Origin and Properties of Striatal Local Field Potential Responses to Cortical Stimulation: Temporal Regulation by Fast Inhibitory Connections

Evoked striatal field potentials are seldom used to study corticostriatal communication in vivo because little is known about their origin and significance. Here we show that striatal field responses evoked by stimulating the prelimbic cortex in mice are reduced by more than 90% after infusing the AMPA receptor antagonist CNQX close to the recording electrode. Moreover, the amplitude of local field responses and dPSPs recorded in striatal medium spiny neurons increase in parallel with increasing stimulating current intensity. Finally, the evoked striatal fields show several of the basic known properties of corticostriatal transmission, including paired pulse facilitation and topographical organization. As a case study, we characterized the effect of local GABAA receptor blockade on striatal field and multiunitary action potential responses to prelimbic cortex stimulation. Striatal activity was recorded through a 24 channel silicon probe at about 600 µm from a microdialysis probe. Intrastriatal administration of the GABAA receptor antagonist bicuculline increased by 65±7% the duration of the evoked field responses. Moreover, the associated action potential responses were markedly enhanced during bicuculline infusion. Bicuculline enhancement took place at all the striatal sites that showed a response to cortical stimulation before drug infusion, but sites showing no field response before bicuculline remained unresponsive during GABAA receptor blockade. Thus, the data demonstrate that fast inhibitory connections exert a marked temporal regulation of input-output transformations within spatially delimited striatal networks responding to a cortical input. Overall, we propose that evoked striatal fields may be a useful tool to study corticostriatal synaptic connectivity in relation to behavior

Corporate reputation past and future: a review and integration of existing literature and a framework for future research

The concept of corporate reputation is steadily growing in interest among management researchers and practitioners. In this article, we trace key milestones in the development of reputation literature over the past six decades to suggest important research gaps as well as to provide contextual background for a subsequent integration of approaches and future outlook. In particular we explore the need for better categorised outcomes; a wider range of causes; and a deeper understanding of contingencies and moderators to advance the field beyond its current state while also taking account of developments in the macro business environment. The article concludes by presenting a novel reputation framework that integrates insights from reputation theory and studies, outlines gaps in knowledge and offers directions for future research

Corporate greed: its effect on customer satisfaction, corporate social responsibility and corporate reputation among bank customers

Corporate greed has received increasing attention in recent years with various stories hitting the headlines, particularly after the global financial crisis and the ensuing negative attitudes toward banks. Customer satisfaction and corporate social responsibility are known to have a positive effect on corporate reputation among customers, but perceived corporate greed is likely to impede their effect. Corporate greed, customer satisfaction, corporate social responsibility and corporate reputation are considered, and a research model is proposed. Results indicate that the effect of corporate greed is stronger on corporate social responsibility than on customer satisfaction, implying that corporate social responsibility activities may be futile if the company is perceived to be acting greedily by its customers. Thus, perceptions of corporate greed need to be dealt with swiftly, to enable management to enhance the corporate reputation of the firm

Monitoring rare categories in sentiment and opinion analysis: a Milan mega event on Twitter platform

This paper proposes a new aggregated classification scheme aimed to support the implementation of semantic text analysis methods in contexts characterized by the presence of rare text categories. The proposed approach starts from the aggregate supervised text classifier developed by Hopkins and King and moves forward, relying on rare event sampling methods. In detail, it enables the analyst to enlarge the number of estimated sentiment categories, both preserving the estimation accuracy and reducing the working time to unconditionally increase the size of the training set. The approach is applied to study the daily evolution of the web reputation of one of the last mega-event taking place in Europe: Expo Milano. The corpus consists of more than one million tweets in both Italian and English, discussing about the event. The analysis provides an interesting portrayal of the evolution of the Expo stakeholders’ opinions over time and allows the identification of the main drivers of the Expo reputation. The algorithm will be implemented as a running option in the next release of the R package ReadMe