Patients with basal ganglia damage show preserved learning in an economic game.

Both basal ganglia (BG) and orbitofrontal cortex (OFC) have been widely implicated in social and non-social decision-making. However, unlike OFC damage, BG pathology is not typically associated with disturbances in social functioning. Here we studied the behavior of patients with focal lesions to either BG or OFC in a multi-strategy competitive game known to engage these regions. We find that whereas OFC patients are significantly impaired, BG patients show intact learning in the economic game. By contrast, when information about the strategic context is absent, both cohorts are significantly impaired. Computational modeling further shows a preserved ability in BG patients to learn by anticipating and responding to the behavior of others using the strategic context. These results suggest that apparently divergent findings on BG contribution to social decision-making may instead reflect a model where higher-order learning processes are dissociable from trial-and-error learning, and can be preserved despite BG damage

Listener’s vmPFC simulates speaker choices when reading between the lines

Humans possess a remarkable ability to understand what is and is not being said by conservational partners. An important class of models hypothesize that listeners decode the intended meaning of an utterance by assuming speakers speak cooperatively, simulating the speaker’s rational choice process and inverting this process for recovering the speaker’s most probable meaning. We investigated whether and how rational simulations of speakers are represented in the listener’s brain, when subjects participated in a referential communication game inside fMRI. In three experiments, we show that listener’s ventromedial prefrontal cortex encodes the probabilistic inference of what a cooperative speaker should say given a communicative goal and context. The listener’s striatum responds to the amount of update on the intended meaning, consistent with inverting a simulated mental model. These findings suggest a neural generative mechanism subserved by the frontal-striatal circuits that underlies our ability to understand communicative and, more generally, social actions

Listener's vmPFC simulates speaker choices when reading between the lines

Humans possess a remarkable ability to understand what is and is not being said by conservational partners. An important class of models hypothesize that listeners decode the intended meaning of an utterance by assuming speakers speak cooperatively, simulating the speaker's rational choice process and inverting this process for recovering the speaker's most probable meaning. We investigated whether and how rational simulations of speakers are represented in the listener's brain, when subjects participated in a referential communication game inside fMRI. In three experiments, we show that the listener's ventromedial prefrontal cortex encodes the probabilistic inference of what a cooperative speaker should say given a communicative goal and context. The listener's striatum responds to the amount of update on the intended meaning, consistent with inverting a simulated mental model. These findings suggest a neural generative mechanism subserved by the frontal-striatal circuits that underlies our ability to understand communicative and, more generally, social actions

Gene Expression Program Underlying Tail Resorption During Thyroid Hormone-Dependent Metamorphosis of the Ornamented Pygmy Frog Microhyla fissipes

Thyroid hormone (T3) is essential for vertebrate development, especially during the so-called postembryonic development, a period around birth in mammals when plasma T3 level peaks and many organs mature into their adult form. Compared to embryogenesis, postembryonic development is poorly studied in mammals largely because of the difficulty to manipulate the uterus-enclosed embryos and neonates. Amphibian metamorphosis is independent of maternal influence and can be easily manipulated for molecular and genetic studies, making it a valuable model to study postembryonic development in vertebrates. Studies on amphibian metamorphosis have been largely focused on the two highly related species Xenopus laevis and Xenopus tropicalis. However, adult X. laevis and X. tropicalis animals remain aquatic. This makes important to study metamorphosis in a species in which postmetamorphic frogs live on land. In this regard, the anuran Microhyla fissipes represents an alternative model for developmental and genetic studies. Here we have made use of the advances in sequencing technologies to investigate the gene expression profiles underlying the tail resorption program during metamorphosis in M. fissipes. We first used single molecule real-time sequencing to obtain 67, 939 expressed transcripts in M. fissipes. We next identified 4,555 differentially expressed transcripts during tail resorption by using Illumina sequencing on RNA samples from tails at different metamorphic stages. Bioinformatics analyses revealed that 11 up-regulated KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways and 88 Gene Ontology (GO) terms as well as 21 down-regulated KEGG pathways and 499 GO terms were associated with tail resorption. Our findings suggest that tail resorption in M. fissipes and X. laevis shares many programs. Future investigations on function and regulation of these genes and pathways should help to reveal the mechanisms governing amphibian tail resorption and adaptive evolution from aquatic to terrestrial life. Furthermore, analysis of the M. fissipes model, especially, on the changes in other organs associated with the transition from aquatic to terrestrial living, should help to reveal important mechanistic insights governing mammalian postembryonic developments

Understanding neural mechanisms of strategic learning: correlates, causality, and applications

This is a systematic study on learning in the repeated game from the neuroeconomics perspective. Theoretically, learning theory has been developed to complement the traditional game theory in seeking to explain how and which equilibria might arise as a consequence of nonequilibrium dynamics among agents with bounded rationality. Empirically, learning models have been widely used to describe the evolvement of observed behavior over the course of field and laboratory experiments. While game theorists are trying to make learning theory more empirically relevant (Fudenberg and K. Levine 2009), experimentalists often found it difficult to distinguish different learning models based on behavioral choice data alone (Salmon 2001; Wilcox 2006). Here I sought to investigate learning mechanism from an alternative perspective: the neuroeconomics perspective, by combining the game theory experimental paradigm, parametric learning models, and neuroscience methods. In the first part of the thesis, I sought to identify the underlying learning rule by investigating how the brain encodes and computes learning signals used to guide behavior in a repeated normal-form game. Specifically, I combined functional neuroimaging of a multi-strategy competitive game with computational modeling of three widely used classes of learning models—reinforcement, belief-based learning, and their hybrid, experience-weighted attraction (EWA). I found evidence for distinct signals for reinforcement and belief-based learning in the brain. More importantly, I rejected the hypothesis of a hybrid EWA process at the neural level, even though it outperforms reinforcement and belief-based learning models behaviorally. Based on these findings, I hypothesized that behavioral choices are a product of a dual-system process at the brain level involving reinforcement and belief-based learning signals. Although the neural imaging method provides a new dimension of data and biologically plausible criterion for model testing, it is silent about the causal relation between brain regions and learning signals. In order to validate the neuroimaging results and establish the necessary roles of brain regions for strategic learning, I then compared ii the behavior of focal brain lesion patients to normal volunteers that are matched in terms of demographics and cognitive measures. In particular, I studied three different types of lesion patients: orbital frontal, dorsal lateral prefrontal and basal ganglia patients, which allowed me to dissociate the different roles necessarily to strategic learning. In the third part of the thesis, I applied the above findings on the neural circuitry underlying strategic learning to explore the behavioral signature of a special yet important population, the elderly individuals. In particular, I compared the behavioral results from the strategic learning under two experimental settings: playing against other intelligent players and against a computer agent; and between two populations: the healthy elderly individuals and young individuals. Our behavioral results suggest that elderly individuals adjust more slowly. Interestingly, this is not because elderly individuals are insensitive to the new experience but because their prior belief decays more slowly than young individuals. I further posited that within elderly population, their prior decays more slowly when they are playing against intelligent people than against a computer agent. This comparative study serves as a first step for developing biomarkers to quantify decision-making deficits and will shed light on the individual differences in productivity and intellectual viability often found within the elderly population

Product design pattern based on big data-driven scenario

This article discusses about new product design patterns in the big data era, gives designer a new rational thinking way, and is a new way to understand the design of the product. Based on the key criteria of the product design process, category, element, and product are used to input the data, which comprises concrete data and abstract data as an enlargement of the criteria of product design process for the establishment of a big data-driven product design pattern’s model. Moreover, an experiment and a product design case are conducted to verify the feasibility of the new pattern. Ultimately, we will conclude that the data-driven product design has two patterns: one is the concrete data supporting the product design, namely “product–data–product” pattern, and the second is based on the value of the abstract data for product design, namely “data–product–data” pattern. Through the data, users are involving themselves in the design development process. Data and product form a huge network, and data plays a role of connection or node. So the essence of the design is to find a new connection based on element, and to find a new node based on category

Neuroeconomic measures of social decision-making across the lifespan.

Social and decision-making deficits are often the first symptoms of a striking number of neurodegenerative disorders associated with aging. These includes not only disorders that directly impact dopamine and basal ganglia, such as Parkinson's disorder, but also degeneration in which multiple neural pathways are affected over the course of normal aging. The impact of such deficits can be dramatic, as in cases of financial fraud, which disproportionately affect the elderly. Unlike memory and motor impairments, however, which are readily recognized as symptoms of more serious underlying neurological conditions, social and decision-making deficits often do not elicit comparable concern in the elderly. Furthermore, few behavioral measures exist to quantify these deficits, due in part to our limited knowledge of the core cognitive components or their neurobiological substrates. Here we probe age-related differences in decision-making using a game theory paradigm previously shown to dissociate contributions of basal ganglia and prefrontal regions to behavior. Combined with computational modeling, we provide evidence that age-related changes in elderly participants are driven primarily by an over-reliance in trial-and-error reinforcement learning that does not take into account the strategic context, which may underlie cognitive deficits that contribute to social vulnerability in elderly individuals