Weber's law in decision making: integrating behavioral data in humans with a neurophysiological model

Recent single-cell studies in monkeys (Romo et al., 2004) show that the activity of neurons in the ventral premotor cortex covaries with the animal's decisions in a perceptual comparison task regarding the frequency of vibrotactile events. The firing rate response of these neurons was dependent only on the frequency differences between the two applied vibrations, the sign of that difference being the determining factor for correct task performance. We present a biophysically realistic neurodynamical model that can account for the most relevant characteristics of this decision-making-related neural activity. One of the nontrivial predictions of this model is that Weber's law will underlie the perceptual discrimination behavior. We confirmed this prediction in behavioral tests of vibrotactile discrimination in humans and propose a computational explanation of perceptual discrimination that accounts naturally for the emergence of Weber's law. We conclude that the neurodynamical mechanisms and computational principles underlying the decision-making processes in this perceptual discrimination task are consistent with a fluctuation-driven scenario in a multistable regime.

Ag Decision Maker, January 2016, Vol. 20, no. 3

A Business Newsletter for Agriculture

Ag Decision Maker, March 2016, Vol. 20, no. 5

A Business Newsletter for Agriculture

Decision-theoretic reflections on processing a fingermark

A recent publication in this journal [Neumann et al., Forensic Sci. Int. 212 (2011) 32-46] presented the results of a field study that revealed the data provided by the fingermarks not processed in a forensic science laboratory. In their study, the authors were interested in the usefulness of this additional data in order to determine whether such fingermarks would have been worth submitting to the fingermark processing workflow. Taking these ideas as a starting point, this communication here places the fingermark in its context of a case brought before a court, and examines the question of processing or not processing a fingermark from a decision-theoretic point of view. The decision-theoretic framework presented provides an answer to this question in the form of a quantified expression of the expected value of information (EVOI) associated with the processed fingermark, which can then be compared with the cost of processing the mark.

Ag Decision Maker, April 2016, Vol. 20, no. 6

A Business Newsletter for Agriculture

Ag Decision Maker, May 2016, Vol. 20, no. 7

A Business Newsletter for Agriculture

The timing of exploratory decision-making revealed by single-trial topographic EEGanalyses.

Decision-making in an uncertain environment is driven by two major needs: exploring the environment to gather information or exploiting acquired knowledge to maximize reward. The neural processes underlying exploratory decision-making have been mainly studied by means of functional magnetic resonance imaging, overlooking any information about the time when decisions are made. Here, we carried out an electroencephalography (EEG) experiment, in order to detect the time when the brain generators responsible for these decisions have been sufficiently activated to lead to the next decision. Our analyses, based on a classification scheme, extract time-unlocked voltage topographies during reward presentation and use them to predict the type of decisions made on the subsequent trial. Classification accuracy, measured as the area under the Receiver Operator's Characteristic curve was on average 0.65 across 7 subjects. Classification accuracy was above chance levels already after 516 ms on average, across subjects. We speculate that decisions were already made before this critical period, as confirmed by a positive correlation with reaction times across subjects. On an individual subject basis, distributed source estimations were performed on the extracted topographies to statistically evaluate the neural correlates of decision-making. For trials leading to exploration, there was significantly higher activity in dorsolateral prefrontal cortex and the right supramarginal gyrus; areas responsible for modulating behavior under risk and deduction. No area was more active during exploitation. We show for the first time the temporal evolution of differential patterns of brain activation in an exploratory decision-making task on a single-trial basis.

A decision support system for selective cleaning

[Abstract]

Automatic Decision-Oriented Mapping of Pollution Data

The paper deals with the development and application of the methodology for automatic mapping of pollution/contamination data. General Regression Neural Network (GRNN) is considered in detail and is proposed as an efficient tool to solve this problem. The automatic tuning of isotropic and an anisotropic GRNN model using cross-validation procedure is presented. Results are compared with k-nearest-neighbours interpolation algorithm using independent validation data set. Quality of mapping is controlled by the analysis of raw data and the residuals using variography. Maps of probabilities of exceeding a given decision level and ?thick? isoline visualization of the uncertainties are presented as examples of decision-oriented mapping. Real case study is based on mapping of radioactively contaminated territories.

Ryhmätyömenetelmät logistiikan strategisessa päätöksenteossa

Työ käsittelee strategisen päätöksenteon menetelmiä sekä ryhmien päätöksentekoprosessin tukemista ja organisointia. Lähtökohtana työssä oli tarve kehittää konkreettisia menetelmiä ja tekniikoitalogistiikan strategisten päätöksentekoryhmien toiminnan tukemiseksi. Päätavoitteena työssä oli selvittää, mitkä ovat päätöksentekoryhmien suurimmat ongelmat jahaasteet päätöksentekoprosessin eri vaiheissa. Tämän pohjalta tavoitteena oli ideoida, kuinka päätöksentekoryhmiä ja niiden toimintaa noissa haasteissa voidaanparhaiten tukea erilaisten apumenetelmien ja tekniikoiden avulla. Kirjallisuuskatsauksessa perehdytään strategisten päätösten luokittelutapoihin, päätöksentekoprosessin luonteeseen, ryhmätyöskentelyn merkitykseen päätöksenteossa sekä erilaisiin ryhmäpäätöksentekotekniikoihin. Näiden pohjalta työssä on mietitty, missä asioissa ja päätöksentekoprosessin vaiheissa ryhmät kaipaavat eniten tukea ja mihin olemassa olevilla tekniikoilla ja menetelmillä ei ole pystytty täysin vastaamaan. Näihin avoimiin alueisiin työssä on pyritty kehittämään menetelmiä ja tekniikoita. Menetelmät antavat tukea erityisesti päätöksentekoprosessin vaiheistamiseen, oikeiden asioiden esille nostamiseen sekä keskustelun ja ryhmän muun toiminnan organisointiin. Työssä on esitelty myös muutama mielenkiintoinen ja lupaavajatkotutkimuskohde aihealueelta.

Angiotensin converting enzyme inhibitor induced angio-oedema: a review of the pathophysiology and risk factors.

Angio-oedema (AE) is a known adverse effect of angiotensin converting enzyme inhibitor (ACE-I) therapy. Over the past several decades, evidence of failure to diagnose this important and potentially fatal reaction is commonly found in the literature. Because this reaction is often seen first in the primary care setting, a review was undertaken to analyse and document the keys to both diagnostic criteria as well as to investigate potential risk factors for ACE-I AE occurrence. A general review of published literature was conducted through Medline, EMBASE, and the Cochrane Database, targeting ACE-I-related AE pathomechanism, diagnosis, epidemiology, risk factors, and clinical decision making and treatment. The incidence and severity of AE appears to be on the rise and there is evidence of considerable delay in diagnosis contributing to significant morbidity and mortality for patients. The mechanism of AE due to ACE-I drugs is not fully understood, but some genomic and metabolomic information has been correlated. Additional epidemiologic data and clinical treatment outcome predictors have been evaluated, creating a basis for future work on the development of clinical prediction tools to aid in risk identification and diagnostic differentiation. Accurate recognition of AE by the primary care provider is essential to limit the rising morbidity associated with ACE-I treatment-related AE. Research findings on the phenotypic indicators relevant to this group of patients as well as basic research into the pathomechanism of AE are available, and should be used in the construction of better risk analysis and clinical diagnostic tools for ACE-I AE.