Brain activation during anticipation of sound sequences

Music consists of sound sequences that require integration over time. As we become familiar with music, associations between notes, melodies, and entire symphonic movements become stronger and more complex. These associations can become so tight that, for example, hearing the end of one album track can elicit a robust image of the upcoming track while anticipating it in total silence. Here, we study this predictive “anticipatory imagery” at various stages throughout learning and investigate activity changes in corresponding neural structures using functional magnetic resonance imaging. Anticipatory imagery (in silence) for highly familiar naturalistic music was accompanied by pronounced activity in rostral prefrontal cortex (PFC) and premotor areas. Examining changes in the neural bases of anticipatory imagery during two stages of learning conditional associations between simple melodies, however, demonstrates the importance of fronto-striatal connections, consistent with a role of the basal ganglia in “training” frontal cortex (Pasupathy and Miller, 2005). Another striking change in neural resources during learning was a shift between caudal PFC earlier to rostral PFC later in learning. Our findings regarding musical anticipation and sound sequence learning are highly compatible with studies of motor sequence learning, suggesting common predictive mechanisms in both domains.

Income, Trade and Pollution in Central Asia, Russia and China: An Econometric Analysis

The study performs a panel estimation of the relationship between per capita income, trade, and airborne pollution in the five Central Asian nations, Russia and China between 1992 and 2008. First, this study uses an environmental Kuznets curve hypothesis (EKC)- an inverted-U relationship between the increase in income and the level of environmental degradation - to examine how income and pollution are related. Second, the study uses a gravity model to estimate the effect of a regional trade agreement (Shanghai Cooperation Organization: SCO) on incomes and carbon dioxide emissions in the region. Empirical analysis confirms the existence of the rising portion of the EKC curve in the region - a positive correlation between per capita income growth and carbon dioxide emissions- and that the volume of bilateral trade, and not the existence of a regional trade agreement, contributes to the increasing level of environmental pollution.

Income, Trade and Pollution in Central Asia, Russia and China: An Econometric Analysis

The study performs a panel estimation of the relationship between per capita income, trade, and airborne pollution in the five Central Asian nations, Russia and China between 1992 and 2008. First, this study uses an environmental Kuznets curve hypothesis (EKC)- an inverted-U relationship between the increase in income and the level of environmental degradation - to examine how income and pollution are related. Second, the study uses a gravity model to estimate the effect of a regional trade agreement (Shanghai Cooperation Organization: SCO) on incomes and carbon dioxide emissions in the region. Empirical analysis confirms the existence of the rising portion of the EKC curve in the region - a positive correlation between per capita income growth and carbon dioxide emissions- and that the volume of bilateral trade, and not the existence of a regional trade agreement, contributes to the increasing level of environmental pollution.