5 to 0.8 suggesting dimensional nature of P50 ASG. The brain regions active during this process were bilateral superior temporal gyrus (STG) and bilateral inferior frontal gyrus (IFG); activation was significantly stronger in IFG during S2 as compared to S1 (at p<0.05). Measures of effective connectivity between these regions using DCM modelling revealed the role of frontal cortex in modulating ASG as suggested by intracranial studies, indicating major role of inhibitory interneuron connections. Findings from this study identified a unique event-related oscillatory pattern for P50 ASG with alpha (STG)-beta (IFG) desynchronization and increase in cortical oscillatory gamma power (IFG) during S2 condition as compared to S1. These findings show that the main generator for P50 response is within temporal lobe and that inhibitory interneurons and gamma oscillations in the frontal cortex contributes substantially towards sensory gating. Our findings also show that ASG is a predictor of personality profiles (introvert vs extrovert dimension).

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Learning and memory in adult females decline during menopause and estrogen replacement therapy is commonly prescribed during menopause. Post-menopausal women tend to suffer from depression and are prescribed antidepressants – in addition to hormone therapy. Estrogen replacement therapy is a topic that engenders debate since several studies contradict its efficacy as a palliative therapy for cognitive decline and neurodegenerative diseases. Signaling transduction pathways can alter brain cell activity, survival, and morphology by facilitating transcription factor DNA binding and protein production. The steroidal hormone estrogen and the anti-depressant drug lithium interact through these signaling transduction pathways facilitating transcription factor activation. The paucity of data on how combined hormones and antidepressants interact in regulating gene expression led me to hypothesize that in primary mixed brain cell cultures, combined 17β-estradiol (E2) and lithium chloride (LiCl) (E2/LiCl) will alter genetic expression of markers involved in synaptic plasticity and neuroprotection. Results from these studies indicated that a 48 h treatment of E2/LiCl reduced glutamate receptor subunit genetic expression, but increased neurotrophic factor and estrogen receptor genetic expression. Combined treatment also failed to protect brain cell cultures from glutamate excitotoxicity. If lithium facilitates protein signaling pathways mediated by estrogen, can lithium alone serve as a palliative treatment for post-menopause? This question led me to hypothesize that in estrogen-deficient mice, lithium alone will increase episodic memory (tested via object recognition), and enhance expression in the brain of factors involved in anti-apoptosis, learning and memory. I used bilaterally ovariectomized (bOVX) C57BL/6J mice treated with LiCl for one month. Results indicated that LiCl-treated bOVX mice increased performance in object recognition compared with non-treated bOVX. Increased performance in LiCl-treated bOVX mice coincided with augmented genetic and protein expression in the brain. Understanding the molecular pathways of estrogen will assist in identifying a palliative therapy for menopause-related dementia, and lithium may serve this purpose by acting as a selective estrogen-mediated signaling modulator.

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Learning and memory in adult females decline during menopause and estrogen replacement therapy is commonly prescribed during menopause. Post-menopausal women tend to suffer from depression and are prescribed antidepressants – in addition to hormone therapy. Estrogen replacement therapy is a topic that engenders debate since several studies contradict its efficacy as a palliative therapy for cognitive decline and neurodegenerative diseases. Signaling transduction pathways can alter brain cell activity, survival, and morphology by facilitating transcription factor DNA binding and protein production. The steroidal hormone estrogen and the anti-depressant drug lithium interact through these signaling transduction pathways facilitating transcription factor activation. The paucity of data on how combined hormones and antidepressants interact in regulating gene expression led me to hypothesize that in primary mixed brain cell cultures, combined 17beta-estradiol (E2) and lithium chloride (LiCl) (E2/LiCl) will alter genetic expression of markers involved in synaptic plasticity and neuroprotection. Results from these studies indicated that a 48 h treatment of E2/LiCl reduced glutamate receptor subunit genetic expression, but increased neurotrophic factor and estrogen receptor genetic expression. Combined treatment also failed to protect brain cell cultures from glutamate excitotoxicity. If lithium facilitates protein signaling pathways mediated by estrogen, can lithium alone serve as a palliative treatment for post-menopause? This question led me to hypothesize that in estrogen-deficient mice, lithium alone will increase episodic memory (tested via object recognition), and enhance expression in the brain of factors involved in anti-apoptosis, learning and memory. I used bilaterally ovariectomized (bOVX) C57BL/6J mice treated with LiCl for one month. Results indicated that LiCl-treated bOVX mice increased performance in object recognition compared with non-treated bOVX. Increased performance in LiCl-treated bOVX mice coincided with augmented genetic and protein expression in the brain. Understanding the molecular pathways of estrogen will assist in identifying a palliative therapy for menopause-related dementia, and lithium may serve this purpose by acting as a selective estrogen-mediated signaling modulator.

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How experience alters neuronal ensemble dynamics and how locus coeruleus-mediated norepinephrine release facilitates memory formation in the brain are the topics of this thesis. Here we employed a visualization technique, cellular compartment analysis of temporal activity by fluorescence in situ hybridization (catFISH), to assess activation patterns of neuronal ensembles in the olfactory bulb (OB) and anterior piriform cortex (aPC) to repeated odor inputs. Two associative learning models were used, early odor preference learning in rat pups and adult rat go-no-go odor discrimination learning. With catFISH of an immediate early gene, Arc, we showed that odor representation in the OB and aPC was sparse (~5-10%) and widely distributed. Odor associative learning enhanced the stability of the rewarded odor representation in the OB and aPC. The stable component, indexed by the overlap between the two ensembles activated by the rewarded odor at two time points, increased from ~25% to ~50% (p = 0.004-1.43E⁻4; Chapter 3 and 4). Adult odor discrimination learning promoted pattern separation between rewarded and unrewarded odor representations in the aPC. The overlap between rewarded and unrewarded odor representations reduced from ~25% to ~14% (p = 2.28E⁻⁵). However, learning an odor mixture as a rewarded odor increased the overlap of the component odor representations in the aPC from ~23% to ~44% (p = 0.010; Chapter 4). Blocking both α- and β-adrenoreceptors in the aPC prevented highly similar odor discrimination learning in adult rats, and reduced OB mitral and granule ensemble stability to the rewarded odor. Similar treatment in the OB only slowed odor discrimination learning. However, OB adrenoceptor blockade disrupted pattern separation and ensemble stability in the aPC when the rats demonstrated deficiency in discrimination (Chapter 5). In another project, the role of α₂-adrenoreceptors in the OB during early odor preference learning was studied. OB α2-adrenoceptor activation was necessary for odor learning in rat pups. α₂-adrenoceptor activation was additive with β-adrenoceptor mediated signalling to promote learning (Chapter 2). Together, these experiments suggest that odor representations are highly adaptive at the early stages of odor processing. The OB and aPC work in concert to support odor learning and top-down adrenergic input exerts a powerful modulation on both learning and odor representation.

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This work studied the drying kinetics of the organic fractions of municipal solid waste (MSW) samples with different initial moisture contents and presented a new method for determination of drying kinetic parameters. A series of drying experiments at different temperatures were performed by using a thermogravimetric technique. Based on the modified Page drying model and the general pattern search method, a new drying kinetic method was developed using multiple isothermal drying curves simultaneously. The new method fitted the experimental data more accurately than the traditional method. Drying kinetic behaviors under extrapolated conditions were also predicted and validated. The new method indicated that the drying activation energies for the samples with initial moisture contents of 31.1 and 17.2 % on wet basis were 25.97 and 24.73 kJ mol−1. These results are useful for drying process simulation and industrial dryer design. This new method can be also applied to determine the drying parameters of other materials with high reliability.

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Background: Increased impulsivity and aberrant response inhibition have been observed in bipolar disorder (BD). This study examined the functional abnormalities and underlying neural processes during response inhibition in BD, and its relationship to impulsivity. Methods: We assessed impulsivity using the Barratt Impulsiveness Scale (BIS) and, using functional magnetic resonance imaging (fMRI), measured neural activity in response to an Affective Go-NoGo Task, consisting of emotional facial stimuli (fear, happy, anger faces) and non-emotional control stimuli (neutral female and male faces) in euthymic BD (n=23) and healthy individuals (HI; n=25). Results: BD patients were significantly more impulsive, yet did not differ from HI on accuracy or reaction time on the emotional go/no-go task. Comparing neural patterns of activation when processing emotional Go versus emotional NoGo trials yielded increased activation in BD within temporal and cingulate cortices and within prefrontal-cortical regions in HI. Furthermore, higher BIS scores for BD were associated with slower reaction times, and indicative of compensatory cognitive strategies to counter increased impulsivity. Conclusions: These findings illustrate cognition-emotion interference in BD and the observed differences in neural activation indicate potentially altered emotion modulation. Increased activation in brain regions previously shown in emotion regulation and response inhibition tasks could represent a disease-specific marker for BD

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Background: Identifying biological markers to aid diagnosis of bipolar disorder (BD) is critically important. To be considered a possible biological marker, neural patterns in BD should be discriminant from those in healthy individuals (HI). We examined patterns of neuromagnetic responses revealed by magnetoencephalography (MEG) during implicit emotion-processing using emotional (happy, fearful, sad) and neutral facial expressions, in sixteen BD and sixteen age- and gender-matched healthy individuals. Methods: Neuromagnetic data were recorded using a 306-channel whole-head MEG ELEKTA Neuromag System, and preprocessed using Signal Space Separation as implemented in MaxFilter (ELEKTA). Custom Matlab programs removed EOG and ECG signals from filtered MEG data, and computed means of epoched data (0-250ms, 250-500ms, 500-750ms). A generalized linear model with three factors (individual, emotion intensity and time) compared BD and HI. A principal component analysis of normalized mean channel data in selected brain regions identified principal components that explained 95% of data variation. These components were used in a quadratic support vector machine (SVM) pattern classifier. SVM classifier performance was assessed using the leave-one-out approach. Results: BD and HI showed significantly different patterns of activation for 0-250ms within both left occipital and temporal regions, specifically for neutral facial expressions. PCA analysis revealed significant differences between BD and HI for mild fearful, happy, and sad facial expressions within 250-500ms. SVM quadratic classifier showed greatest accuracy (84%) and sensitivity (92%) for neutral faces, in left occipital regions within 500-750ms. Conclusions: MEG responses may be used in the search for disease specific neural markers.

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We propose a mathematically well-founded approach for locating the source (initial state) of density functions evolved within a nonlinear reaction-diffusion model. The reconstruction of the initial source is an ill-posed inverse problem since the solution is highly unstable with respect to measurement noise. To address this instability problem, we introduce a regularization procedure based on the nonlinear Landweber method for the stable determination of the source location. This amounts to solving a sequence of well-posed forward reaction-diffusion problems. The developed framework is general, and as a special instance we consider the problem of source localization of brain tumors. We show numerically that the source of the initial densities of tumor cells are reconstructed well on both imaging data consisting of simple and complex geometric structures.