Distinct neural activations correlate with maximization of reward magnitude versus frequency.

Choice selection strategies and decision-making are typically investigated using multiple-choice gambling paradigms that require participants to maximize expected value of rewards. However, research shows that performance in such paradigms suffers from individual biases towards the frequency of gains such that users often choose smaller frequent gains over larger rarely occurring gains, also referred to as melioration. To understand the basis of this subjective tradeoff, we used a simple 2-choice reward task paradigm in 186 healthy human adult subjects sampled across the adult lifespan. Cortical source reconstruction of simultaneously recorded electroencephalography suggested distinct neural correlates for maximizing reward magnitude versus frequency. We found that activations in the parahippocampal and entorhinal areas, which are typically linked to memory function, specifically correlated with maximization of reward magnitude. In contrast, maximization of reward frequency was correlated with activations in the lateral orbitofrontal cortices and operculum, typical areas involved in reward processing. These findings reveal distinct neural processes serving reward frequency versus magnitude maximization that can have clinical translational utility to optimize decision-making.

Applying the matching law as micro-foundation of social phenomena.

Social phenomena are suggested to be explained by the matching law - an empirical regularity of individual behaviour. While a considerable amount of psychological research on this law exists, only a few sociological applications can be found. This paper points to the problems that come with its usage as micro-foundation of social behaviour and provides solutions. In particular, a model of melioration learning enables the derivation of social phenomena from the matching law. The proposed approach is illustrated by the application of the learning model to the volunteer's dilemma. In contrast to game-theoretical solutions, the matching law leads to more intuitive results in case of the asymmetric dilemma. The relationship between the matching law and utility maximisation is discussed by its integration into economic consumer theory.

Influence of Mineralized Water Sources on the Properties of Calcisol and Yield of Wheat (Triticum aestivum L.).

The use of conservation agriculture (SWC-soil and water conservation) technologies is now becoming more and more necessary. For the soils in arid ecosystems, the problem of irrigation deficiencies has always been relevant, and clean fresh water is always insufficient to irrigate these agricultural lands. This paper provides a brief historical overview of the use of mineralized water sources in agriculture and their impacts on soils and plants (Triticum aestivum L.). The experiment involving wheat cultivation in saline soils irrigated with mineralized water was set for 3 years. The main chemical and physical-chemical properties of the agro-transformed solonchaks and mineralized water sources were investigated. According to the contents of mobile forms of N, P, and K, the soils were poorly supplied; after a series of irrigation phases, they remained the same. There were signs of the growth of mobile phosphorus in the variants where mineralized water sources were applied. Our results showed that under conditions of irrigation with water sources with mineralization rates of up to 2.8-3.5 g/L, the wheat yield increased by 1.5 c/ha compared to the control. The use of mineralized water for irrigation purposes will reduce the use of clean river water.

Simulating Root Growth as a Function of Soil Strength and Yield With a Field-Scale Crop Model Coupled With a 3D Architectural Root Model.

Accurate prediction of root growth and related resource uptake is crucial to accurately simulate crop growth especially under unfavorable environmental conditions. We coupled a 1D field-scale crop-soil model running in the SIMPLACE modeling framework with the 3D architectural root model CRootbox on a daily time step and implemented a stress function to simulate root elongation as a function of soil bulk density and matric potential. The model was tested with field data collected during two growing seasons of spring barley and winter wheat on Haplic Luvisol. In that experiment, mechanical strip-wise subsoil loosening (30-60 cm) (DL treatment) was tested, and effects on root and shoot growth at the melioration strip as well as in a control treatment were evaluated. At most soil depths, strip-wise deep loosening significantly enhanced observed root length densities (RLDs) of both crops as compared to the control. However, the enhanced root growth had a beneficial effect on crop productivity only in the very dry season in 2018 for spring barley where the observed grain yield at the strip was 18% higher as compared to the control. To understand the underlying processes that led to these yield effects, we simulated spring barley and winter wheat root and shoot growth using the described field data and the model. For comparison, we simulated the scenarios with the simpler 1D conceptual root model. The coupled model showed the ability to simulate the main effects of strip-wise subsoil loosening on root and shoot growth. It was able to simulate the adaptive plasticity of roots to local soil conditions (more and thinner roots in case of dry and loose soil). Additional scenario runs with varying weather conditions were simulated to evaluate the impact of deep loosening on yield under different conditions. The scenarios revealed that higher spring barley yields in DL than in the control occurred in about 50% of the growing seasons. This effect was more pronounced for spring barley than for winter wheat. Different virtual root phenotypes were tested to assess the potential of the coupled model to simulate the effect of varying root traits under different conditions.

Melioration revisited: a systematic replication of Vaughan (1981).

Organisms that behave so as to forfeit a relatively higher overall rate of reinforcement in favor of a relatively lower rate are said to engage in suboptimal choice. Suboptimal choice has been linked with maladaptive behavior in humans. Melioration theory offers one explanatory framework for suboptimal choice. Melioration theory suggests behavior is controlled by differences in local reinforcer rates between alternatives. Vaughan (1981) arranged two experimental conditions in which maximizing the overall rate of reinforcement required behavior that was compatible, or incompatible, with melioration. Vaughan found pigeons allocated more time to a locally richer alternative even when doing so resulted in suboptimal choice. However, Vaughan did not show whether these effects could systematically reverse and did not provide within-session data to show that choice across short time spans remains under the control of differences in local reinforcer rates. The present study used pigeons to replicate and extend Vaughan's findings. We investigated shifts in overall- and within-session choice across repeated conditions, according to arranged local contingencies. Behavior systematically followed changes in local contingencies for most pigeons. Within-session data suggests that, providing differences in local reinforcer rates are discriminated, pigeons will allocate more time to a locally richer alternative, even if this leads to suboptimal choice. These findings facilitate the more confident use of similar procedures that investigate how melioration contributes to suboptimal choice.

The dynamics of the law of effect: a comparison of models.

Dynamical models based on three steady-state equations for the law of effect were constructed under the assumption that behavior changes in proportion to the difference between current behavior and the equilibrium implied by current reinforcer rates. A comparison of dynamical models showed that a model based on Navakatikyan's (2007) two-component functions law-of-effect equations performed better than models based on Herrnstein's (1970) and Davison and Hunter's (1976) equations. Navakatikyan's model successfully described the behavioral dynamics in schedules with negative-slope feedback functions, concurrent variable-ratio schedules, Vaughan's (1981) melioration experiment, and experiments that arranged equal, and constant-ratio unequal, local reinforcer rates.