Archivio per 7 luglio 2015

07
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15

Thick psychophysiology for empathic design Elliott Bruce Hedma

See on Scoop.itSocial Neuroscience Advances

Over the course of six years, I brought ambulatory psychophysiology into a variety of industries as a means of conducting design research. I looked at the stress of children in occupational therapy, the frustration of playing Hasbro board games, the thrill of driving a Google Self Driving Car, the confidence of shopping at Best Buy and Lowes, the excitement of playing LEGO Technic for the first time, the tension of watching one’s first symphony, and the anxiety of talking about birth control. Working with stake holders within these settings I developed “Thick Psychophysiology,” defined by four characteristics:

1. Psychophysiological data is quantitatively measured,

2. The research answers explorative, open ended questions,

3. The research measures external context, and 4. The research measures internal context.

By combining ethnographic methods with psychophysiology, researchers can address the challenges of specificity that ambulatory, explorative research produces. Two case studies of preliminary design research are provided about the LEGO Group and the New World Symphony, showcasing how thick psychophysiology can help uncover customer’s unarticulated needs.

Once needs are uncovered, the challenge is how to motivate an organization to address those needs

See on dspace.mit.edu

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07
Lug
15

Stochastic game dynamics under demographic fluctuations

See on Scoop.itSocial Foraging

Frequency-dependent selection and demographic fluctuations play important roles in evolutionary and ecological processes. Under frequency-dependent selection, the average fitness of the population may increase or decrease based on interactions between individuals within the population. This should be reflected in fluctuations of the population size even in constant environments. Here, we propose a stochastic model that naturally combines these two evolutionary ingredients by assuming frequency-dependent competition between different types in an individual-based model. In contrast to previous game theoretic models, the carrying capacity of the population, and thus the population size, is determined by pairwise competition of individuals mediated by evolutionary games and demographic stochasticity. In the limit of infinite population size, the averaged stochastic dynamics is captured by deterministic competitive Lotka–Volterra equations. In small populations, demographic stochasticity may instead lead to the extinction of the entire population. Because the population size is driven by fitness in evolutionary games, a population of cooperators is less prone to go extinct than a population of defectors, whereas in the usual systems of fixed size the population would thrive regardless of its average payoff.

See on pnas.org

07
Lug
15

Greece debt crisis: PM Tsipras to present new plan at eurozone summit – BBC News

See on Scoop.itFiscal Policy & Regulation

Greek Prime Minister Alexis Tsipras is to present new proposals at a eurozone emergency summit on his country’s growing debt crisis.

See on bbc.co.uk

07
Lug
15

S0960-9822(14)00738-6.pdf

See on Scoop.itBounded Rationality and Beyond
Summary

Prior information about features of a stimulus is a strong modulator of perception. For instance, the prospect of more intense pain leads to an increased perception of pain, whereas the expectation of analgesia reduces pain, as shown in placebo analgesia and expectancy modulations during drug administration [1] . This influence is commonly assumed to be rooted in altered sensory processing and expectancy-related modulations in the spinal cord [2] , are often taken as evidence for this notion. Contemporary models of perception, however, suggest that prior information can also modulate perception by biasing perceptual decision-making — the inferential process underlying perception in which prior information is used to interpret sensory information. In this type of bias, the information is already present in the system before the stimulus is observed [3] . Computational models can distinguish between changes in sensory processing and altered decision-making as they result in different response times for incorrect choices in a perceptual decision-making task ( Figure S1 A,B) [4] . Using a drift-diffusion model, we investigated the influence of both processes in two independent experiments. The results of both experiments strongly suggest that these changes in pain perception are predominantly based on altered perceptual decision-making.

See on cell.com

07
Lug
15

Representations of Value in the Brain: An Embarrassment of Riches?

See on Scoop.itBounded Rationality and Beyond

Abstract

Over the past two decades, neuroscientists have increasingly turned their attention to the question of how the brain implements decisions between differently valued options. This emerging field, called neuroeconomics, has made quick progress in identifying a plethora of brain areas that track or are modulated by reward value. However, it is still unclear how and where in the brain value coding takes place. A primate study by Strait and colleagues in this issue of PLOS Biology finds overlapping signals of value coding in two brain regions central to the valuation process: the ventromedial prefrontal cortex and the ventral striatum. This finding reconciles the primate and rodent literatures, provides valuable insight into the complexity of value computation, and helps set the agenda for future work in this area.

  

See on ncbi.nlm.nih.gov

07
Lug
15

A Neuro-Computational Model of Economic Decisions

See on Scoop.itBounded Rationality and Beyond
Abstract

Neuronal recordings and lesion studies indicate that key aspects of economic decisions take place in the orbitofrontal cortex (OFC). Previous work identified in this area three groups of neurons encoding the offer value, the chosen value and the identity of the chosen good. An important and open question is whether and how decisions could emerge from a neural circuit formed by these three populations. Here we adapted a biophysically realistic neural network previously proposed for perceptual decisions (Wang 2002; Wong and Wang 2006). The domain of economic decisions is significantly broader than that for which the model was originally designed: yet the model performed remarkably well. The input and output nodes of the network were naturally mapped onto two groups of cells in OFC. Surprisingly, the activity of interneurons in the network closely resembled that of the third group of cells, namely chosen value cells. The model reproduced several phenomena related to the neuronal origins of choice variability. It also generated testable predictions on the excitatory/inhibitory nature of different neuronal populations and on their connectivity. Some aspects of the empirical data were not reproduced, but simple extensions of the model could overcome these limitations. These results render a biologically credible model for the neuronal mechanisms of economic decisions. They demonstrate that choices could emerge from the activity of cells in the OFC, suggesting that chosen value cells directly participate in the decision process. Importantly, Wang’s model provides a platform to investigate the implications of neuroscience results for economic theory.

 
See on jn.physiology.org




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