Indiana University Bloomington
NSF
An IGERT Training Program

The Dynamics of Brain-Body-Environment Systems in Behavior and Cognition

Our training program builds on four areas of research excellence at Indiana University, with the goal of providing training in the skills necessary to unify and work across levels. Each of these component research areas is primarily focused at one or an adjacent pair of brain, behavior, and social levels of analysis, and they each employ a combination of experimental and theoretical approaches. Our training program both exposes students to ongoing cutting-edge interdisciplinary research within each of these areas, and encourages the integrative study of behavioral and cognitive phenomena across these levels.

Brain Dynamics and Connectivity

This research area centers on the complex dynamics of neurons and brain areas and how their interactions are influenced by and shape behavior. The Beggs laboratory's main research focus is on emergent properties of living neural networks, particularly cortical neuronal cultures and slices. Based on multielectrode recordings of neuronal activity, the lab has developed and applied computational techniques to elucidate network patterns of information transmission and processing. The Brown laboratory investigates how humans monitor and adjust their behavior as they evaluate potential outcomes associated with available alternatives in decision-making. The lab uses a combination of computational neural modeling, fMRI and cognitive psychology methodologies. The laboratory of Thomas James investigates the neural mechanisms of multi-sensory object recognition. Using fMRI methods, he is particularly interested in how the brain integrates across inputs from different sensory systems in order to interpret a potentially ambiguous environment. The Newman laboratory studies the neural basis of sentence comprehension and problem-solving. Using fMRI approaches, the lab measures differences in functional connectivity across individuals to obtain a better characterization of the neural network that supports cognition. The Sporns lab studies brain connectivity and dynamics in both simulated and empirically derived brain networks using a blend of computational tools from dynamical systems theory, graph theory, and information theory. Research focuses on how brain dynamics is shaped by interactions with the environment and by the topology of neural connections. Together, this group of researchers will provide trainees with a strong foundation in experimental and theoretical tools for studying the properties of brain connectivity and dynamics and their role in behavior and cognition.

Self-Organization of Individual Behavior

This research area investigates how behavior and cognition arise from the closed-loop interaction between an agent and its environment. The Bingham laboratory focuses on the information and dynamics of human perception/action tasks through a combination of experimental and dynamical modeling methods. Their work include studies of perceptual coupling in bimanual coordination, visual event recognition, spatial perception, visually-guided reaching-to-grasp and long-distance throwing. The Beer laboratory uses evolutionary algorithms to evolve nervous systems for model agents and then uses the tools of dynamical systems theory to analyze the resulting brain-body-environment interactions. Behaviors that have been studied include walking, visually-guided reaching, categorical perception and selective attention. The Busemeyer laboratory develops dynamical models of decision-making using decision field theory. The Scheutz laboratory focuses on how humans and robots can interact in natural and effective ways. This work includes both experimental studies of people's perceptions and mental models of robots and computational studies of architectural principles and algorithms for robots. The Yaeger lab builds computational models of evolving agents to study the relationship between neural architectures and behavioral performance in an environment. Neural connectivity is shaped by evolutionary constraints and the resulting complexity of neural structures and dynamics is observed as a function of changes in environment and fitness. Finally, Allen studies the philosophical underpinnings of explanations of human and nonhuman animal behavior. He is particularly interested in what grounds attributions of goal-directedness and intentionality, and the differing perspectives brought to these issues by psychologists and biologists, as well as the nature of concepts and ways of modeling conceptual structures computationally. Together, this group of researchers will provide trainees with a strong foundation in experimental and theoretical tools for studying how behavior and cognition of individual agents arises from the interaction between that agentŐs nervous system, body and environment.

Processes of Change

This research area investigate how an individual's own activity creates long-term change in the system and its intrinsic dynamics, as well as the cascading consequences of this change. This group includes the experimental analysis of learning and developmental change as well as computational modeling and mathematical analysis of such change. Karin James' laboratory focuses on the effects of sensory-motor activity on the development of visuomotor processes, including the role of action in the development of the visual system. The work, which uses both behavioral and fMRI methods with children as young as 4 years of age, is especially interested in how the motor and visual systems in the brain are interconnected and how their development is affected by multi-modal experience. Kruschke and Shiffrin study computational and formal models of learning, especially as they apply to changes in attention. Linda Smith's laboratory focuses on the mechanisms of change in infants' and toddlers' learning about objects with special emphasis on the interactions of perception, action, and language. The key idea concerns how moment-to-moment activity creates long term change that then creates new opportunities for (and constraints on) future learning. Theoretical approaches include dynamic field models and connectionist models. Yu's laboratory examines how language learning is grounded in sensorimotor interaction and uses computational modeling and behavioral studies of infants. In addition this work (in collaboration with Smith) also examines the dynamic coupling of parent-toddler behavior in naturalistic settings and as related to object name learning using measures of head movements, hand movements, and using head cameras. Together this group of researchers will provide trainees with a strong foundation in experimental and theoretical tools for studying how processes of change contribute to the dynamics of brain-body-environment interactions.

Self-Organization of Group Behavior

Cognitive scientists traditionally have focused on the behavior of single individuals thinking and perceiving on their own. However, interacting groups of people also create emergent organizations at a higher level than the individual. This research area focuses on the dynamics of collective behavior, how people influence one another, and how groups organize themselves over evolutionary, historical, and briefer time-scales. Goldstone's laboratory has developed an internet-based experimental platform that allows groups of people to interact with each other in real time on networked computers. They study the competitive foraging for resources by individuals inhabiting an environment consisting largely of other individuals foraging for the same resources, the dissemination of innovations in social networks, group coordination, and how groups create rules that then govern their patterns of organization. Also interested in how groups search for information, Rocha's laboratory explores how social foraging is accomplished online, by examining patterns of web-based information exchanges and social interactions. They develop information retrieval and recommendation algorithms that infer thematically coherent communities in online resources, and predict future social relationships. Eliot Smith's research involves both human experimentation and agent-based modeling and focuses on when, why, and how people turn to using information provided by others in preference to using information that they obtain individually from the environment. The interplay of several motivations for conforming or copying shapes collective outcomes as groups self-organize, whether converging to uniformity of opinions and behavior or maintaining diversity. Todd's work focuses on how people can make appropriate decisions in adaptively important domains, such as mate choice and food choice, by using simple heuristics that are shaped to fit the structures of information available in the environment. Often, the decision environment is composed of other individuals, as when people are searching sequentially for mates who must also choose them in return.