Modulation of Mediotemporal and Ventrostriatal Function in Humans by Delta 9-Tetrahydrocannabinol A Neural Basis for the Effects of Cannabis sativa on Learning and Psychosis

Context: Cannabis sativa use can impair verbal learning, provoke acute psychosis, and increase the risk of schizophrenia. It is unclear where C sativa acts in the human brain to modulate verbal learning and to induce psychotic symptoms. Objectives: To investigate the effects of 2 main psychoactive constituents of C sativa, Delta 9-tetrahydrocannabinol (Delta 9-THC) and cannabidiol, on regional brain function during verbal paired associate learning. Design: Subjects were studied on 3 separate occasions using a block design functional magnetic resonance imaging paradigm while performing a verbal paired associate learning task. Each imaging session was preceded by the ingestion of Delta 9-THC (10 mg), cannabidiol (600 mg), or placebo in a double-blind, randomized, placebo-controlled, repeated-measures, within-subject design. Setting: University research center. Participants: Fifteen healthy, native English-speaking, right-handed men of white race/ethnicity who had used C sativa 15 times or less and had minimal exposure to other illicit drugs in their lifetime. Main Outcome Measures: Regional brain activation ( blood oxygen level-dependent response), performance in a verbal learning task, and objective and subjective ratings of psychotic symptoms, anxiety, intoxication, and sedation. Results: Delta 9-Tetrahydrocannabinol increased psychotic symptoms and levels of anxiety, intoxication, and sedation, whereas no significant effect was noted on these parameters following administration of cannabidiol. Performance in the verbal learning task was not significantly modulated by either drug. Administration of Delta 9-THC augmented activation in the parahippocampal gyrus during blocks 2 and 3 such that the normal linear decrement in activation across repeated encoding blocks was no longer evident. Delta 9-Tetrahydrocannabinol also attenuated the normal time-dependent change in ventrostriatal activation during retrieval of word pairs, which was directly correlated with concurrently induced psychotic symptoms. In contrast, administration of cannabidiol had no such effect. Conclusion: The modulation of mediotemporal and ventrostriatal function by Delta 9-THC may underlie the effects of C sativa on verbal learning and psychotic symptoms, respectively.

Organizational Learning in the Context of an Agri-Food Chain

This paper reports on the outcomes of the first stage of a longitudinal study that focused on the transformational change process being undertaken within the Supply Chain and Operations Area of a major Australian food manufacturing company. Organizational learning is an essential prerequisite for any successful change process and an organization's ability to learn is dependent on the existence of an environment within the organization that nurtures learning and the presence of key enablers that facilitate the learning process. An organization's capacity to learn can be enhanced through its ability to form and sustain collaborative relationships with its chain partners. The results show that an environment that supports organizational learning is being developed through consultative leadership and the empowerment of individuals within a culture that supports innovation and cross-functional teamwork but demands responsibility and accountability. The impact of these changes within the Supply Chain and Operations Area is evident in the significant improvement in the Area's productivity and efficiency levels over the past twelve months. The company's endeavours to engage its major supply chain partners in the learning process have been limited by the turmoil within the company. However the company has involved its supply chain partners in a series of mutually beneficial projects that have improved communication and built trust thereby laying the foundations for more collaborative chain relationships.

A Comparison of Bayesian and Sampling Theory Inferences in a Probit Model

HE PROBIT MODEL IS A POPULAR DEVICE for explaining binary choice decisions in econometrics. It has been used to describe choices such as labor force participation, travel mode, home ownership, and type of education. These and many more examples can be found in papers by Amemiya (1981) and Maddala (1983). Given the contribution of economics towards explaining such choices, and given the nature of data that are collected, prior information on the relationship between a choice probability and several explanatory variables frequently exists. Bayesian inference is a convenient vehicle for including such prior information. Given the increasing popularity of Bayesian inference it is useful to ask whether inferences from a probit model are sensitive to a choice between Bayesian and sampling theory techniques. Of interest is the sensitivity of inference on coefficients, probabilities, and elasticities. We consider these issues in a model designed to explain choice between fixed and variable interest rate mortgages. Two Bayesian priors are employed: a uniform prior on the coefficients, designed to be noninformative for the coefficients, and an inequality restricted prior on the signs of the coefficients. We often know, a priori, whether increasing the value of a particular explanatory variable will have a positive or negative effect on a choice probability. This knowledge can be captured by using a prior probability density function (pdf) that is truncated to be positive or negative. Thus, three sets of results are compared:those from maximum likelihood (ML) estimation, those from Bayesian estimation with an unrestricted uniform prior on the coefficients, and those from Bayesian estimation with a uniform prior truncated to accommodate inequality restrictions on the coefficients.