Concept Formation and Categorization in Dynamic Cognitive Tasks What are the cognitive processes that determine successful problem solving during goal-directed behavior? How do people determine and selectively employ only the relevant aspects of their knowledge about common objects in the world when they attempt to accomplish an everyday task? The presence of a goal e.
The Temporal Dynamics of Cognitive Processing | Frontiers Research Topic
Importantly, this activation of semantic knowledge is modulated by the availability of ideal means in the environment toward goal achievement e. Although concept formation and problem solving are areas not typically examined in conjunction with each other, I have presented a new theoretical model of goal oriented action that is anchored in categorization processes Chrysikou, I further provided for the first time experimental evidence suggesting that goal-derived categorization is implicated considerably in problem solving: In a series of behavioral experiments I have shown that training individuals to categorize common objects in alternative ways e.
What are the cognitive and neural mechanisms underlying these effects? Importantly, what is their duration and generalizability to other tasks?
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Within this line of work, the questions I aim to pursue in the future focus on the characterization of flexible cognitive control in dynamic everyday tasks. Papers Table of contents 35 papers About About these proceedings Table of contents Search within book.
Front Matter Pages Pages Recent Advances in Neurocognitive Pattern Analysis. Dynamic Changes in Steady-State Responses. Cortical Structure and Electrogenesis. Petsche, H.
A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making
Pockberger, P. Electromagnetic Field Interactions in the Brain. Chaotic Dynamics in Brain Activity. In this project we study the effects of experiential learning on reducing biases and increasing sensitivity about the challenges that women and minority groups confront in the workplace. Cybersecurity has become a critical issue in our society. The assessment of the threats, vulnerabilities and successful defense in cyber space is surrounded by many challenges.
Some of those challenges are technology-driven. For example, the ability to continuously monitor a network and integrate information from multiple sources: network traffic, vulnerabilities, patch status, scan results, etc. But many other challenges are human-driven, for example, the evaluation of the collected data, the assessment of risks, and the ability to make appropriate mitigation decisions.
The DDMLab plays a key role in integrating models of human behavior and decision making in particular to technological solutions in cyber defense. We are in charge of the cognitive and psychosocial work developed in the Cyber Security collaborative Research Alliance of the Army Research Laboratories.
We hope that these models will bring more understanding to advance current theories of cognition and decision making and to develop new theoretical mechanisms to help address the new behavioral challenges on cyber-security. Network science focuses on the interactions between decision makers and their emergent social phenomena. By bringing together cognitive architectures, network science, and decision support technology, our project will advance scientific knowledge about group dynamics, decision support technology, and their links to individual and group cognition.
The DDMLab plays a key role in the development of models that scale up from individual cognition of network science models. We are part of a Collaborative Technology Alliance for Network Science, in which we aim to develop formal cognitive models that combine the interactions of individual dynamic decision-making processes with the emergent dynamics of network structure. Using simple laboratory representations of these types of situations, we study how decisions are made from experience during and after repeated choices.
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Using IBL models, we study the cognitive processes by which these decisions are made, and we are able to make predictions regarding human decisions from experience in novel conditions of choice. Rather than choosing between discrete alternatives, we often make decisions aimed at keeping a system "under control.
In all of these examples, the main goal is to keep a stock accumulation at a target level or within an acceptable range by altering inflows which increase a stock and outflows which decrease a stock. As such, a diabetic maintains optimal blood sugar levels via diet, exercise, and medication; a manager keeps inventory at an optimal level where sales are maintained and storage costs are minimized; and humanity attempts to maintain a level of CO2 by reducing emissions and assessing the levels of absorption from natural processes.
- Relating dynamic cognitive variables to neural population activity!
- The Ubiquitous Roles of Cytochrome P450 Proteins: Metal Ions in Life Sciences.
- The Facts of Life: and Other Dirty Jokes.
- Cognitive Processes Supporting Recognition in Complex and Dynamic Tasks.
- The Clothes on Their Backs?
- Dynamic Decision Making Laboratory.
Despite the ubiquity of these systems, research often demonstrates the frailty and fallibility of human performance in these tasks. Using simple laboratory representations of stock and flow systems, we study how people keep these types of dynamic systems under control. Research in dynamic decision making often relies on representations of real life problems in computer simulations, decision making games, and cognitive computational models.
- Seneca and the Idea of Tragedy?
- The Fundamentals of Hedge Fund Management: How to Successfully Launch and Operate a Hedge Fund (Wiley Finance).
- Dynamics of Sensory and Cognitive Processing by the Brain | SpringerLink;
Under this research theme, we investigate methodological issues in dynamic decision making research. Detecting Targets from Visual Cues.