933 resultados para Individual differences in children.


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Partial migration, whereby only a fraction of the population migrates, is thought to be the most common type of migration in the animal kingdom, and can have important ecological and evolutionary consequences. Despite this, the factors that influence which individuals migrate and which remain resident are poorly understood. Recent work has shown that consistent individual differences in personality traits in animals can be ecologically important, but field studies integrating personality traits with migratory behaviour are extremely rare. In this study, we investigate the influence of individual boldness, an important personality trait, upon the migratory propensity of roach, a freshwater fish, over two consecutive migration seasons. We assay and individually tag 460 roach and show that boldness influences migratory propensity, with bold individuals being more likely to migrate than shy fish. Our data suggest that an extremely widespread personality trait in animals can have significant ecological consequences via influencing individual-level migratory behaviour.

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Attentional blink (AB) refers to impaired identification of a target (T2) when this target follows a preceding target (T1) after about 150-450 ms within a stream of rapidly presented stimuli. Previous research on a possible relation between AB and mental ability (MA) turned out to be highly ambiguous. The present study investigated MA-related individual differences in consolidation of T2 in working memory during the AB as indicated by the P300 component of the event-related potential. Thirty high (HA) and 30 low MA (LA) female participants performed an AB task while their brain activity was recorded. The AB did not differ between the two groups. HA individuals exhibited a larger P300 amplitude and longer P300 latencies during the AB suggesting higher mental effort. This higher mental effort, however, did not result in better performance presumably because of more competition between target and distractor stimuli in HA than LA individuals.

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Humans engage in deceptive behavior that negatively affects others. The propensity to deceive is,however, characterized by vast inter-individual heterogeneity that is poorly understood. Attempts to investigate the origins of this heterogeneity have so far mainly relied on subjective measures and have shown little predictive power. Here, we used resting electroencephalography to measure objective and stable individual differences in neural baseline activation in combination with an ecologically valid deception paradigm. Results showed that task-independent baseline activation in the anterior insula, a brain area implicated in mapping internal bodily states and in representing emotional arousal and consciousfeelings, predicts individuals’ propensity for deceptive behavior. The higher the neural baseline activation in this area is, the lower individuals’ propensity to deceive. Moreover, results provide evidence that high baseline activation in the anterior insula is associated with negative affect and dispositional tendencies to avoid aversive emotional situations. These results provide converging neural and psychological evidence that individuals might avoid a deceptive act due to a highly active negative emotional system which would make a deceptive act too stressful and bothersome.

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The close association between psychometric intelligence and general discrimination ability (GDA), conceptualized as latent variable derived from performance on different sensory discrimination tasks, is empirically well-established but theoretically widely unclear. The present study contrasted two alternative explanations for this association. The first explanation is based on what Spearman (1904) referred to as a central function underlying this relationship in the sense of the g factor of intelligence and becoming most evident in GDA. In this case, correlations between different aspects of cognitive abilities, such as working memory (WM) capacity, and psychometric intelligence should be mediated by GDA if their correlation is caused by g. Alternatively, the second explanation for the relationship between psychometric intelligence and GDA proceeds from fMRI studies which emphasize the role of WM functioning for sensory discrimination. Given the well-known relationship between WM and psychometric intelligence, the relationship between GDA and psychometric intelligence might be attributed to WM. The present study investigated these two alternative explanations at the level of latent variables. In 197 young adults, a model in which WM mediated the relationship between GDA and psychometric intelligence described the data better than a model in which GDA mediated the relationship between WM and psychometric intelligence. Moreover, GDA failed to explain portions of variance of psychometric intelligence above and beyond WM. These findings clearly support the view that the association between psychometric intelligence and GDA must be understood in terms of WM functioning.

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The capacity to inhibit inappropriate responses is crucial for goal-directed behavior. Inhibiting such responses seems to come more easily to some of us than others, however. From where do these individual differences originate? Here, we measured 263 participants' neural baseline activation using resting electroencephalogram. Then, we used this stable neural marker to predict a reliable electrophysiological index of response inhibition capacity in the cued Continuous Performance Test, the NoGo-Anteriorization (NGA). Using a source-localization technique, we found that resting delta, theta, and alpha1 activity in the left middle frontal gyrus and resting alpha1 activity in the right inferior frontal gyrus were negatively correlated with the NGA. As a larger NGA is thought to represent better response inhibition capacity, our findings demonstrate that lower levels of resting slow-wave oscillations in the lateral prefrontal cortex, bilaterally, are associated with a better response inhibition capacity.

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Research demonstrates that social preferences are characterized by significant individual differences. An important question, often overlooked, is from where do these individual differences originate? And what are the processes that underlie such differences? In this paper, we outline the neural trait approach to uncovering sources of individual differences in social preferences, particularly as evidenced in economic games. We focus on two primary methods—resting-state electroencephalography and structural magnetic resonance imaging—used by researchers to quantify task-independent, brain-based characteristics that are stable over time. We review research that has employed these methods to investigate social preferences with an emphasis on a key psychological process in social decision-making; namely, self-control. We then highlight future opportunities for the neural trait approach in cutting-edge decision-making research. Finally, we explore the debate about self-control in social decision-making and the potential role neural trait research could play in this issue.

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During intertemporal decisions, the preference for smaller, sooner reward over larger-delayed rewards (temporal discounting, TD) exhibits substantial inter-subject variability; however, it is currently unclear what are the mechanisms underlying this apparently idiosyncratic behavior. To answer this question, here we recorded and analyzed mouse movement kinematics during intertemporal choices in a large sample of participants (N = 86). Results revealed a specific pattern of decision dynamics associated with the selection of “immediate” versus “delayed” response alternatives, which well discriminated between a “discounter” versus a “farsighted” behavior—thus representing a reliable behavioral marker of TD preferences. By fitting the Drift Diffusion Model to the data, we showed that differences between discounter and farsighted subjects could be explained in terms of different model parameterizations, corresponding to the use of different choice mechanisms in the two groups. While farsighted subjects were biased toward the “delayed” option, discounter subjects were not correspondingly biased toward the “immediate” option. Rather, as shown by the dynamics of evidence accumulation over time, their behavior was characterized by high choice uncertainty.

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The attentional blink (AB) is a fundamental limitation of the ability to select relevant information from irrelevant information. It can be observed with the detection rate in an AB task as well as with the corresponding P300 amplitude of the event-related potential. In previous research, however, correlations between these two levels of observation were weak and rather inconsistent. A possible explanation of this finding might be that multiple processes underlie the AB and, thus, obscure a possible relationship between AB-related detection rate and the corresponding P300 amplitude. The present study investigated this assumption by applying a fixed-links modeling approach to represent behavioral individual differences in the AB as a latent variable. Concurrently, this approach enabled us to control for additional sources of variance in AB performance by deriving two additional latent variables. The correlation between the latent variable reflecting behavioral individual differences in AB magnitude and a corresponding latent variable derived from the P300 amplitude was high (r=.70). Furthermore, this correlation was considerably stronger than the correlations of other behavioral measures of the AB magnitude with their psychophysiological counterparts (all rs<.40). Our findings clearly indicate that the systematic disentangling of various sources of variance by utilizing the fixed-links modeling approach is a promising tool to investigate behavioral individual differences in the AB and possible psychophysiological correlates of these individual differences.

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Inter-individual differences in cognitive performance are based on an efficient use of task-related brain resources. However, little is known yet on how these differences might be reflected on resting-state brain networks. Here we used Magnetoencephalography resting-state recordings to assess the relationship between a behavioral measurement of verbal working memory and functional connectivity as measured through Mutual Information. We studied theta (4?8 Hz), low alpha (8?10 Hz), high alpha (10?13 Hz), low beta (13?18 Hz) and high beta (18?30 Hz) frequency bands. A higher verbal working memory capacity was associated with a lower mutual information in the low alpha band, prominently among right-anterior and left-lateral sensors. The results suggest that an efficient brain organization in the domain of verbal working memory might be related to a lower resting-state functional connectivity across large-scale brain networks possibly involving right prefrontal and left perisylvian areas.

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The relationship between brain activity and reading performance was examined to test the hypothesis that dyslexia involves a deficit in a specific visual pathway known as the magnocellular (M) pathway. Functional magnetic resonance imaging was used to measure brain activity in dyslexic and control subjects in conditions designed to preferentially stimulate the M pathway. Dyslexics showed reduced activity compared with controls both in the primary visual cortex and in a secondary cortical visual area (MT+) that is believed to receive a strong M pathway input. Most importantly, significant correlations were found between individual differences in reading rate and brain activity. These results support the hypothesis for an M pathway abnormality in dyslexia and imply a strong relationship between the integrity of the M pathway and reading ability.

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The underlying bases of the considerable interindividual variability in pain-related traits are starting to be revealed. Although the relative importance of genes versus experience in human pain perception remains unclear, rodent populations display large and heritable differences in both nociceptive and analgesic sensitivity. The identification and characterization of particularly divergent populations provides a powerful initial step in the genetic analysis of pain, because these models can be exploited to identify genes contributing to the behavior-level variability. Ultimately, DNA sequence differences representing the differential alleles at pain-relevant genes can be identified. Thus, by using a combination of “top-down” and “bottom-up” strategies, we are now able to genetically dissect even complex biological traits like pain. The present review summarizes the current progress toward these ends in both humans and rodents.

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Using a sample of 339 university graduates from the University of Alicante (Spain) three years after completion of their studies, we studied the relationships between general intelligence (GI), personality traits, emotional intelligence (EI), academic performance, and occupational attainment and compared the results of conventional regression analysis with the results obtained from applying regression mixture models. The results reveal the influence of unobserved population heterogeneity (latent class) on the relationship between predictors and criteria and the improvement in the prediction obtained from applying regression mixture models compared to applying a conventional regression model.