Studying dynamic systems models in Simulink

This article addresses the convergence and complementarity between self-regulatory control-process models of behavior and dynamic systems models. The control-process view holds that people have a goal in mind and try to move toward it (or away from it), monitoring the extent to which a discrepancy remains between the goal and one's present state and taking steps to reduce the discrepancy (or enlarge it). Dynamic systems models tend to emphasize a bottom-up self-organization process, in which a coherence arises from among many simultaneous influences, moving the system toward attractors and away from repellers. We suggest that these differences in emphasis reflect two facets of a more complex reality involving both types of processes. Discussion focuses on how self-organization may occur within constituent elements of a feedback system—the input function, the output function, and goal values being used by the system—and how feedback processes themselves can reflect self-organizing tendencies.

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Dynamic systems methods for models of developmental psychopathology

Development and Psychopathology ◽

10.1017/s0954579403000324 ◽

2003 ◽

Vol 15 (3) ◽

pp. 641-669 ◽

Cited By ~ 112

Author(s):

ISABELA GRANIC ◽

TOM HOLLENSTEIN

Keyword(s):

State Space ◽

Dynamic Systems ◽

Developmental Psychopathology ◽

Open Systems ◽

Change Processes ◽

New Methods ◽

Research Designs ◽

State Space Grids ◽

Systems Models ◽

The One

A survey of dynamic systems (DS) methods appropriate for testing systems-based models in developmental psychopathology is provided. The rationale for developing new methods for the field is reviewed first. In line with other scholars, we highlight the fundamental incompatibility between developmentalists' organismic, open systems models and the mechanistic research methods with which these models are tested. Key DS principles are explained and their commensurability with developmental psychopathologists' core theoretical concerns are discussed. Next, a survey of research designs and methodological techniques currently being used and refined by developmental DS researchers is provided. The strengths and limitations of each approach are discussed throughout this review. Finally, we elaborate on one specific dynamic systems method, state space grids, which addresses many of the limitations of previous DS techniques and may prove most useful for the discipline. This approach was developed as a middle road between DS methods that are mathematically heavy on the one hand and purely descriptive on the other. Examples of developmental and clinical studies that have applied state space grids are reviewed and suggestions for future analyses are made. We conclude with some implications for the application of this new methodology for studying change processes in clinical research.

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The contribution of cross-cultural study to dynamic systems modeling of emotions

Behavioral and Brain Sciences ◽

10.1017/s0140525x05300045 ◽

2005 ◽

Vol 28 (2) ◽

pp. 201-202

Author(s):

Greg Downey

Keyword(s):

Dynamic Systems ◽

Neural Plasticity ◽

Cross Cultural ◽

Appraisal Theory ◽

Cultural Variation ◽

Systems Model ◽

Cross Cultural Study ◽

Brain Sciences ◽

Systems Models ◽

The Brain

Lewis neglects cross-cultural data in his dynamic systems model of emotion, probably because appraisal theory disregards behavior and because anthropologists have not engaged discussions of neural plasticity in the brain sciences. Considering cultural variation in emotion-related behavior, such as grieving, indigenous descriptions of emotions, and alternative developmental regimens, such as sport, opens up avenues to test dynamic systems models.

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