Krasnow Institute for Advanced Study

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The Krasnow Institute seeks to expand understanding of mind, brain, and intelligence by conducting research at the intersection of the separate fields of cognitive psychology, neurobiology, and the computer-driven study of artificial intelligence and complex adaptive systems. These separate disciplines increasingly overlap and promise progressively deeper insight into human thought processes. The Institute also examines how new insights from cognitive science research can be applied for human benefit in the areas of mental health, neurological disease, education, and computer design.

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Conflict in Complex Socio-Natural Systems: Using Agent-Based Modeling to Understand the Behavioral Roots of Social Unrest within the Mandera Triangle
(Human Behavior-Computational Modeling and Interoperability Conference, 2009-06) Rouleau, Mark; Coletti, Mark; Bassett, Jeffrey K.; Hailegiorgis, Atesmachew B.; Gulden, Tim; Kennedy, William G.
Conflict resolution research relies upon a deep understanding of human behavior within highly complex socionatural systems. Scholars must isolate the source of conflict among individuals reacting to the feedback of changing socionatural conditions. Fortunately, the oft-obscured roots of conflict typically surface at critical points of change within the system. We use the Mandera Triangle region of East Africa as an example of this surfacing of behavioral drivers. Our research fuses a wide range of backgrounds to construct a simulation model of Mandera and to gain a better understanding of the roots of human behavior in relation to social conflict.
MASON AfriLand: A Regional Multi-Country Agent-Based Model with Cultural and Environmental Dynamics
(2009-06) Cioffi-Revilla, C.; Rouleau, M.
Agent-based models of regions of the international system composed of several countries are few and not as advanced as other classes of spatial computational models on a comparable scale. Most relevant extant models are of a single country or polity, or they model an entire international system putatively comprising all countries as in a world system. Here we present AfriLand, a new agentbased model for developing a large-scale and more detailed model of the geographic region of contemporary Eastern Africa. AfriLand is part of the Mason-HRAF Joint Project on Eastern Africa funded by a multi-year ONR-MURI grant. We present the motivation and challenges behind the AfriLand agent-based model design and a description of the model architecture and dynamics. AfriLand offers a useful scale for analyzing socio-cultural and environmental dynamics that transcend national boundaries, such as refugee flows, transnational conflict and crime (narcotics, trafficking in persons, smuggling) and natural hazards across national frontiers. AfriLand also presents visualization challenges that call for a range of solutions from software to hardware.
GeoMason: Geospatial Support for MASON
(Department of Computer Science, George Mason University, 2010) Sullivan, Keith; Coletti, Mark; Luke, Sean
MASON is a free, open-source Java-based discrete event multi-agent simulation toolkit that has been used to model network intrusions, unmanned aerial vehicles, nomadic migrations, and farmer/herder conflicts, among others. Many multi-agent models use georeferenced data which represent such things as road networks, rivers, vegetation coverage, population, and topology. However, MASON does not directly support georeferenced data. Therefore practitioners using MASON must hand craft such support, which may be difficult and error prone. In this paper we describe newly added geospatial functionality in MASON that addresses this problem. We discuss the design of this functionality, called GeoMASON, and its use and limitations. Finally, we give examples on how to import and manipulate georeferenced data.
An Agent-Based Model of Climate Change and Conflict among Pastoralists in East Africa
(International Environmental Modelling and Software Society (iEMSs), 2010) Hailegiorgis, A.B.; Kennedy, W.G.; Balan, G.C.; Bassett, J.K.; Gulden, T.
Presented is an agent-based model of human-environment interaction and conflict in East Africa using the MASON agent-based simulation environment. The model focuses on the complex interaction of pastoral groups with their environment and other emerging external actors. The model supports the observation that increased seasonal rainfall variability and droughts create tremendous stress on pastoralists groups and challenges their long-term resilience and adaptive response mechanisms.
MASON RebeLand: An Agent-Based Model of Politics, Environment, and Insurgency
(2010-02) Cioffi-Revilla, Claudio; Rouleau, Mark
Problem overview: explore the complex relationship between Society, Government, and Issues, using an explicit polity (political system) model; understand the feedback amongst Citizen Satisfaction, Issue Management, and Government Legitimacy; and generate emergence of civil unrest and polity instability from the “Bottom Up” within an Agent-Based Model.
An Agent-Based Model of Conflict in East Africa and the Effect of Watering Holes
(Conference on Behavior Representation in Modeling and Simulation, 2010-03) Kennedy, W.G.; Hailegiorgis, A.B.; Rouleau, M.; Bassett, J.K.; Coletti, M.; Balan, G.C.; Gulden, T.
An agent-based model conflict between herdsmen in east Africa using the MASON agent-based simulation environment is presented. Herders struggle to keep their herds fed and watered in a GIS-based, spatially diverse environment with data-driven seasonal cycles. The model produces realistic carrying capacity dynamics and basically plausible conflict dynamics. With the rather basic set of behaviors, herders come into conflict over limited resources and one clan is eventually eliminated. We find that greater environmental scarcity leads to faster domination by a single group. At the same time, we note that there is tremendous variability from run to run in the rate and timing of the transition from a conflict-prone, multi-clan environment to hegemony of a single group.
MASON RebeLand: An Agent-Based Model of Politics, Environment, and Insurgency
(Wiley-Blackwell, 2010-03) Cioffi-Revilla, Claudio; Rouleau, Mark
Social simulation models from computational social science are beginning to provide significant advances in terms of implementing more complex social, human, and natural dynamics that are characteristic of how countries operate in the real world. In particular, increasingly realistic agent-based models can improve capacity for early warning, understanding, and prediction. The MASON RebeLand model presents three innovations over earlier models: (i) an explicit polity model with politically complete structure and processes; (ii) social and natural model components within an integrated socio-natural system; and (iii) generative dynamics where insurgency and the state of the polity (stable, unstable, failing, failed, and recovering) occur as emergent phenomena under a range of social and environmental conditions. Three scenarios are demonstrated, showing stable, unstable, and failing polity conditions. The MASON computational system for agent-based and network modeling also permits additional experiments and extensions.
Integrating Fast and Slow Cognitive Processes
(International Conference on Cognitive Modeling, 2010-08) Kennedy, William, G.; Bugjska, Magdalena
Human reactions appear to be controlled by two separate types of mental processes: one fast, automatic, and unconscious and the other slow, deliberate, and conscious. With the attention in the literature focused on the taxonomy of the two processes, there is little discussion of how they interact. In this paper, we focus on modeling the slower process’s ability to inhibit the fast process. We present computational cognitive models in which different strategies allow a human to consciously inhibit an undesirable fast response. These general strategies include (a) blocking sensory input, (b), blocking or interrupting the fast process’s response, and (c) slowing down or delaying processing by introducing additional task. Furthermore, we discuss an approach to learning such strategies based on the inference of the causes and effects of the fast process.
MASON HerderLand: Origins of Conflict in East Africa
(2010-11) Kennedy, W.G.; Hailegiorgis, A.B.; Rouleau, M.; Bassett, J.K.; Coletti, M.; Balan, G.C.; Gulden, T.; Cioffi-Revilla, C.
HerderLand is an agent-based model of the people and environment in the Mandera Triangle area of Eastern Africa developed to address the causes of conflict in the area. With it we have conducted three sets of experiments varying the major environmental parameters we believed would affect conflict in the region.
The "Fast and Frugal" Cognitive Architecture for Computational Social Simulations
(Behavior Representation in Modeling & Simulation (BRIMS) Conference 2011, 2011-03) Kennedy, William G.; Bassett, Jeffrey K.
Computational social simulations involving humans require models of human behavior but their behavior can be represented and modeled in many ways. The two dimensions of this challenge we are interested in are the degree of cognitive plausibility in the representation of the behavior of humans and the computational intensity involved.
Pandemonium in Silico: Individual Radicalization for Agent-Based Modeling
(International Studies Association, 2011-03) Cioffi-Revilla, Claudio; Harrison, Joseph F.
How do individuals become radicalized, turning into terrorists, insurgents, violent actors.Computational agent-based models of irregular warfare, internal war, domestic political violence, and related conflicts require violent agents capable of carrying out attacks. Rather than introducing such agents as an exogenous process, as a Deus ex machina, this paper presents an agent-based model where radicalization is generated as an emergent phenomenon from within a population of individuals. The model (tentatively called “MASONRadicalAgent’’) is based on a new process-based theory of individual radicalization and is implemented in the MASON simulation system. Our paper describes the underlying theory, model structure, and some preliminary results intended for demonstration.This modeling effort is part of a broader project for modeling conflict in complex polities by combining computational simulations and network models.
Complex Polities in the Age of Modern States
(International Studies Association, 2011-03-16) Cioffi-Revilla, Claudio
Complex polities are political systems composed of both official "vertical" state institutions as well as one or more alternative set of "horizontal" institutions, such as religious, economic, paramilitary, or even criminal organizations. Both vertical and horizontal polities that compose complex polities have policy-making capacity engaged in the provision of public (and in some cases private) goods aimed at addressing various societal needs. While complex polities have existed since early antiquity, from a world historical perspective it is only since ca. 1500 CE and the formation of modern European states that contending vertical and horizontal polities have produced specialized institutions in competition and collaboration with the state. Moreover, complex polities for global governance also appear in the world system since ca. 1500 CE. This paper will present a theory of complex polities based on a computational perspective that is implemented in agent-based models of coupled socio-techno-natural systems - i.e., systems of governance that integrate societies and natural environments through artificial systems that mediate between the two at many scales, from local to global.
Comparing Agent-Based Computational Simulation Models in Cross-Cultural Research
(SAGE, 2011-05) Cioffi-Revilla, Claudio
Mel Ember was co-Principal Investigator in the Mason-HRAF Joint Project on Eastern Africa, a multiyear project aimed at developing and analyzing advanced computational agent-based models of human societies across 10 countries and 12 ecosystems. A major unsolved challenge in this kind of social science research is to devise a systematic way to compare, contrast, and communicate different models of social dynamics along relevant dimensions and characteristics, given the inherent complexity of most computational agent-based models. This article proposes a viable systematic framework for comparing models and illustrates its application using some of the models that Mel helped inspire and develop as senior project participant.
Geographic Information Systems (GIS) and Spatial Agent-Based Model (ABM) Simulations for Sustainable Development
(Association for Computing Machinery (ACM), 2011-10) Cioffi-Revilla, Claudio; Roger, J. Daniel; Hailegiorgis, Atesmachew
In recent years the interdisciplinary field of Computational Social Science has developed theory and methodologies for building spatial Agent-Based Social Simulation (ABSS) models of human societies that are situated in ecosystems with land cover and climate. This article explains the needs and demand for Geographic Information Systems (GIS) in these types of agent-based models, with an emphasis on models applied to Eastern Africa and Inner Asia and relevance for understanding and analyzing development issues. The models are implemented with the MASON (Multi-Agent Simulator Of Networks and Neighborhoods) system, an open-source simulation environment in the Java language and suitable for developing ABSS models with GIS for representing spatial features.
Evolutionary Computation and Agent-based Modeling: Biologically-inspired Approaches for Understanding Complex Social Systems
(Kluwer, 2012-06-18) Cioffi-Revilla, Claudio; De Jong, Kenneth; Bassett, Jeffrey
Computational social science in general, and social agent-based modeling (ABM) simulation in particular, are challenged by modeling and analyzing complex adaptive social systems with emergent properties that are hard to understand in terms of components, even when the organization of component agents is know. Evolutionary computation (EC) is a mature field that provides a bio-inspired approach and a suite of techniques that are applicable to and provide new insights on complex adaptive social systems. This paper demonstrates a combined EC-ABM approach illustrated through the RebeLand model of a simple but complete polity system. Results highlight tax rates and frequency of public issue that stress society as significant features in phase transitions between stable and unstable governance regimes. These initial results sug- gest further applications of EC to ABM in terms of multi-population models with heterogeneous agents, multi-objective optimization, dynamic environments, and evolving executable objects for modeling social change.
Signaling Pathways Involved in Striatal Synaptic Plasticity are Sensitive to Temporal Pattern and Exhibit Spatial Specificity
(Public Library of Science, 2013-03-14) Kim, BoHung; Hawes, Sarah L.; Gillani, Fawad; Wallace, Lane J.; Blackwell, Kim T.
The basal ganglia is a brain region critically involved in reinforcement learning and motor control. Synaptic plasticity in the striatum of the basal ganglia is a cellular mechanism implicated in learning and neuronal information processing. Therefore, understanding how different spatio-temporal patterns of synaptic input select for different types of plasticity is key to understanding learning mechanisms. In striatal medium spiny projection neurons (MSPN), both long term potentiation (LTP) and long term depression (LTD) require an elevation in intracellular calcium concentration; however, it is unknown how the post-synaptic neuron discriminates between different patterns of calcium influx. Using computer modeling, we investigate the hypothesis that temporal pattern of stimulation can select for either endocannabinoid production (for LTD) or protein kinase C (PKC) activation (for LTP) in striatal MSPNs. We implement a stochastic model of the post-synaptic signaling pathways in a dendrite with one or more diffusionally coupled spines. The model is validated by comparison to experiments measuring endocannabinoid-dependent depolarization induced suppression of inhibition. Using the validated model, simulations demonstrate that theta burst stimulation, which produces LTP, increases the activation of PKC as compared to 20 Hz stimulation, which produces LTD. The model prediction that PKC activation is required for theta burst LTP is confirmed experimentally. Using the ratio of PKC to endocannabinoid production as an index of plasticity direction, model simulations demonstrate that LTP exhibits spine level spatial specificity, whereas LTD is more diffuse. These results suggest that spatio-temporal control of striatal information processing employs these Gq coupled pathways.
Augmenting Weak Semantic Cognitive Maps with an “Abstractness” Dimension
(Hindawi Publishing, 2013-04-29) Samsonovich, Alexei
The emergent consensus on dimensional models of sentiment, appraisal, emotions, and values is on the semantics of the principal dimensions, typically interpreted as valence, arousal, and dominance. The notion of weak semantic maps was introduced recently as distribution of representations in abstract spaces that are not derived from human judgments, psychometrics, or any other a priori information about their semantics. Instead, they are defined entirely by binary semantic relations among representations, such as synonymy and antonymy. An interesting question concerns the ability of the antonymy-based semantic maps to capture all “universal” semantic dimensions. The present work shows that those narrow weak semantic maps are not complete in this sense and can be augmented with other semantic relations. Specifically, including hyponym-hypernym relations yields a new semantic dimension of the map labeled here “abstractness” (or ontological generality) that is not reducible to any dimensions represented by antonym pairs or to traditional affective space dimensions. It is expected that including other semantic relations (e.g., meronymy/holonymy) will also result in the addition of new semantic dimensions to the map. These findings have broad implications for automated quantitative evaluation of the meaning of text and may shed light on the nature of human subjective experience.
Employment Growth through Labor Flow Networks
(Public Library of Science, 2013-05-02) Guerrero, Omar A.; Axtell, Robert L.
It is conventional in labor economics to treat all workers who are seeking new jobs as belonging to a labor pool, and all firms that have job vacancies as an employer pool, and then match workers to jobs. Here we develop a new approach to study labor and firm dynamics. By combining the emerging science of networks with newly available employment micro-data, comprehensive at the level of whole countries, we are able to broadly characterize the process through which workers move between firms. Specifically, for each firm in an economy as a node in a graph, we draw edges between firms if a worker has migrated between them, possibly with a spell of unemployment in between. An economy's overall graph of firm-worker interactions is an object we call the labor flow network (LFN). This is the first study that characterizes a LFN for an entire economy. We explore the properties of this network, including its topology, its community structure, and its relationship to economic variables. It is shown that LFNs can be useful in identifying firms with high growth potential. We relate LFNs to other notions of high performance firms. Specifically, it is shown that fewer than 10% of firms account for nearly 90% of all employment growth. We conclude with a model in which empirically-salient LFNs emerge from the interaction of heterogeneous adaptive agents in a decentralized labor market.
Not so cool? Menthol’s discovered actions on the nicotinic receptor and its implications for nicotine addiction
(Frontiers, 2013-07-23) Kabbani, Nadine
Nicotine cigarette smoke is a large public health burden worldwide, contributing to various types of disease. Anti-tobacco media campaigns and control programs have significantly reduced smoking in the United States, yet trends for menthol cigarette smoking have not been as promising. Menthol cigarette smoking is particularly prevalent among young adults and African Americans, with implications for long-term impacts on health care. Continuing high rates of menthol cigarette addiction call into question the role of menthol in nicotine addiction. To date, a biological basis for the high rate of addiction and relapse among menthol cigarette smokers has not been defined. Studies have demonstrated a role for menthol in the metabolism of nicotine in the body. More recent findings now reveal an interaction between menthol and the nicotinic acetylcholine (nACh) receptor in cells. This receptor is central to the actions of nicotine in the brain, and plays an important role in nicotine addiction. The newly discovered effect of menthol on nACh receptors may begin to explain the unique addictive properties of menthol cigarettes.
Functional Genomic Analyses of Two Morphologically Distinct Classes of Drosophila Sensory Neurons: Post-Mitotic Roles of Transcription Factors in Dendritic Patterning
(Public Library of Science, 2013-08-15) Iyer, Eswar Prasad R.; Iyer, Srividya Chandramouli; Sullivan, Luis; Wang, Dennis; Meduri, Ramakrishna; Graybeal, Lacey L.; Cox, Daniel N.
Background Neurons are one of the most structurally and functionally diverse cell types found in nature, owing in large part to their unique class specific dendritic architectures. Dendrites, being highly specialized in receiving and processing neuronal signals, play a key role in the formation of functional neural circuits. Hence, in order to understand the emergence and assembly of a complex nervous system, it is critical to understand the molecular mechanisms that direct class specific dendritogenesis. Methodology/Principal Findings We have used the Drosophila dendritic arborization (da) neurons to gain systems-level insight into dendritogenesis by a comparative study of the morphologically distinct Class-I (C-I) and Class-IV (C-IV) da neurons. We have used a combination of cell-type specific transcriptional expression profiling coupled to a targeted and systematic in vivo RNAi functional validation screen. Our comparative transcriptomic analyses have revealed a large number of differentially enriched/depleted gene-sets between C-I and C-IV neurons, including a broad range of molecular factors and biological processes such as proteolytic and metabolic pathways. Further, using this data, we have identified and validated the role of 37 transcription factors in regulating class specific dendrite development using in vivo class-specific RNAi knockdowns followed by rigorous and quantitative neurometric analysis. Conclusions/Significance This study reports the first global gene-expression profiles from purified Drosophila C-I and C-IV da neurons. We also report the first large-scale semi-automated reconstruction of over 4,900 da neurons, which were used to quantitatively validate the RNAi screen phenotypes. Overall, these analyses shed global and unbiased novel insights into the molecular differences that underlie the morphological diversity of distinct neuronal cell-types. Furthermore, our class-specific gene expression datasets should prove a valuable community resource in guiding further investigations designed to explore the molecular mechanisms underlying class specific neuronal patterning.

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