Contributions of the ventromedial prefrontal cortex to goal-directed action selection

In this article, it will be argued that one of the key contributions of the ventromedial prefrontal cortex (vmPFC) to goal-directed action selection lies both in retrieving the value of goals that are the putative outcomes of the decision process and in establishing a relative preference ranking for these goals by taking into account the value of each of the different goals under consideration in a given decision-making scenario. These goal-value signals are then suggested to be used as an input into the on-line computation of action values mediated by brain regions outside of the vmPFC, such as parts of the parietal cortex, supplementary motor cortex, and dorsal striatum. Collectively, these areas can be considered to be constituent elements of a multistage decision process whereby the values of different goals must first be represented and ranked before the value of different courses of action available for the pursuit of those goals can be computed

Moral Concerns about Food Products and Production Methods among Consumers of Organic Foods: A Report of Some Preliminary Results from an On-Going Qualitative Study

The paper presents information regarding the research design and part of the theoretical framework employed in a qualitative analysis of data collected by means of focus groups undertaken among 3 sub-groups og consumers. The study compares supermarket customers with subscribers to farmer-run box schemes and customers at farmer-run market stalls in urban areas, with particular regard to their conceptions of organic products, producers and production methods. The results presented regard the use of visual data as a means of elucidating implicit consumer conceptions

Decoding the neural substrates of reward-related decision making with functional MRI

Although previous studies have implicated a diverse set of brain regions in reward-related decision making, it is not yet known which of these regions contain information that directly reflects a decision. Here, we measured brain activity using functional MRI in a group of subjects while they performed a simple reward-based decision-making task: probabilistic reversal-learning. We recorded brain activity from nine distinct regions of interest previously implicated in decision making and separated out local spatially distributed signals in each region from global differences in signal. Using a multivariate analysis approach, we determined the extent to which global and local signals could be used to decode subjects' subsequent behavioral choice, based on their brain activity on the preceding trial. We found that subjects' decisions could be decoded to a high level of accuracy on the basis of both local and global signals even before they were required to make a choice, and even before they knew which physical action would be required. Furthermore, the combined signals from three specific brain areas (anterior cingulate cortex, medial prefrontal cortex, and ventral striatum) were found to provide all of the information sufficient to decode subjects' decisions out of all of the regions we studied. These findings implicate a specific network of regions in encoding information relevant to subsequent behavioral choice

Consumption of Organic Foods from a Life History Perspective: An Exploratory Study among Danish Consumers

No summary availabl

Temporal isolation of neural processes underlying face preference decisions

Decisions about whether we like someone are often made so rapidly from first impressions that it is difficult to examine the engagement of neural structures at specific points in time. Here, we used a temporally extended decision-making paradigm to examine brain activation with functional MRI (fMRI) at sequential stages of the decision-making process. Activity in reward-related brain structures—the nucleus accumbens (NAC) and orbitofrontal cortex (OFC)—was found to occur at temporally dissociable phases while subjects decided which of two unfamiliar faces they preferred. Increases in activation in the OFC occurred late in the trial, consistent with a role for this area in computing the decision of which face to choose. Signal increases in the NAC occurred early in the trial, consistent with a role for this area in initial preference formation. Moreover, early signal increases in the NAC also occurred while subjects performed a control task (judging face roundness) when these data were analyzed on the basis of which of those faces were subsequently chosen as preferred in a later task. The findings support a model in which rapid, automatic engagement of the NAC conveys a preference signal to the OFC, which in turn is used to guide choice

An Environmental Input-Output Model for Ireland

This paper is presented in two parts. The first part demonstrates an environmental input-output model for Ireland for the year 2000. Selected emissions are given a monetary value on the basis of benefit-transfer. This modelling procedure reveals that certain sectors pollute more than others – even when normalised by the sectoral value added. Mining, agriculture, metal production and construction stand out as the dirtiest industries. On average, however, each sector adds more value than it does environmental damage. The second part uses the results of this input-output model – as well as historical data – to forecast emissions, waste and water use out to 2020. The growth in emissions of fluorinated gases and carbon monoxide and the growth of hazardous industrial waste exceed economic growth. Other emissions grow more slowly than the economy. Emissions of acid rain gases (SO2, NOx and NH3) will decrease, even if the economy grows rapidly.

Overlapping Prediction Errors in Dorsal Striatum During Instrumental Learning With Juice and Money Reward in the Human Brain

Prediction error signals have been reported in human imaging studies in target areas of dopamine neurons such as ventral and dorsal striatum during learning with many different types of reinforcers. However, a key question that has yet to be addressed is whether prediction error signals recruit distinct or overlapping regions of striatum and elsewhere during learning with different types of reward. To address this, we scanned 17 healthy subjects with functional magnetic resonance imaging while they chose actions to obtain either a pleasant juice reward (1 ml apple juice), or a monetary gain (5 cents) and applied a computational reinforcement learning model to subjects' behavioral and imaging data. Evidence for an overlapping prediction error signal during learning with juice and money rewards was found in a region of dorsal striatum (caudate nucleus), while prediction error signals in a subregion of ventral striatum were significantly stronger during learning with money but not juice reward. These results provide evidence for partially overlapping reward prediction signals for different types of appetitive reinforcers within the striatum, a finding with important implications for understanding the nature of associative encoding in the striatum as a function of reinforcer type

Human Dorsal Striatal Activity during Choice Discriminates Reinforcement Learning Behavior from the Gambler’s Fallacy

Reinforcement learning theory has generated substantial interest in neurobiology, particularly because of the resemblance between phasic dopamine and reward prediction errors. Actor–critic theories have been adapted to account for the functions of the striatum, with parts of the dorsal striatum equated to the actor. Here, we specifically test whether the human dorsal striatum—as predicted by an actor–critic instantiation—is used on a trial-to-trial basis at the time of choice to choose in accordance with reinforcement learning theory, as opposed to a competing strategy: the gambler's fallacy. Using a partial-brain functional magnetic resonance imaging scanning protocol focused on the striatum and other ventral brain areas, we found that the dorsal striatum is more active when choosing consistent with reinforcement learning compared with the competing strategy. Moreover, an overlapping area of dorsal striatum along with the ventral striatum was found to be correlated with reward prediction errors at the time of outcome, as predicted by the actor–critic framework. These findings suggest that the same region of dorsal striatum involved in learning stimulus–response associations may contribute to the control of behavior during choice, thereby using those learned associations. Intriguingly, neither reinforcement learning nor the gambler's fallacy conformed to the optimal choice strategy on the specific decision-making task we used. Thus, the dorsal striatum may contribute to the control of behavior according to reinforcement learning even when the prescriptions of such an algorithm are suboptimal in terms of maximizing future rewards

Temporal trends in bulk milk antibodies to Salmonella, Neospora caninum, and Leptospira interrogans serovar hardjo in Irish dairy herds

peer-reviewedBulk milk samples were collected from 309 Irish dairy herds at four time points during 2009 and tested for antibodies to Salmonella spp., N. caninum, and L. hardjo, three abortifacient agents in Irish dairy herds. Of the 312 study herds, 49% vaccinated against Salmonella and 76% vaccinated against L. hardjo. In unvaccinated herds, the overall prevalence of antibody positive herds was 49% for Salmonella, 19% for N. caninum and 86% for L. hardjo. There was no association between both testing positive for and incidence of Salmonella or L. hardjo on sample date and calving season. A significant association was found between sample date and both testing positive for [p = <0.0001 OR = 2.41 (95% CI 1.54–3.80)] and incidence [p = 0.001 OR = 3.10 (95% CI 1.72–5.57)] of N. caninum. No association with region of Ireland was found for either testing positive for or incidence of N. caninum, or L. hardjo. There was however a tendency towards a higher incidence of Salmonella in regions of Ireland with higher cattle densities