Using confirmatory factor analysis to measure contemporaneous activation of defined neuronal networks in functional magnetic resonance imaging

a b s t r a c t a r t i c l e i n f o Functional neuroimaging often generates large amounts of data on regions of interest. Such data can be addressed effectively with a widely-used statistical technique based on measurement theory that has not yet been applied to neuroimaging. Confirmatory factor analysis is a convenient hypothesis-driven modeling environment that can be used to conduct formal statistical tests comparing alternative hypotheses regarding the elements of putative neuronal networks. In such models, measures of each activated region of interest are treated as indicators of an underlying latent construct that represents the contemporaneous activation of the elements in the network. As such, confirmatory factor analysis focuses analyses on the activation of hypothesized networks as a whole, improves statistical power by modeling measurement error, and provides a theory-based approach to data reduction with a robust statistical basis. This approach is illustrated using data on seven regions of interest in a hypothesized mesocorticostriatal reward system in a sample of 262 adult volunteers assessed during a card-guessing reward task. A latent construct reflecting contemporaneous activation of the reward system was found to be significantly associated with a latent construct measuring impulsivity, particularly in males

Improving STEM mathematics achievement through self-efficacy, student perception, and mathematics connection: The mediating role of student interest

Science, technology, engineering, mathematics (STEM) education, the current engine for this technological generation, has made its way into Ghana's education system and is progressively becoming autonomous, particularly at the senior high level. It depends extensively on student mathematics performance to progress into their various dream STEM career programs. It is worthwhile to study the relationships between STEM students' mathematics (perception, self-efficacy, and connection) and mathematics achievement with their study interest mediating between them. The researchers purposively and conveniently sampled 385 general science respondents from eight selected senior high schools in the Kumasi metropolis for this study. The study produces results by quantifying and analyzing the collected data by investigating the six distinct hypotheses with structural equation model (SEM) using SPSS (26) and AMOS (24) software to confirm or refute fundamental assumptions. The study suggests that general science students' mathematics self-efficacy and connection directly impact their mathematics performance and, at the same time, somewhat mediate their ability to perform well in mathematics through their study interest. Moreover, there was no relationship between mathematical perception and student interest or achievement. Students must continue to evaluate the efficacy of their learning tactics to achieve academic excellence, and they must make reliable and self-efficacious evaluations of their mathematical learning as well as their mathematics connections to other STEM subjects to improve their study interest and mathematics achievement. The study recommends that stakeholders, curriculum developers, and implementers of the new STEM curriculum try to connect mathematics to all aspects of STEM as much as possible to either directly improve their performance or increase their interest in improving their mathematics education

The Hierarchical Organization of Impulse Control: Implications for Decision Making

<p>The research studies presented as this dissertation constitute a methodologically diverse and conceptually integrative approach to understanding impulsiveness in the context of cognitive control and decision making. Broadly, these findings address the validity of current conceptions of trait impulsiveness, relationships between those traits and brain or laboratory measures of cognitive control, and links between impulsive traits and economic decisions under conditions of delay or uncertainty. The findings presented in this thesis affirm the multidimensional nature of impulsiveness as a construct, and link individual differences in specific impulsive types to behavioral and neurobiological measures of control function. The nature of motor, attentional, and nonplanning impulsive types are contextualized by reference to evidence supporting a broad theory of behavioral control based on hierarchical organization of action, ranging from concrete acts to abstract plans and strategies. We provide evidence linking concrete forms of urgent/motor impulsiveness to behavior and brain activation during response-related control, and more abstract and future-oriented premedititative/nonplanning impulsiveness to strategic control signals in more rostral PFC. Finally, these findings are complemented by causal evidence from a neurostimulation study linking a contextual control network to risky decision making and attentional impulsiveness.</p>Dissertatio