Predictive neural coding of reward preference involves dissociable responses in human ventral midbrain and ventral striatum.

Food preferences are acquired through experience and can exert strong influence on choice behavior. In order to choose which food to consume, it is necessary to maintain a predictive representation of the subjective value of the associated food stimulus. Here, we explore the neural mechanisms by which such predictive representations are learned through classical conditioning. Human subjects were scanned using fMRI while learning associations between arbitrary visual stimuli and subsequent delivery of one of five different food flavors. Using a temporal difference algorithm to model learning, we found predictive responses in the ventral midbrain and a part of ventral striatum (ventral putamen) that were related directly to subjects' actual behavioral preferences. These brain structures demonstrated divergent response profiles, with the ventral midbrain showing a linear response profile with preference, and the ventral striatum a bivalent response. These results provide insight into the neural mechanisms underlying human preference behavior.

The neural signature of escalating frustration in humans.

Mammalian studies show that frustration is experienced when goal-directed activity is blocked. Despite frustration's strongly negative role in health, aggression and social relationships, the neural mechanisms are not well understood. To address this we developed a task in which participants were blocked from obtaining a reward, an established method of producing frustration. Levels of experienced frustration were parametrically varied by manipulating the participants' motivation to obtain the reward prior to blocking. This was achieved by varying the participants' proximity to a reward and the amount of effort expended in attempting to acquire it. In experiment 1, we confirmed that proximity and expended effort independently enhanced participants' self-reported desire to obtain the reward, and their self-reported frustration and response vigor (key-press force) following blocking. In experiment 2, we used functional magnetic resonance imaging (fMRI) to show that both proximity and expended effort modulated brain responses to blocked reward in regions implicated in animal models of reactive aggression, including the amygdala, midbrain periaqueductal grey (PAG), insula and prefrontal cortex. Our findings suggest that frustration may serve an energizing function, translating unfulfilled motivation into aggressive-like surges via a cortical, amygdala and PAG network.

Molecular basis of transferrin polymorphism in goldfish (Carassius auratus)

Transferrin (TF) polymorphism was investigated in a color variety of goldfish (Carassius auratus), and its molecular basis analyzed. Three TF variants (A(1), A(2) and B-1) were identified from an inbred strain of the goldfish, of which A(1) and B-1 displayed a large electrophoretic difference on both native and SDS-PAGE gels. The TF cDNAs corresponding to variants A(1) and B-1 were cloned and sequenced from A(1)A(1), A(1)B(1) and B1B1 individuals, and their deduced amino acid sequences were analyzed. Substantial amino acid variation occurred between variants A(1) and B-1, with significant differences in peptide length, theoretical molecular weight (Mw) and isoelectric point (pI). No potential glycosylation sites were observed in the two amino acid sequences, which excluded the possibility that carbohydrate difference might cause electrophoretic variation among the TF variants. Further analysis suggested that the distinct electrophoretic mobility of the two variants A(1) and B-1 by SDS-PAGE resulted from their Mw difference, while the difference by the native PAGE could be explained by their pI variation. Furthermore, genomic DNA fragments containing the transferrin alleles were amplified and subjected to RFLP analysis in A(1)A(1), A(1)B(1) and B1B1 individuals. The data revealed characteristic banding patterns for each TF genotype, and demonstrated that the TF alleles A(1) and B-1 could be used as a co-dominant marker system. The initial work relating to the goldfish TF variants will benefit the understanding of the evolutionary and functional significance of TF polymorphism in fish.

Energetic basis of molecular recognition in a DNA aptamer

The thermal stability and ligand binding properties of the L-argininamide-binding DNA aptamer (5'-GATCGAAACGTAGCGCCTTCGATC3') were studied by spectroscopic and calorimetric methods. Differential calorimetric studies showed that the uncomplexed aptamer melted in a two-state reaction with a melting temperature T-m = 50.2 +/- 0.2 degrees C and a folding enthalpy Delta H degrees(fold) = -49.0 +/- 2.1 kcal mol(-1). These values agree with values of T-m = 49.6 degrees C and Delta H degrees(fold) = -51.2 kcal mol(-1) predicted for a simple hairpin structure. Melting of the uncomplexed aptamer was dependent upon salt concentration, but independent of strand concentration. The T of aptamer melting was found to increase as L-argininamide concentrations increased. Analysis of circular dichroism titration data using a single-site binding model resulted in the determination of a binding free energy Delta G degrees(bind) = -5.1 kcal mol(-1). Isothermal titration calorimetry studies revealed an exothermic binding reaction with Delta H degrees(bind) = -8.7 kcal mol(-1). Combination of enthalpy and free energy produce ail unfavorable entropy of -T Delta S degrees = +3.6 kcal mol(-1). A molar heat capacity change of -116 cal mol(-1) K-1 was determined from calorimetric measurements at four temperatures over the range of 15-40 degrees C. Molecular dynamics simulations were used to explore the structures of the unligated and ligated aptamer structures.

Theoretical estimation of thermodynamic properties of the system PS/PPO on the basis of modified combining rule of Sanchez-Lacombe lattice fluid model

The three scaling parameters described in Sanchez-Lacombe lattice fluid theory (SLLFT), T*, P* and rho* of pure polystyrene (PS), pure poly(2,6-dimethyl-1,4-phenylene oxide) (PPO) and their mixtures are obtained by fitting corresponding experimental pressure volume-temperature data with equation-of-state of SLLFT. A modified combining rule in SLLFT used to match the volume per mer, v* of the PS/PPO mixtures was advanced and the enthalpy of mixing and Flory-Huggins (FH) interaction parameter were calculated using the new rule. It is found that the difference between the new rule and the old one presented by Sanchez and Lacombe is quite small in the calculation of the enthalpy of mixing and FH interaction parameter and the effect of volume-combining rule on the calculation of thermodynamic properties is much smaller than that of energy-combining rule. But the relative value of interaction parameter changes much due to the new volume-based combining rule. This effect can affect the position of phase diagram very much, which is reported elsewhere [Macromolecules 34 (2001) 6291]

Ecological basis of Alpine meadow ecosystem management in Tibet: Haibei Alpine Meadow Ecosystem Research Station

Alpine meadow and shrub are the main pasture types on the Tibetan Plateau, and they cover about 35% of the total land area. In order to understand the structural and functional aspects of the alpine ecosystem and to promote a sustainable animal production system, the Haibei Alpine Meadow Research Station was established in 1976. A series of intensive studies on ecosystem structure and function, including the energy flow and nutrient cycling of the ecosystem, were the main tasks during the first 10 years. Meanwhile, studies with 5 different grazing intensities on both summer and winter pasture have been conducted. In the early years of the 1990s, the research station started to focus its research work on global warming, biodiversity and sustainable animal production systems in pastoral areas. Various methods for improving degraded pasturelands have been developed in the region.

Neural Dynamics of Autistic Behaviors: Cognitive, Emotional, and Timing Substrates

What brain mechanisms underlie autism and how do they give rise to autistic behavioral symptoms? This article describes a neural model, called the iSTART model, which proposes how cognitive, emotional, timing, and motor processes may interact together to create and perpetuate autistic symptoms. These model processes were originally developed to explain data concerning how the brain controls normal behaviors. The iSTART model shows how autistic behavioral symptoms may arise from prescribed breakdowns in these brain processes.

A Neural Model of Surface Perception: Lightness, Anchoring, and Filling-in

This article develops a neural model of how the visual system processes natural images under variable illumination conditions to generate surface lightness percepts. Previous models have clarified how the brain can compute the relative contrast of images from variably illuminate scenes. How the brain determines an absolute lightness scale that "anchors" percepts of surface lightness to us the full dynamic range of neurons remains an unsolved problem. Lightness anchoring properties include articulation, insulation, configuration, and are effects. The model quantatively simulates these and other lightness data such as discounting the illuminant, the double brilliant illusion, lightness constancy and contrast, Mondrian contrast constancy, and the Craik-O'Brien-Cornsweet illusion. The model also clarifies the functional significance for lightness perception of anatomical and neurophysiological data, including gain control at retinal photoreceptors, and spatioal contrast adaptation at the negative feedback circuit between the inner segment of photoreceptors and interacting horizontal cells. The model retina can hereby adjust its sensitivity to input intensities ranging from dim moonlight to dazzling sunlight. A later model cortical processing stages, boundary representations gate the filling-in of surface lightness via long-range horizontal connections. Variants of this filling-in mechanism run 100-1000 times faster than diffusion mechanisms of previous biological filling-in models, and shows how filling-in can occur at realistic speeds. A new anchoring mechanism called the Blurred-Highest-Luminance-As-White (BHLAW) rule helps simulate how surface lightness becomes sensitive to the spatial scale of objects in a scene. The model is also able to process natural images under variable lighting conditions.