115 resultados para Functional-cognitive approach


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Two factors that have been suggested as key in explaining individual differences in fluid intelligence are working memory and sensory discrimination ability. A latent variable approach was used to explore the relative contributions of these two variables to individual differences in fluid intelligence in middle to late childhood. A sample of 263 children aged 7–12 years was examined. Correlational analyses showed that general discrimination ability (GDA)and working memory (WM) were related to each other and to fluid intelligence. Structural equation modeling showed that within both younger and older age groups and the sample as a whole, the relation between GDA and fluid intelligence could be accounted for by WM. While WM was able to predict variance in fluid intelligence above and beyond GDA, GDA was not able to explain significant amounts of variance in fluid intelligence, either in the whole sample or within the younger or older age group. We concluded that compared to GDA, WM should be considered the better predictor of individual differences in fluid intelligence in childhood. WM and fluid intelligence, while not being separable in middle childhood, develop at different rates, becoming more separable with age.

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CONTEXT Although open radical cystectomy (ORC) is still the standard approach, laparoscopic radical cystectomy (LRC) and robot-assisted radical cystectomy (RARC) are increasingly performed. OBJECTIVE To report on a systematic literature review and cumulative analysis of pathologic, oncologic, and functional outcomes of RARC in comparison with ORC and LRC. EVIDENCE ACQUISITION Medline, Scopus, and Web of Science databases were searched using a free-text protocol including the terms robot-assisted radical cystectomy or da Vinci radical cystectomy or robot* radical cystectomy. RARC case series and studies comparing RARC with either ORC or LRC were collected. A cumulative analysis was conducted. EVIDENCE SYNTHESIS The searches retrieved 105 papers, 87 of which reported on pathologic, oncologic, or functional outcomes. Most series were retrospective and had small case numbers, short follow-up, and potential patient selection bias. The lymph node yield during lymph node dissection was 19 (range: 3-55), with half of the series following an extended template (yield range: 11-55). The lymph node-positive rate was 22%. The performance of lymphadenectomy was correlated with surgeon and institutional volume. Cumulative analyses showed no significant difference in lymph node yield between RARC and ORC. Positive surgical margin (PSM) rates were 5.6% (1-1.5% in pT2 disease and 0-25% in pT3 and higher disease). PSM rates did not appear to decrease with sequential case numbers. Cumulative analyses showed no significant difference in rates of surgical margins between RARC and ORC or RARC and LRC. Neoadjuvant chemotherapy use ranged from 0% to 31%, with adjuvant chemotherapy used in 4-29% of patients. Only six series reported a mean follow-up of >36 mo. Three-year disease-free survival (DFS), cancer-specific survival (CSS), and overall survival (OS) rates were 67-76%, 68-83%, and 61-80%, respectively. The 5-yr DFS, CSS, and OS rates were 53-74%, 66-80%, and 39-66%, respectively. Similar to ORC, disease of higher pathologic stage or evidence of lymph node involvement was associated with worse survival. Very limited data were available with respect to functional outcomes. The 12-mo continence rates with continent diversion were 83-100% in men for daytime continence and 66-76% for nighttime continence. In one series, potency was recovered in 63% of patients who were evaluable at 12 mo. CONCLUSIONS Oncologic and functional data from RARC remain immature, and longer-term prospective studies are needed. Cumulative analyses demonstrated that lymph node yields and PSM rates were similar between RARC and ORC. Conclusive long-term survival outcomes for RARC were limited, although oncologic outcomes up to 5 yr were similar to those reported for ORC. PATIENT SUMMARY Although open radical cystectomy (RC) is still regarded as the standard treatment for muscle-invasive bladder cancer, laparoscopic and robot-assisted RCs are becoming more popular. Templates of lymph node dissection, lymph node yields, and positive surgical margin rates are acceptable with robot-assisted RC. Although definitive comparisons with open RC with respect to oncologic or functional outcomes are lacking, early results appear comparable.

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In the present work, we examine the role of self-control resources within the relationship between anxiety and cognitive test performance. We argue that self-control is required for keeping attention away from anxiety-related worries, which would otherwise distract a person from performing on the test. In Study 1 (N = 67) and Study 2 (N = 96), we found that state anxiety was negatively related to performance of verbal learning and mental arithmetic if participants' self-control resources were depleted, but it was unrelated if participants' self-control was intact. In Study 3 (N = 99), the worry component of trait test anxiety was more strongly related to perceived distraction by worries while performing an arithmetic task for participants with depleted self-control resources than for nondepleted participants. Furthermore, distraction by worries showed to be responsible for suboptimal performance. The findings may help to clarify the anxiety-performance relationship and offer a novel approach for counteracting performance decrements associated with test anxiety.

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One of the earliest accounts of duration perception by Karl von Vierordt implied a common process underlying the timing of intervals in the sub-second and the second range. To date, there are two major explanatory approaches for the timing of brief intervals: the Common Timing Hypothesis and the Distinct Timing Hypothesis. While the common timing hypothesis also proceeds from a unitary timing process, the distinct timing hypothesis suggests two dissociable, independent mechanisms for the timing of intervals in the sub-second and the second range, respectively. In the present paper, we introduce confirmatory factor analysis (CFA) to elucidate the internal structure of interval timing in the sub-second and the second range. Our results indicate that the assumption of two mechanisms underlying the processing of intervals in the second and the sub-second range might be more appropriate than the assumption of a unitary timing mechanism. In contrast to the basic assumption of the distinct timing hypothesis, however, these two timing mechanisms are closely associated with each other and share 77% of common variance. This finding suggests either a strong functional relationship between the two timing mechanisms or a hierarchically organized internal structure. Findings are discussed in the light of existing psychophysical and neurophysiological data.

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OBJECTIVE We examined cognitive performance in children after stroke to study the influence of age at stroke, seizures, lesion characteristics, neurologic impairment (NI), and functional outcome on cognitive outcome. METHODS This was a prospectively designed study conducted in 99 children who sustained an arterial ischemic stroke (AIS) between the age of 1 month and 16 years. All children underwent cognitive and neurologic follow-up examination sessions 2 years after the insult. Cognitive development was assessed with age-appropriate instruments. RESULTS Although mean cognitive performance was in the lower normative range, we found poorer results in subtests measuring visuoconstructive skills, short-term memory, and processing speed. Risk factors for negative cognitive outcome were young age at stroke, seizures, combined lesion location (cortical and subcortical), as well as marked NI. CONCLUSIONS We recommend that all children with a history of AIS undergo regularly scheduled neuropsychological assessment to ensure implementation of appropriate interventions and environmental adjustments as early as possible.

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Randomised controlled trials (RCTs) of psychotherapeutic interventions assume that specific techniques are used in treatments, which are responsible for changes in the client's symptoms. This assumption also holds true for meta-analyses, where evidence for specific interventions and techniques is compiled. However, it has also been argued that different treatments share important techniques and that an upcoming consensus about useful treatment strategies is leading to a greater integration of treatments. This makes assumptions about the effectiveness of specific interventions ingredients questionable if the shared (common) techniques are more often used in interventions than are the unique techniques. This study investigated the unique or shared techniques in RCTs of cognitive-behavioural therapy (CBT) and short-term psychodynamic psychotherapy (STPP). Psychotherapeutic techniques were coded from 42 masked treatment descriptions of RCTs in the field of depression (1979-2010). CBT techniques were often used in studies identified as either CBT or STPP. However, STPP techniques were only used in STPP-identified studies. Empirical clustering of treatment descriptions did not confirm the original distinction of CBT versus STPP, but instead showed substantial heterogeneity within both approaches. Extraction of psychotherapeutic techniques from the treatment descriptions is feasible and could be used as a content-based approach to classify treatments in systematic reviews and meta-analyses.

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We report an electrochemical gating approach with [similar]100% efficiency to tune the conductance of single-molecule 4,4′-bipyridine junctions using scanning-tunnelling-microscopy break junction technique. Density functional theory calculation suggests that electrochemical gating aligns molecular frontier orbitals relative to the electrode Fermi-level, switching the molecule from an off resonance state to “partial” resonance.

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Effective adaptive behavior rests on an appropriate understanding of how much responsibility we have over outcomes in the environment. This attribution of agency to ourselves or to an external event influences our behavioral and affective response to the outcomes. Despite its special importance to understanding human motivation and affect, the neural mechanisms involved in self-attributed rewards and punishments remain unclear. Previous evidence implicates the anterior insula (AI) in evaluating the consequences of our own actions. However, it is unclear if the AI has a general role in feedback evaluation (positive and negative) or plays a specific role during error processing. Using functional magnetic resonance imaging and a motion prediction task, we investigate neural responses to self- and externally attributed monetary gains and losses. We found that attribution effects vary according to the valence of feedback: significant valence × attribution interactions in the right AI, the anterior cingulate cortex (ACC), the midbrain, and the right ventral putamen. Self-attributed losses were associated with increased activity in the midbrain, the ACC and the right AI, and negative BOLD response in the ventral putamen. However, higher BOLD activity to self-attributed feedback (losses and gains) was observed in the left AI, the thalamus, and the cerebellar vermis. These results suggest a functional lateralization of the AI. The right AI, together with the midbrain and the ACC, is mainly involved in processing the salience of the outcome, whereas the left is part of a cerebello-thalamic-cortical pathway involved in cognitive control processes important for subsequent behavioral adaptations.

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Dealing with one's emotions is a core skill in everyday life. Effective cognitive control strategies have been shown to be neurobiologically represented in prefrontal structures regulating limbic regions. In addition to cognitive strategies, mindfulness-associated methods are increasingly applied in psychotherapy. We compared the neurobiological mechanisms of these two strategies, i.e. cognitive reappraisal and mindfulness, during both the cued expectation and perception of negative and potentially negative emotional pictures. Fifty-three healthy participants were examined with functional magnetic resonance imaging (47 participants included in analysis). Twenty-four subjects applied mindfulness, 23 used cognitive reappraisal. On the neurofunctional level, both strategies were associated with comparable activity of the medial prefrontal cortex and the amygdala. When expecting negative versus neutral stimuli, the mindfulness group showed stronger activations in ventro- and dorsolateral prefrontal cortex, supramarginal gyrus as well as in the left insula. During the perception of negative versus neutral stimuli, the two groups only differed in an increased activity in the caudate in the cognitive group. Altogether, both strategies recruited overlapping brain regions known to be involved in emotion regulation. This result suggests that common neural circuits are involved in the emotion regulation by mindfulness-based and cognitive reappraisal strategies. Identifying differential activations being associated with the two strategies in this study might be one step towards a better understanding of differential mechanisms of change underlying frequently used psychotherapeutic interventions.

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Plant functional traits reflect different evolutionary responses to environmental variation, and among extant species determine the outcomes of interactions between plants and their environment, including other plant species. Thus, combining phylogenetic and trait-based information can be a powerful approach for understanding community assembly processes across a range of spatial scales. We used this approach to investigate tree community composition at Phou Khao Khouay National Park (18°14’-18°32’N; 102°38’- 102°59’E), Laos, where several distinct forest types occur in close proximity. The aim of our study was to examine patterns of plant community assembly across the strong environmental gradients evident at our site. We hypothesized that differences in tree community composition were being driven by an underlying gradient in soil conditions. Thus, we predicted that environmental filtering would predominate at the site and that the filtering would be strongest on sandier soil with low pH, as these are the conditions least favorable to plant growth. We surveyed eleven 0.25 ha (50x50 m) plots for all trees above 10 cm dbh (1221 individual trees, including 47 families, 70 genera and 123 species) and sampled soils in each plot. For each species in the community, we measured 11 commonly studied plant functional traits covering both the leaf and wood economic spectrum traits and we reconstructed a phylogenetic tree for 115 of the species in the community using rbcL and matK sequences downloaded from Genebank (other species were not available). Finally we compared the distribution of trait values and species at two scales (among plots and 10x10m subplots) to examine trait and phylogenetic community structures. Although there was strong evidence that an underlying soil gradient was determining patterns of species composition at the site, our results did not support the hypothesis that the environmental filtering dominated community assembly processes. For the measured plant functional traits there was no consistent pattern of trait dispersion across the site, either when traits were considered individually or when combined in a multivariate analysis. However, there was a significant correlation between the degree of phylogenetic dispersion and the first principle component axis (PCA1) for the soil parameters.Moreover, the more phylogenetically clustered plots were on sandier soils with lower pH. Hence, we suggest that the community assembly processes across our sitemay reflect the influence ofmore conserved traits that we did not measure. Nevertheless, our results are equivocal and other interpretations are possible. Our study illustrates some difficulties in combining trait and phylogenetic approaches that may result from the complexities of integrating spatial and evolutionary processes that vary at different scales.

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The new computing paradigm known as cognitive computing attempts to imitate the human capabilities of learning, problem solving, and considering things in context. To do so, an application (a cognitive system) must learn from its environment (e.g., by interacting with various interfaces). These interfaces can run the gamut from sensors to humans to databases. Accessing data through such interfaces allows the system to conduct cognitive tasks that can support humans in decision-making or problem-solving processes. Cognitive systems can be integrated into various domains (e.g., medicine or insurance). For example, a cognitive system in cities can collect data, can learn from various data sources and can then attempt to connect these sources to provide real time optimizations of subsystems within the city (e.g., the transportation system). In this study, we provide a methodology for integrating a cognitive system that allows data to be verbalized, making the causalities and hypotheses generated from the cognitive system more understandable to humans. We abstract a city subsystem—passenger flow for a taxi company—by applying fuzzy cognitive maps (FCMs). FCMs can be used as a mathematical tool for modeling complex systems built by directed graphs with concepts (e.g., policies, events, and/or domains) as nodes and causalities as edges. As a verbalization technique we introduce the restriction-centered theory of reasoning (RCT). RCT addresses the imprecision inherent in language by introducing restrictions. Using this underlying combinatorial design, our approach can handle large data sets from complex systems and make the output understandable to humans.

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Seizure freedom in patients suffering from pharmacoresistant epilepsies is still not achieved in 20–30% of all cases. Hence, current therapies need to be improved, based on a more complete understanding of ictogenesis. In this respect, the analysis of functional networks derived from intracranial electroencephalographic (iEEG) data has recently become a standard tool. Functional networks however are purely descriptive models and thus are conceptually unable to predict fundamental features of iEEG time-series, e.g., in the context of therapeutical brain stimulation. In this paper we present some first steps towards overcoming the limitations of functional network analysis, by showing that its results are implied by a simple predictive model of time-sliced iEEG time-series. More specifically, we learn distinct graphical models (so called Chow–Liu (CL) trees) as models for the spatial dependencies between iEEG signals. Bayesian inference is then applied to the CL trees, allowing for an analytic derivation/prediction of functional networks, based on thresholding of the absolute value Pearson correlation coefficient (CC) matrix. Using various measures, the thus obtained networks are then compared to those which were derived in the classical way from the empirical CC-matrix. In the high threshold limit we find (a) an excellent agreement between the two networks and (b) key features of periictal networks as they have previously been reported in the literature. Apart from functional networks, both matrices are also compared element-wise, showing that the CL approach leads to a sparse representation, by setting small correlations to values close to zero while preserving the larger ones. Overall, this paper shows the validity of CL-trees as simple, spatially predictive models for periictal iEEG data. Moreover, we suggest straightforward generalizations of the CL-approach for modeling also the temporal features of iEEG signals.

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BACKGROUND AND OBJECTIVE Connective tissue grafts are frequently applied, together with Emdogain(®) , for root coverage. However, it is unknown whether fibroblasts from the gingiva and from the palate respond similarly to Emdogain. The aim of this study was therefore to evaluate the effect of Emdogain(®) on fibroblasts from palatal and gingival connective tissue using a genome-wide microarray approach. MATERIAL AND METHODS Human palatal and gingival fibroblasts were exposed to Emdogain(®) and RNA was subjected to microarray analysis followed by gene ontology screening with Database for Annotation, Visualization and Integrated Discovery functional annotation clustering, Kyoto Encyclopedia of Genes and Genomes pathway analysis and the Search Tool for the Retrieval of Interacting Genes/Proteins functional protein association network. Microarray results were confirmed by quantitative RT-PCR analysis. RESULTS The transcription levels of 106 genes were up-/down-regulated by at least five-fold in both gingival and palatal fibroblasts upon exposure to Emdogain(®) . Gene ontology screening assigned the respective genes into 118 biological processes, six cellular components, eight molecular functions and five pathways. Among the striking patterns observed were the changing expression of ligands targeting the transforming growth factor-beta and gp130 receptor family as well as the transition of mesenchymal epithelial cells. Moreover, Emdogain(®) caused changes in expression of receptors for chemokines, lipids and hormones, and for transcription factors such as SMAD3, peroxisome proliferator-activated receptor gamma and those of the ETS family. CONCLUSION The present data suggest that Emdogain(®) causes substantial alterations in gene expression, with similar patterns observed in palatal and gingival fibroblasts.

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Background Nowadays there is extensive evidence available showing the efficacy of cognitive remediation (CR). To date, only limited evidence is available about the impact of the duration of illness on CR effects. The Integrated Neurocognitive Therapy (INT) represents a new developed CR approach. It is a manualized group therapy targeting all 11 NIMH-MATRICS domains. Methods In an international multicenter study, 166 schizophrenia outpatients (DSM-IV-TR) were randomly assigned either to INT or to Treatment-As-Usual (TAU). 60 patients were defined as Early Course group (EC) characterized by less than 5 years of illness, 40 patients were in the Long-Term group (LT) characterized by more than 15 years of illness, and 76 patients were in the Medium-Long-Term group (MLT) characterized by an illness of 5-15 years. Treatment comprised of 15 biweekly sessions. Assessments were conducted before and after treatment and at follow up (1 year). Multivariate General Linear Models (GLM) examined our hypothesis, whether EC, LT, and MLT groups differ under INT and TAU from each other in outcome. Results First of all, the attendance rate of 65% was significantly lower and the drop out rate of 18.5% during therapy was higher in the EC group compared to the other groups. Interaction effects regarding proximal outcome showed that the duration of illness has a strong impact on neurocognitive functioning in speed of processing (F>2.4) and attention (F>2.8). But INT intervention compared to TAU only had a significant effect in more chronically ill patients of MLT and LT, but not in younger patients in EC. In social cognitive domains, only the EC group showed a significant change in attribution (hostility; F>2.5), LT and MLT groups did not. However, no differences between the 3 groups were evident in memory, problem solving, and emotion perception. Regarding more distal outcome, LT patients had more symptoms compared to EC (F>4.4). Finally, EC patients showed higher improvements in psychosocial functioning compared to LT and MLT (F=1.8). Conclusions Against common expectations, long-term, more chronically ill patients showed higher effects in basal cognitive functions compared to younger patients and patients without any active therapy (TAU). On the other hand, early-course patients had a greater potential to change in attribution, symptoms and psychosocial functioning. Consequently, more integrated therapy offers are also recommended for long-term course schizophrenia patients.

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Optimal adjustment of brain networks allows the biased processing of information in response to the demand of environments and is therefore prerequisite for adaptive behaviour. It is widely shown that a biased state of networks is associated with a particular cognitive process. However, those associations were identified by backward categorization of trials and cannot provide a causal association with cognitive processes. This problem still remains a big obstacle to advance the state of our field in particular human cognitive neuroscience. In my talk, I will present two approaches to address the causal relationships between brain network interactions and behaviour. Firstly, we combined connectivity analysis of fMRI data and a machine leaning method to predict inter-individual differences of behaviour and responsiveness to environmental demands. The connectivity-based classification approach outperforms local activation-based classification analysis, suggesting that interactions in brain networks carry information of instantaneous cognitive processes. Secondly, we have recently established a brand new method combining transcranial alternating current stimulation (tACS), transcranial magnetic stimulation (TMS), and EEG. We use the method to measure signal transmission between brain areas while introducing extrinsic oscillatory brain activity and to study causal association between oscillatory activity and behaviour. We show that phase-matched oscillatory activity creates the phase-dependent modulation of signal transmission between brain areas, while phase-shifted oscillatory activity blunts the phase-dependent modulation. The results suggest that phase coherence between brain areas plays a cardinal role in signal transmission in the brain networks. In sum, I argue that causal approaches will provide more concreate backbones to cognitive neuroscience.