The orbitofrontal cortex (OFC) and its interactions with the basolateral amygdala (BLA) are critical for goal-directed behavior, especially for adapting to changes in reward value. Here we used a reinforcer devaluation paradigm to investigate the contribution of OFC to this behavior in four macaques. Subjects that had formed associations between objects and two different primary reinforcers (fo...

The posterior dorsomedial striatum (pDMS) is essential for the acquisition and expression of the specific response-outcome (R-O) associations that underlie goal-directed action. Here we examined the role of a pathway linking the basolateral amygdala (BLA) and pDMS in such goal-directed learning. In Experiment 1, rats received unilateral lesions of the BLA and were implanted with cannula targeti...

The role of the amygdala central nucleus (CeN) in habit learning was assessed in two experiments. First, we examined the effects of bilateral lesions of the anterior CeN on an overtraining-induced lever press habit evaluated using an outcome devaluation protocol. Overtraining generated habitual performance and rendered sham lesioned rats insensitive to outcome devaluation, an effect that was al...

Using a small macroeconometric model that examines the determinants of India’s trade and inflation, this paper addresses the effects of a reform policy package similar to those implemented in 1991. Policy simulations using dynamic simulation method compare the responses to devaluation with the responses to tight credit policy. It is shown that the trade balance effects of tight credit policy ar...

A 40-percent devaluation and its multiplier effects could cost approximately 1 percent of the state's total employment, or about 75,000 jobs, over the next three years. Because the state has been gaining employment at an annual rate of 240,000 jobs per year, such a loss represents about four month's worth of growth. Texas' economy should continue to expand in 1995, but the peso devaluation will...

A hierarchical framework is proposed to address the issues of modeling different type of words in keyword spotting (KWS). Keyword models are built at various levels according to the availability of training set resources for each individual word. The proposed approach improves the performance of KWS even when no training speech is available for the keywords. It also suggests an easier way to co...